Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics

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} div.type-section h2 { font-size: 20px; line-height: 26px; font-weight: 300; } div.type-section h3 { margin-left: 15px; margin-bottom: 0px; font-weight: 300; } .journal-tabs .tab-title.active a { } </style> <link rel="stylesheet" href="https://pub.mdpi-res.com/assets/css/slick.css?f38b2db10e01b157?1732286508"> <meta name="title" content="Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics"> <meta name="description" content="Nanotechnological methods for creating multifunctional fabrics are attracting global interest. The incorporation of nanoparticles in the field of textiles enables the creation of multifunctional textiles exhibiting UV irradiation protection, antimicrobial properties, self-cleaning properties and photocatalytic. Nanomaterials-loaded textiles have many innovative applications in pharmaceuticals, sports, military the textile industry etc. This study details the biosynthesis and characterization of silver nanoparticles (AgNPs) using the aqueous mycelial-free filtrate of Aspergillus flavus. The formation of AgNPs was indicated by a brown color in the extracellular filtrate and confirmed by UV-Vis spectroscopy with a peak at 426 nm. The Box-Behnken design (BBD) is used to optimize the physicochemical parameters affecting AgNPs biosynthesis. The desirability function was employed to theoretically predict the optimal conditions for the biosynthesis of AgNPs, which were subsequently experimentally validated. Through the desirability function, the optimal conditions for the maximum predicted value for the biosynthesized AgNPs (235.72 µg/mL) have been identified as follows: incubation time (58.12 h), initial pH (7.99), AgNO3 concentration (4.84 mM/mL), and temperature (34.84 °C). Under these conditions, the highest experimental value of AgNPs biosynthesis was 247.53 µg/mL. Model validation confirmed the great accuracy of the model predictions. Scanning electron microscopy (SEM) revealed spherical AgNPs measuring 8.93–19.11 nm, which was confirmed by transmission electron microscopy (TEM). Zeta potential analysis indicated a positive surface charge (+1.69 mV), implying good stability. X-ray diffraction (XRD) confirmed the crystalline nature, while energy-dispersive X-ray spectroscopy (EDX) verified elemental silver (49.61%). Scanning electron microscopy (SEM) revealed uniformly sized spherical AgNPs. Transmission electron microscopy (TEM) revealed spherical particles measuring 8.93–19.11 nm. EDX spectrum revealed that silver is the dominant element in the AgNPs. The Zeta potential measurement revealed a positive surface charge (+1.69 mV). X-ray diffraction (XRD) confirmed the crystalline character. FTIR findings indicate the presence of phenols, proteins, alkanes, alkenes, aliphatic and aromatic amines, and alkyl groups which play significant roles in the reduction, capping, and stabilization of AgNPs. Cotton fabrics embedded with AgNPs biosynthesized using the aqueous mycelial-free filtrate of Aspergillus flavus showed strong antimicrobial activity. The disc diffusion method revealed inhibition zones of 15, 12, and 17 mm against E. coli (Gram-negative), S. aureus (Gram-positive), and C. albicans (yeast), respectively. These fabrics have potential applications in protective clothing, packaging, and medical care. In silico modeling suggested that the predicted compound derived from AgNPs on cotton fabric could inhibit Penicillin-binding proteins (PBPs) and Lanosterol 14-alpha-demethylase (L-14α-DM), with binding energies of −4.7 and −5.2 Kcal/mol, respectively. Pharmacokinetic analysis and sensitizer prediction indicated that this compound merits further investigation." > <link rel="image_src" href="https://pub.mdpi-res.com/img/journals/jfb-logo.png?8600e93ff98dbf14" > <meta name="dc.title" content="Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics"> <meta name="dc.creator" content="Nada S. Shweqa"> <meta name="dc.creator" content="Noura El-Ahmady El-Naggar"> <meta name="dc.creator" content="Hala M. Abdelmigid"> <meta name="dc.creator" content="Amal A. Alyamani"> <meta name="dc.creator" content="Naglaa Elshafey"> <meta name="dc.creator" content="Hadeel El-Shall"> <meta name="dc.creator" content="Yasmin M. Heikal"> <meta name="dc.creator" content="Hoda M. Soliman"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="Journal of Functional Biomaterials 2024, Vol. 15, Page 354"> <meta name="dc.date" content="2024-11-21"> <meta name ="dc.identifier" content="10.3390/jfb15120354"> <meta name="dc.publisher" content="Multidisciplinary Digital Publishing Institute"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf" > <meta name="dc.language" content="en" > <meta name="dc.description" content="Nanotechnological methods for creating multifunctional fabrics are attracting global interest. The incorporation of nanoparticles in the field of textiles enables the creation of multifunctional textiles exhibiting UV irradiation protection, antimicrobial properties, self-cleaning properties and photocatalytic. Nanomaterials-loaded textiles have many innovative applications in pharmaceuticals, sports, military the textile industry etc. This study details the biosynthesis and characterization of silver nanoparticles (AgNPs) using the aqueous mycelial-free filtrate of Aspergillus flavus. The formation of AgNPs was indicated by a brown color in the extracellular filtrate and confirmed by UV-Vis spectroscopy with a peak at 426 nm. The Box-Behnken design (BBD) is used to optimize the physicochemical parameters affecting AgNPs biosynthesis. The desirability function was employed to theoretically predict the optimal conditions for the biosynthesis of AgNPs, which were subsequently experimentally validated. Through the desirability function, the optimal conditions for the maximum predicted value for the biosynthesized AgNPs (235.72 µg/mL) have been identified as follows: incubation time (58.12 h), initial pH (7.99), AgNO3 concentration (4.84 mM/mL), and temperature (34.84 °C). Under these conditions, the highest experimental value of AgNPs biosynthesis was 247.53 µg/mL. Model validation confirmed the great accuracy of the model predictions. Scanning electron microscopy (SEM) revealed spherical AgNPs measuring 8.93–19.11 nm, which was confirmed by transmission electron microscopy (TEM). Zeta potential analysis indicated a positive surface charge (+1.69 mV), implying good stability. X-ray diffraction (XRD) confirmed the crystalline nature, while energy-dispersive X-ray spectroscopy (EDX) verified elemental silver (49.61%). Scanning electron microscopy (SEM) revealed uniformly sized spherical AgNPs. Transmission electron microscopy (TEM) revealed spherical particles measuring 8.93–19.11 nm. EDX spectrum revealed that silver is the dominant element in the AgNPs. The Zeta potential measurement revealed a positive surface charge (+1.69 mV). X-ray diffraction (XRD) confirmed the crystalline character. FTIR findings indicate the presence of phenols, proteins, alkanes, alkenes, aliphatic and aromatic amines, and alkyl groups which play significant roles in the reduction, capping, and stabilization of AgNPs. Cotton fabrics embedded with AgNPs biosynthesized using the aqueous mycelial-free filtrate of Aspergillus flavus showed strong antimicrobial activity. The disc diffusion method revealed inhibition zones of 15, 12, and 17 mm against E. coli (Gram-negative), S. aureus (Gram-positive), and C. albicans (yeast), respectively. These fabrics have potential applications in protective clothing, packaging, and medical care. In silico modeling suggested that the predicted compound derived from AgNPs on cotton fabric could inhibit Penicillin-binding proteins (PBPs) and Lanosterol 14-alpha-demethylase (L-14α-DM), with binding energies of −4.7 and −5.2 Kcal/mol, respectively. Pharmacokinetic analysis and sensitizer prediction indicated that this compound merits further investigation." > <meta name="dc.subject" content="nanoparticles" > <meta name="dc.subject" content="silver" > <meta name="dc.subject" content="green synthesis" > <meta name="dc.subject" content="<i>Aspergillus flavus</i>" > <meta name="dc.subject" content="statistical optimization" > <meta name="dc.subject" content="characterization" > <meta name="dc.subject" content="cotton fabrics" > <meta name="dc.subject" content="antimicrobial activity" > <meta name="dc.subject" content="molecular docking analysis" > <meta name ="prism.issn" content="2079-4983"> <meta name ="prism.publicationName" content="Journal of Functional Biomaterials"> <meta name ="prism.publicationDate" content="2024-11-21"> <meta name ="prism.volume" content="15"> <meta name ="prism.number" content="12"> <meta name ="prism.section" content="Article" > <meta name ="prism.startingPage" content="354" > <meta name="citation_issn" content="2079-4983"> <meta name="citation_journal_title" content="Journal of Functional Biomaterials"> <meta name="citation_publisher" content="Multidisciplinary Digital Publishing Institute"> <meta name="citation_title" content="Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics"> <meta name="citation_publication_date" content="2024/12"> <meta name="citation_online_date" content="2024/11/21"> <meta name="citation_volume" content="15"> <meta name="citation_issue" content="12"> <meta name="citation_firstpage" content="354"> <meta name="citation_author" content="Shweqa, Nada S."> <meta name="citation_author" content="El-Naggar, Noura El-Ahmady"> <meta name="citation_author" content="Abdelmigid, Hala M."> <meta name="citation_author" content="Alyamani, Amal A."> <meta name="citation_author" content="Elshafey, Naglaa"> <meta name="citation_author" content="El-Shall, Hadeel"> <meta name="citation_author" content="Heikal, Yasmin M."> <meta name="citation_author" content="Soliman, Hoda M."> <meta name="citation_doi" content="10.3390/jfb15120354"> <meta name="citation_id" content="mdpi-jfb15120354"> <meta name="citation_abstract_html_url" content="https://www.mdpi.com/2079-4983/15/12/354"> <meta name="citation_pdf_url" content="https://www.mdpi.com/2079-4983/15/12/354/pdf?version=1732192528"> <link rel="alternate" type="application/pdf" title="PDF Full-Text" href="https://www.mdpi.com/2079-4983/15/12/354/pdf?version=1732192528"> <meta name="fulltext_pdf" content="https://www.mdpi.com/2079-4983/15/12/354/pdf?version=1732192528"> <meta name="citation_fulltext_html_url" content="https://www.mdpi.com/2079-4983/15/12/354/htm"> <link rel="alternate" type="text/html" title="HTML Full-Text" href="https://www.mdpi.com/2079-4983/15/12/354/htm"> <meta name="fulltext_html" content="https://www.mdpi.com/2079-4983/15/12/354/htm"> <link rel="alternate" type="text/xml" title="XML Full-Text" href="https://www.mdpi.com/2079-4983/15/12/354/xml"> <meta name="fulltext_xml" content="https://www.mdpi.com/2079-4983/15/12/354/xml"> <meta name="citation_xml_url" content="https://www.mdpi.com/2079-4983/15/12/354/xml"> <meta name="twitter:card" content="summary" /> <meta name="twitter:site" content="@MDPIOpenAccess" /> <meta name="twitter:image" content="https://pub.mdpi-res.com/img/journals/jfb-logo-social.png?8600e93ff98dbf14" /> <meta property="fb:app_id" content="131189377574"/> <meta property="og:site_name" content="MDPI"/> <meta property="og:type" content="article"/> <meta property="og:url" content="https://www.mdpi.com/2079-4983/15/12/354" /> <meta property="og:title" content="Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics" /> <meta property="og:description" content="Nanotechnological methods for creating multifunctional fabrics are attracting global interest. The incorporation of nanoparticles in the field of textiles enables the creation of multifunctional textiles exhibiting UV irradiation protection, antimicrobial properties, self-cleaning properties and photocatalytic. Nanomaterials-loaded textiles have many innovative applications in pharmaceuticals, sports, military the textile industry etc. This study details the biosynthesis and characterization of silver nanoparticles (AgNPs) using the aqueous mycelial-free filtrate of Aspergillus flavus. The formation of AgNPs was indicated by a brown color in the extracellular filtrate and confirmed by UV-Vis spectroscopy with a peak at 426 nm. The Box-Behnken design (BBD) is used to optimize the physicochemical parameters affecting AgNPs biosynthesis. The desirability function was employed to theoretically predict the optimal conditions for the biosynthesis of AgNPs, which were subsequently experimentally validated. Through the desirability function, the optimal conditions for the maximum predicted value for the biosynthesized AgNPs (235.72 µg/mL) have been identified as follows: incubation time (58.12 h), initial pH (7.99), AgNO3 concentration (4.84 mM/mL), and temperature (34.84 °C). Under these conditions, the highest experimental value of AgNPs biosynthesis was 247.53 µg/mL. Model validation confirmed the great accuracy of the model predictions. Scanning electron microscopy (SEM) revealed spherical AgNPs measuring 8.93–19.11 nm, which was confirmed by transmission electron microscopy (TEM). Zeta potential analysis indicated a positive surface charge (+1.69 mV), implying good stability. X-ray diffraction (XRD) confirmed the crystalline nature, while energy-dispersive X-ray spectroscopy (EDX) verified elemental silver (49.61%). Scanning electron microscopy (SEM) revealed uniformly sized spherical AgNPs. Transmission electron microscopy (TEM) revealed spherical particles measuring 8.93–19.11 nm. EDX spectrum revealed that silver is the dominant element in the AgNPs. The Zeta potential measurement revealed a positive surface charge (+1.69 mV). X-ray diffraction (XRD) confirmed the crystalline character. FTIR findings indicate the presence of phenols, proteins, alkanes, alkenes, aliphatic and aromatic amines, and alkyl groups which play significant roles in the reduction, capping, and stabilization of AgNPs. Cotton fabrics embedded with AgNPs biosynthesized using the aqueous mycelial-free filtrate of Aspergillus flavus showed strong antimicrobial activity. The disc diffusion method revealed inhibition zones of 15, 12, and 17 mm against E. coli (Gram-negative), S. aureus (Gram-positive), and C. albicans (yeast), respectively. These fabrics have potential applications in protective clothing, packaging, and medical care. In silico modeling suggested that the predicted compound derived from AgNPs on cotton fabric could inhibit Penicillin-binding proteins (PBPs) and Lanosterol 14-alpha-demethylase (L-14α-DM), with binding energies of −4.7 and −5.2 Kcal/mol, respectively. 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</div> </div> </div> </div> </div> <article ><div class='html-article-content'> <span itemprop="publisher" content="Multidisciplinary Digital Publishing Institute"></span><span itemprop="url" content="https://www.mdpi.com/2079-4983/15/12/354"></span> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <h1 class="title hypothesis_container" itemprop="name"> Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics </h1> <div class="art-authors hypothesis_container"> by <span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428235' data-options='is_hover:true, hover_timeout:5000'> Nada S. Shweqa</div><div id="profile-card-drop13428235" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Nada S. Shweqa</span></div></div></div><div class="profile-card__buttons" style="margin-bottom: 10px;"><a href="https://sciprofiles.com/profile/4037642?utm_source=mdpi.com&utm_medium=website&utm_campaign=avatar_name" class="button button--color-inversed" target="_blank"> SciProfiles </a><a href="https://scilit.net/scholars?q=Nada%20S.%20Shweqa" class="button button--color-inversed" target="_blank"> Scilit </a><a href="https://www.preprints.org/search?search1=Nada%20S.%20Shweqa&field1=authors" class="button button--color-inversed" target="_blank"> Preprints.org </a><a href="https://scholar.google.com/scholar?q=Nada%20S.%20Shweqa" class="button button--color-inversed" target="_blank" rels="noopener noreferrer"> Google Scholar </a></div></div><sup> 1</sup><span style="display: inline; margin-left: 5px;"></span><a class="toEncode emailCaptcha visibility-hidden" data-author-id="13428235" href="/cdn-cgi/l/email-protection#cfe0aca1abe2aca8a6e0a3e0aaa2aea6a3e2bfbda0bbaaacbba6a0a1ecffffffa9f9aaffaeffa9feabffa9fffdffa9fff9faacfaaafaaafaaafdaafffcffa9fffffeabfbffffadffaefeadfbffffadfff6"><sup><i class="fa fa-envelope-o"></i></sup></a><a href="https://orcid.org/0000-0002-1487-3035" target="_blank" rel="noopener noreferrer"><img src="https://pub.mdpi-res.com/img/design/orcid.png?0465bc3812adeb52?1732286508" title="ORCID" style="position: relative; width: 13px; margin-left: 3px; max-width: 13px !important; height: auto; top: -5px;"></a>, </span><span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428236' data-options='is_hover:true, hover_timeout:5000'> Noura El-Ahmady El-Naggar</div><div id="profile-card-drop13428236" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Noura El-Ahmady El-Naggar</span></div></div></div><div class="profile-card__buttons" style="margin-bottom: 10px;"><a href="https://sciprofiles.com/profile/author/U29BbXJkL1g0VjlIL0dOazdyb0JmWGtpbmN6RGFJN0x1N01pRGVyc3VZbz0=?utm_source=mdpi.com&utm_medium=website&utm_campaign=avatar_name" class="button button--color-inversed" target="_blank"> SciProfiles </a><a href="https://scilit.net/scholars?q=Noura%20El-Ahmady%20El-Naggar" class="button button--color-inversed" target="_blank"> Scilit </a><a href="https://www.preprints.org/search?search1=Noura%20El-Ahmady%20El-Naggar&field1=authors" class="button button--color-inversed" target="_blank"> Preprints.org </a><a href="https://scholar.google.com/scholar?q=Noura%20El-Ahmady%20El-Naggar" class="button button--color-inversed" target="_blank" rels="noopener noreferrer"> Google Scholar </a></div></div><sup> 2</sup><span style="display: inline; margin-left: 5px;"></span><a class="toEncode emailCaptcha visibility-hidden" data-author-id="13428236" href="/cdn-cgi/l/email-protection#1c337f7278317f7b7533703379717d7570316c6e7368797f687573723f2c2c2c7e2a792c2e2c7a2c2a2c2f2c7a2c7d2d2b2e792d782d7f2d7d2c7a2c782c2b2d7d2d2b282c2d782c782c2b282c2c7e2c25"><sup><i class="fa fa-envelope-o"></i></sup></a><a href="https://orcid.org/0000-0001-8493-9194" target="_blank" rel="noopener noreferrer"><img src="https://pub.mdpi-res.com/img/design/orcid.png?0465bc3812adeb52?1732286508" title="ORCID" style="position: relative; width: 13px; margin-left: 3px; max-width: 13px !important; height: auto; top: -5px;"></a>, </span><span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428237' data-options='is_hover:true, hover_timeout:5000'> Hala M. Abdelmigid</div><div id="profile-card-drop13428237" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Hala M. 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Alyamani</div><div id="profile-card-drop13428238" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Amal A. 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width: 13px; margin-left: 3px; max-width: 13px !important; height: auto; top: -5px;"></a>, </span><span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428239' data-options='is_hover:true, hover_timeout:5000'> Naglaa Elshafey</div><div id="profile-card-drop13428239" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Naglaa Elshafey</span></div></div></div><div class="profile-card__buttons" style="margin-bottom: 10px;"><a href="https://sciprofiles.com/profile/2100170?utm_source=mdpi.com&utm_medium=website&utm_campaign=avatar_name" class="button button--color-inversed" target="_blank"> SciProfiles </a><a href="https://scilit.net/scholars?q=Naglaa%20Elshafey" class="button button--color-inversed" target="_blank"> Scilit </a><a href="https://www.preprints.org/search?search1=Naglaa%20Elshafey&field1=authors" class="button button--color-inversed" target="_blank"> Preprints.org </a><a href="https://scholar.google.com/scholar?q=Naglaa%20Elshafey" class="button button--color-inversed" target="_blank" rels="noopener noreferrer"> Google Scholar </a></div></div><sup> 4</sup><span style="display: inline; margin-left: 5px;"></span><a class="toEncode emailCaptcha visibility-hidden" data-author-id="13428239" href="/cdn-cgi/l/email-protection#efc08c818bc28c8886c083c08a828e8683c29f9d809b8a8c9b868081ccdfdfdcded98adfd7df89de8edfd9dfd8dd8adf89de8cde8ddbdfdf8ddf8ede8ddbdfdf8ddfd6"><sup><i class="fa fa-envelope-o"></i></sup></a><a href="https://orcid.org/0000-0002-1660-9406" target="_blank" rel="noopener noreferrer"><img src="https://pub.mdpi-res.com/img/design/orcid.png?0465bc3812adeb52?1732286508" title="ORCID" style="position: relative; width: 13px; margin-left: 3px; max-width: 13px !important; height: auto; top: -5px;"></a>, </span><span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428240' data-options='is_hover:true, hover_timeout:5000'> Hadeel El-Shall</div><div id="profile-card-drop13428240" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; 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width: 13px; margin-left: 3px; max-width: 13px !important; height: auto; top: -5px;"></a>, </span><span class="inlineblock "><div class='profile-card-drop' data-dropdown='profile-card-drop13428241' data-options='is_hover:true, hover_timeout:5000'> Yasmin M. 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Soliman</div><div id="profile-card-drop13428242" data-dropdown-content class="f-dropdown content profile-card-content" aria-hidden="true" tabindex="-1"><div class="profile-card__title"><div class="sciprofiles-link" style="display: inline-block"><div class="sciprofiles-link__link"><img class="sciprofiles-link__image" src="/bundles/mdpisciprofileslink/img/unknown-user.png" style="width: auto; height: 16px; border-radius: 50%;"><span class="sciprofiles-link__name">Hoda M. 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Funct. Biomater.</em> <b>2024</b>, <em>15</em>(12), 354; <a href="https://doi.org/10.3390/jfb15120354">https://doi.org/10.3390/jfb15120354</a> </div> <div class="pubhistory" style="font-weight: bold; padding-bottom: 10px;"> <span style="display: inline-block">Submission received: 14 October 2024</span> / <span style="display: inline-block">Revised: 16 November 2024</span> / <span style="display: inline-block">Accepted: 18 November 2024</span> / <span style="display: inline-block">Published: 21 November 2024</span> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/jfb/special_issues/5M67K81738 ">Biomaterials, Bioconjugated Materials, and Biomaterial Composites with Antimicrobial Properties</a>)<br/> </div> <div class="highlight-box1"> <div class="download"> <a class="button button--color-inversed button--drop-down" data-dropdown="drop-download-1526241" aria-controls="drop-supplementary-1526241" aria-expanded="false"> Download <i class="material-icons">keyboard_arrow_down</i> </a> <div id="drop-download-1526241" class="f-dropdown label__btn__dropdown label__btn__dropdown--button" data-dropdown-content aria-hidden="true" tabindex="-1"> <a class="UD_ArticlePDF" href="/2079-4983/15/12/354/pdf?version=1732192528" data-name="Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics" data-journal="jfb">Download PDF</a> <br/> <a id="js-pdf-with-cover-access-captcha" href="#" data-target="/2079-4983/15/12/354/pdf-with-cover" class="accessCaptcha">Download PDF with Cover</a> <br/> <a id="js-xml-access-captcha" href="#" data-target="/2079-4983/15/12/354/xml" class="accessCaptcha">Download XML</a> <br/> <a href="/2079-4983/15/12/354/epub" id="epub_link">Download Epub</a> <br/> <a href="javascript:void(0);" data-reveal-id="supplementaryModal">Download Supplementary Material</a> <br/> </div> <div class="js-browse-figures" style="display: inline-block;"> <a href="#" class="button button--color-inversed margin-bottom-10 openpopupgallery UI_BrowseArticleFigures" data-target='article-popup' data-counterslink = "https://www.mdpi.com/2079-4983/15/12/354/browse" >Browse Figures</a> </div> <div id="article-popup" class="popupgallery" style="display: inline; line-height: 200%"> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g001.png?1732192635" title=" <strong>Figure 1</strong><br/> <p>Identification of <span class="html-italic">Aspergillus</span> via morphological and structural analysis: (<b>A</b>) Characteristic growth on PDA medium after 7 days at 25 °C; (<b>B</b>,<b>C</b>) Microscopic views at 100× and 400× magnification, displaying septate branched mycelium with conidia; (<b>D</b>) SEM imaging.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g002.png?1732192636" title=" <strong>Figure 2</strong><br/> <p>A construct of the phylogenetic tree of <span class="html-italic">Aspergillus</span> sp. based on internal transcribed spacer (ITS) region sequences with 1000 bootstrap replicates. The accession numbers are indicated in parentheses and the red box indicates the studied strain.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png?1732192637" title=" <strong>Figure 3</strong><br/> <p>Production of AgNPs using the aqueous mycelial-free filtrate of <span class="html-italic">A. flavus</span>. (<b>A</b>) Control flask (the aqueous mycelial-free filtrate without silver ions), (<b>B</b>) Experimental flask (the aqueous mycelial-free filtrate with silver ions) following 72 h cultivation, (<b>C</b>) Ultraviolet-visible absorption spectrum of the synthesized AgNPs (300–700 nm).</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png?1732192641" title=" <strong>Figure 4</strong><br/> <p>3D plots illustrating the interactive impacts of AgNO<sub>3</sub> concentration (X<sub>1</sub>), starting pH value (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) on the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of <span class="html-italic">A. flavus</span>. (<b>A</b>–<b>C</b>) illustrated the effect of AgNO<sub>3</sub> concentration on AgNPs biosynthesis when interacting with initial pH level, temperature and incubation period; respectively. (<b>A</b>,<b>D</b>,<b>E</b>) illustrated the effect of initial pH level on AgNPs biosynthesis when interacting with AgNO<sub>3</sub> concentration, temperature, and incubation time; respectively. (<b>B</b>,<b>D</b>,<b>F</b>) illustrated the effect of temperature on AgNPs biosynthesis when interacting with the AgNO<sub>3</sub> concentration, initial pH level and incubation time; respectively.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png?1732192643" title=" <strong>Figure 5</strong><br/> <p>(<b>A</b>) Normal probability plot of internally studentized residuals, (<b>B</b>) plot of predicted versus actual, (<b>C</b>) Box-Cox plot of model transformation and (<b>D</b>) plot of internally studentized residuals versus predicted values of AgNPs biosynthesis using aqueous mycelial-free filtrate of <span class="html-italic">A. flavus</span> as affected by AgNO<sub>3</sub> conc. (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>) and incubation time (X<sub>4</sub>).</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png?1732192645" title=" <strong>Figure 6</strong><br/> <p>The optimization plot displays the desirability function and the optimal predicted values for the synthesis of AgNPs using aqueous mycelial-free filtrate of <span class="html-italic">A. flavus</span>. The red and blue circles represent the highest values for the variables and AgNPs; respectively.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png?1732192648" title=" <strong>Figure 7</strong><br/> <p>Biogenic AgNPs by <span class="html-italic">A. flavus</span> comprising: (<b>A</b>) SEM image, (<b>B</b>) TEM micrograph, (<b>C</b>) SADP for a single nanosilver particle, and (<b>D</b>) EDX examination illustrating the elemental composition of native silver.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png?1732192650" title=" <strong>Figure 8</strong><br/> <p>Analysis of biogenic AgNPs using (<b>A</b>) Zeta potential measurement, (<b>B</b>) XRD pattern of silver nanoparticles and (<b>C</b>) FTIR spectroscopy to identify functional groups that stabilize or cap AgNPs.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png?1732192652" title=" <strong>Figure 9</strong><br/> <p>Antimicrobial activity of AgNPs bio-synthesized by the aqueous mycelial-free filtrate of <span class="html-italic">Aspergillus flavus</span> loaded on cotton fabrics.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png?1732192653" title=" <strong>Figure 10</strong><br/> <p>Prediction of forward reaction mechanism between bio-synthesized AgNPs and cellulose in cotton fabric.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png?1732192654" title=" <strong>Figure 11</strong><br/> <p>Molecular docking interactions between predicted compounds from AgNPs-loaded cotton fabrics (cellulose) with microbial proteins: (<b>A</b>) PBPs in Gram +ve and −ve bacteria, (<b>B</b>) Lanosterol-14α-demethylase (L-14α-DM) protein in <span class="html-italic">Candida albicans</span>.</p> "> </a> <a href="https://pub.mdpi-res.com/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png?1732192656" title=" <strong>Figure 12</strong><br/> <p>Sensitizer prediction of the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>A</b>) Prediction of keratinocyte responses to the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>B</b>) Prediction of human repeated insult patch test (HRIPT) and human maximization test (HMT) of the predicted compound resulting from AgNPs loaded on cotton fabrics.</p> "> </a> </div> <a class="button button--color-inversed" href="/2079-4983/15/12/354/review_report">Review Reports</a> <a class="button button--color-inversed" href="/2079-4983/15/12/354/notes">Versions Notes</a> </div> </div> <div class="responsive-moving-container small hidden" data-id="article-counters" style="margin-top: 15px;"></div> <div class="html-dynamic"> <section> <div class="art-abstract art-abstract-new in-tab hypothesis_container"> <p> <div><section class="html-abstract" id="html-abstract"> <h2 id="html-abstract-title">Abstract</h2><b>:</b> <div class="html-p">Nanotechnological methods for creating multifunctional fabrics are attracting global interest. The incorporation of nanoparticles in the field of textiles enables the creation of multifunctional textiles exhibiting UV irradiation protection, antimicrobial properties, self-cleaning properties and photocatalytic. Nanomaterials-loaded textiles have many innovative applications in pharmaceuticals, sports, military the textile industry etc. This study details the biosynthesis and characterization of silver nanoparticles (AgNPs) using the aqueous mycelial-free filtrate of <span class="html-italic">Aspergillus flavus</span>. The formation of AgNPs was indicated by a brown color in the extracellular filtrate and confirmed by UV-Vis spectroscopy with a peak at 426 nm. The Box-Behnken design (BBD) is used to optimize the physicochemical parameters affecting AgNPs biosynthesis. The desirability function was employed to theoretically predict the optimal conditions for the biosynthesis of AgNPs, which were subsequently experimentally validated. Through the desirability function, the optimal conditions for the maximum predicted value for the biosynthesized AgNPs (235.72 µg/mL) have been identified as follows: incubation time (58.12 h), initial pH (7.99), AgNO<sub>3</sub> concentration (4.84 mM/mL), and temperature (34.84 °C). Under these conditions, the highest experimental value of AgNPs biosynthesis was 247.53 µg/mL. Model validation confirmed the great accuracy of the model predictions. Scanning electron microscopy (SEM) revealed spherical AgNPs measuring 8.93–19.11 nm, which was confirmed by transmission electron microscopy (TEM). Zeta potential analysis indicated a positive surface charge (+1.69 mV), implying good stability. X-ray diffraction (XRD) confirmed the crystalline nature, while energy-dispersive X-ray spectroscopy (EDX) verified elemental silver (49.61%). Scanning electron microscopy (SEM) revealed uniformly sized spherical AgNPs. Transmission electron microscopy (TEM) revealed spherical particles measuring 8.93–19.11 nm. EDX spectrum revealed that silver is the dominant element in the AgNPs. The Zeta potential measurement revealed a positive surface charge (+1.69 mV). X-ray diffraction (XRD) confirmed the crystalline character. FTIR findings indicate the presence of phenols, proteins, alkanes, alkenes, aliphatic and aromatic amines, and alkyl groups which play significant roles in the reduction, capping, and stabilization of AgNPs. Cotton fabrics embedded with AgNPs biosynthesized using the aqueous mycelial-free filtrate of <span class="html-italic">Aspergillus flavus</span> showed strong antimicrobial activity. The disc diffusion method revealed inhibition zones of 15, 12, and 17 mm against <span class="html-italic">E. coli</span> (Gram-negative), <span class="html-italic">S. aureus</span> (Gram-positive), and <span class="html-italic">C. albicans</span> (yeast), respectively. These fabrics have potential applications in protective clothing, packaging, and medical care. In silico modeling suggested that the predicted compound derived from AgNPs on cotton fabric could inhibit Penicillin-binding proteins (PBPs) and Lanosterol 14-alpha-demethylase (L-14α-DM), with binding energies of −4.7 and −5.2 Kcal/mol, respectively. Pharmacokinetic analysis and sensitizer prediction indicated that this compound merits further investigation.</div> </section> <div id="html-keywords"> <div class="html-gwd-group"><div id="html-keywords-title">Keywords: </div><a href="/search?q=nanoparticles">nanoparticles</a>; <a href="/search?q=silver">silver</a>; <a href="/search?q=green+synthesis">green synthesis</a>; <a href="/search?q=Aspergillus+flavus"><span class="html-italic">Aspergillus flavus</span></a>; <a href="/search?q=statistical+optimization">statistical optimization</a>; <a href="/search?q=characterization">characterization</a>; <a href="/search?q=cotton+fabrics">cotton fabrics</a>; <a href="/search?q=antimicrobial+activity">antimicrobial activity</a>; <a href="/search?q=molecular+docking+analysis">molecular docking analysis</a></div> <div> </div> </div> </div> </p> </div> </section> </div> <div class="hypothesis_container"> <ul class="menu html-nav" data-prev-node="#html-quick-links-title"> </ul> <div class="html-body"> <section id='sec1-jfb-15-00354' type='intro'><h2 data-nested='1'> 1. Introduction</h2><div class='html-p'>Nanotechnology, a rapidly expanding field, is focused on the fabrication and engineering of materials at an incredibly small scale of less than one micron [<a href="#B1-jfb-15-00354" class="html-bibr">1</a>]. The nanoparticles exhibit distinct properties from the bulk material because of their tiny size, quantum related effects, and high surface area-to-volume ratio [<a href="#B2-jfb-15-00354" class="html-bibr">2</a>]. Among them, silver nanoparticles (AgNPs) have attracted increasing interest due to their unique physicochemical characteristics. These characteristics include exceptional thermal and electrical conductivity, longer chemical stability, unique catalytic properties, their interaction with light through surface plasmon resonance, and unique optical properties [<a href="#B3-jfb-15-00354" class="html-bibr">3</a>]. The global industrial production of AgNPs has significantly increased, with predictions suggesting that the annual production will reach 800 tons by 2025 [<a href="#B4-jfb-15-00354" class="html-bibr">4</a>].</div><div class='html-p'>AgNPs have a wide range of potential applications, including agriculture, medicine, engineering, and environmental sciences. AgNPs applications include biosensors, bio-labeling materials, surface coating and medical device coating, optical receptors, catalysts in chemical and biochemical reactions, electronics, cosmetics, textiles [<a href="#B5-jfb-15-00354" class="html-bibr">5</a>,<a href="#B6-jfb-15-00354" class="html-bibr">6</a>]. AgNPs properties include antibacterial, antifungal, antiviral, anti-inflammatory, anti-angiogenic, and antitumor activities [<a href="#B5-jfb-15-00354" class="html-bibr">5</a>].</div><div class='html-p'>Traditionally, AgNPs have been fabricated employing chemical reduction and physical methods. The production of nanoparticles via traditional methods is extremely costly, and generates toxic, hazardous chemicals that pose environmental risks. Moreover, the potential sedimentation of chemicals on the surfaces of nanoparticles produced via these methods reduces their predicted purity. Consequently, synthesizing silver nanoparticles of the desired size may pose challenges, requiring an additional step to avoid particle aggregation [<a href="#B7-jfb-15-00354" class="html-bibr">7</a>]. Compared to conventional methods, green synthesis of nanoparticles offers a more feasible, non-toxic, eco-friendly and cost-effective alternative. For the green synthesis of nanoparticles, plant extract, fungi, yeast, bacteria, and even plant-derived materials were used as a reducing, capping, and stabilizing agent to aid in the green synthesis of AgNPs [<a href="#B8-jfb-15-00354" class="html-bibr">8</a>]. It has the potential to produce nanoparticles with diverse characteristics, which could lead to new and interesting applications [<a href="#B9-jfb-15-00354" class="html-bibr">9</a>]. Fungi are exceptional producers of diverse metabolites including amino acids, proteins, and enzymes. These substances facilitate the environmentally friendly production of nanoparticles (NPs) and enhance their stability. Furthermore, fungi present several benefits: they are easily managed, scalable for production, yield substantial biomass, exhibit minimal toxicity, and can generate NPs both internally and externally [<a href="#B10-jfb-15-00354" class="html-bibr">10</a>]. Fungal strains were used to synthesize eco-friendly metal and metal oxide nanoparticles including Ag, Au, Pt, Si, ZnO, ZrO<sub>2</sub>, Zr, TiO<sub>2</sub>, and Ti [<a href="#B11-jfb-15-00354" class="html-bibr">11</a>,<a href="#B12-jfb-15-00354" class="html-bibr">12</a>]. Fouda, et al. [<a href="#B13-jfb-15-00354" class="html-bibr">13</a>] highlighted the great efficacy of <span class='html-italic'>Aspergillus flavus</span> as a biocatalyst for the green synthesis of AgNPs.</div><div class='html-p'>The factor-by-factor technique, commonly referred as the traditional technique, is the first method for optimizing the biosynthesis process of nanoparticles. It involves changing one independent variable while keeping the other variables at their optimal values in order to identify the appropriate conditions [<a href="#B14-jfb-15-00354" class="html-bibr">14</a>]. The traditional factor-by-factor method has several disadvantages, including being time-consuming, expensive, labor-intensive, and requiring a lot of reagents and materials. Additionally, the interaction effects between the independent variables are ignored by the factor-by-factor technique [<a href="#B15-jfb-15-00354" class="html-bibr">15</a>]. A variety of mathematical and statistical methods can be applied to optimize multiple variables simultaneously. In contrast to conventional methods, Box-Behnken design (BBD) is a highly efficient response surface mathematical design that facilitates the elucidation of relationships between the studied variables and responses, optimizing multiple variables simultaneously, minimizing the overall experimental trials, defining the optimal process conditions, and maintaining a high degree of accuracy in the final result. Moreover, it is cost-effective, highly adaptable, and faster [<a href="#B16-jfb-15-00354" class="html-bibr">16</a>].</div><div class='html-p'>Cotton textiles are known for their excellent air permeability, high moisture absorption, and pleasant tactile sensations. Nanotechnology can enhance cotton garments with advanced features [<a href="#B17-jfb-15-00354" class="html-bibr">17</a>,<a href="#B18-jfb-15-00354" class="html-bibr">18</a>]. Zhou, et al. [<a href="#B19-jfb-15-00354" class="html-bibr">19</a>] demonstrated that plasma treatment can generate AgNPs on cotton fabric, improving its antibacterial properties. Additionally, combining silver nitrate (AgNO<sub>3</sub>) and <span class='html-italic'>Aloe vera</span> extract can imbue cotton fabrics with ultraviolet protection and antimicrobial activity through the in-situ production of AgNPs. In situ synthesis of AgNPs achieves appropriate particle deposition by eliminating the need for a separate reaction period [<a href="#B20-jfb-15-00354" class="html-bibr">20</a>].</div><div class='html-p'>Cellulose has shown no antibacterial properties against Gram-positive or Gram-negative bacteria, which has restricted its use in antibacterial applications. However, this polysaccharide can be modified by incorporating antibacterial agents, such as nanomaterials, to enable its use in the pharmaceutical, food packaging, and cosmetic industries [<a href="#B21-jfb-15-00354" class="html-bibr">21</a>]. In addition, cellulose can be modified by combining it with other polymers, nanoparticles, or biomaterials to produce composite materials. These composites exhibit enhanced characteristics such as greater tensile strength, superior barrier properties, and increased biocompatibility, making them suitable for applications in environmental cleanup, medical devices, and packaging [<a href="#B22-jfb-15-00354" class="html-bibr">22</a>].</div><div class='html-p'>Nonetheless, the high water content in cotton enriched with cellulose makes fibers more sensitive to microbial attack and creates an ideal environment for bacterial and fungal growth [<a href="#B23-jfb-15-00354" class="html-bibr">23</a>,<a href="#B24-jfb-15-00354" class="html-bibr">24</a>]. AgNPs, which have long been recognized as effective biocides with antibacterial activity, now have more applications in textiles. Smaller particle sizes result in greater antimicrobial effectiveness [<a href="#B25-jfb-15-00354" class="html-bibr">25</a>]. Furthermore, the effectiveness of AgNPs in combating microbial infections is attributed to their positive charge, which enables them to interface and damage the negatively charged microbial plasma membrane [<a href="#B26-jfb-15-00354" class="html-bibr">26</a>]. This interaction effectively inhibits microbial growth and prevents the spread of infection. In the realm of medical devices, coatings containing AgNPs can improve their performance by endowing them with antimicrobial properties. Jain, et al. [<a href="#B27-jfb-15-00354" class="html-bibr">27</a>] demonstrated that fabrics treated with AgNPs exhibited the strongest antibacterial effect against <span class='html-italic'>Bacillus licheniformis</span>, with 93.3% inhibition. The same fabric displayed moderate effectiveness against <span class='html-italic'>Klebsiella pneumoniae</span> and <span class='html-italic'>Escherichia coli</span> with inhibition rates of 20% and 10%, respectively. Patil, et al. [<a href="#B28-jfb-15-00354" class="html-bibr">28</a>] found that cotton fabrics infused with AgNPs have outstanding antibacterial properties against gram-positive and gram-negative microorganisms, such as <span class='html-italic'>Bacillus subtilis, Pseudomonas aeruginosa</span>, <span class='html-italic'>Staphylococcus aureus</span>, and <span class='html-italic'>Escherichia coli</span>.</div><div class='html-p'>Silver nanoparticles (AgNPs) have been confirmed as an amazing antimicrobial agent due to their broad-spectrum antimicrobial actions against Gram-positive and Gram-negative bacteria, fungi, viruses, and mycobacteria. When microorganisms are exposed to AgNPs, silver ions are continuously released from the nanoparticles. Microorganisms are killed by the constant release of silver ions from AgNPs, free silver ions absorbed by cells inhibit respiratory enzymes, which results in the production of reactive oxygen species (ROS) that interfere with the synthesis of adenosine triphosphate. ROS serves as the primary agents responsible for inducing DNA alterations and damaging cell membranes [<a href="#B29-jfb-15-00354" class="html-bibr">29</a>]. Also, silver ions readily adhere to the cell wall and cytoplasmic membrane due to their close association with sulfur proteins and the influence of electrostatic attraction [<a href="#B30-jfb-15-00354" class="html-bibr">30</a>]. The binding of AgNPs to microbial membranes induces irreversible morphological alterations in the cell membrane structure and the changes in cell structure can lead to increased permeability of the cell membrane, subsequently impacting the cell’s ability to regulate its activities effectively [<a href="#B31-jfb-15-00354" class="html-bibr">31</a>]. Molecular docking is utilized to determine ligand and receptor interactions. Although prediction tools for computational synthesis are currently not widely integrated, this situation is anticipated to evolve rapidly as the field progresses rapidly [<a href="#B32-jfb-15-00354" class="html-bibr">32</a>]. Quantitative Structure-Activity Relationship (QSAR) modeling serves as a vital computational method in medicinal chemistry and toxicology research. This method is instrumental for identifying new bioactive compounds and evaluating their chemical safety. The models generated through QSAR were then applied to forecast the desired properties of unexplored or untested substances [<a href="#B33-jfb-15-00354" class="html-bibr">33</a>].</div><div class='html-p'>Our study focused on the green synthesis of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>Aspergillus flavus</span>. To optimize the process, BBD was employed, considering four crucial factors: incubation duration (X<sub>1</sub> in hours), starting pH (X<sub>2</sub>), silver nitrate concentration (X<sub>3</sub> in mM/mL), and temperature (X<sub>4</sub> in °C). The biosynthesized AgNPs were then characterized, and their antibacterial efficacy was assessed using the disc diffusion technique with AgNPs-loaded cotton fabrics. Additionally, computational and forward synthesis techniques was utilized to anticipate the interaction between AgNPs produced by the aqueous mycelial-free filtrate of <span class='html-italic'>Aspergillus flavus</span> and cotton fabrics, regarded as the most unadulterated form of cellulose, containing roughly 90% cellulose. The study also aimed to predict the resulting compound’s potential for human skin sensitization and pharmacokinetic characteristics.</div></section><section id='sec2-jfb-15-00354' type=''><h2 data-nested='1'> 2. Materials and Methods</h2><section id='sec2dot1-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.1. Fungal Isolate and Biomass Preparation</h4><div class='html-p'><span class='html-italic'>Aspergillus</span> sp. obtained from the Mycology Laboratory at Mansoura University’s Faculty of Science, Egypt, was cultured on Potato Dextrose Agar (PDA) plates prepared by combining potato extract (200 g), dextrose (20 g), and agar (20 g) in 1 L of distilled water, followed by autoclaving at 121 °C for 20 min. The cultured <span class='html-italic'>Aspergillus</span> sp. was incubated at 25 °C for five days and stored at 4 °C for subsequent AgNPs synthesis.</div></section><section id='sec2dot2-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.2. Fungal Morphological and Molecular Identification</h4><div class='html-p'>Two microscopic methodologies were used to determine the fungus’s morphological characteristics: (1) The fungal isolate’s vegetative and reproductive structures were examined using a digital light microscope (Optika Model B-380 Ver. 2, Italy) with 100× and 400× magnification and (2) The isolate was examined using scanning electron microscopy (SEM) (JSM-6510 L.V, JEOL Ltd., Tokyo, Japan) at the Electron Microscope Unit at Mansoura University in Egypt. After drying, the specimen was mounted on metallic stubs and sputter-coated with a thin layer of gold prior to imaging [<a href="#B34-jfb-15-00354" class="html-bibr">34</a>]. <span class='html-italic'>Aspergillus</span> sp. was then identified using 18S rDNA gene sequence analysis. The extraction of DNA from the fungal isolate and the amplification of the 18S rDNA gene region by PCR are the steps in this method. Subsequently, the precise fungal species was identified by comparing the DNA sequence obtained to the NCBI GenBank database.</div><div class='html-p'>DNA was isolated using the CTAB technique, as outlined by Doyle [<a href="#B35-jfb-15-00354" class="html-bibr">35</a>] to obtain DNA from the fungal mycelium. The Internal Transcribed Spacer (ITS) region was amplified for molecular identification of <span class='html-italic'>Aspergillus</span> sp. using Primer3 software (<a href='https://primer3.org/' target='_blank' rel="noopener noreferrer">https://primer3.org/</a> (accessed on 1 August 2023)) [<a href="#B36-jfb-15-00354" class="html-bibr">36</a>] designed primers 5′-AGAAACGGCTACCACATCCA-3′ (forward) and 5′-TCTGGACCTGGTGAGTTTCC-3′ (reverse), synthesized by BIONEER Inc. (Oakland, CA, USA) targeting this conserved fungal identification region. The 18S rDNA region of the selected isolate was PCR-amplified in a 50 μL reaction containing 25–50 ng DNA, 50 mM primers, 0.5 U/μL Taq DNA polymerase, and 0.2 mM each dNTP. The protocol included denaturation at 94 °C for 6 min; 35 cycles of denaturation at 94 °C for 45 s, annealing at 56 °C for 45 s, and synthesis at 72 °C for 45 s; and a final extension at 72 °C for 5 min. PCR products were stored at −20 °C and visualized on a 2% agarose gel with 0.5 μg/mL ethidium bromide using a MicroDoc gel documentation system (Cleaver Scientifc Ltd., Rugby, UK).The 18S rDNA gene sequence, obtained using an ABI 3730XL DNA Analyzer (Applied Biosystems, Waltham, MA, USA) and edited with Finch (version 1.4.0), was analyzed using BLAST (<a href='http://blast.ncbi.nlm.nih.gov' target='_blank' rel="noopener noreferrer">http://blast.ncbi.nlm.nih.gov</a> (accessed on 30 September 2023)). Mega 11 [<a href="#B37-jfb-15-00354" class="html-bibr">37</a>] was used to construct phylogenetic tree. A comparison of the fungus’s 18S rDNA gene sequence to known sequences in the NCBI GenBank database was conducted using BLASTn and neighbor-joining to investigate its evolutionary relationships [<a href="#B38-jfb-15-00354" class="html-bibr">38</a>], The sequenced gene was deposited in the database for future reference and sharing.</div></section><section id='sec2dot3-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.3. Extracellular Synthesis of AgNPs Using A. flavus</h4><div class='html-p'>Extracellular AgNPs synthesis using <span class='html-italic'>A. flavus</span> involves cultivating fungal biomass on PDA plates. After incubation, the biomass was filtered and washed with sterile dH<sub>2</sub>O to eliminate the residual media, and 10 g (wet weight) of this biomass was incubated in 100 mL of sterile deionized H<sub>2</sub>O for 24 h at 25 ± 1 °C with agitation at 150 rpm. In order to prevent the photooxidation of silver ions, AgNO<sub>3</sub> was added in the dark to achieve a final concentration of 1 mM. Control flasks with the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> were prepared under the same conditions but without Ag<sup>+</sup> ions. Different AgNPs concentration series (10–100 μg/mL) was obtained by diluting AgNPs stock solution (500 μg/mL) with deionized water. Those standards were measured together with samples to obtain the corresponding UV-Vis and the calibration curve for calculating sample concentrations.</div></section><section id='sec2dot4-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.4. The Optimization of AgNPs Biosynthesis: A Box-Behnken Design Approach</h4><div class='html-p'>To optimize the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>, the Box-Behnken design was employed. The goal of this method is to investigate the interactions between the process variables and optimize the response (amount of AgNPs yield). Four independent variables were assessed: incubation time (h) (X<sub>1</sub>), initial pH (X<sub>2</sub>), AgNO<sub>3</sub> concentration in mM/mL (X<sub>3</sub>), and temperature (°C) (X<sub>4</sub>). Each variable was tested at three levels (−1, 0, and 1). In total, 29 experimental runs were carried out. To analyze the results, a second-order polynomial equation was utilized. This equation mathematically delineates the connection between the coded independent variables and anticipated AgNPs yield:</div><div class='html-p'>The following second-order polynomial equation was applied to analyze the relationship between the independent variables and the predicted AgNPs:<div class='html-disp-formula-info' id='FD1-jfb-15-00354'> <div class='f'> <math display='block'><semantics> <mrow> <mi mathvariant="normal">Y</mi> <mo>=</mo> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> <mo>+</mo> <mrow> <munder> <mo stretchy="false">∑</mo> <mrow> <mi mathvariant="normal">i</mi> </mrow> </munder> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> </msub> <mo>+</mo> <mrow> <munder> <mo stretchy="false">∑</mo> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">i</mi> </mrow> </munder> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">i</mi> </mrow> </msub> <msubsup> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> <mo>+</mo> </mrow> </mrow> </mrow> </mrow> <mrow> <munder> <mo stretchy="false">∑</mo> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">j</mi> </mrow> </munder> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">j</mi> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">j</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math> </div> <div class='l'> <label >(1)</label> </div> </div> Y: Predicted AgNPs yield; <math display='inline'><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math>: Regression coefficient; <math display='inline'><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> </msub> </mrow> </semantics></math>: Linear coefficients; <math display='inline'><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> </mrow> </msub> <mtext> </mtext> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">n</mi> <mi mathvariant="normal">d</mi> <mtext> </mtext> <msub> <mrow> <mi mathvariant="normal">X</mi> </mrow> <mrow> <mi mathvariant="normal">j</mi> </mrow> </msub> </mrow> </semantics></math>: Levels of the independent variables; <math display='inline'><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">i</mi> </mrow> </msub> </mrow> </semantics></math>: Quadratic coefficients; <math display='inline'><semantics> <mrow> <msub> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> <mrow> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">j</mi> </mrow> </msub> </mrow> </semantics></math>: Interaction coefficients.</div></section><section id='sec2dot5-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.5. Characterization of Bio-Synthesized AgNPs</h4><div class='html-p'>Various techniques have been employed to characterize the biosynthesized AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. These techniques offer crucial insights into the shape, dimensions, surface chemistry, crystallinity, and stability of the NPs.</div><section id='sec2dot5dot1-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.1. Ultraviolet-Visible (UV-Vis) Spectral Analysis</h4><div class='html-p'>AgNPs formation was assessed using UV-Vis spectroscopy following the method described by Basavaraja, et al. [<a href="#B39-jfb-15-00354" class="html-bibr">39</a>]. A Uni Camry UV-VIS Spectrometer UV2 (USA) was used to measure the absorption spectrum of the AgNPs solution between 300 and 700 nm, with deionized water as a blank for background correction. A characteristic peak in the visible spectrum, termed surface plasmon resonance (SPR), indicates the formation of AgNPs.</div></section><section id='sec2dot5dot2-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.2. Scanning Electron Microscopy (SEM) Analysis</h4><div class='html-p'>SEM was used to analyze the dimensions and structure of AgNPs. The sample was prepared by depositing a drop of the centrifuged AgNPs suspension onto a clean glass surface and allowing water to evaporate, leaving AgNPs on the substrate. SEM analysis, performed with a JEOL JSM-6510 L.V low-vacuum SEM at an accelerating voltage of 30 kV, revealed details regarding the size, shape, and surface characteristics of individual AgNPs.</div></section><section id='sec2dot5dot3-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.3. Transmission Electron Microscopy (TEM) Analysis</h4><div class='html-p'>TEM provides high-resolution images of AgNPs, enabling detailed analysis of their size and structure. A drop of the AgNPs suspension was placed on a carbon-coated grid (Type G 200, 3.05 μm diameter, EMS, Hatfield, PA, USA) and dried under an infrared lamp. The sample was then examined with a JEOL JEM 2100 (Tokyo, Japan) microscope at Mansoura University, Egypt, operating at 200 kV. This method, as described by Wang [<a href="#B40-jfb-15-00354" class="html-bibr">40</a>], offers vital insights into the size distribution, morphology, and crystalline structure of AgNPs.</div></section><section id='sec2dot5dot4-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.4. Selected Area Electron Diffraction (SAED) Pattern</h4><div class='html-p'>SAED analysis was employed to examine the crystalline structure of the produced AgNPs. The SAED pattern shows concentric diffraction rings, which describe the crystal planes and lattice structure of the NPs [<a href="#B38-jfb-15-00354" class="html-bibr">38</a>]. This technique usually requires a very thin sample with a thickness of approximately 100 nm and high-energy electrons with an energy of 100–400 keV to interact with the material as waves instead of particles.</div></section><section id='sec2dot5dot5-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.5. Zeta Potential Distribution</h4><div class='html-p'>The Zeta potential of the AgNPs was detected utilizing a Zeta Potential Analyzer (Zetasizer ver. 7.01; Malvern Instruments, Westborough, MA, USA) to determine their stability. Specifically, 5 mg of AgNPs were combined with 5 mL of ultrapure water and stirred at room temperature for 30 min. Zeta potential was measured using an EM unit at Mansoura University, Egypt, at a 90° detection angle. This value reflects the surface charge of the NPs, and a high absolute value (+ve or −ve) indicates good colloidal stability owing to electrostatic repulsion between particles.</div></section><section id='sec2dot5dot6-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.6. Energy-Dispersive X-Ray Spectroscopy (EDX) Analysis</h4><div class='html-p'>Energy-dispersive X-ray Spectroscopy (EDX) was used to confirm the composition of the AgNPs using an X-ray microanalyzer (Oxford 6587 INCA) attached to a JEOL JSM-5500 LV SEM at 20 kV. The EDX spectrum, taken in the spot profile mode from a densely populated AgNPs area on the sample surface [<a href="#B41-jfb-15-00354" class="html-bibr">41</a>], showed a significant Ag signal, verifying the presence of metallic Ag in the NPs.</div></section><section id='sec2dot5dot7-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.7. X-Ray Diffractometer (XRD) Analysis</h4><div class='html-p'>XRD analysis was employed to detect the crystalline structures of the produced dried powder of AgNPs. The analysis was performed with XRD (Shimadzu Xlab 6100, Japan) at Japan University of Science and Technology, Egypt. The values of 2θ were measured between 20° to 80°. The X-ray diffractometer was operated with continuous scanning at 40 kV, a current of 30 mA and a speed of scanning of 12°/min.</div></section><section id='sec2dot5dot8-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.5.8. Fourier Transform Infrared (FTIR) Spectroscopy</h4><div class='html-p'>FTIR spectroscopy, performed at a 4 cm<sup>−1</sup> resolution over wavenumbers from 400 to 4000 cm<sup>−1</sup>, identified functional groups on the biosynthesized AgNPs, revealing adsorbed biomolecules that influence their stability and biological activity. The samples were prepared by dispersing AgNPs in a dry KBr matrix, compressing them into a clear disc, and analyzing them using a JASCO FTIR spectrometer (Tokoyo, Japan) with a KBr pellet standard at the Faculty of Science, Mansoura University, Egypt.</div></section></section><section id='sec2dot6-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.6. Evaluation of Antimicrobial Activity Using AgNPs-Loaded Cotton Fabrics</h4><div class='html-p'>Cotton fabrics were employed as an innovative delivery mechanism for the biosynthesized AgNPs to assess their antimicrobial effectiveness. The cotton fabrics were subjected to comprehensive washing, disinfection, and air-drying procedures, following the methods outlined by Durán, et al. [<a href="#B42-jfb-15-00354" class="html-bibr">42</a>]. Subsequently, AgNPs were applied to the fabric surface and then cut into 1 cm × 1 cm squares [<a href="#B43-jfb-15-00354" class="html-bibr">43</a>]. The fabric pieces were left to dry in the air. The effectiveness of AgNPs -loaded fabrics was tested against Gram-positive bacteria (<span class='html-italic'>Staphylococcus aureus</span>), Gram-negative bacteria (<span class='html-italic'>Escherichia coli</span>), and yeast (<span class='html-italic'>Candida albicans</span>) cultured on Luria-Bertani (LB) agar plates. The disc diffusion technique was applied to assess the antimicrobial potency. AgNPs-loaded fabric squares measuring 1 cm × 1 cm were positioned on the inoculated agar plates. To determine the influence of AgNPs independently, a control group (sterile cotton fabrics without AgNPs) were used. The inoculated plates were incubated at 30 °C. Following the incubation time, the plates were assessed for the presence of inhibition zones (clear areas surrounding the fabric squares). The inhibition zones demonstrate the suppression of microbial growth by AgNPs. The diameter of these zones was measured in millimeters to quantify the efficacy of antibacterial activity [<a href="#B43-jfb-15-00354" class="html-bibr">43</a>].</div></section><section id='sec2dot7-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.7. Molecular Docking Approach</h4><section id='sec2dot7dot1-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.7.1. Ligand Preparation</h4><div class='html-p'>From the PubChem database, the 3D structure of cellulose (Pumchem CID: 16211032), which has the chemical formula C1<sub>2</sub>H<sub>22</sub>O<sub>11</sub>, was retrieved in the SDF format. Following this, Avogadro 1.2.0 software [<a href="#B44-jfb-15-00354" class="html-bibr">44</a>] was employed to conduct energy minimization using the MMFF94 force field.</div></section><section id='sec2dot7dot2-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.7.2. Forward Reaction Prediction</h4><div class='html-p'>To gain insight into the various combined reactions between cellulose (in the form of cotton fabric) and biosynthesized AgNPs, a forward reaction prediction method was employed. The ASKCOS MIT [<a href="#B45-jfb-15-00354" class="html-bibr">45</a>] system (<a href='https://askcos.mit.edu/forward?tab=forward' target='_blank' rel="noopener noreferrer">https://askcos.mit.edu/forward?tab=forward</a> (accessed on 30 September 2024)) was used to forecast all the potential forward reactions. The process utilized all previously prepared files in SDF format for the reaction, with default settings.</div></section><section id='sec2dot7dot3-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.7.3. Protein Preparation</h4><div class='html-p'>Penicillin-binding proteins (PBPs) are key targets of beta-lactam antibiotics and have an essential role in the synthesis and maintenance of bacterial cell walls. These proteins are located in the periplasm and are associated with the membranes. Bacteria have developed various resistance strategies, including modification of target enzymes to decrease their attraction to beta-lactam antibiotics. We examined a protein structure from the database, identified as PDB ID: 1QMF, with a Resolution of 2.80 Å, which was crystallized using X-ray diffraction techniques [<a href="#B46-jfb-15-00354" class="html-bibr">46</a>]. In addition, we investigated lanosterol 14-alpha-demethylase (L-14α-DM), an enzyme that functions as a valuable pharmacological target for a wide spectrum of anticandidal and antifungal treatments in eukaryotic organisms, including humans. This enzyme is effective against commensal and pathogenic fungi. For this part of the study, we analyzed the protein structure from the database labeled PDB ID: 5V5Z, with a resolution of 2.90 Å, also crystallized through X-ray diffraction methods [<a href="#B47-jfb-15-00354" class="html-bibr">47</a>].</div></section><section id='sec2dot7dot4-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.7.4. Molecular Docking Process</h4><div class='html-p'>AutoDockTools-1.5.7 Świątek, et al. [<a href="#B48-jfb-15-00354" class="html-bibr">48</a>] was utilized to simulate the attachment of biologically synthesized AgNPs to cotton fabrics at the protein-binding site. The results of the ligand-target docking process were subsequently cataloged based on the binding energy (∆G) in kcal/mol. BIOVIA Discovery Studio 2021 [<a href="#B46-jfb-15-00354" class="html-bibr">46</a>] was employed to depict the molecular docking interactions between the protein receptors and docked predicted molecules.</div></section><section id='sec2dot7dot5-jfb-15-00354' type=''><h4 class='' data-nested='3'> 2.7.5. ADMET, Pharmacokinetics, and Skin Sensitization Prediction of Products Generated from AgNPs-Loaded Cotton Fabrics</h4><div class='html-p'>The online computational platform Swiss-ADME (<a href='http://www.swissadme.ch/' target='_blank' rel="noopener noreferrer">http://www.swissadme.ch/</a> (accessed on 1 October 2024)) was used to determine ADMET and pharmacokinetic profiles [<a href="#B49-jfb-15-00354" class="html-bibr">49</a>]. Beginning with the SMILES formula, this tool enables the calculation of a chemical compound’s physicochemical characteristics, pharmacokinetic properties, and drug-likeness with a predictive accuracy between 72% and 94%. Furthermore, the Pred-Skin computational tool was used to evaluate chemically induced skin sensitization [<a href="#B50-jfb-15-00354" class="html-bibr">50</a>].</div></section></section><section id='sec2dot8-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 2.8. Statistical Analysis</h4><div class='html-p'>The optimization design was generated using Design-Expert software (Version 7.0.0, created by Stat-Ease, Inc., Minneapolis, MN, USA). Experimental data were analyzed using ANOVA via multiple regression analysis, determining <span class='html-italic'>p</span>-value, <span class='html-italic'>f</span>-value, and confidence levels, alongside the calculation of the determination coefficient (<span class='html-italic'>R</span><sup>2</sup>) and adjusted <span class='html-italic'>R</span><sup>2</sup>. STATISTICA software (Version 8, StatSoft, Inc., Tulsa, OK, USA) was utilized to generate three-dimensional surface plots for visualization purposes.</div></section></section><section id='sec3-jfb-15-00354' type='results'><h2 data-nested='1'> 3. Results and Discussion</h2><div class='html-p'>Nanoparticles, which typically range in size from 1 to 100 nm, are an interesting class of materials in nanotechnology. Although traditional chemical and physical synthesis approaches usually require tight control measures, this study investigates a potential alternative: a biological approach to nanoparticles synthesis. This alternative approach has various advantages over traditional methods. First, biological processes have the ability to produce NPs with an uniform size distribution, which is critical for optimal performance in various applications [<a href="#B51-jfb-15-00354" class="html-bibr">51</a>]. Second, biological methods provide a significant cost advantage over chemical and physical procedures for NPs synthesis. Third, these methods frequently reduce the usage of harsh chemicals, lessening the environmental impact [<a href="#B51-jfb-15-00354" class="html-bibr">51</a>]. Finally, biologically synthesized nanoparticles may be more biocompatible than chemically generated NPs.</div><div class='html-p'>Fungi are emerging as powerful bio-synthesizers for NPs due to their ability to produce enormous quantities of extracellular enzymes that might facilitate downstream processing and improve nanoparticles characteristics. In comparison to bacteria, fungi are capable of producing a greater quantity of NPs due to their increased production of proteins, which are involved in the synthesis of nanoparticles. Consequently, fungi constitute a sustainable and promising source for nanoparticles production [<a href="#B52-jfb-15-00354" class="html-bibr">52</a>]. AgNPs were synthesized in this study using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> in a simple, rapid, environmentally friendly, and cost-effective approach. The metabolites reduced and stabilized Ag<sup>+</sup> ions, transforming them into Ag<sup>0</sup>. Furthermore, the production of Ag-NPs using <span class='html-italic'>A. flavus</span> was previously reported by Gopa and Pullapukuri [<a href="#B53-jfb-15-00354" class="html-bibr">53</a>].</div><section id='sec3dot1-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.1. Identification of A. flavus</h4><div class='html-p'><span class='html-italic'>Aspergillus</span> sp. strain SF-4 was first identified according to the macroscopic and microscopic morphological features. Molecular identification was performed to identify isolate at the species level. <span class='html-italic'>Aspergillus</span> sp. strain SF-4 displayed a yellowish green aerial hyphal growth (<a href="#jfb-15-00354-f001" class="html-fig">Figure 1</a>A). The microscopic characteristics of the fungus are depicted in <a href="#jfb-15-00354-f001" class="html-fig">Figure 1</a>B,C displaying septate, branched mycelium, vesicle, and conidia. <a href="#jfb-15-00354-f001" class="html-fig">Figure 1</a>D shows the SEM image of <span class='html-italic'>Aspergillus</span> sp. strain SF-4, produced abundant conidiophores with abundant spherical conidia in long chains.</div><div class='html-p'>At the molecular level, the identification of fungal species is shown in <a href="#jfb-15-00354-f002" class="html-fig">Figure 2</a>. To accomplish this, genomic DNA was extracted from the mycelia of the fungus and the ITS gene region was amplified using specific primers. The resulting PCR products were then purified and sequenced. Subsequently, the BLAST search tool was employed for comparison of the obtained sequence data with all the available fungal sequences from the GenBank database. The phylogenetic analysis in <a href="#jfb-15-00354-f002" class="html-fig">Figure 2</a> indicated that the present sequences are identical to the ITS sequences of <span class='html-italic'>Aspergillus flavus</span> strain SF-4. The phylogenetic tree has been divided into two primary groups. One of these groups was further divided into two subgroups, one of which contained our isolate with accession number MH511139 and five additional species. The isolate was most closely related to the <span class='html-italic'>Aspergillus flavus</span> strain I.P-7 (MH511107) species with 98% matching, and the second cluster consisted of three species. According to the study of ITS gene sequence, together with its phenotypic characteristics, the <span class='html-italic'>Aspergillus</span> sp. strain SF-4 (MH511139) was identified as <span class='html-italic'>Aspergillus flavus</span> strain SF-4. These results were agreed with Derbalah, et al. [<a href="#B54-jfb-15-00354" class="html-bibr">54</a>].</div></section><section id='sec3dot2-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.2. Extracellular Synthesis of AgNPs Using A. flavus</h4><div class='html-p'><a href="#jfb-15-00354-f003" class="html-fig">Figure 3</a>A,B show that the reaction mixture turned brown, indicating the biosynthesis of AgNPs [<a href="#B44-jfb-15-00354" class="html-bibr">44</a>].The intensity of the color correlates with the number of electrons generated from the reduction of NO<sub>3</sub> to NO<sub>2</sub>, facilitating the conversion of Ag<sup>+</sup> into metallic ions (Ag<sup>0</sup>) [<a href="#B45-jfb-15-00354" class="html-bibr">45</a>]. UV/VIS spectral analysis was conducted to characterize the biosynthesized AgNPs, covering the range 300–700 nm, as depicted in <a href="#jfb-15-00354-f003" class="html-fig">Figure 3</a>C. The AgNPs displayed a characteristic single peak in their optical absorption spectrum, with the maximum absorbance occurring at 426 nm. Brause, et al. [<a href="#B55-jfb-15-00354" class="html-bibr">55</a>] proposed that the optical absorption spectrum of metallic nanoparticles is primarily influenced by the surface plasmon resonance (SPR) phenomenon. They also observed a direct correlation between the absorption peak location and the particles dimensions. Research by Fouda, et al. [<a href="#B13-jfb-15-00354" class="html-bibr">13</a>] demonstrated that while the absorption increased, the maximum SPR peak remained constant at 415 nm. They explained this phenomenon as a result of the total elimination of Ag<sup>+</sup> ions, which led to an intensification of color after 15 days.</div></section><section id='sec3dot3-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.3. Optimizing AgNPs Biosynthesis Using Box-Behnken Design (BBD)</h4><div class='html-p'>In the current study, the effects of four bioprocess variables on the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> were assessed. These variables were the AgNO<sub>3</sub> conc. (mM), initial pH level, temperature (°C), and incubation time (h). BBD was used to determine the optimal values for these variables that maximize the biosynthesis of AgNPs. As well as, to investigate the individual, interaction, and quadratic effects of these variables on the biosynthesis of AgNPs. <a href="#jfb-15-00354-t001" class="html-table">Table 1</a> shows that each variable was assessed at three distinct levels (−1, 0, and 1). BBD involved 29 experimental runs, with six of these (runs 1, 2, 10, 13, 27, and 28) situated at the central point. According to <a href="#jfb-15-00354-t001" class="html-table">Table 1</a>, run No. 25 yielded the lowest AgNPs biosynthesis of 8.19 µg/mL, which was achieved under the following conditions: pH of 7, incubation time of 48 h, silver nitrate concentration of 1 mM/mL, and a temperature of 25 °C. Conversely, the highest biosynthesis of AgNPs achieved was 235.03 µg/mL in run No. 22, which was performed under the following conditions: pH of 8, an incubation duration of 72 h, a silver nitrate concentration of 3 mM/mL, and a temperature of 30 °C. <a href="#jfb-15-00354-t001" class="html-table">Table 1</a> shows the results obtained for both the synthesized AgNPs and the anticipated values. Notably, the actual results closely matched the predicted outcomes for the AgNPs.</div></section><section id='sec3dot4-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.4. Model Fitting</h4><div class='html-p'>The BBD data for the biosynthesized AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> was subjected to statistical analysis through multiple regression and analysis of variance (ANOVA). The ANOVA results are summarized in <a href="#jfb-15-00354-t002" class="html-table">Table 2</a>. The coefficient of determination (<span class='html-italic'>R</span>²) serves as a statistical metric to assess the model’s fit. It quantifies the proportion of variance in the values of the response variable that can be attributed to the independent experimental variables and their mutual interactions [<a href="#B56-jfb-15-00354" class="html-bibr">56</a>]. According to the estimated <span class='html-italic'>R</span><sup>2</sup> value of 0.9994, the independent selected variables were responsible for 99.94% of the variance in the biosynthesized AgNPs, which were synthesized using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. Consequently, the model is unable to effectively describe only 0.06% of the total variance in the biosynthesized AgNPs. The <span class='html-italic'>R</span><sup>2</sup> value for a regression model generally falls between 0 and 1. A higher <span class='html-italic'>R</span><sup>2</sup> value, closer to 1, indicates that the model is more effective in predicting the response yield [<a href="#B57-jfb-15-00354" class="html-bibr">57</a>]. A regression models having an <span class='html-italic'>R</span><sup>2</sup> value greater than 0.9 was considered to be highly correlated [<a href="#B58-jfb-15-00354" class="html-bibr">58</a>]. The value of the adjusted <span class='html-italic'>R</span><sup>2</sup> was 0.9988, while the predicted <span class='html-italic'>R</span><sup>2</sup> was 0.9976. To ascertain the model’s significance and precision, the predicted <span class='html-italic'>R</span><sup>2</sup> and adjusted <span class='html-italic'>R</span><sup>2</sup> values must be within 20% of each other, indicating a substantial degree of agreement between the two metrics [<a href="#B59-jfb-15-00354" class="html-bibr">59</a>].</div><div class='html-p'><a href="#jfb-15-00354-t002" class="html-table">Table 2</a> represents the significance of each coefficient and the interactions effects between various factors, determined probability values (<span class='html-italic'>p</span>-values) and <span class='html-italic'>f</span>-values. Lower <span class='html-italic'>p</span>-values indicate higher significance of the corresponding coefficient. In addition, our findings indicated that the process variables with <span class='html-italic'>p</span>-values < 0.05 significantly influencing the biosynthesis of AgNPs. Process variables with <span class='html-italic'>p</span>-values less than 0.05 were considered to exert a significant effect on the response, hence validating the validity of the model terms [<a href="#B60-jfb-15-00354" class="html-bibr">60</a>].</div><div class='html-p'>The model <span class='html-italic'>f</span>-value of 1734.16 and a <span class='html-italic'>p</span>-value < 0.0001, suggesting a high level of significance. The <span class='html-italic'>p</span>-values less than 0.05 suggest that the linear coefficients of AgNO<sub>3</sub> conc. (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) are statistically significant and may function as limiting variables for the rate of biosynthesis of AgNPs with slight variations in their values. The <span class='html-italic'>f</span>-values for X<sub>1</sub>, X<sub>2</sub>, X<sub>3</sub>, and X<sub>4</sub> were 39.79, 11,471.09, 3146.50, and 1139.43; respectively. The quadratic coefficients (X<sub>1</sub><sup>2</sup>, X<sub>2</sub><sup>2</sup>, X<sub>3</sub><sup>2</sup> and X<sub>4</sub><sup>2</sup>) had significant <span class='html-italic'>p</span>-values of <0.0001 and <span class='html-italic'>f</span>-values of 971.13, 4741.96, 83.53, and 72.15, respectively. Based on the <span class='html-italic'>p</span>-values of the coefficient, it can be concluded that the interaction effects among combinations of X<sub>1</sub> X<sub>2</sub>, X<sub>1</sub> X<sub>4</sub>, X<sub>2</sub> X<sub>3</sub>, X<sub>2</sub> X<sub>4</sub> and X<sub>3</sub> X<sub>4</sub> are significant (<span class='html-italic'>p</span> < 0.0001). Nevertheless, the interaction effect between AgNO<sub>3</sub> concentration and temperature is not statistically significant.</div><div class='html-p'>Moreover, the signs (+ or −) of the calculated coefficients were utilized to understand their influence on the response variable yield [<a href="#B61-jfb-15-00354" class="html-bibr">61</a>]. The positive coefficients of linear effects for all variables (X<sub>1</sub>, X<sub>2</sub>, X<sub>3</sub>, X<sub>4</sub>) indicated an increase in the AgNPs biosynthesis.</div><div class='html-p'>Positive coefficients indicate synergistic interactions between two variables. While negative coefficients indicate antagonistic interactions between two variables.</div><div class='html-p'>The positive coefficients of the interaction effects between the different combinations of X<sub>1</sub> X<sub>2</sub>, X<sub>2</sub> X<sub>3</sub>, X<sub>2</sub> X<sub>4</sub>, X<sub>3</sub> X<sub>4</sub> and the quadratic coefficients (X<sub>2</sub><sup>2</sup>, and X<sub>4</sub><sup>2</sup>) suggested an increase in AgNPs biosynthesis. Furthermore, the negative coefficients for the interaction effects between X<sub>1</sub> X<sub>3</sub>, X<sub>1</sub> X<sub>4</sub>, as well as the quadratic coefficients (X<sub>1</sub><sup>2</sup>, X<sub>3</sub><sup>2</sup>), suggested a reduction in the AgNPs biosynthesis (<a href="#jfb-15-00354-t002" class="html-table">Table 2</a>). Notably, the statistically significant positive coefficients for the interaction effects between different variables (<span class='html-italic'>p</span> < 0.0001) demonstrated their significant contribution to the enhancement of AgNPs biosynthesis. The model’s accuracy was assessed using the signal-to-noise ratio, which can be analyzed by checking the adequate precision value. This value must exceed four in order to suggest a robust model. The current model’s adequate precision value is 167.47.</div><div class='html-p'><a href="#jfb-15-00354-t003" class="html-table">Table 3</a> presents the fit summary results. The fit summary was employed to identify the most appropriate model for synthesizing AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> among linear, two-factor interaction (2FI), and quadratic models. The fit summary results indicate that the quadratic model is the most significant model and the most appropriate model for synthesizing AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> with insignificant lack-of-fit test (<span class='html-italic'>f</span>-value = 0.65, <span class='html-italic'>p</span>-value = 0.735) and <span class='html-italic'>p</span>-value < 0.0001. The quadratic model displayed the highest values of <span class='html-italic'>R</span><sup>2</sup> adj. <span class='html-italic'>R</span><sup>2</sup> and predicted <span class='html-italic'>R</span><sup>2</sup> values of 0.9994, 0.9988 and 0.9976; respectively and the lower standard deviation value (1.87).</div><div class='html-p'>To explore the relationships between the independent variables [AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>)] and the dependent variable [predicted AgNPs biosynthesis (Y)], a second-order polynomial equation was employed. The following equation allows for the determination of optimal values for each independent variable that would lead to the highest predicted AgNPs biosynthesis. <div class='html-disp-formula-info' id=''> <div class='f'> Y = 72.88+ 3.41X<sub>1</sub> + 57.95X<sub>2</sub> + 30.35X<sub>3</sub> +18.26X<sub>4</sub> + 12.32X<sub>1</sub>X<sub>2</sub> − 1.93X<sub>1</sub>X<sub>3</sub> − 4.18X<sub>1</sub>X<sub>4</sub> + 17.61X<sub>2</sub>X<sub>3</sub> + 27.26X<sub>2</sub>X<sub>4</sub> + 6.72X<sub>3</sub>X<sub>4</sub> − 22.93X<sub>1</sub>² + 50.68X<sub>2</sub>² −6.73X<sub>3</sub>² + 6.25X<sub>4</sub>² </div> <div class='l'> <label >(2)</label> </div> </div></div><section id='sec3dot4dot1-jfb-15-00354' type=''><h4 class='' data-nested='3'> 3.4.1. Three-Dimensional (3D) Surface Plot</h4><div class='html-p'>The three-dimensional graphs are tools that are used for explaining the interactions between the various variables and to predict the most favorable conditions for the maximum response [<a href="#B62-jfb-15-00354" class="html-bibr">62</a>]. 3D response surface plots were applied in this study to investigate the pairwise interactions between initial pH level, time of incubation, concentration of AgNO<sub>3</sub>, and temperature, to identify the optimal conditions for maximizing AgNPs biosynthesis (<a href="#jfb-15-00354-f004" class="html-fig">Figure 4</a>). El-Naggar, et al. [<a href="#B63-jfb-15-00354" class="html-bibr">63</a>] reported that the temperature, initial pH level, silver nitrate concentration, and incubation time are crucial in AgNPs biosynthesis.</div><div class='html-p'>The 3D surface graphs (<a href="#jfb-15-00354-f004" class="html-fig">Figure 4</a>A–C) illustrated the effect of AgNO<sub>3</sub> concentration on AgNPs biosynthesis using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> when interacting with the other three factors: initial pH level, temperature and incubation period; respectively. The 3D surface plots indicate that AgNPs biosynthesis increased by the increasing the AgNO<sub>3</sub> concentration. The maximum AgNPs biosynthesis was obtained toward the center level of the AgNO<sub>3</sub> concentration (~3 mM/mL).</div><div class='html-p'>The 3D surface graphs (<a href="#jfb-15-00354-f004" class="html-fig">Figure 4</a>A,D,E) illustrated the effect of initial pH level on AgNPs biosynthesis using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> when interacting with the other three factors: AgNO<sub>3</sub> concentration, temperature, and incubation time; respectively. These plots reveal a positive correlation between initial pH and AgNPs yield. The maximum biosynthesis of AgNPs was found at an initial pH level of approximately 8. Several studies highlighted the significant impact of pH on the size, shape, and stability of AgNPs [<a href="#B64-jfb-15-00354" class="html-bibr">64</a>]. In this context, Khan and Jameel [<a href="#B65-jfb-15-00354" class="html-bibr">65</a>] reported that the maximum AgNPs was obtained at pH 8. In contrast, Singh, et al. [<a href="#B66-jfb-15-00354" class="html-bibr">66</a>] synthesized spherical AgNPs (12–17 nm) from the extract of hibiscus leaves at pH 6.</div><div class='html-p'>The 3D surface graphs (<a href="#jfb-15-00354-f004" class="html-fig">Figure 4</a>B,D,F) illustrated the effect of temperature on AgNPs biosynthesis using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> when interacting with the other three factors: AgNO<sub>3</sub> concentration, initial pH level and incubation time; respectively. The biosynthesis of AgNPs was found to increase as the temperature increased, as evidenced by the 3D surface plots. The highest AgNPs yield was achieved at a high temperature of 30–35 °C.</div><div class='html-p'>The 3D surface graphs (<a href="#jfb-15-00354-f004" class="html-fig">Figure 4</a>C,E,F) illustrated the effect of incubation period on AgNPs biosynthesis using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> when interacting with the other three factors: AgNO<sub>3</sub> concentration, initial pH level and temperature; respectively. The 3D surface plots indicate a positive correlation between the incubation time and AgNPs biosynthesis. AgNPs biosynthesis increased by increasing the incubation time. The highest AgNPs yield was obtained toward the high level of the incubation time (56–71 h).</div></section><section id='sec3dot4dot2-jfb-15-00354' type=''><h4 class='' data-nested='3'> 3.4.2. The Model’s Adequacy</h4><div class='html-p'>In <a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>A, the normal probability plot (NPP) illustrates that the data are normally distributed since the residuals are in line with a straight line. This indicates that the experimental results are consistent with the predicted data, which confirms the model’s accuracy [<a href="#B67-jfb-15-00354" class="html-bibr">67</a>].</div><div class='html-p'><a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>B shows the actual against predicted values of AgNPs biosynthesis. <a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>B illustrates that all data points are closely aligned with the prediction line. This signifies an appropriate correlation between the experimental and predicted data [<a href="#B68-jfb-15-00354" class="html-bibr">68</a>].</div><div class='html-p'>The Box-Cox plot in <a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>C shows the model transformation for the biosynthesis of AgNPs. The best lambda (<span class='html-italic'>λ</span> = 0.99) is marked by the green line in <a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>C, whereas the blue line indicates the current lambda (<span class='html-italic'>λ</span> = 1). The lowest and highest values of the 95% confidence interval, shown by red lines, ranges from 0.91 to 1.07. The current <span class='html-italic'>λ</span> locates between the two vertical red lines which suggests that the model fits well the experimental data and no need for data transformation [<a href="#B68-jfb-15-00354" class="html-bibr">68</a>].</div><div class='html-p'><a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>D represents the residual against the predicted values of AgNPs biosynthesis. <a href="#jfb-15-00354-f005" class="html-fig">Figure 5</a>D demonstrates the goodness-of-fit of the model, displaying randomly scattered residuals around the zero-line with a uniform distribution. This suggests that the experimental results variance is constant for all values, which are crucial for statistical precision [<a href="#B69-jfb-15-00354" class="html-bibr">69</a>].</div></section><section id='sec3dot4dot3-jfb-15-00354' type=''><h4 class='' data-nested='3'> 3.4.3. The Desirability Function</h4><div class='html-p'>The optimal conditions for maximal AgNPs biosynthesis were theoretically predicted using the desirability function, which was experimentally validated. The desirability function value ranges from 0 (undesirable) to 1 (desirable) [<a href="#B70-jfb-15-00354" class="html-bibr">70</a>]. Desirability functions are typically calculated mathematically before experimental validation [<a href="#B71-jfb-15-00354" class="html-bibr">71</a>]. The optimum predicted conditions for maximizing AgNPs biosynthesis, using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>, has been determined through the desirability function as follows: incubation time (58.12 h), initial pH (7.99), AgNO<sub>3</sub> concentration (4.84 mM/mL), and temperature (34.84 °C). The highest predicted value for the biosynthesized AgNPs was 235.72 µg/mL, as shown in <a href="#jfb-15-00354-f006" class="html-fig">Figure 6</a>. The highest experimental value of AgNPs biosynthesis under these conditions was 247.53 µg/mL. The validation demonstrated the high accuracy of the applied model.</div></section></section><section id='sec3dot5-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.5. Characterization of the Biosynthesized AgNPs</h4><div class='html-p'>The present study characterized AgNPs synthesized by <span class='html-italic'>A. flavus</span> using diverse methods, including UV-visible spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area diffraction pattern (SADP), energy-dispersive X-ray spectroscopy (EDX), zeta potential analysis, X-ray diffractometer (XRD) and FTIR transform infrared attributes.</div><div class='html-p'>The application of SEM in the investigation of AgNPs provided insights into the size and surface features of the NPs. The results proved that the AgNPs had uniformly sized spherical particles as observed in <a href="#jfb-15-00354-f007" class="html-fig">Figure 7</a>A, as opposed to any irregular shape, and were free of agglomeration. The sizes of the synthesized nanoparticles varied between 1–50 nm, although a few particles displayed signs of clustering [<a href="#B72-jfb-15-00354" class="html-bibr">72</a>].</div><div class='html-p'>The TEM micrographs revealed the morphology and size distribution of the particles, ranging from 8.93 to 19.11 nm. The micrograph depicts both individual and aggregated particles, with a capping agent maintaining separation and causing repulsion between protein-based NPs. Spherical nanosilver particles were observed (<a href="#jfb-15-00354-f007" class="html-fig">Figure 7</a>B). Particles of varied shapes and sizes, similar to biological systems, are commonly observed [<a href="#B73-jfb-15-00354" class="html-bibr">73</a>]. Fouda, et al. [<a href="#B13-jfb-15-00354" class="html-bibr">13</a>] reported synthesized Ag-NPs ranging from 3 to 28 nm, averaging 12.5 ± 5.1 nm. Raza, et al. [<a href="#B74-jfb-15-00354" class="html-bibr">74</a>] found that 15 nm spherical nanoparticles were more toxic to Gram-negative bacteria <span class='html-italic'>Escherichia coli</span> and <span class='html-italic'>Pseudomonas aeruginosa</span> than larger spherical and triangular shapes. Therefore, we expect the AgNPs synthesized in this study to exhibit high activity owing to their smaller size.</div><div class='html-p'>Crystallographic experiments, including selected area diffraction pattern (SADP) analyses, were performed TEM. The SADP technique enables the investigation of separate droplets from nano-colloidal mixtures, revealing the diffraction pattern of nano-silver as luminous points against a dark field. The presence of distinctive diffraction rings in this pattern verifies the crystalline nature and successful production of nano silver [<a href="#B64-jfb-15-00354" class="html-bibr">64</a>], as illustrated in <a href="#jfb-15-00354-f007" class="html-fig">Figure 7</a>C.</div><div class='html-p'>Energy-dispersive X-ray spectroscopy (EDX) was employed to analyze the characteristics, distribution, and concentration of elements in AgNPs using TEM as illustrated in <a href="#jfb-15-00354-f007" class="html-fig">Figure 7</a>D. EDX spectrum provided strong evidence for silver as the dominant element in the AgNPs. The fabrication process of AgNPs may cause structural changes; therefore, EDX can help detect variations. EDX spectrum showed peaks around 3.40 keV, corresponding to AgL [<a href="#B75-jfb-15-00354" class="html-bibr">75</a>]. As shown in <a href="#jfb-15-00354-f007" class="html-fig">Figure 7</a>D, these peaks might also be attributed to biomolecules adhering to the AgNPs surface.</div><div class='html-p'>To assess the repulsive forces between the generated AgNPs, the zeta potential of the biogenic AgNPs was measured. As shown in <a href="#jfb-15-00354-f008" class="html-fig">Figure 8</a>A, a single peak with a value of +1.69 mV indicated repulsion among the particles. The zeta potential is of paramount significance for ensuring the stability of nanoparticles. Highly positive or negative zeta potential values result in strong repulsion, which effectively prevents aggregation [<a href="#B76-jfb-15-00354" class="html-bibr">76</a>]. Conversely, low zeta potential values indicate weak repulsive forces, facilitating particle aggregation and cluster formation.</div><div class='html-p'>X-ray diffraction (XRD) analysis is considered one of the simplest, universally recognized analytical techniques, to prove the construction of nanoparticles, and evaluate its crystal structures [<a href="#B77-jfb-15-00354" class="html-bibr">77</a>]. As presented in <a href="#jfb-15-00354-f008" class="html-fig">Figure 8</a>B, the XRD diffractogram of AgNPs, showed brilliant crystal quality and revealed the presence of 4 discrete intense diffraction peaks at 2θ° over the entire spectrum, which ranged from 20 to 80 nm, hence validating the achievement of great purity. The peaks were detected at 27.5, 32, 45.9, and 54.6 which closely coincide to crystal planes 210,113,124 and 142; respectively [<a href="#B78-jfb-15-00354" class="html-bibr">78</a>,<a href="#B79-jfb-15-00354" class="html-bibr">79</a>]. In consistent with our result Majeed, et al. [<a href="#B80-jfb-15-00354" class="html-bibr">80</a>] found that the XRD analysis pattern of AgNPs presented sharp diffraction 2θ° at 27, 32, 46, 54, 57, and 67. Consequently, the highly strong peak of the XRD pattern has confirmed that the resultant particles in the sample are in the form of crystalline silver nanoparticles with face centered cubic structure [<a href="#B81-jfb-15-00354" class="html-bibr">81</a>]. Hence, the XRD analysis has revealed that the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> has the ability to reduce silver ions and synthesized AgNPs with well-defined dimensions.</div><div class='html-p'>FTIR spectroscopy identified functional groups on AgNPs that are essential for stabilizing and reducing silver ions. FTIR analysis of the synthesized AgNPs showed characteristic vibrational frequencies at 3448, 2960, 2929, 1801, 1633, 1025, and 522 cm<sup>−1</sup>, as depicted in <a href="#jfb-15-00354-f008" class="html-fig">Figure 8</a>C. These peaks likely correspond to the functional groups involved in the biomolecular interactions, stabilization, and reduction of AgNPs. The peaks at 3448 and 2960 cm<sup>−1</sup> correspond to the N–H stretching of primary and secondary amides of proteins and O–H stretching of alcohols and phenols, respectively. The 2929 cm<sup>−1</sup> peak corresponds to C–H symmetrical stretching of alkanes. The 1801 cm<sup>−1</sup> peak corresponds to the C=O in carboxylic acids. The peak at 1633 cm<sup>−1</sup> corresponds to carbonyl stretching of the amide I bond in proteins. The peaks at 1025 cm<sup>−1</sup> and 522 cm<sup>−1</sup> correspond to aliphatic amines and C–Cl stretching of alkyl halides, respectively. These findings indicate the presence of various functional groups in the aqueous mycelial-free filtrate of <span class='html-italic'>Aspergillus flavus</span>, such as alkanes, alkenes, aliphatic and aromatic amines, and alkyl groups, which play significant roles in the reduction, capping, and stabilization of AgNPs. Previous studies on AgNPs synthesized by <span class='html-italic'>Trichoderma longibrachiatum</span> identified unique FTIR peaks at 1634.92, 2156.94, and 3269.31 cm<sup>−1</sup>, which are linked to primary amines [<a href="#B82-jfb-15-00354" class="html-bibr">82</a>] and protein structures [<a href="#B83-jfb-15-00354" class="html-bibr">83</a>]. The band around 1651 cm<sup>−1</sup> signifies protein amide bonds (bending vibrations), whereas the 3448 cm<sup>−1</sup> peak indicates primary amine stretching vibrations [<a href="#B84-jfb-15-00354" class="html-bibr">84</a>]. These FTIR findings suggest that phenols and proteins act as reducing, stabilizing, and capping agents for AgNPs, facilitating the transformation of silver radicals into silver ions [<a href="#B85-jfb-15-00354" class="html-bibr">85</a>].</div></section><section id='sec3dot6-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.6. Antimicrobial Efficacy of Cotton Fabrics Loaded with Bio-Synthesized AgNPs</h4><div class='html-p'>The agar well diffusion method assessed the antimicrobial efficacy of AgNPs-embedded cotton fabric against <span class='html-italic'>E. coli</span>, <span class='html-italic'>S. aureus</span>, and <span class='html-italic'>C. albicans</span> (<a href="#jfb-15-00354-f009" class="html-fig">Figure 9</a>). A 24-h incubation revealed clear inhibition zones, demonstrating the release of the antimicrobial agent. The AgNPs-treated fabric exhibited inhibition zones of 15, 12, and 17 mm against <span class='html-italic'>E. coli</span>, <span class='html-italic'>S. aureus</span>, and <span class='html-italic'>C. albicans</span>, respectively, indicating AgNPs diffusion into the agar. The inhibitory mechanism of Ag<sup>+</sup> ions involves interactions with negatively charged cell membranes through electrostatic forces [<a href="#B86-jfb-15-00354" class="html-bibr">86</a>,<a href="#B87-jfb-15-00354" class="html-bibr">87</a>]. Patil, et al. [<a href="#B28-jfb-15-00354" class="html-bibr">28</a>] found that AgNPs-coated cotton fabrics showed significant antibacterial activity against gram-positive and gram-negative bacteria, with larger inhibition zones confirming efficacy. Ibrahim and Hassan [<a href="#B88-jfb-15-00354" class="html-bibr">88</a>] reported strong antibacterial activity for AgNPs -treated fabrics at all doses, with inhibition zones of 13–17 mm, even at the lowest AgNPs concentration (1 mM). Antibacterial activity was more pronounced against <span class='html-italic'>E. coli</span> than against <span class='html-italic'>S. aureus</span>. The AgNPs -incorporated cotton fibers produced in this study consistently exhibited inhibition zones greater than 12 mm.</div><div class='html-p'>AgNPs possess advantages such as diminutive dimensions and increased surface area, facilitating bacterial cell penetration and nuclear access [<a href="#B89-jfb-15-00354" class="html-bibr">89</a>,<a href="#B90-jfb-15-00354" class="html-bibr">90</a>]. Studies have highlighted the role of electrostatic attraction between negatively charged bacterial cells and positively charged AgNPs in antibacterial effectiveness [<a href="#B43-jfb-15-00354" class="html-bibr">43</a>,<a href="#B71-jfb-15-00354" class="html-bibr">71</a>]. Our findings indicated the greatest inhibition zone against <span class='html-italic'>C. albicans</span>, followed by <span class='html-italic'>E. coli</span> and <span class='html-italic'>S. aureus</span>, consistent with Fatima, et al. [<a href="#B91-jfb-15-00354" class="html-bibr">91</a>], who reported that AgNPs synthesized using a specific <span class='html-italic'>A. flavus</span> strain demonstrate antibacterial and antifungal activity against Trichoderma sp.</div></section><section id='sec3dot7-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.7. Molecular Docking Analysis of AgNPs Biosynthesized by the Aqueous Mycelial-Free Filtrate of A. flavus Loaded onto Cotton Fabrics</h4><div class='html-p'>Both rule-based and machine-learning approaches have been employed in forward synthesis tools. These methods are used to identify the reactions from the available in silico list that can generate product structures. As depicted in <a href="#jfb-15-00354-f010" class="html-fig">Figure 10</a>, the forward interaction between cotton fabric cellulose and the biosynthesized AgNPs was demonstrated. From the results, the cellulase is predicted to break down by AgNPs and form smaller polymer units that can spread into microbial environments. The resulting polymers can attach to proteins in microbes, thereby suppressing microbial proliferation. Combining innovative synthetic approaches with computer-aided retrosynthesis and forward synthesis methods can significantly expand the structural variety of compounds that are feasible for synthesis. These approaches can encompass a large portion of the relevant chemical reactions by utilizing extensive unbiased reaction databases [<a href="#B92-jfb-15-00354" class="html-bibr">92</a>]. In this investigation, in silico analysis of predicted monomer compound derived from biosynthesized AgNPs loaded on cotton fabric exhibited the potential to inhibit bacterial and Candida proliferation, the binding energies between predicted monomer compound and various receptor proteins linked to antibiotic and antifungal resistance in bacteria and fungi including penicillin-binding proteins (PBPs) and Lanosterol-14-demethylase (L-14α-DM), showed in <a href="#jfb-15-00354-t004" class="html-table">Table 4</a>.</div><div class='html-p'>The study showed that integrating biosynthesized silver nanoparticles with cotton fabric resulted in antimicrobial effects against both Gram-positive and Gram-negative bacteria, including <span class='html-italic'>Staphylococcus aureus</span> and <span class='html-italic'>E. coli</span>, respectively. These outcomes are consistent with the work of Hashem, et al. [<a href="#B93-jfb-15-00354" class="html-bibr">93</a>], which indicated that cellulose modified with nanoformulations successfully impeded the growth of gram-negative bacteria (<span class='html-italic'>Pseudomonas aeruginosa</span> and <span class='html-italic'>E. coli</span>) and Gram-positive bacteria (<span class='html-italic'>Staphylococcus aureus</span> and <span class='html-italic'>Bacillus subtilis</span>). Altering the structure of cellulose provides practical approaches to changing the characteristics of this material, facilitating its application in various fields while preserving its environmentally friendly and renewable nature. In the near future, the adoption of these technological innovations could lead to the development of novel and eco-friendly materials [<a href="#B22-jfb-15-00354" class="html-bibr">22</a>].</div><div class='html-p'>The results also demonstrated that the predicted compound derived from synthesized AgNPs attached to cotton fabrics exhibited stronger binding energy with L-14α-DM proteins than PBPs. The marginally higher binding energy of L-14α-DM (−5.2 kcal/mol) than PBPs (−4.7 kcal/mol) indicates a more robust interaction with this protein, which is attributed to the presence of a covalent hydrogen bond with an unfavorable donor bond involving amino acid residues (<a href="#jfb-15-00354-f011" class="html-fig">Figure 11</a> and <a href="#jfb-15-00354-t004" class="html-table">Table 4</a>).</div><div class='html-p'>Penicillin-binding proteins (PBPs) are a group of molecules that exhibit strong attraction to the β-lactam antibiotic, penicillin. These membrane-bound proteins are vital for the synthesis of peptidoglycan, which is the primary structural component of bacterial cell walls. The significance of PBPs lies in their diverse roles, including protein-protein interactions, antibiotic resistance mechanisms, cell wall construction, and various regulatory functions [<a href="#B94-jfb-15-00354" class="html-bibr">94</a>]. β-lactams specifically attach to the active site through covalent bonding or to both the allosteric site via non-covalent bonding and the active site through covalent bonding [<a href="#B95-jfb-15-00354" class="html-bibr">95</a>]. Current docking studies suggest that the moderate binding affinity between the compound predicted from AgNPs and cotton fabric could potentially disrupt PBPs function and hinder peptidoglycan cross-linking in the bacterial cell wall, resulting in cellular death. As noted in Farid, et al. [<a href="#B96-jfb-15-00354" class="html-bibr">96</a>], the interaction with arginine and glutamic acid residues indicated the existence of electrostatic or hydrogen bond interactions between the predicted compound and the PBPs protein, while the interaction with proline may help stabilize the connection between proteins and the predicted compound derived from AgNPs with cotton fabric. However, developing an effective antifungal therapeutic agent is more challenging because of the eukaryotic nature of <span class='html-italic'>Candida</span>. A range of pharmacological compounds is currently used to treat <span class='html-italic'>Candida</span> infections, each targeting different essential factors [<a href="#B97-jfb-15-00354" class="html-bibr">97</a>].</div><div class='html-p'>This study revealed that the compound predicted from AgNPs -loaded cotton fabrics exhibited binding affinity with lanosterol-14-demethylase (L-14α-DM) through molecular docking interactions. L-14α-DM serves as an excellent therapeutic target for a wide range of anticandidal and antifungal treatments [<a href="#B98-jfb-15-00354" class="html-bibr">98</a>]. These findings indicate a more robust interaction with PBPs, suggesting substantial interference with lanosterol-14-demethylase (L-14α-DM) and disruption of ergosterol production in the cell membrane, ultimately causing cell death, which is in line with a previous report. Many studies have shown that one factor contributing to <span class='html-italic'>C. albicans</span> antibiotic resistance is a mutation in the L-14α-DM enzyme [<a href="#B99-jfb-15-00354" class="html-bibr">99</a>].</div><div class='html-p'>Our molecular docking analysis verified that the interruption of sterol biosynthesis leads to cell death. The interaction between serine and methionine may help stabilize the predicted compound near the active site through hydrogen bond formation, whereas the interaction between methionine and its sulfur side chain aids the predicted compound from AgNPs with cotton fabric in inhibiting enzyme and histidine function. This observation aligns with that of Ganeshkumar, et al. [<a href="#B100-jfb-15-00354" class="html-bibr">100</a>], who noted that <span class='html-italic'>C. albicans</span> amino acid residues, specifically SER 378, SER 378, HIS 377, and MET 508, exhibited strong interactions with posaconazole and VT-1161, resulting in cell death. Furthermore, the systematic development of environmental substances that lack skin-sensitizing properties is in line with the green chemistry principles [<a href="#B101-jfb-15-00354" class="html-bibr">101</a>]. Computational approaches offer an appealing method for creating safer chemical compounds [<a href="#B102-jfb-15-00354" class="html-bibr">102</a>].</div></section><section id='sec3dot8-jfb-15-00354' type=''><h4 class='html-italic' data-nested='2'> 3.8. Pharmacokinetic Properties of the Predicted Compound Resulting from AgNPs Loaded onto Cotton Fabrics</h4><div class='html-p'>Computational methods were applied to explore the pharmacological attributes and toxicity of the predicted compound derived from cotton fabrics loaded with AgNPs (<a href="#app1-jfb-15-00354" class="html-app">Table S1</a>). The findings revealed that the compound had poor absorption in the gastrointestinal tract, suggesting limited effectiveness for oral administration, as noted by Martins, et al. [<a href="#B103-jfb-15-00354" class="html-bibr">103</a>]. Furthermore, the compound’s log Kp value for skin permeability was determined to be −9.49, indicating minimal penetration through the skin, which aligns with the results reported in [<a href="#B104-jfb-15-00354" class="html-bibr">104</a>]. The compound’s pharmacokinetic profile suggested it could be a promising candidate for additional research. The KeratinoSens assay results classified the test compound as a non-sensitizer, suggesting it does not trigger skin sensitization by interfering with the Keap1-Nrf2-ARE signaling pathway in differentiated human keratinocytes (<a href="#jfb-15-00354-f012" class="html-fig">Figure 12</a>A). To enhance the use of existing data, this study combined previous HRIPT and HMT information with IRR and MRL when examining allergen responses. Based on predictions from the Human Repeat Insult Patch Test (HRIPT) or Human Maximization Test (HMT), the compound is expected to be a non-sensitizer. This indicates that it is not likely to induce skin sensitization in humans when tested under the conditions specified in these assessments (<a href="#jfb-15-00354-f012" class="html-fig">Figure 12</a>B).</div><div class='html-p'>The compound currently predicted from AgNPs deposited on cotton fabric in the computational KeratinoSens assay demonstrates chemical and structural characteristics that are consistent with the model’s prediction range. This alignment indicates a strong likelihood of obtaining reliable results. A confidence level of 94% indicates a high probability that the substance will not induce skin sensitization. An accurate probability map of non-sensitizers is unlikely to contain groups comprising reactive centers or chemotypes capable of initiating stress signals in keratinocytes. The molecule does not exhibit electrophilic positions or other functional groups that could potentially participate in the formation of covalent bonds with skin proteins during the sensitization process [<a href="#B105-jfb-15-00354" class="html-bibr">105</a>].</div><div class='html-p'>When predicting the results of HRIPT and HMT for substances derived from cotton fabrics containing AgNPs, the Applicability Domain, and Confiability suggest that the substance’s structure or characteristics fall outside the range the predictive model was trained on. Therefore, caution is warranted when interpreting the result, as the model may lack sufficient data to accurately predict the effect of this compound. A reliability of 94.9% indicates a high level of confidence in the result, although the compound was found to be outside the AD, which aligns with the conclusions drawn by Herzler et al. [<a href="#B106-jfb-15-00354" class="html-bibr">106</a>].</div></section></section><section id='sec4-jfb-15-00354' type='conclusions'><h2 data-nested='1'> 4. Conclusions</h2><div class='html-p'>The research findings demonstrated an easy, affordable, and environmentally friendly method for the synthesis of AgNPs using the extracellular filtrate of the <span class='html-italic'>Aspergillus flavus</span> fungal strain and an aqueous solution of silver nitrate. This method is environmentally friendly because it does not require toxic chemicals or organic solvents. Our results demonstrated that the synthesized AgNPs exhibited promising antimicrobial properties against specific bacteria and fungi, suggesting their potential applications in biomedicine. These findings indicated that they are particularly important from a technological aspect for producing antibacterial finishes. This treatment is suitable for the manufacture of antimicrobial coatings and fabrics. More research should be conducted on curing processes, which play a significant role in the stabilization of AgNPs applied on fabric surfaces. In addition to the in silico approach, a compound predicted from AgNPs deposited on cotton fabric showed promising pharmacokinetic properties, particularly as a non-skin sensitizer with minimal potential for drug interactions.</div></section> </div> <div class="html-back"> <section><section id='app1-jfb-15-00354' type=''><h2 data-nested='1'> Supplementary Materials</h2><div class='html-p'>The following supporting information can be downloaded at: <a href='https://www.mdpi.com/article/10.3390/jfb15120354/s1' target='_blank' rel="noopener noreferrer">https://www.mdpi.com/article/10.3390/jfb15120354/s1</a>, Table S1: Pharmacokinetics properties of predicted compound resulted from AgNPs loaded on cotton fabrics.</div></section></section><section class='html-notes'><h2 >Author Contributions</h2><div class='html-p'>Conceptualization N.E.-A.E.-N., Y.M.H. and H.M.S.; methodology, N.E.-A.E.-N., Y.M.H. and N.S.S.; software, N.E.-A.E.-N. and N.S.S.; validation, Y.M.H. and N.E.-A.E.-N.; formal analysis, N.E.-A.E.-N., N.E., H.E.-S., Y.M.H. and N.S.S.; investigation, N.E.-A.E.-N., Y.M.H. and H.M.S.; resources, A.A.A. and H.M.A.; data curation, A.A.A. and H.M.A.; writing—original draft preparation, N.E.-A.E.-N., N.S.S., H.M.A. and Y.M.H.; writing—review and editing, N.E.-A.E.-N., H.M.S., Y.M.H., A.A.A., N.E., H.E.-S. and H.M.A.; visualization, N.E.-A.E.-N., Y.M.H., N.E., H.E.-S. and N.S.S.; supervision, N.E.-A.E.-N., Y.M.H. and H.M.S.; project administration, N.E.-A.E.-N., H.M.S., Y.M.H. and H.M.A.; funding acquisition, H.M.A. and A.A.A. All authors have read and agreed to the published version of the manuscript.</div></section><section class='html-notes'><h2>Funding</h2><div class='html-p'>The research was funded by Taif University, Saudi Arabia, Project No. (TU-DSPP-2024-213).</div></section><section class='html-notes'><h2 >Institutional Review Board Statement</h2><div class='html-p'>Not applicable.</div></section><section class='html-notes'><h2 >Informed Consent Statement</h2><div class='html-p'>Not applicable.</div></section><section class='html-notes'><h2 >Data Availability Statement</h2><div class='html-p'>The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.</div></section><section id='html-ack' class='html-ack'><h2 >Acknowledgments</h2><div class='html-p'>The authors extend their appreciation to Mansoura University, Egypt and Taif University, Saudi Arabia, for supporting this work.</div></section><section class='html-notes'><h2 >Conflicts of Interest</h2><div class='html-p'>The authors declare no conflicts of interest.</div></section><section id='html-references_list'><h2>References</h2><ol class='html-xxx'><li id='B1-jfb-15-00354' class='html-x' data-content='1.'>A Afolalu, S.; Soetan, S.B.; O Ongbali, S.; A Abioye, A.; Oni, A.S. 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The accession numbers are indicated in parentheses and the red box indicates the studied strain.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f002"> <div class="html-caption"> <b>Figure 2.</b> A construct of the phylogenetic tree of <span class='html-italic'>Aspergillus</span> sp. based on internal transcribed spacer (ITS) region sequences with 1000 bootstrap replicates. The accession numbers are indicated in parentheses and the red box indicates the studied strain.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g002.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g002.png" alt="Jfb 15 00354 g002" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g002.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f003"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f003"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png" alt="Jfb 15 00354 g003" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f003"></a> </div> </div> <div class="html-fig_description"> <b>Figure 3.</b> Production of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. (<b>A</b>) Control flask (the aqueous mycelial-free filtrate without silver ions), (<b>B</b>) Experimental flask (the aqueous mycelial-free filtrate with silver ions) following 72 h cultivation, (<b>C</b>) Ultraviolet-visible absorption spectrum of the synthesized AgNPs (300–700 nm).  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f003"> <div class="html-caption"> <b>Figure 3.</b> Production of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. (<b>A</b>) Control flask (the aqueous mycelial-free filtrate without silver ions), (<b>B</b>) Experimental flask (the aqueous mycelial-free filtrate with silver ions) following 72 h cultivation, (<b>C</b>) Ultraviolet-visible absorption spectrum of the synthesized AgNPs (300–700 nm).</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png" alt="Jfb 15 00354 g003" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g003.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f004"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f004"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png" alt="Jfb 15 00354 g004" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f004"></a> </div> </div> <div class="html-fig_description"> <b>Figure 4.</b> 3D plots illustrating the interactive impacts of AgNO<sub>3</sub> concentration (X<sub>1</sub>), starting pH value (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) on the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. (<b>A</b>–<b>C</b>) illustrated the effect of AgNO<sub>3</sub> concentration on AgNPs biosynthesis when interacting with initial pH level, temperature and incubation period; respectively. (<b>A</b>,<b>D</b>,<b>E</b>) illustrated the effect of initial pH level on AgNPs biosynthesis when interacting with AgNO<sub>3</sub> concentration, temperature, and incubation time; respectively. (<b>B</b>,<b>D</b>,<b>F</b>) illustrated the effect of temperature on AgNPs biosynthesis when interacting with the AgNO<sub>3</sub> concentration, initial pH level and incubation time; respectively.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f004"> <div class="html-caption"> <b>Figure 4.</b> 3D plots illustrating the interactive impacts of AgNO<sub>3</sub> concentration (X<sub>1</sub>), starting pH value (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) on the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. (<b>A</b>–<b>C</b>) illustrated the effect of AgNO<sub>3</sub> concentration on AgNPs biosynthesis when interacting with initial pH level, temperature and incubation period; respectively. (<b>A</b>,<b>D</b>,<b>E</b>) illustrated the effect of initial pH level on AgNPs biosynthesis when interacting with AgNO<sub>3</sub> concentration, temperature, and incubation time; respectively. (<b>B</b>,<b>D</b>,<b>F</b>) illustrated the effect of temperature on AgNPs biosynthesis when interacting with the AgNO<sub>3</sub> concentration, initial pH level and incubation time; respectively.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png" alt="Jfb 15 00354 g004" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g004.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f005"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f005"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png" alt="Jfb 15 00354 g005" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f005"></a> </div> </div> <div class="html-fig_description"> <b>Figure 5.</b> (<b>A</b>) Normal probability plot of internally studentized residuals, (<b>B</b>) plot of predicted versus actual, (<b>C</b>) Box-Cox plot of model transformation and (<b>D</b>) plot of internally studentized residuals versus predicted values of AgNPs biosynthesis using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> as affected by AgNO<sub>3</sub> conc. (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>) and incubation time (X<sub>4</sub>).  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f005"> <div class="html-caption"> <b>Figure 5.</b> (<b>A</b>) Normal probability plot of internally studentized residuals, (<b>B</b>) plot of predicted versus actual, (<b>C</b>) Box-Cox plot of model transformation and (<b>D</b>) plot of internally studentized residuals versus predicted values of AgNPs biosynthesis using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> as affected by AgNO<sub>3</sub> conc. (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>) and incubation time (X<sub>4</sub>).</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png" alt="Jfb 15 00354 g005" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g005.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f006"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f006"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png" alt="Jfb 15 00354 g006" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f006"></a> </div> </div> <div class="html-fig_description"> <b>Figure 6.</b> The optimization plot displays the desirability function and the optimal predicted values for the synthesis of AgNPs using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. The red and blue circles represent the highest values for the variables and AgNPs; respectively.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f006"> <div class="html-caption"> <b>Figure 6.</b> The optimization plot displays the desirability function and the optimal predicted values for the synthesis of AgNPs using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span>. The red and blue circles represent the highest values for the variables and AgNPs; respectively.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png" alt="Jfb 15 00354 g006" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g006.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f007"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f007"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png" alt="Jfb 15 00354 g007" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f007"></a> </div> </div> <div class="html-fig_description"> <b>Figure 7.</b> Biogenic AgNPs by <span class='html-italic'>A. flavus</span> comprising: (<b>A</b>) SEM image, (<b>B</b>) TEM micrograph, (<b>C</b>) SADP for a single nanosilver particle, and (<b>D</b>) EDX examination illustrating the elemental composition of native silver.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f007"> <div class="html-caption"> <b>Figure 7.</b> Biogenic AgNPs by <span class='html-italic'>A. flavus</span> comprising: (<b>A</b>) SEM image, (<b>B</b>) TEM micrograph, (<b>C</b>) SADP for a single nanosilver particle, and (<b>D</b>) EDX examination illustrating the elemental composition of native silver.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png" alt="Jfb 15 00354 g007" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g007.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f008"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f008"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png" alt="Jfb 15 00354 g008" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f008"></a> </div> </div> <div class="html-fig_description"> <b>Figure 8.</b> Analysis of biogenic AgNPs using (<b>A</b>) Zeta potential measurement, (<b>B</b>) XRD pattern of silver nanoparticles and (<b>C</b>) FTIR spectroscopy to identify functional groups that stabilize or cap AgNPs.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f008"> <div class="html-caption"> <b>Figure 8.</b> Analysis of biogenic AgNPs using (<b>A</b>) Zeta potential measurement, (<b>B</b>) XRD pattern of silver nanoparticles and (<b>C</b>) FTIR spectroscopy to identify functional groups that stabilize or cap AgNPs.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png" alt="Jfb 15 00354 g008" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g008.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f009"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f009"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png" alt="Jfb 15 00354 g009" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f009"></a> </div> </div> <div class="html-fig_description"> <b>Figure 9.</b> Antimicrobial activity of AgNPs bio-synthesized by the aqueous mycelial-free filtrate of <span class='html-italic'>Aspergillus flavus</span> loaded on cotton fabrics.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f009"> <div class="html-caption"> <b>Figure 9.</b> Antimicrobial activity of AgNPs bio-synthesized by the aqueous mycelial-free filtrate of <span class='html-italic'>Aspergillus flavus</span> loaded on cotton fabrics.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png" alt="Jfb 15 00354 g009" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g009.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f010"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f010"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png" alt="Jfb 15 00354 g010" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f010"></a> </div> </div> <div class="html-fig_description"> <b>Figure 10.</b> Prediction of forward reaction mechanism between bio-synthesized AgNPs and cellulose in cotton fabric.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f010"> <div class="html-caption"> <b>Figure 10.</b> Prediction of forward reaction mechanism between bio-synthesized AgNPs and cellulose in cotton fabric.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png" alt="Jfb 15 00354 g010" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g010.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f011"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f011"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png" alt="Jfb 15 00354 g011" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f011"></a> </div> </div> <div class="html-fig_description"> <b>Figure 11.</b> Molecular docking interactions between predicted compounds from AgNPs-loaded cotton fabrics (cellulose) with microbial proteins: (<b>A</b>) PBPs in Gram +ve and −ve bacteria, (<b>B</b>) Lanosterol-14α-demethylase (L-14α-DM) protein in <span class='html-italic'>Candida albicans</span>.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f011"> <div class="html-caption"> <b>Figure 11.</b> Molecular docking interactions between predicted compounds from AgNPs-loaded cotton fabrics (cellulose) with microbial proteins: (<b>A</b>) PBPs in Gram +ve and −ve bacteria, (<b>B</b>) Lanosterol-14α-demethylase (L-14α-DM) protein in <span class='html-italic'>Candida albicans</span>.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png" alt="Jfb 15 00354 g011" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g011.png" /></div> </div> <div class="html-fig-wrap" id="jfb-15-00354-f012"> <div class='html-fig_img'> <div class="html-figpopup html-figpopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f012"> <img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png" alt="Jfb 15 00354 g012" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012-550.jpg" /> <a class="html-expand html-figpopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#fig_body_display_jfb-15-00354-f012"></a> </div> </div> <div class="html-fig_description"> <b>Figure 12.</b> Sensitizer prediction of the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>A</b>) Prediction of keratinocyte responses to the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>B</b>) Prediction of human repeated insult patch test (HRIPT) and human maximization test (HMT) of the predicted compound resulting from AgNPs loaded on cotton fabrics.  </div> </div> <div class="html-fig_show mfp-hide" id="fig_body_display_jfb-15-00354-f012"> <div class="html-caption"> <b>Figure 12.</b> Sensitizer prediction of the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>A</b>) Prediction of keratinocyte responses to the predicted compound resulting from AgNPs loaded on cotton fabrics. (<b>B</b>) Prediction of human repeated insult patch test (HRIPT) and human maximization test (HMT) of the predicted compound resulting from AgNPs loaded on cotton fabrics.</div> <div class="html-img"><img data-large="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png" data-original="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png" alt="Jfb 15 00354 g012" data-lsrc="/jfb/jfb-15-00354/article_deploy/html/images/jfb-15-00354-g012.png" /></div> </div> <div class="html-table-wrap" id="jfb-15-00354-t001"> <div class="html-table_wrap_td"> <div class="html-tablepopup html-tablepopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href='#table_body_display_jfb-15-00354-t001'> <img data-lsrc="https://pub.mdpi-res.com/img/table.png" /> <a class="html-expand html-tablepopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#table_body_display_jfb-15-00354-t001"></a> </div> </div> <div class="html-table_wrap_discription"> <b>Table 1.</b> The Box-Behnken design matrix illustrates <span class='html-italic'>A. flavus</span>-mediated biosynthesis of AgNPs, as affected by AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) with both coded and actual factor levels. </div> </div> <div class="html-table_show mfp-hide " id="table_body_display_jfb-15-00354-t001"> <div class="html-caption"><b>Table 1.</b> The Box-Behnken design matrix illustrates <span class='html-italic'>A. flavus</span>-mediated biosynthesis of AgNPs, as affected by AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>) with both coded and actual factor levels.</div> <table > <thead ><tr ><th rowspan='2' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Std</th><th rowspan='2' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Run</th><th colspan='4' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Variables</th><th colspan='2' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >AgNPs (µg/mL)</th><th rowspan='2' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Residuals</th></tr><tr ><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub></th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub></th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>3</sub></th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>4</sub></th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Experimental</th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Predicted</th></tr></thead><tbody ><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >76.0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >75.23</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.77</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >124.77</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >126.82</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−2.05</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >77.48</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >77.78</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−0.30</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >27</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >71.26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.62</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >13</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >5</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >47.56</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >46.15</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1.41</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >20</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >75.48</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >75.06</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.42</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >7</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >49.75</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >51.59</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.84</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >8</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >174.72</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >174.31</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.40</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >12</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >9</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >74.1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >73.7</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.4</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >16</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >10</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >221.69</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >222.75</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.06</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >22</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >143.2</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >142.24</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.96</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >12</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18.22</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.66</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >13</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >142.84</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >142.84</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.00</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >9</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.32</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.34</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−0.02</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >23</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >15</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >62.99</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >62.87</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.12</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >16</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >71.1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.78</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >17</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >32.33</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >33.77</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.44</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >19</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.51</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.09</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.42</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >21</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >19</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >80.19</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >80.86</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−0.67</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >7</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >20</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >52.47</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >53.61</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.14</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >5</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >21</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.96</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.51</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.45</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >24</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >22</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >235.03</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >233.28</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1.75</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >15</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >23</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >74.03</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >71.62</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2.41</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >8</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >24</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >125.85</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >127.74</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.89</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >17</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >25</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >8.19</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >7.53</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.66</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >25</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >73.11</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.23</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >10</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >27</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >45.11</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >45.53</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−0.43</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >29</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >28</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.55</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−0.33</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >28</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >29</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >76.43</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3.55</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >76.01</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >75.23</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.78</td></tr><tr ><td rowspan='2' colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Variable</b></td><td rowspan='2' colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Code</b></td><td colspan='3' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Coded and Actual Levels</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>−1</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>0</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>1</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >AgNO<sub>3</sub> conc. (mM)</td><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Initial pH level </td><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >7</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >5</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Temperature (°C)</td><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>3</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >25</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >8</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Incubation time (h)</td><td colspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>4</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >24</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >48</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >35</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr></tbody> </table> </div> <div class="html-table-wrap" id="jfb-15-00354-t002"> <div class="html-table_wrap_td"> <div class="html-tablepopup html-tablepopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href='#table_body_display_jfb-15-00354-t002'> <img data-lsrc="https://pub.mdpi-res.com/img/table.png" /> <a class="html-expand html-tablepopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#table_body_display_jfb-15-00354-t002"></a> </div> </div> <div class="html-table_wrap_discription"> <b>Table 2.</b> ANOVA of Box–Behnken experimental design used for synthesizing AgNPs using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> to evaluate the effects of four factors: AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>). </div> </div> <div class="html-table_show mfp-hide " id="table_body_display_jfb-15-00354-t002"> <div class="html-caption"><b>Table 2.</b> ANOVA of Box–Behnken experimental design used for synthesizing AgNPs using aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> to evaluate the effects of four factors: AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>).</div> <table > <thead ><tr ><th colspan='2' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Source of Variance</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Coefficient Estimate</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Sum of Squares</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Degrees of Freedom</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Mean Square</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>f</span>-Value</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>p</span>-Value</th></tr></thead><tbody ><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Model</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Intercept</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >85,288.54</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6092.04</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1734.16</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td rowspan='4' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Linear effect</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3.41</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >139.79</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >139.79</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >39.79</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >57.95</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >40,297.60</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >40,297.60</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11,471.09</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>3</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.35</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11,053.54</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11,053.54</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3146.50</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>4</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18.26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4002.78</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4002.78</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1139.43</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td rowspan='6' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Interaction effect</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub> X<sub>2</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >12.32</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >607.53</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >607.53</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >172.94</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub> X<sub>3</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−1.93</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14.90</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14.90</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4.24</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.0586</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub> X<sub>4</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−4.18</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >69.97</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >69.97</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >19.92</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.0005 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub> X<sub>3</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >17.61</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1240.68</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1240.68</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >353.17</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub> X<sub>4</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >27.26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2971.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2971.88</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >845.97</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>3</sub> X<sub>4</sub></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6.72</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >180.41</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >180.41</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >51.36</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td rowspan='4' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Quadratic effect</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>1</sub><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−22.93</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3411.56</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3411.56</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >971.13</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>2</sub><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >50.68</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >16,658.37</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >16,658.37</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4741.96</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>3</sub><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−6.73</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >293.42</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >293.42</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >83.53</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >X<sub>4</sub><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6.25</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >253.46</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >253.46</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >72.15</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td rowspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Error effect</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Lack of Fit</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.47</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >10</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3.05</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.65</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.735</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Pure Error</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >18.71</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4.68</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>R</span><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9994</td><td rowspan='4' colspan='6' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' > </td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Adj <span class='html-italic'>R</span><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9988</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Pred <span class='html-italic'>R</span><sup>2</sup></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9976</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Adeq Precision</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >167.47</td></tr></tbody> </table> <div class='html-table_foot html-p'><div class='html-p' style='text-indent:0em;'><span class='html-fn-content'>* Significant values, <span class='html-italic'>f</span>: Fishers’s function, <span class='html-italic'>p</span>: Level of significance.</span></div><div style='clear:both;'></div></div> </div> <div class="html-table-wrap" id="jfb-15-00354-t003"> <div class="html-table_wrap_td"> <div class="html-tablepopup html-tablepopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href='#table_body_display_jfb-15-00354-t003'> <img data-lsrc="https://pub.mdpi-res.com/img/table.png" /> <a class="html-expand html-tablepopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#table_body_display_jfb-15-00354-t003"></a> </div> </div> <div class="html-table_wrap_discription"> <b>Table 3.</b> The fit summary results of Box–Behnken experimental design used for synthesizing AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> as influenced by AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>). </div> </div> <div class="html-table_show mfp-hide " id="table_body_display_jfb-15-00354-t003"> <div class="html-caption"><b>Table 3.</b> The fit summary results of Box–Behnken experimental design used for synthesizing AgNPs using the aqueous mycelial-free filtrate of <span class='html-italic'>A. flavus</span> as influenced by AgNO<sub>3</sub> concentration (X<sub>1</sub>), initial pH level (X<sub>2</sub>), temperature (X<sub>3</sub>), and incubation time (X<sub>4</sub>).</div> <table > <thead ><tr ><th colspan='6' align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Sequential Model Sum of Squares</th></tr><tr ><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Source</th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Sum of Squares</th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>df</span></th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Mean Square</th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>f</span>-Value</th><th align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><span class='html-italic'>p</span>-Value<br><span class='html-italic'>p</span>rob ><span class='html-italic'>f</span></th></tr></thead><tbody ><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Linear vs. Mean</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >55,493.71</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >13,873.43</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >11.16</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2FI vs. Linear</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >5085.37</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >847.56</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.6162</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.7148</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Quadratic vs. 2FI</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >24,709.46</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >4</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >6177.36</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1758.45</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td colspan='6' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Lack of Fit Tests</b></td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Source</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Sum of Squares</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b><span class='html-italic'>df</span></b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Mean Square</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b><span class='html-italic'>f</span>-Value</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b><span class='html-italic'>p</span>-Value</b><br><b><span class='html-italic'>p</span>rob ><span class='html-italic'>f</span></b></td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Linear</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >29,825.3</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >20</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1491.27</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >318.83</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2FI</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >24,739.93</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >14</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1767.14</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >377.81</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><0.0001 *</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Quadratic </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >30.47</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >10</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >3.05</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.65</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.735</td></tr><tr ><td colspan='6' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Model Summary Statistics</b></td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Source</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Standard Deviation</b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b><span class='html-italic'>R</span><sup>2</sup></b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Adjusted <span class='html-italic'>R</span><sup>2</sup></b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>Predicted <span class='html-italic'>R</span><sup>2</sup></b></td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' ><b>PRESS</b></td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Linear</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >35.26</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.6503</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.592</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.4558</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >46,441.64</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >2FI</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >37.09</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.7099</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.5487</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.0541</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >80,717.46</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Quadratic </td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >1.87</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9994</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9988</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >0.9976</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >204.75</td></tr></tbody> </table> <div class='html-table_foot html-p'><div class='html-p' style='text-indent:0em;'><span class='html-fn-content'>* Significant values, <span class='html-italic'>df</span>: degree of freedom, PRESS: Prediction Error Sum Square, 2FI: two-factor interaction.</span></div><div style='clear:both;'></div></div> </div> <div class="html-table-wrap" id="jfb-15-00354-t004"> <div class="html-table_wrap_td"> <div class="html-tablepopup html-tablepopup-link" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href='#table_body_display_jfb-15-00354-t004'> <img data-lsrc="https://pub.mdpi-res.com/img/table.png" /> <a class="html-expand html-tablepopup" data-counterslinkmanual = "https://www.mdpi.com/2079-4983/15/12/354/display" href="#table_body_display_jfb-15-00354-t004"></a> </div> </div> <div class="html-table_wrap_discription"> <b>Table 4.</b> Molecular Docking Analysis of predicted compounds resulting from biosynthesized AgNPs loaded on cotton fabrics as antimicrobial agents. </div> </div> <div class="html-table_show mfp-hide " id="table_body_display_jfb-15-00354-t004"> <div class="html-caption"><b>Table 4.</b> Molecular Docking Analysis of predicted compounds resulting from biosynthesized AgNPs loaded on cotton fabrics as antimicrobial agents.</div> <table > <thead ><tr ><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Predicted Compound Derived From</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Target Protein</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Binding Affinity Kcal/mol</th><th align='center' valign='middle' style='border-top:solid thin;border-bottom:solid thin' class='html-align-center' >Amino Acids Residues</th></tr></thead><tbody ><tr ><td rowspan='2' align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >AgNPs-loaded on cotton fabrics (cellulose)</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Penicillin-binding proteins (PBPs)</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−4.7</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >AGR: A654, AGR: A463, PRO: A424, GLUA:476</td></tr><tr ><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >Lanosterol-14-demethylase (L-14α-DM) protein</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >−5.2</td><td align='center' valign='middle' style='border-bottom:solid thin' class='html-align-center' >SER: A507, MET: A508, HIS: A377</td></tr></tbody> </table> </div> </section><section class='html-fn_group'><table><tr 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Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>J. Funct. Biomater.</em> <b>2024</b>, <em>15</em>, 354. https://doi.org/10.3390/jfb15120354 </p> <div style="display: block"> <b>AMA Style</b><br> <p> Shweqa NS, El-Naggar NE-A, Abdelmigid HM, Alyamani AA, Elshafey N, El-Shall H, Heikal YM, Soliman HM. Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>Journal of Functional Biomaterials</em>. 2024; 15(12):354. https://doi.org/10.3390/jfb15120354 </p> <b>Chicago/Turabian Style</b><br> <p> Shweqa, Nada S., Noura El-Ahmady El-Naggar, Hala M. Abdelmigid, Amal A. Alyamani, Naglaa Elshafey, Hadeel El-Shall, Yasmin M. Heikal, and Hoda M. Soliman. 2024. "Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics" <em>Journal of Functional Biomaterials</em> 15, no. 12: 354. https://doi.org/10.3390/jfb15120354 </p> <b>APA Style</b><br> <p> Shweqa, N. S., El-Naggar, N. E. -A., Abdelmigid, H. M., Alyamani, A. A., Elshafey, N., El-Shall, H., Heikal, Y. M., & Soliman, H. M. (2024). Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>Journal of Functional Biomaterials</em>, <em>15</em>(12), 354. https://doi.org/10.3390/jfb15120354 </p> </div> </div> <div class="info-box no-margin"> Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. 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Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>J. Funct. Biomater.</em> <b>2024</b>, <em>15</em>, 354. https://doi.org/10.3390/jfb15120354 </p> <div style="display: block"> <b>AMA Style</b><br> <p> Shweqa NS, El-Naggar NE-A, Abdelmigid HM, Alyamani AA, Elshafey N, El-Shall H, Heikal YM, Soliman HM. Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>Journal of Functional Biomaterials</em>. 2024; 15(12):354. https://doi.org/10.3390/jfb15120354 </p> <b>Chicago/Turabian Style</b><br> <p> Shweqa, Nada S., Noura El-Ahmady El-Naggar, Hala M. Abdelmigid, Amal A. Alyamani, Naglaa Elshafey, Hadeel El-Shall, Yasmin M. Heikal, and Hoda M. Soliman. 2024. "Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics" <em>Journal of Functional Biomaterials</em> 15, no. 12: 354. https://doi.org/10.3390/jfb15120354 </p> <b>APA Style</b><br> <p> Shweqa, N. S., El-Naggar, N. E. -A., Abdelmigid, H. M., Alyamani, A. A., Elshafey, N., El-Shall, H., Heikal, Y. M., & Soliman, H. M. (2024). Green Fabrication of Silver Nanoparticles, Statistical Process Optimization, Characterization, and Molecular Docking Analysis of Their Antimicrobial Activities onto Cotton Fabrics. <em>Journal of Functional Biomaterials</em>, <em>15</em>(12), 354. https://doi.org/10.3390/jfb15120354 </p> </div> </div> <div class="info-box no-margin"> Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. 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