Non-Coding RNA | An Open Access Journal from MDPI

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</option> <option value="endocrines" > Endocrines </option> <option value="energies" > Energies </option> <option value="esa" > Energy Storage and Applications (ESA) </option> <option value="eng" > Eng </option> <option value="engproc" > Engineering Proceedings </option> <option value="entropy" > Entropy </option> <option value="eesp" > Environmental and Earth Sciences Proceedings </option> <option value="environments" > Environments </option> <option value="epidemiologia" > Epidemiologia </option> <option value="epigenomes" > Epigenomes </option> <option value="ebj" > European Burn Journal (EBJ) </option> <option value="ejihpe" > European Journal of Investigation in Health, Psychology and Education (EJIHPE) </option> <option value="fermentation" > Fermentation </option> <option value="fibers" > Fibers </option> <option value="fintech" > FinTech </option> <option value="fire" > Fire </option> <option value="fishes" > Fishes </option> <option value="fluids" > Fluids </option> <option 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value="genealogy" > Genealogy </option> <option value="genes" > Genes </option> <option value="geographies" > Geographies </option> <option value="geohazards" > GeoHazards </option> <option value="geomatics" > Geomatics </option> <option value="geometry" > Geometry </option> <option value="geosciences" > Geosciences </option> <option value="geotechnics" > Geotechnics </option> <option value="geriatrics" > Geriatrics </option> <option value="glacies" > Glacies </option> <option value="gucdd" > Gout, Urate, and Crystal Deposition Disease (GUCDD) </option> <option value="grasses" > Grasses </option> <option value="greenhealth" > Green Health </option> <option value="hardware" > Hardware </option> <option value="healthcare" > Healthcare </option> <option value="hearts" > Hearts </option> <option value="hemato" > Hemato </option> <option value="hematolrep" > Hematology Reports </option> <option value="heritage" > Heritage </option> <option value="histories" > Histories </option> <option value="horticulturae" > Horticulturae </option> <option value="hospitals" > Hospitals </option> <option value="humanities" > Humanities </option> <option value="humans" > Humans </option> <option value="hydrobiology" > Hydrobiology </option> <option value="hydrogen" > Hydrogen </option> <option value="hydrology" > Hydrology </option> <option value="hygiene" > Hygiene </option> <option value="immuno" > Immuno </option> <option value="idr" > Infectious Disease Reports </option> <option value="informatics" > Informatics </option> <option value="information" > Information </option> <option value="infrastructures" > Infrastructures </option> <option value="inorganics" > Inorganics </option> <option value="insects" > Insects </option> <option value="instruments" > Instruments </option> <option value="iic" > Intelligent Infrastructure and Construction </option> <option value="ijerph" > International Journal of Environmental Research and Public Health (IJERPH) </option> <option value="ijfs" > 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Longevity (JAL) </option> <option value="jcdd" > Journal of Cardiovascular Development and Disease (JCDD) </option> <option value="jcto" > Journal of Clinical & Translational Ophthalmology (JCTO) </option> <option value="jcm" > Journal of Clinical Medicine (JCM) </option> <option value="jcs" > Journal of Composites Science (J. Compos. Sci.) </option> <option value="jcp" > Journal of Cybersecurity and Privacy (JCP) </option> <option value="jdad" > Journal of Dementia and Alzheimer's Disease (JDAD) </option> <option value="jdb" > Journal of Developmental Biology (JDB) </option> <option value="jeta" > Journal of Experimental and Theoretical Analyses (JETA) </option> <option value="jemr" > Journal of Eye Movement Research (JEMR) </option> <option value="jfb" > Journal of Functional Biomaterials (JFB) </option> <option value="jfmk" > Journal of Functional Morphology and Kinesiology (JFMK) </option> <option value="jof" > Journal of Fungi (JoF) </option> <option value="jimaging" > Journal of Imaging (J. Imaging) </option> <option value="jintelligence" > Journal of Intelligence (J. Intell.) </option> <option value="jlpea" > Journal of Low Power Electronics and Applications (JLPEA) </option> <option value="jmmp" > Journal of Manufacturing and Materials Processing (JMMP) </option> <option value="jmse" > Journal of Marine Science and Engineering (JMSE) </option> <option value="jmahp" > Journal of Market Access & Health Policy (JMAHP) </option> <option value="jmms" > Journal of Mind and Medical Sciences (JMMS) </option> <option value="jmp" > Journal of Molecular Pathology (JMP) </option> <option value="jnt" > Journal of Nanotheranostics (JNT) </option> <option value="jne" > Journal of Nuclear Engineering (JNE) </option> <option value="ohbm" > Journal of Otorhinolaryngology, Hearing and Balance Medicine (JOHBM) </option> <option value="jop" > Journal of Parks </option> <option value="jpm" > Journal of Personalized Medicine (JPM) </option> <option value="jpbi" > Journal of Pharmaceutical and BioTech Industry (JPBI) </option> <option value="jor" > Journal of Respiration (JoR) </option> <option value="jrfm" > Journal of Risk and Financial Management (JRFM) </option> <option value="jsan" > Journal of Sensor and Actuator Networks (JSAN) </option> <option value="joma" > Journal of the Oman Medical Association (JOMA) </option> <option value="jtaer" > Journal of Theoretical and Applied Electronic Commerce Research (JTAER) </option> <option value="jvd" > Journal of Vascular Diseases (JVD) </option> <option value="jox" > Journal of Xenobiotics (JoX) </option> <option value="jzbg" > Journal of Zoological and Botanical Gardens (JZBG) </option> <option value="journalmedia" > Journalism and Media </option> <option value="kidneydial" > Kidney and Dialysis </option> <option value="kinasesphosphatases" > Kinases and Phosphatases </option> <option value="knowledge" > Knowledge </option> <option value="labmed" > LabMed </option> <option value="laboratories" > Laboratories </option> <option value="land" > Land </option> <option value="languages" > Languages </option> <option value="laws" > Laws </option> <option value="life" > Life </option> <option value="limnolrev" > Limnological Review </option> <option value="lipidology" > Lipidology </option> <option value="liquids" > Liquids </option> <option value="literature" > Literature </option> <option value="livers" > Livers </option> <option value="logics" > Logics </option> <option value="logistics" > Logistics </option> <option value="lubricants" > Lubricants </option> <option value="lymphatics" > Lymphatics </option> <option value="make" > Machine Learning and Knowledge Extraction (MAKE) </option> <option value="machines" > Machines </option> <option value="macromol" > Macromol </option> <option value="magnetism" > Magnetism </option> <option value="magnetochemistry" > Magnetochemistry </option> <option value="marinedrugs" > Marine Drugs </option> <option value="materials" > Materials </option> <option value="materproc" > Materials Proceedings </option> <option value="mca" > Mathematical and Computational Applications (MCA) </option> <option value="mathematics" > Mathematics </option> <option value="medsci" > Medical Sciences </option> <option value="msf" > Medical Sciences Forum </option> <option value="medicina" > Medicina </option> <option value="medicines" > Medicines </option> <option value="membranes" > Membranes </option> <option value="merits" > Merits </option> <option value="metabolites" > Metabolites </option> <option value="metals" > Metals </option> <option value="meteorology" > Meteorology </option> <option value="methane" > Methane </option> <option value="mps" > Methods and Protocols (MPs) </option> <option value="metrics" > Metrics </option> <option value="metrology" > Metrology </option> <option value="micro" > Micro </option> <option value="microbiolres" > Microbiology Research </option> <option value="micromachines" > Micromachines </option> <option value="microorganisms" > Microorganisms </option> <option value="microplastics" > Microplastics </option> <option value="microwave" > Microwave </option> <option value="minerals" > Minerals </option> <option value="mining" > Mining </option> <option value="modelling" > Modelling </option> <option value="mmphys" > Modern Mathematical Physics </option> <option value="molbank" > Molbank </option> <option value="molecules" > Molecules </option> <option value="mti" > Multimodal Technologies and Interaction (MTI) </option> <option value="muscles" > Muscles </option> <option value="nanoenergyadv" > Nanoenergy Advances </option> <option value="nanomanufacturing" > Nanomanufacturing </option> <option value="nanomaterials" > Nanomaterials </option> <option value="ndt" > NDT </option> <option value="network" > Network </option> <option value="neuroglia" > Neuroglia </option> <option value="neurolint" > Neurology International </option> <option value="neurosci" > NeuroSci </option> <option value="nitrogen" > Nitrogen </option> <option value="ncrna" selected='selected'> Non-Coding RNA (ncRNA) </option> <option value="nursrep" > Nursing Reports </option> <option value="nutraceuticals" > Nutraceuticals </option> <option value="nutrients" > Nutrients </option> <option value="obesities" > Obesities </option> <option value="oceans" > Oceans </option> <option value="onco" > Onco </option> <option value="optics" > Optics </option> <option value="oral" > Oral </option> <option value="organics" > Organics </option> <option value="organoids" > Organoids </option> <option value="osteology" > Osteology </option> <option value="oxygen" > Oxygen </option> <option value="parasitologia" > Parasitologia </option> <option value="particles" > Particles </option> <option value="pathogens" > Pathogens </option> <option value="pathophysiology" > Pathophysiology </option> <option value="pediatrrep" > Pediatric Reports </option> <option value="pets" > Pets </option> <option value="pharmaceuticals" > Pharmaceuticals </option> <option value="pharmaceutics" > Pharmaceutics </option> <option value="pharmacoepidemiology" > Pharmacoepidemiology </option> <option value="pharmacy" > Pharmacy </option> <option value="philosophies" > Philosophies </option> <option value="photochem" > Photochem </option> <option value="photonics" > Photonics </option> <option value="phycology" > Phycology </option> <option value="physchem" > Physchem </option> <option value="psf" > Physical Sciences Forum </option> <option value="physics" > Physics </option> <option value="physiologia" > Physiologia </option> <option value="plants" > Plants </option> <option value="plasma" > Plasma </option> <option value="platforms" > Platforms </option> <option value="pollutants" > Pollutants </option> <option value="polymers" > Polymers </option> <option value="polysaccharides" > Polysaccharides </option> <option value="populations" > Populations </option> <option value="poultry" > Poultry </option> <option value="powders" > Powders </option> <option value="proceedings" > Proceedings </option> <option 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value="reports" > Reports </option> <option value="reprodmed" > Reproductive Medicine (Reprod. Med.) </option> <option value="resources" > Resources </option> <option value="rheumato" > Rheumato </option> <option value="risks" > Risks </option> <option value="robotics" > Robotics </option> <option value="ruminants" > Ruminants </option> <option value="safety" > Safety </option> <option value="sci" > Sci </option> <option value="scipharm" > Scientia Pharmaceutica (Sci. Pharm.) </option> <option value="sclerosis" > Sclerosis </option> <option value="seeds" > Seeds </option> <option value="sensors" > Sensors </option> <option value="separations" > Separations </option> <option value="sexes" > Sexes </option> <option value="signals" > Signals </option> <option value="sinusitis" > Sinusitis </option> <option value="smartcities" > Smart Cities </option> <option value="socsci" > Social Sciences </option> <option value="siuj" > Société Internationale d’Urologie Journal (SIUJ) </option> <option value="societies" > Societies </option> <option value="software" > Software </option> <option value="soilsystems" > Soil Systems </option> <option value="solar" > Solar </option> <option value="solids" > Solids </option> <option value="spectroscj" > Spectroscopy Journal </option> <option value="sports" > Sports </option> <option value="standards" > Standards </option> <option value="stats" > Stats </option> <option value="stresses" > Stresses </option> <option value="surfaces" > Surfaces </option> <option value="surgeries" > Surgeries </option> <option value="std" > Surgical Techniques Development </option> <option value="sustainability" > Sustainability </option> <option value="suschem" > Sustainable Chemistry </option> <option value="symmetry" > Symmetry </option> <option value="synbio" > SynBio </option> <option value="systems" > Systems </option> <option value="targets" > Targets </option> <option value="taxonomy" > Taxonomy </option> <option value="technologies" > Technologies </option> <option value="telecom" > Telecom </option> <option value="textiles" > Textiles </option> <option value="thalassrep" > Thalassemia Reports </option> <option value="therapeutics" > Therapeutics </option> <option value="thermo" > Thermo </option> <option value="timespace" > Time and Space </option> <option value="tomography" > Tomography </option> <option value="tourismhosp" > Tourism and Hospitality </option> <option value="toxics" > Toxics </option> 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<div class="content__container content__container__orbit "> <div id="title-story" class=""> <ul class="title-story-orbit" data-orbit> <li > <a href="/2311-553X/11/1/2"> <img src="https://pub.mdpi-res.com/title_story/title_story_17375148253535.jpg?1738220884" alt="LncRNA <em>3222401L13Rik</em> Is Upregulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3" /> <div class="orbit-caption"> LncRNA <em>3222401L13Rik</em> Is Upregulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3 </div> </a> </li> <li class="hidden"> <a href="/2311-553X/11/1/4"> <img src="https://pub.mdpi-res.com/title_story/title_story_17375147883419.jpg?1738220884" alt="Integrative Analysis of Whole-Genome and Transcriptomic Data Reveals Novel Variants in Differentially Expressed Long Noncoding RNAs Associated with Asthenozoospermia" /> <div class="orbit-caption"> Integrative Analysis of Whole-Genome and Transcriptomic Data Reveals Novel Variants in Differentially Expressed Long Noncoding RNAs Associated with Asthenozoospermia </div> </a> </li> </ul> </div> </div> <div class="content__container"> <div class="custom-accordion-for-small-screen-link show-for-small-only"> <h2 class="no-padding-left no-margin">Journal Description</h2> </div> <div class="custom-accordion-for-small-screen-content show-for-medium-up"> <div class="journal__description"> <h1> <em>Non-Coding RNA</em> </h1> <div class="journal__description__content"> <em>Non-Coding RNA</em> is an international, <a href="https://www.mdpi.com/editorial_process">peer-reviewed</a>, open access journal on non-coding RNA research dealing with elucidating the structure, function and biology of regulatory non-coding RNAs. <em>Non-Coding RNA</em> is published bimonthly online by MDPI. <a href="https://clarissa-gomes-v6pb.squarespace.com/">Cardiolinc</a> is affiliated with <em>Non-Coding RNA</em>. <ul> <li><strong><span class="label openaccess"><a title="Open Access" 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appreciation of the work done.</li> </ul> </div> <div style="margin-bottom: 15px;"> <strong>Impact Factor:</strong> 3.6 (2023) </div> <div> <a href="/journal/ncrna/imprint" class="UI_JournalImprintsInfoButton"> <i class="material-icons spaced-link">subject</i> Imprint Information </a>    <a href="/journal/ncrna/ncrna_flyer.pdf" class="UD_JournalFlyer"> <i class="material-icons spaced-link">get_app</i> Journal Flyer </a>     <a class="oa-link" href="https://www.mdpi.com/about/openaccess"> <i class="material icons spaced-link"></i> Open Access </a>     <strong> ISSN: 2311-553X </strong> </div> <div style="clear: both;"></div> </div> </div> </div> <div class="content__container content__container--overflow-initial"> <div class="custom-accordion-for-small-screen-link active"> <h2 class="no-padding-left">Latest Articles</h2> </div> <div class="custom-accordion-for-small-screen-content"> <div class="expanding-div collapsed"> <div class="generic-item article-item no-border"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 1200 KiB   </span> <a href="/2311-553X/11/1/9/pdf?version=1738161349" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Long Intergenic Non-Coding RNAs and BRCA1 in Breast Cancer Pathogenesis: Neighboring Companions or Nemeses?" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/11/1/9">Long Intergenic Non-Coding RNAs and <i>BRCA1</i> in Breast Cancer Pathogenesis: Neighboring Companions or Nemeses?</a> <div class="authors"> by <span class="inlineblock "><strong>Olalekan Olatunde Fadebi</strong>, </span><span class="inlineblock "><strong>Thabiso Victor Miya</strong>, </span><span class="inlineblock "><strong>Richard Khanyile</strong>, </span><span class="inlineblock "><strong>Zodwa Dlamini</strong> and </span><span class="inlineblock "><strong>Rahaba Marima</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 9; <a href="https://doi.org/10.3390/ncrna11010009">https://doi.org/10.3390/ncrna11010009</a> - 29 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Breast cancer is one of the leading causes of mortality among women, primarily due to its complex molecular landscape and heterogeneous nature. The tendency of breast cancer patients to develop metastases poses significant challenges in clinical management. Notably, mutations in the breast cancer <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/9/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Breast cancer is one of the leading causes of mortality among women, primarily due to its complex molecular landscape and heterogeneous nature. The tendency of breast cancer patients to develop metastases poses significant challenges in clinical management. Notably, mutations in the breast cancer gene 1 (<i>BRCA1</i>) significantly elevate breast cancer risk. The current research endeavors employ diverse molecular approaches, including RNA, DNA, and protein studies, to explore avenues for the early diagnosis and treatment of breast cancer. Recent attention has shifted towards long non-coding RNAs (lncRNAs) as promising diagnostic, prognostic, and therapeutic targets in the multifaceted progression of breast cancer. Among these, long intergenic non-coding RNAs (lincRNAs), a specific class of lncRNAs, play critical roles in regulating various aspects of tumorigenesis, including cell proliferation, apoptosis, epigenetic modulation, tumor invasion, and metastasis. Their distinctive expression patterns in cellular and tissue contexts underscore their importance in breast cancer development and progression. Harnessing lincRNAs’ sensitivity and precision as diagnostic, therapeutic, and prognostic markers holds significant promise for the clinical management of breast cancer. However, the potential of lincRNAs remains relatively underexplored, particularly in the context of <i>BRCA1</i>-mutated breast cancer and other clinicopathological parameters such as receptor status and patient survival. Consequently, there is an urgent need for comprehensive investigations into novel diagnostic and prognostic breast cancer biomarkers. This review examines the roles of lincRNAs associated with <i>BRCA1</i> in the landscape of breast cancer, highlighting the potential avenues for future research and clinical applications. <a href="/2311-553X/11/1/9">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/9/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1579808"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1579808"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1579808" data-cycle-prev="#prev1579808" data-cycle-progressive="#images1579808" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1579808-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g001-550.jpg?1738161418" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1579808" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1579808-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g002-550.jpg?1738161419'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1579808-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g003-550.jpg?1738161420'><p>Figure 3</p></div></script></div></div><div id="article-1579808-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g001-550.jpg?1738161418" title=" <strong>Figure 1</strong><br/> <p>Estimated cancer incidence and mortality rates worldwide in 2022. Data Source: GLOBOCAN 2022, Graph Production: Global Cancer Observatory <a href="http://gco.iarc.fr" target="_blank">http://gco.iarc.fr</a> (accessed on 8 October 2024). International Agency for Research on Cancer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/9'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g002-550.jpg?1738161419" title=" <strong>Figure 2</strong><br/> <p>(<b>a</b>) Main roles of <span class="html-italic">BRCA1</span>. An overview of <span class="html-italic">BRCA1</span>’<span class="html-italic">s</span> physiological functions in HR, repair during the DNA-replication recruitment of DNA damage site, G1/MS-phase checkpoint regulation, and DNA end resection. (<b>b</b>) <span class="html-italic">BRCA1</span>-mutated breast cancer associated with TNBC based on their expression of hormone receptors (ER, PR, and HER2). The image was self-created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/9'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00009/article_deploy/html/images/ncrna-11-00009-g003-550.jpg?1738161420" title=" <strong>Figure 3</strong><br/> <p>Regulation of the pRB and p53 pathways by the lincRNAs <span class="html-italic">ANRIL</span>, <span class="html-italic">lincRNA-p21</span>, and <span class="html-italic">lincRNA-ROR</span>. These lincRNAs regulate the pRB and p53 pathways by modulating the expression of CDK inhibitors p15 and p16, which impact pRB activity. <span class="html-italic">ANRIL</span> acts as a coregulator by binding to polycomb proteins. In response to DNA damage, p53 produces <span class="html-italic">lincRNA-p21</span>, <span class="html-italic">lincRNA-ROR</span>, and <span class="html-italic">PANDA</span> to regulate apoptosis. The image was self-created using BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/9'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="extending-content content-ready"> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1571943" aria-controls="drop-supplementary-1571943" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1571943" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2311-553X/11/1/8/s1?version=1737386951"> Supplementary File 1 (ZIP, 9195 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 2376 KiB   </span> <a href="/2311-553X/11/1/8/pdf?version=1737700731" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Anti-HIV-1 Effect of the Fluoroquinolone Enoxacin and Modulation of Pro-Viral hsa-miR-132 Processing in CEM-SS Cells" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/11/1/8">Anti-HIV-1 Effect of the Fluoroquinolone Enoxacin and Modulation of Pro-Viral hsa-miR-132 Processing in CEM-SS Cells</a> <div class="authors"> by <span class="inlineblock "><strong>Verena Schlösser</strong>, </span><span class="inlineblock "><strong>Helen Louise Lightfoot</strong>, </span><span class="inlineblock "><strong>Christine Leemann</strong>, </span><span class="inlineblock "><strong>Aathma Merin Bejoy</strong>, </span><span class="inlineblock "><strong>Shashank Tiwari</strong>, </span><span class="inlineblock "><strong>Jeffrey L. Schloßhauer</strong>, </span><span class="inlineblock "><strong>Valentina Vongrad</strong>, </span><span class="inlineblock "><strong>Andreas Brunschweiger</strong>, </span><span class="inlineblock "><strong>Jonathan Hall</strong>, </span><span class="inlineblock "><strong>Karin J. Metzner</strong> and </span><span class="inlineblock "><strong>Jochen Imig</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 8; <a href="https://doi.org/10.3390/ncrna11010008">https://doi.org/10.3390/ncrna11010008</a> - 20 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background: Despite tremendous advances in antiretroviral therapy (ART) against HIV-1 infections, no cure or vaccination is available. Therefore, discovering novel therapeutic strategies remains an urgent need. In that sense, miRNAs and miRNA therapeutics have moved intensively into the focus of recent HIV-1-related investigations. <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/8/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background: Despite tremendous advances in antiretroviral therapy (ART) against HIV-1 infections, no cure or vaccination is available. Therefore, discovering novel therapeutic strategies remains an urgent need. In that sense, miRNAs and miRNA therapeutics have moved intensively into the focus of recent HIV-1-related investigations. A strong reciprocal interdependence has been demonstrated between HIV-1 infection and changes of the intrinsic cellular miRNA milieu. This interrelationship may direct potential alterations of the host cells’ environment beneficial for the virus or its suppression of replication. Whether this tightly balanced and controlled battle can be exploited therapeutically remains to be further addressed. In this context, the fluoroquinolone antibiotic Enoxacin has been demonstrated as a potent modulator of miRNA processing. Here, we test the hypothesis that this applies also to selected HIV-1-related miRNAs. Methods: We studied the effect of Enoxacin on HIV-1 replication coupled with miRNA qRT-PCR analysis of HIV-1-related miRNAs in CEM-SS and MT-4 T-cells. The effects of miRNA mimic transfections combined with Enoxacin treatment on HIV-1 replication were assessed. Finally, we employed an in vitro DICER1 cleavage assay to study the effects of Enoxacin on a pro-HIV-1 miRNA hsa-miR-132 processing. Results: We established that Enoxacin, but not the structurally similar compound nalidixic acid, exhibits strong anti-HIV-1 effects in the T-cell line CEM-SS, but not MT-4. We provide experimental data that this effect of Enoxacin is partly attributed to the specific downregulation of mature hsa-miR-132-3p, but not other tested pro- or anti-HIV-1 miRNAs, which is likely due to affecting DICER1 processing. Conclusions: Our findings show an anti-retroviral activity of Enoxacin at least in part by downregulation of hsa-miR-132-3p, which may be relevant for future antiviral therapeutic applications by modulation of the RNA interference pathway. <a href="/2311-553X/11/1/8">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/ncrna/sections/Small_Non-Coding_RNA">Small Non-Coding RNA</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/8/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1571943"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1571943"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1571943" data-cycle-prev="#prev1571943" data-cycle-progressive="#images1571943" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1571943-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g001-550.jpg?1737700824" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1571943" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1571943-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g002-550.jpg?1737700825'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1571943-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g003-550.jpg?1737700827'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1571943-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g004-550.jpg?1737700829'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1571943-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g005-550.jpg?1737700831'><p>Figure 5</p></div></script></div></div><div id="article-1571943-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g001-550.jpg?1737700824" title=" <strong>Figure 1</strong><br/> <p>TaqMan qRT-PCR analysis of selected anti- and pro-HIV miRNAs in CEM-SS cells. Cells were treated for 4 and 7 days post-infection with 50 µM final concentration of (<b>a</b>) Enoxacin, (<b>b</b>) nalidixic acid relative to equivalent volume of DMSO control. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01 two-tailed Student’s t-test. Error bars indicate ± 1 s.d.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/8'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g002-550.jpg?1737700825" title=" <strong>Figure 2</strong><br/> <p>Effect of Enoxacin and nalidixic acid on HIV-1 replication in (<b>a</b>) CEM-SS cells over two to ten days p.i. (red arrows indicate time points of qPCR in (<b>c</b>)) measured by p24-ELISA. (<b>b</b>) Fold inhibition of Enoxacin at 50 µM final concentration on HIV-1 replication compared to controls in CEM-SS and (<b>c</b>) MT-4 cells were spin-infected with HIV-1HXB2 at MOI 0.01 and monitored for p24 expression in cell culture supernatant. Untreated cells infected with HIV-1 served as positive, DMSO treatment as negative and no virus as background controls, respectively. (<span class="html-italic">n</span> = 4, technical duplicates, DMSO control = nominator, fold-inhibition = 1), ** <span class="html-italic">p</span> &lt; 0.01, two-tailed Mann Whitney U test. Error bars indicate ± 1 s.d. (<b>d</b>) Pro-HIV-1 miR-132-3p relative expression mirrors the anti-HIV-1 effect of Enoxacin at days 4 and 7 but not control miR-223 (anti-HIV-1) or miR-23-a (T-cell miRNA) compared to DMSO by qRT-PCR. ** <span class="html-italic">p</span> &lt; 0.01 two-tailed Student’s <span class="html-italic">t</span>-test. Error bars indicate ± 1 s.d., red arrows indicate time points of significance for p24-ELISA and corresponding qPCR.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/8'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g003-550.jpg?1737700827" title=" <strong>Figure 3</strong><br/> <p>Hsa-miR-132-3p enhances HIV-1 replication in CEM-SS cells. Cells were spin-infected with HIV-1HXB2 at MOI 0.01 and monitored for p24 expression in supernatant at days 0 and 10 post-infection (p.i.) reverse transfected with miR-mimic or scrambled control at 100 nM plus DMSO. DMSO/mock transfection served as negative and cells and virus alone as positive control. Grey arrow indicates time of transfection. <span class="html-italic">n</span> = 2, * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01, two-tailed Student’s <span class="html-italic">t</span>-test. Error bars indicate ± 1 s.d.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/8'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g004-550.jpg?1737700829" title=" <strong>Figure 4</strong><br/> <p>Hsa-miR-132-3p partially rescues Enoxacin-dependent anti-HIV-1 effect in CEM-SS cells. Cells were spin-infected with HIV-1HXB2 at MOI 0.01 and monitored for p24 expression in supernatant over 4 to 10 days post-infection (p.i.) in the presence of 50 µM final concentration of Enoxacin or respective equivalent volume of DMSO control as shown as fold HIV-1 inhibition by p24 ELISA. Untreated cells infected with HIV-1 served as positive control. Cells were reverse transfected in DMSO or Enoxacin treatment with 100 nM concentration of hsa-miR-132-3p mimic or scrambled control. DMSO and Enoxacin treatment with mock transfection served as additional controls. <span class="html-italic">n</span> = 2, two-tailed Mann-Whitney U-test, error bars indicate ± 1 s.d.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/8'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00008/article_deploy/html/images/ncrna-11-00008-g005-550.jpg?1737700831" title=" <strong>Figure 5</strong><br/> <p>In vitro DICER1 cleavage assay in CEM-SS lysates (<b>a</b>) or recombinant DICER1 protein alone (<b>b</b>). miR-132 hairpin was 5′- (<b>a</b>) or 3′ (<b>b</b>) γ-phosphate labeled and incubated in 100 µM, 300 µM and 1 mM Enoxacin or DMSO control at 37 °C for between 0 and 60 min and PAGE-gel separated. Pre-miR and miR bands were densitometrically quantified and DICER1 processing effect was plotted as normalized ratio to DMSO (<b>a</b>) or % cleavage (<b>b</b>). Note: See full autoradiograms and other replicates <a href="#app1-ncrna-11-00008" class="html-app">Figure S5</a>. (<b>c</b>) In vitro SHAPE-MaP reactivity scores plotted on RNAstructure prediction of pre-miR-132 in the presence of 150 and 300 µM Enoxacin and negative control (0 µM Enoxacin). Red triangles indicate DICER1 and blue triangles DROSHA cleavage sites. Light red sequences indicate significant structural rearrangements (marked by asterisks) determined by SHAPE scores of Enoxacin treatment vs. control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/8'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 2348 KiB   </span> <a href="/2311-553X/11/1/7/pdf?version=1737093349" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Role of Long Non-Coding RNA in the Pathogenesis of Psoriasis" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/11/1/7">The Role of Long Non-Coding RNA in the Pathogenesis of Psoriasis</a> <div class="authors"> by <span class="inlineblock "><strong>Kajetan Kiełbowski</strong>, </span><span class="inlineblock "><strong>Anna Jędrasiak</strong>, </span><span class="inlineblock "><strong>Estera Bakinowska</strong> and </span><span class="inlineblock "><strong>Andrzej Pawlik</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 7; <a href="https://doi.org/10.3390/ncrna11010007">https://doi.org/10.3390/ncrna11010007</a> - 17 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Psoriasis is a chronic immune-mediated disease with complex pathogenesis. The altered proliferation and differentiation of keratinocytes, together with the activity of dendritic cells and T cells, are crucial drivers of psoriasis progression. Long non-coding RNAs (lncRNAs) are composed of over 200 nucleotides and <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/7/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Psoriasis is a chronic immune-mediated disease with complex pathogenesis. The altered proliferation and differentiation of keratinocytes, together with the activity of dendritic cells and T cells, are crucial drivers of psoriasis progression. Long non-coding RNAs (lncRNAs) are composed of over 200 nucleotides and exert a large variety of functions, including the regulation of gene expression. Under pathological conditions, the expression of lncRNAs is frequently dysregulated. Recent studies demonstrated that lncRNAs significantly affect major cellular processes, and their aberrant expression is likely involved in the pathogenesis of various disorders. In this review, we will discuss the role of lncRNAs in the pathophysiology of psoriasis. We will summarize recent studies that investigated the relationships between lncRNAs and keratinocyte proliferation and pro-inflammatory responses. <a href="/2311-553X/11/1/7">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/7/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1568968"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1568968"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1568968" data-cycle-prev="#prev1568968" data-cycle-progressive="#images1568968" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1568968-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g001-550.jpg?1737093446" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1568968" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1568968-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g002-550.jpg?1737093447'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1568968-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g003-550.jpg?1737093448'><p>Figure 3</p></div></script></div></div><div id="article-1568968-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g001-550.jpg?1737093446" title=" <strong>Figure 1</strong><br/> <p>A simplified model of immune cells implicated in the pathogenesis of psoriasis. Dendritic cells secrete IL-23, which induces the differentiation of Th22 and Th17 cells. Cytokines secreted by differentiated T cells induce keratinocyte activation and drive the development of psoriatic lesions. Created in BioRender. Kiełbowski, K. <a href="https://BioRender.com/p62u479" target="_blank">https://BioRender.com/p62u479</a>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/7'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g002-550.jpg?1737093447" title=" <strong>Figure 2</strong><br/> <p>Long non-coding RNAs regulate the expression of STAT3 transcription factor to mediate keratinocyte proliferation. Created in BioRender. Kiełbowski, K. <a href="https://BioRender.com/u84r183" target="_blank">https://BioRender.com/u84r183</a>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/7'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00007/article_deploy/html/images/ncrna-11-00007-g003-550.jpg?1737093448" title=" <strong>Figure 3</strong><br/> <p>The involvement of long non-coding RNA in the IL-22- and IL-17-mediated stimulation of keratinocyte proliferation. Created in BioRender. Kiełbowski, K. <a href="https://BioRender.com/v29i018" target="_blank">https://BioRender.com/v29i018</a>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/7'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 3151 KiB   </span> <a href="/2311-553X/11/1/6/pdf?version=1736927322" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="In Silico Prediction of Maize microRNA as a Xanthine Oxidase Inhibitor: A New Approach to Treating Hyperuricemia Patients" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/11/1/6">In Silico Prediction of Maize microRNA as a Xanthine Oxidase Inhibitor: A New Approach to Treating Hyperuricemia Patients</a> <div class="authors"> by <span class="inlineblock "><strong>Manas Joshi</strong> and </span><span class="inlineblock "><strong>Mohd Mabood Khan</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 6; <a href="https://doi.org/10.3390/ncrna11010006">https://doi.org/10.3390/ncrna11010006</a> - 15 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Introduction: Hyperuricemia is characterized by increased uric acid (UA) in the body. The ability to block xanthine oxidase (XO) is a useful way to check how different bioactive molecules affect hyperuricemia. Previous reports showed the significant effect of corn against hyperuricemia disorder with <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/6/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Introduction: Hyperuricemia is characterized by increased uric acid (UA) in the body. The ability to block xanthine oxidase (XO) is a useful way to check how different bioactive molecules affect hyperuricemia. Previous reports showed the significant effect of corn against hyperuricemia disorder with its anti-XO activity. The identification of stable Zea mays miRNA (zma-miR) in humans has opened up a new avenue for speculation about its part in regulating novel human gene targets. Aims: The aim of this study was to investigate the prospects of zma-miRs in XO gene regulation, the possible mechanism, and the interaction analysis of the zma-miR-XO mRNA transcript. Method: Significant features of miRNA-mRNA interaction were revealed using two popular miRNA target prediction software—intaRNA (version 3.3.1) and RNA hybrid (version 2.2.1) Results: Only 12 zma-miR-156 variants, out of the 325 zma-miR’s sequences reported in the miRNA database, efficiently interact with the 3′UTR of the XO gene. Characteristics of miRNA-mRNA interaction were as follows: the positioning of zma-miR-156 variants shows that they all have the same 11-mer binding sites, guanine (G), and uracil (U) loops at the 13th and 14th positions from the 5′ end, and no G: U wobble pairing. These factors are related to the inhibition of functional mRNA expression. Additionally, the zma-miR-156 variants exhibit a single-base variation (SBV), which leads to distinct yet highly effective alterations in their interaction pattern with the XO mRNA transcript and the corresponding free energy values. Conclusion: Therefore, we propose that zma-miR-156 variants may be a promising new bioactive compound against hyperuricemia and related diseases. <a href="/2311-553X/11/1/6">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/6/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1567223"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1567223"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1567223" data-cycle-prev="#prev1567223" data-cycle-progressive="#images1567223" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1567223-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00006/article_deploy/html/images/ncrna-11-00006-g001-550.jpg?1736927401" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1567223" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1567223-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00006/article_deploy/html/images/ncrna-11-00006-g002-550.jpg?1736927403'><p>Figure 2</p></div></script></div></div><div id="article-1567223-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00006/article_deploy/html/images/ncrna-11-00006-g001-550.jpg?1736927401" title=" <strong>Figure 1</strong><br/> <p>Sequence alignment figure of zma-miR-156 variants generated by the T-coffee alignment program. Nucleotide differences in zma miR 156 variants from conserved sequence are indicated in red, and the extra nucleotide is indicated in green.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/6'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00006/article_deploy/html/images/ncrna-11-00006-g002-550.jpg?1736927403" title=" <strong>Figure 2</strong><br/> <p>Diagrammatic view of the xanthine oxidase pathways and mode of action of the zma-miRNA 156 family.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/6'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 1409 KiB   </span> <a href="/2311-553X/11/1/5/pdf?version=1736848579" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Plasma Humanin and Non-Coding RNAs as Biomarkers of Endothelial Dysfunction in Rheumatoid Arthritis: A Pilot Study" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/11/1/5">Plasma Humanin and Non-Coding RNAs as Biomarkers of Endothelial Dysfunction in Rheumatoid Arthritis: A Pilot Study</a> <div class="authors"> by <span class="inlineblock "><strong>Donatella Coradduzza</strong>, </span><span class="inlineblock "><strong>Sara Cruciani</strong>, </span><span class="inlineblock "><strong>Biagio Di Lorenzo</strong>, </span><span class="inlineblock "><strong>Maria Rosaria De Miglio</strong>, </span><span class="inlineblock "><strong>Angelo Zinellu</strong>, </span><span class="inlineblock "><strong>Margherita Maioli</strong>, </span><span class="inlineblock "><strong>Serenella Medici</strong>, </span><span class="inlineblock "><strong>Gian Luca Erre</strong> and </span><span class="inlineblock "><strong>Ciriaco Carru</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 5; <a href="https://doi.org/10.3390/ncrna11010005">https://doi.org/10.3390/ncrna11010005</a> - 14 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background:</b> Rheumatoid arthritis (RA) is a chronic autoimmune disorder associated with an increased risk of cardiovascular disease (CVD), largely driven by peripheral endothelial dysfunction (ED). Humanin, a mitochondrial-derived peptide, has been suggested to play a protective role in endothelial function. However, the relationship <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/5/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background:</b> Rheumatoid arthritis (RA) is a chronic autoimmune disorder associated with an increased risk of cardiovascular disease (CVD), largely driven by peripheral endothelial dysfunction (ED). Humanin, a mitochondrial-derived peptide, has been suggested to play a protective role in endothelial function. However, the relationship between Humanin levels and ED in RA, as well as the interaction between Humanin and non-coding RNAs such as Long Non-Coding RNA GAS5, microRNA-21 (miR-21), and microRNA-103 (miR-103), remains unclear. <b>Objective:</b> This study aimed to investigate the relationship between circulating Humanin levels, non-coding RNAs (GAS5, miR-21, miR-103), and endothelial dysfunction (ED) in patients with RA. Additionally, we explored the correlation between Humanin expression and specific non-coding RNAs (GAS5, miR-21, and miR-103) to better understand their potential role in vascular health. <b>Methods:</b> Peripheral ED was assessed using flow-mediated pulse amplitude tonometry, with Ln-RHI values <0.51 indicating dysfunction. Humanin levels, GAS5, miR-21, and miR-103 were measured in RA patients. Univariate and multivariate analyses were conducted to determine the relationship between these biomarkers and ED. Kaplan–Meier survival analysis and ROC curve analysis were used to assess the prognostic value of Humanin. <b>Results:</b> Higher Humanin levels were significantly associated with better endothelial function (OR = 0.9774, <i>p</i> = 0.0196). Kaplan–Meier analysis demonstrated that higher Humanin levels correlated with improved survival (<i>p</i> < 0.0001). The non-coding RNAs (GAS5, miR-21, and miR-103) did not show significant associations with ED. <b>Conclusions:</b> Humanin is a potential protective biomarker for endothelial dysfunction and survival in RA patients. Further research is needed to explore the interaction between Humanin and non-coding RNAs in the context of vascular health. <a href="/2311-553X/11/1/5">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/5/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1566571"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1566571"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1566571" data-cycle-prev="#prev1566571" data-cycle-progressive="#images1566571" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1566571-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g001-550.jpg?1736848663" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1566571" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1566571-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g002-550.jpg?1736848665'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1566571-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g003-550.jpg?1736848666'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1566571-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g004-550.jpg?1736848667'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1566571-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g005-550.jpg?1736848669'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1566571-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g006-550.jpg?1736848669'><p>Figure 6</p></div></script></div></div><div id="article-1566571-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g001-550.jpg?1736848663" title=" <strong>Figure 1</strong><br/> <p>miRNA expression in plasma and exosomes. The expression of miR-21 Panels (<b>A</b>) and (<b>B</b>) and miR-103 Panels (<b>C</b>) and (<b>D</b>) was evaluated in plasma and exosomes. mRNA levels were normalized to U6snRNA. The data are presented as the mean ± SD relative to the control (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, and **** <span class="html-italic">p</span> ≤ 0.0001).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g002-550.jpg?1736848665" title=" <strong>Figure 2</strong><br/> <p>Lnc-RNA GAS5 expression in plasma (<b>A</b>) and (<b>B</b>). Expression levels were normalized to Glyceraldehyde-3-Phosphate-Dehydrogenase (GAPDH). The data are presented as the mean ± SD relative to the control (**** <span class="html-italic">p</span> ≤ 0.0001).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g003-550.jpg?1736848666" title=" <strong>Figure 3</strong><br/> <p>Humanin levels in plasma were determined by ELISA. Data are presented as mean ± SD relative to control (**** <span class="html-italic">p</span> ≤ 0.0001).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g004-550.jpg?1736848667" title=" <strong>Figure 4</strong><br/> <p>ROC curve analysis for Humanin’s predictive value for ED.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g005-550.jpg?1736848669" title=" <strong>Figure 5</strong><br/> <p>Kaplan–Meier survival analysis to evaluate the prognostic value of Humanin levels for survival outcomes. 0 = patients with serum Humanin concentration &lt; 124.44pg/mL; 1 = patients with serum Humanin concentration ≥ 124.44pg/mL.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00005/article_deploy/html/images/ncrna-11-00005-g006-550.jpg?1736848669" title=" <strong>Figure 6</strong><br/> <p>The Kaplan–Meier survival curve showing the survival probabilities for the two groups based on the ROC-determined Humanin levels. Group 0 (blue): Higher survival probability. Group 1 (red dashed): Lower survival probability. The number at risk at different time points is detailed in <a href="#ncrna-11-00005-t005" class="html-table">Table 5</a>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/5'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1566268" aria-controls="drop-supplementary-1566268" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1566268" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2311-553X/11/1/4/s1?version=1736835520"> Supplementary File 1 (ZIP, 412 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 23 pages, 1698 KiB   </span> <a href="/2311-553X/11/1/4/pdf?version=1737338187" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Integrative Analysis of Whole-Genome and Transcriptomic Data Reveals Novel Variants in Differentially Expressed Long Noncoding RNAs Associated with Asthenozoospermia" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/11/1/4">Integrative Analysis of Whole-Genome and Transcriptomic Data Reveals Novel Variants in Differentially Expressed Long Noncoding RNAs Associated with Asthenozoospermia</a> <div class="authors"> by <span class="inlineblock "><strong>Maria-Anna Kyrgiafini</strong>, </span><span class="inlineblock "><strong>Maria Katsigianni</strong>, </span><span class="inlineblock "><strong>Themistoklis Giannoulis</strong>, </span><span class="inlineblock "><strong>Theologia Sarafidou</strong>, </span><span class="inlineblock "><strong>Alexia Chatziparasidou</strong> and </span><span class="inlineblock "><strong>Zissis Mamuris</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 4; <a href="https://doi.org/10.3390/ncrna11010004">https://doi.org/10.3390/ncrna11010004</a> - 14 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background/Objectives</b>: Asthenozoospermia, characterized by reduced sperm motility, is a common cause of male infertility. Emerging evidence suggests that noncoding RNAs, particularly long noncoding RNAs (lncRNAs), play a critical role in the regulation of spermatogenesis and sperm function. Coding regions have a well-characterized <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/4/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background/Objectives</b>: Asthenozoospermia, characterized by reduced sperm motility, is a common cause of male infertility. Emerging evidence suggests that noncoding RNAs, particularly long noncoding RNAs (lncRNAs), play a critical role in the regulation of spermatogenesis and sperm function. Coding regions have a well-characterized role and established predictive value in asthenozoospermia. However, this study was designed to complement previous findings and provide a more holistic understanding of asthenozoospermia, this time focusing on noncoding regions. This study aimed to identify and prioritize variants in differentially expressed (DE) lncRNAs found exclusively in asthenozoospermic men, focusing on their impact on lncRNA structure and lncRNA–miRNA–mRNA interactions. <b>Methods</b>: Whole-genome sequencing (WGS) was performed on samples from asthenozoospermic and normozoospermic men. Additionally, an RNA-seq dataset from normozoospermic and asthenozoospermic individuals was analyzed to identify DE lncRNAs. Bioinformatics analyses were conducted to map unique variants on DE lncRNAs, followed by prioritization based on predicted functional impact. The structural impact of the variants and their effects on lncRNA–miRNA interactions were assessed using computational tools. Gene ontology (GO) and KEGG pathway analyses were employed to investigate the affected biological processes and pathways. <b>Results</b>: We identified 4173 unique variants mapped to 258 DE lncRNAs. After prioritization, 5 unique variants in 5 lncRNAs were found to affect lncRNA structure, while 20 variants in 17 lncRNAs were predicted to disrupt miRNA–lncRNA interactions. Enriched pathways included Wnt signaling, phosphatase binding, and cell proliferation, all previously implicated in reproductive health. <b>Conclusions</b>: This study identifies specific variants in DE lncRNAs that may play a role in asthenozoospermia. Given the limited research utilizing WGS to explore the role of noncoding RNAs in male infertility, our findings provide valuable insights and a foundation for future studies. <a href="/2311-553X/11/1/4">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ncrna/special_issues/NNSO9RA0IP ">Exploring Non-coding RNAs: Insights into Male Infertility</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/4/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1566268"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1566268"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1566268" data-cycle-prev="#prev1566268" data-cycle-progressive="#images1566268" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1566268-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g001-550.jpg?1737338279" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1566268" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1566268-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g002-550.jpg?1737338282'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1566268-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g003-550.jpg?1737338283'><p>Figure 3</p></div></script></div></div><div id="article-1566268-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g001-550.jpg?1737338279" title=" <strong>Figure 1</strong><br/> <p>Chromosomal distribution of unique variants found on DE lncRNAs in asthenozoospermic men. The <span class="html-italic">x</span>-axis represents the chromosomes, while the <span class="html-italic">y</span>-axis shows the number of variants.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/4'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g002-550.jpg?1737338282" title=" <strong>Figure 2</strong><br/> <p>Statistically significant (<b>a</b>) GO biological process, (<b>b</b>) GO molecular function, (<b>c</b>) GO cellular component, (<b>d</b>) KEGG pathway terms associated with the gene targets of the miRNAs that are affected by variants in DE lncRNAs (miRNA–lncRNA interaction disruption). The size and color of the dots represent the number of genes and the range of statistical significance, respectively. The <span class="html-italic">y</span>-axis represents biological terms, and the <span class="html-italic">x</span>-axis, the fold enrichment. The <span class="html-italic">p</span>-values were corrected for multiple tests using the false discovery rate (FDR).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/4'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00004/article_deploy/html/images/ncrna-11-00004-g003-550.jpg?1737338283" title=" <strong>Figure 3</strong><br/> <p>Flow chart of the study methodology and findings.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/4'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 1908 KiB   </span> <a href="/2311-553X/11/1/3/pdf?version=1736760419" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Perspectives in MicroRNA Therapeutics for Cystic Fibrosis" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/11/1/3">Perspectives in MicroRNA Therapeutics for Cystic Fibrosis</a> <div class="authors"> by <span class="inlineblock "><strong>Alessia Finotti</strong> and </span><span class="inlineblock "><strong>Roberto Gambari</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 3; <a href="https://doi.org/10.3390/ncrna11010003">https://doi.org/10.3390/ncrna11010003</a> - 12 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The discovery of the involvement of microRNAs (miRNAs) in cystic fibrosis (CF) has generated increasing interest in the past years, due to their possible employment as a novel class of drugs to be studied in pre-clinical settings of therapeutic protocols for cystic fibrosis. <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/3/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The discovery of the involvement of microRNAs (miRNAs) in cystic fibrosis (CF) has generated increasing interest in the past years, due to their possible employment as a novel class of drugs to be studied in pre-clinical settings of therapeutic protocols for cystic fibrosis. In this narrative review article, consider and comparatively evaluate published laboratory information of possible interest for the development of miRNA-based therapeutic protocols for cystic fibrosis. We consider miRNAs involved in the upregulation of CFTR, miRNAs involved in the inhibition of inflammation and, finally, miRNAs exhibiting antibacterial activity. We suggest that antago-miRNAs and ago-miRNAs (miRNA mimics) can be proposed for possible validation of therapeutic protocols in pre-clinical settings. <a href="/2311-553X/11/1/3">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/3/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1565279"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1565279"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1565279" data-cycle-prev="#prev1565279" data-cycle-progressive="#images1565279" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1565279-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g001-550.jpg?1736760529" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1565279" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1565279-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g002-550.jpg?1736760530'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1565279-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g003-550.jpg?1736760531'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1565279-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g004-550.jpg?1736760532'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1565279-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g005-550.jpg?1736760533'><p>Figure 5</p></div></script></div></div><div id="article-1565279-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g001-550.jpg?1736760529" title=" <strong>Figure 1</strong><br/> <p>MicroRNA therapeutics. Picture created using <a href="http://Bio-Render.com" target="_blank">Bio-Render.com</a> (7 November 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/3'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g002-550.jpg?1736760530" title=" <strong>Figure 2</strong><br/> <p>MicroRNA Therapeutics: the anti-miRNA approach. A forced inhibition of the miRNA activity can be obtained using antago-miRNA (anti-miRNA) oligonucleotides (AMOs) (e.g., DNA, RNA, and nucleic acids analogs such as LNA, PNA, 2′-MOE), delivered with vectors (A) or bioconjugated for an increased cellular uptake (e.g., R-PNAs) and/or a targeted delivery (B). MicroRNA inhibition can also be achieved using anti-miRNA sponge RNA sequences that contain multiple microRNA binding sites (C). The approach based on the use of zipper oligonucleotides is shown in panel (D) [<a href="#B31-ncrna-11-00003" class="html-bibr">31</a>]. The binding between the miRNA and the anti-miRNA molecules leads to the inactivation of the miRNA, as it can no longer bind to its molecular target, i.e., messenger RNA, thus increasing protein production. Picture created using <a href="http://Bio-Render.com" target="_blank">Bio-Render.com</a> (7 November 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/3'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g003-550.jpg?1736760531" title=" <strong>Figure 3</strong><br/> <p>MicroRNA therapeutics: the “miRNA-masking” approach. The down-regulation of microRNA functions is obtained through miRNA masking oligonucleotides and analogs delivered to cells (A,B), which act by masking the miRNAs binding site of target mRNAs through a direct hybridization of the miRNA “mask” with the 3′UTR region of mRNA. Created using <a href="http://Bio-Render.com" target="_blank">Bio-Render.com</a> (7 November 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/3'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g004-550.jpg?1736760532" title=" <strong>Figure 4</strong><br/> <p>MicroRNA therapeutics: the “miRNA-replacement” approach. This strategy is based on the use of molecules (mature double-strand microRNA mimics or pre-miRNA oligonucleotides) that can restore physiological levels of miRNA with consequent inhibition of mRNA translation. Created using <a href="http://Bio-Render.com" target="_blank">Bio-Render.com</a> (7 November 2024).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/3'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00003/article_deploy/html/images/ncrna-11-00003-g005-550.jpg?1736760533" title=" <strong>Figure 5</strong><br/> <p>Mechanism of action and molecular targets of miR-93-5p according to the reports published by Fabbri et al. [<a href="#B106-ncrna-11-00003" class="html-bibr">106</a>], Xu et al. [<a href="#B109-ncrna-11-00003" class="html-bibr">109</a>], and Gao et al. [<a href="#B111-ncrna-11-00003" class="html-bibr">111</a>]. MicroRNA miR-93-5p directly interacts with <span class="html-italic">IL-8</span> mRNA, thereby inhibiting IL-8 production and release [<a href="#B106-ncrna-11-00003" class="html-bibr">106</a>]; in addition, miR-93-5p inhibits <span class="html-italic">IRAK1</span>, thereby preventing NF-kB activation and expression of NF-kB-dependent genes, such as <span class="html-italic">IL-8</span> [<a href="#B109-ncrna-11-00003" class="html-bibr">109</a>]; in addition, miR-93-5p is able to interact with <span class="html-italic">TLR-4</span> mRNA [<a href="#B112-ncrna-11-00003" class="html-bibr">112</a>], thereby down-regulating the NF-kB pathway.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/3'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1563558" aria-controls="drop-supplementary-1563558" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1563558" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2311-553X/11/1/2/s1?version=1736429271"> Supplementary File 1 (ZIP, 1878 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 24 pages, 5992 KiB   </span> <a href="/2311-553X/11/1/2/pdf?version=1737908455" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="LncRNA 3222401L13Rik Is Upregulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/11/1/2">LncRNA <i>3222401L13Rik</i> Is Upregulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3</a> <div class="authors"> by <span class="inlineblock "><strong>Sophie Schröder</strong>, </span><span class="inlineblock "><strong>M. Sadman Sakib</strong>, </span><span class="inlineblock "><strong>Dennis M. Krüger</strong>, </span><span class="inlineblock "><strong>Tonatiuh Pena</strong>, </span><span class="inlineblock "><strong>Susanne Burkhardt</strong>, </span><span class="inlineblock "><strong>Anna-Lena Schütz</strong>, </span><span class="inlineblock "><strong>Farahnaz Sananbenesi</strong> and </span><span class="inlineblock "><strong>André Fischer</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 2; <a href="https://doi.org/10.3390/ncrna11010002">https://doi.org/10.3390/ncrna11010002</a> - 9 Jan 2025 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Aging leads to cognitive decline and increased risk of neurodegenerative diseases. While molecular changes in central nervous system (CNS) cells contribute to this decline, the mechanisms are not fully understood. Long non-coding RNAs (lncRNAs) are key regulators of cellular functions. <b>Background/Objectives:</b> The roles <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/2/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Aging leads to cognitive decline and increased risk of neurodegenerative diseases. While molecular changes in central nervous system (CNS) cells contribute to this decline, the mechanisms are not fully understood. Long non-coding RNAs (lncRNAs) are key regulators of cellular functions. <b>Background/Objectives:</b> The roles of lncRNAs in aging, especially in glial cells, are not well characterized. <b>Methods:</b> We investigated lncRNA expression in non-neuronal cells from aged mice and identified 3222401L13Rik, a previously unstudied lncRNA, as upregulated in astrocytes during aging. <b>Results:</b> Knockdown of 3222401L13Rik in primary astrocytes revealed its critical role in regulating genes for neuronal support and synapse organization, a function conserved in human iPSC-derived astrocytes. A 3222401L13Rik interacts with the transcription factor Neuronal PAS Domain Protein 3 (Npas3), and overexpression of Npas3 rescues deficits in astrocytes lacking 3222401L13Rik. <b>Conclusions:</b> These data suggest that 3222401L13Rik upregulation may help delay age-related cognitive decline. <a href="/2311-553X/11/1/2">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/ncrna/sections/clinical_applications">Clinical Applications of Non-Coding RNA</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/2/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1563558"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1563558"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1563558" data-cycle-prev="#prev1563558" data-cycle-progressive="#images1563558" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1563558-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g001-550.jpg?1737908559" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1563558" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1563558-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g002-550.jpg?1737908561'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1563558-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g003-550.jpg?1737908564'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1563558-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g004-550.jpg?1737908566'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1563558-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g005-550.jpg?1737908569'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1563558-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g006-550.jpg?1737908572'><p>Figure 6</p></div></script></div></div><div id="article-1563558-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g001-550.jpg?1737908559" title=" <strong>Figure 1</strong><br/> <p>Aging induces changes in glial lncRNA expression patterns. (<b>A</b>) Schematic illustration of the experimental approach of this study. (<b>B</b>) Heatmap showing gene expression changes in Neu– nuclei isolated in 3- vs. 16-month-old mice. (<b>C</b>) Volcano plot showing the up- and downregulated coding transcripts when comparing Neu– nuclei from 3 vs. 16-month-old mice (log2fold changes are depicted as 16/3 months). (<b>D</b>) Volcano plot showing expression changes in lncRNAs in Neu– nuclei (log2fold changes are depicted as 16/3 months).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g002-550.jpg?1737908561" title=" <strong>Figure 2</strong><br/> <p>A <span class="html-italic">3222401L13Rik</span> is a glial lncRNA that is upregulated in astrocytes during aging. (<b>A</b>) Schematic illustration of the genomic localization of <span class="html-italic">3222401L13Rik</span> in the mouse and <span class="html-italic">ENSG00000272070</span> in the human genome. (<b>B</b>) Expression of the lncRNA <span class="html-italic">3222401L13Rik</span> in NeuN+ and NeuN− cells isolated from the hippocampal CA1 region of 3-month-old mice (unpaired <span class="html-italic">t</span>-test; **** <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) qPCR data showing the expression of <span class="html-italic">3222401L13Rik</span> in NeuN− cells from 3- and 16-month-old mice (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05). (<b>D</b>) Expression of <span class="html-italic">3222401L13Rik</span> in astrocytes, oligodendrocytes, and microglia isolated from the brains of 3-month-old mice using MACS (One-way ANOVA; ns = not significant). (<b>E</b>) Expression of <span class="html-italic">3222401L13Rik</span> in astrocytes, oligodendrocytes, and microglia isolated from the brains of 3- and 16-month-old mice using MACS technology (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05, ns = not significant). Data are depicted as mean ± standard error.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g003-550.jpg?1737908564" title=" <strong>Figure 3</strong><br/> <p><span class="html-italic">3222401L13Rik</span> controls the expression of genes linked to innate immune response and synaptic support functions. (<b>A</b>) Representative image showing the nuclear localization of <span class="html-italic">3222401L13Rik</span> (RNAscope) in astrocytes (immunofluorescence for Gfap) in the adult mouse brain. Nuclei are stained using DAPI. (<b>B</b>) Bar chart showing the results of a qCPR that analyzes the expression of <span class="html-italic">3222401L13Rik</span> in nuclear and cytoplasmic fractions isolated from primary astrocytes (unpaired <span class="html-italic">t</span>-test; **** <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) Bar charts showing qPCR results to measure the expression levels of <span class="html-italic">3222401L13Rik</span> after treatment with NC or KD ASOs (**** <span class="html-italic">p</span> &lt; 0.0001). (<b>D</b>) Volcano Plot showing the up- and downregulated genes 48 h after the KD of <span class="html-italic">3222401L13Rik</span> in primary astrocytes (log2fold changes are depicted as KD/WT). (<b>E</b>) Gene Ontology analysis of the genes shown in (<b>D</b>). Analysis was performed using clusterProfiler (v4.6.0) [<a href="#B31-ncrna-11-00002" class="html-bibr">31</a>]. (Two-sided hypergeometric test was used to calculate the importance of each term, and the Benjamini–Hochberg procedure was applied for <span class="html-italic">p</span>-value correction). (<b>F</b>) Expression levels of selected genes that were deregulated after the KD of <span class="html-italic">3222401L13Rik</span>. Upper panel: upregulated genes. Lower panel: downregulated genes (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001). Data are depicted as mean ± standard error. NC: negative control, KD: knockdown of <span class="html-italic">3222401L13Rik</span>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g004-550.jpg?1737908566" title=" <strong>Figure 4</strong><br/> <p>The KD of <span class="html-italic">3222401L13Rik</span> affects glutamate uptake, Ca<sup>2+</sup> signaling, and the support of neuronal function. (<b>A</b>) qPCR showing the expression levels of the glutamate transporters <span class="html-italic">Glt-1</span> and <span class="html-italic">Glast</span> after the KD of <span class="html-italic">3222401L13Rik</span> in primary astrocytes (unpaired <span class="html-italic">t</span>-test; *** <span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) Left panel: Representative immunoblot images of Glt-1 and Glast following the KD of <span class="html-italic">3222401L13Rik</span>. in primary astrocytes. Right panel: Quantification of the left panel (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) Glutamate uptake of primary astrocytes after the KD of <span class="html-italic">3222401L13Rik</span> (unpaired <span class="html-italic">t</span>-test; ** <span class="html-italic">p</span> &lt; 0.01). (<b>D</b>) Increase in intracellular Ca<sup>2+</sup> levels in response to ATP treatment after the KD of <span class="html-italic">3222401L13Rik</span> (unpaired <span class="html-italic">t</span>-test; **** <span class="html-italic">p</span> &lt; 0.0001). (<b>E</b>) Survival of neurons after treatment with 100 µM glutamate cultured alone or co-cultured with NC or KD astrocytes (One-way ANOVA; * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, ns = not significant). (<b>F</b>) Left panel: Representative images of dendrite and spine labeling of neurons cultured alone or co-cultured with NC or KD astrocytes. Right panel: Quantification of spines shown in the left panel (One-way ANOVA; **** <span class="html-italic">p</span> &lt; 0.0001; ns = not significant). Data are depicted as mean ± standard error. NC: negative control. KD: knockdown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g005-550.jpg?1737908569" title=" <strong>Figure 5</strong><br/> <p>The synaptic support functions of <span class="html-italic">3222401L13Rik</span> are conserved in human astrocytes. (<b>A</b>) KD of <span class="html-italic">ENSG00000272070</span> in human iPSC-derived astrocytes (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Expression levels of interferon response genes after the KD of <span class="html-italic">ENSG00000272070</span> in human iPSC-derived astrocytes (unpaired <span class="html-italic">t</span>-test; *** <span class="html-italic">p</span> &lt; 0.001; ns = not significant). (<b>C</b>) Expression levels of genes associated with synaptic support after the KD of <span class="html-italic">ENSG00000272070</span> in human iPSC-derived astrocytes (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01). (<b>D</b>) qPCR showing the expression of the glutamate transporters <span class="html-italic">GLT-1</span> and <span class="html-italic">GLAST</span> after the KD of <span class="html-italic">ENSG00000272070</span> in human iPSC-derived astrocytes (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01). (<b>E</b>) Glutamate uptake after the KD of <span class="html-italic">ENSG00000272070</span> (unpaired <span class="html-italic">t</span>-test; *** <span class="html-italic">p</span> &lt; 0.001). (<b>F</b>) Increase in intracellular Ca<sup>2+</sup> levels in response to ATP stimulation after the KD of <span class="html-italic">ENSG00000272070</span> (unpaired <span class="html-italic">t</span>-test; ** <span class="html-italic">p</span> &lt; 0.01). Data are depicted as mean ± standard error. NC: negative control. KD: knockdown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00002/article_deploy/html/images/ncrna-11-00002-g006-550.jpg?1737908572" title=" <strong>Figure 6</strong><br/> <p>The overexpression of the interaction partner Npas3 can rescue molecular and functional changes induced by the loss of <span class="html-italic">3222401L13Rik</span>. (<b>A</b>) qPCR showing the expression levels of <span class="html-italic">Npas3/NPAS3</span> in mouse (left panel) and human iPSC-derived (right panel) astrocytes after the KD of <span class="html-italic">3222401L13Rik</span> (unpaired <span class="html-italic">t</span>-test; * <span class="html-italic">p</span> &lt; 0.05, **** <span class="html-italic">p</span> &lt; 0.0001). (<b>B</b>) Venn diagram showing the proportion of downregulated genes (352 out of 765) containing a promoter region that can bind <span class="html-italic">3222401L13Rik</span>. The Triplex Domain Finder tool [<a href="#B39-ncrna-11-00002" class="html-bibr">39</a>] was used to identify promoter regions of the downregulated genes that have a binding motif for <span class="html-italic">3222401L13Rik</span>. (<b>C</b>) Scheme depicting the significant DNA binding domains (DBD) in the sequence of <span class="html-italic">3222401L13Rik</span> determined using the Triplex Domain Finder tool and the sequence motifs where <span class="html-italic">3222401L13Rik</span> binds to the promoter of Npas3. (<b>D</b>) RNA immunoprecipitation for Npas3, followed by qPCR for <span class="html-italic">3222401L13Rik</span> in mouse primary astrocytes (unpaired <span class="html-italic">t</span>-test; ** <span class="html-italic">p</span> &lt; 0.01). (<b>E</b>) Representative immunofluorescence images showing the transfection of primary astrocytes with Gfp- or Gfp-Npas3-overexpression plasmids. Scale bar: 100 µm. (<b>F</b>) Expression levels of <span class="html-italic">3222401L13Rik</span> and Npas3 after the simultaneous KD of <span class="html-italic">3222401L13Rik</span> and overexpression of Npas3 in primary astrocytes (One-way ANOVA; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001; ns = not significant). (<b>G</b>) Expression levels of <span class="html-italic">Glt-1</span>, <span class="html-italic">Glast,</span> and <span class="html-italic">Nrxn1</span> after the simultaneous KD of <span class="html-italic">3222401L13Rik</span> and overexpression of Npas3 in primary astrocytes (One-way ANOVA; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; ns = not significant). (<b>H</b>) Glutamate uptake of primary astrocytes after the simultaneous KD of <span class="html-italic">3222401L13Rik</span> and overexpression of Npas3 (One-way ANOVA; ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001; ns = not significant). (<b>I</b>) Increase in intracellular Ca<sup>2+</sup> levels in response to ATP stimulation after the simultaneous KD of <span class="html-italic">3222401L13Rik</span> and overexpression of Npas3 (One-way ANOVA; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ns = not significant). Data are depicted as mean ± standard error. NC: negative control. KD: knockdown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/2'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 26 pages, 2100 KiB   </span> <a href="/2311-553X/11/1/1/pdf?version=1735053324" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="RNA Metabolism and the Role of Small RNAs in Regulating Multiple Aspects of RNA Metabolism" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/11/1/1">RNA Metabolism and the Role of Small RNAs in Regulating Multiple Aspects of RNA Metabolism</a> <div class="authors"> by <span class="inlineblock "><strong>Pranav Dawar</strong>, </span><span class="inlineblock "><strong>Indra Adhikari</strong>, </span><span class="inlineblock "><strong>Swarupa Nanda Mandal</strong> and </span><span class="inlineblock "><strong>Bhumika Jayee</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2025</b>, <em>11</em>(1), 1; <a href="https://doi.org/10.3390/ncrna11010001">https://doi.org/10.3390/ncrna11010001</a> - 24 Dec 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> RNA metabolism is focused on RNA molecules and encompasses all the crucial processes an RNA molecule may or will undergo throughout its life cycle. It is an essential cellular process that allows all cells to function effectively. The transcriptomic landscape of a cell <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/1/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> RNA metabolism is focused on RNA molecules and encompasses all the crucial processes an RNA molecule may or will undergo throughout its life cycle. It is an essential cellular process that allows all cells to function effectively. The transcriptomic landscape of a cell is shaped by the processes such as RNA biosynthesis, maturation (RNA processing, folding, and modification), intra- and inter-cellular transport, transcriptional and post-transcriptional regulation, modification, catabolic decay, and retrograde signaling, all of which are interconnected and are essential for cellular RNA homeostasis. In eukaryotes, sRNAs, typically 20–31 nucleotides in length, are a class of ncRNAs found to function as nodes in various gene regulatory networks. sRNAs are known to play significant roles in regulating RNA population at the transcriptional, post-transcriptional, and translational levels. Along with sRNAs, such as miRNAs, siRNAs, and piRNAs, new categories of ncRNAs, i.e., lncRNAs and circRNAs, also contribute to RNA metabolism regulation in eukaryotes. In plants, various genetic screens have demonstrated that sRNA biogenesis mutants, as well as RNA metabolism pathway mutants, exhibit similar growth and development defects, misregulated primary and secondary metabolism, as well as impaired stress response. In addition, sRNAs are both the “products” and the “regulators” in broad RNA metabolism networks; gene regulatory networks involving sRNAs form autoregulatory loops that affect the expression of both sRNA and the respective target. This review examines the interconnected aspects of RNA metabolism with sRNA regulatory pathways in plants. It also explores the potential conservation of these pathways across different kingdoms, particularly in plants and animals. Additionally, the review highlights how cellular RNA homeostasis directly impacts adaptive responses to environmental changes as well as different developmental aspects in plants. <a href="/2311-553X/11/1/1">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ncrna/special_issues/67RRTK6Z55 ">Non-Coding RNA and Their Regulatory Roles in Plant</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/11/1/1/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1551743"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1551743"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1551743" data-cycle-prev="#prev1551743" data-cycle-progressive="#images1551743" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1551743-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g001-550.jpg?1735053427" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1551743" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1551743-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g002-550.jpg?1735053429'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1551743-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g003-550.jpg?1735053430'><p>Figure 3</p></div></script></div></div><div id="article-1551743-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g001-550.jpg?1735053427" title=" <strong>Figure 1</strong><br/> <p>sRNA biogenesis models for plants and animals. (<b>A</b>) miRNA biogenesis pathway—RNAPII transcribes the <span class="html-italic">MIR</span> specific. Primary miRNA (pri-miRNA) is then spliced into a single hairpin structure by DICER-LIKE 1, which furthermore gets cleaved into a miRNA duplex of 21 nt with the help of nuclear dicing bodies (D-bodies) including DICER-LIKE 1/3/4 (DCL1/3/4), HYPONASTIC LEAVES 1 (HYL1), SERRATE (SE), and TOUGH (TGH). The duplex is then methylated at the 3′ ends catalyzed with HUA ENHANCER1. With the assistance of HEAT SHOCK PROTEIN70/90 (HSP70/90), the mature miRNA gets loaded into the ARGONAUTE1/10 (AGO1/10) (also known as RISC) based on the specific miRNAs. (<b>B</b>) Secondary siRNAs (phasiRNA, tasiRNA, and easiRNA) biogenesis model—After PHAS loci, TAS loci, and active transposons are transcribed via RNAP II, AGO1/7-loaded mature miRNA cleaves the transcribed mRNA. 5′ fragment of the cleaved mRNA degrades, while the 3′ strand is converted into a double strand with the help of RDR6. SGS3 and SDE5 help in recruiting RDR6 to the recognition site. DCL4/3 participates in ta-siRNA and phasiRNA production, whereas DCL2/4 participates in easiRNA production. The 21–24 nt mature siRNA strand then gets loaded into AGO1/7 for downstream gene regulation. (<b>C</b>) Plant endogenous siRNA biogenesis—The transposable elements, repetitive regions, or gene introns get transcribed with RNAP IV, which then gets converted into dsRNA with the help of RDR2/4. The dsRNA then gets cleaved into 20–24 nt fragments with the help of DCL2/3/4. HSP90 then helps to load the mature siRNA strand in the respective AGO4/6/9, based on their origin. (<b>D</b>) Canonical and miRNA Biogenesis in Animals—After the transcription of the <span class="html-italic">MIR</span>-specific locus with DNA-dependent RNA polymerase II, pri-miRNAs were converted to single hairpin-like structures (pre-miRNAs) with the help of Drosha. The pre-miRNA transported into the cytoplasm with Exportin1/5 proteins then gets further cleaved into miRNA duplexes by Dicer proteins. The pathways create this miRNA duplex without Dorsal/Dicer acting upon the primary miRNA. The mature miRNA strand then gets loaded in the AGO2. (<b>E</b>) Endo- and exogenous modes of siRNA production in <span class="html-italic">Caenorhabditis elegans</span>—siRNAs derived from ssRNA, and dsRNA are loaded into primary Argonaute proteins, ERGO-1 and RDE1, respectively. The loaded primary Argonaute protein, with the help of RRF1 and Mutator, mediates the conversion of 26 nt long 5′-guanosine siRNA into 22G siRNA. The produced siRNAs are then loaded into the secondary Argonaute proteins for downstream gene silencing. (<b>F</b>) Biogenesis of piRNA and the regulatory ping pong cycle of biogenesis in <span class="html-italic">Drosophila melanogaster</span>—<span class="html-italic">piRNA</span> gene sequences are marked by an upstream Ruby motif. The piRNA precursors are transcribed by RNAP II and then exported to the cytoplasm. These precursors are then processed by endonuclease Zucchini and an unknown 3′–5′ exonuclease. Via DmHen1/Pimet methyltransferase, the 3′ end of the mature piRNA gets 2′-O-methylated. The mature piRNA gets loaded into PIWI, forming piRISC to regulate methylation of TEs. Apart from PIWI protein alone, some gets loaded into Aub, which then initiates the ping pong cycle of biogenesis. Aub loaded with piRNA and AGO3 loaded with secondary piRNA repress TE activity through DNA cytosine methylation. PIWI-related Gene 1 (PRG-1) is required for primary piRNA activity, whereas HRDE-1 (Heritable RNA interference (RNAi) deficient protein-1) is the Argonaute protein that carries RdRP-amplified 22 nt, 5′-guanosine siRNA (22-GsiRNA). (Modified from [<a href="#B16-ncrna-11-00001" class="html-bibr">16</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/1'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g002-550.jpg?1735053429" title=" <strong>Figure 2</strong><br/> <p>PTGS and TGS Mode of Action for miRNA, siRNA, and piRNA in Plants and Animals. (<b>A</b>,<b>B</b>) Post-transcriptional gene silencing of plant and animal miRNAs through mRNA cleavage, RNA decay, and translational repression. (<b>C</b>) Exogenous siRNA is only able to participate in PTGS through mRNA cleavage. (<b>D</b>) Plant and animals endogenous siRNA and piRNAs, the loaded AGO protein, after being transported back to the nucleus, target nascent RNA Pol-V transcripts (line represented in red) through complementary siRNA and form the RdDM complex (RNA-dependent DNA methylation). GW/WG protein, associated with RNAP V, KTF1 acts as an organizer by coordinating with AGO and 5-meC (5-methylCytosine). Similarly, the AGO-associated protein RDM1 interacts with DRM2, a RdDM complex catalytically active de novo methyltransferase, and binds with single-stranded methylated DNA. DRM3, a catalytically inactive paralogue of DRM2, is also known to be involved in the RdDM complex, but its function is still unknown. After all these proteins are localized, DRM2 catalyzes methylation of cytosine in all sequence contexts. (Modified from [<a href="#B16-ncrna-11-00001" class="html-bibr">16</a>,<a href="#B18-ncrna-11-00001" class="html-bibr">18</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/1'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-11-00001/article_deploy/html/images/ncrna-11-00001-g003-550.jpg?1735053430" title=" <strong>Figure 3</strong><br/> <p>miRNA-mediated mRNA decay pathway in plants and animals. (<b>A</b>) miRNA binds to the complementary site in the Open Reading frame and induces endonucleolytic cleavage at the splice site (between the nucleotides 10 and 11). The 5′ fragment is uridylated by HUA Enhancer 1 Suppressor 1 (HESO 1) and is degraded by XRN4 in a 5′ to 3′ direction. Similarly, the 3′ cleaved fragments are degraded by XRN4 without uridylation. (<b>B</b>) miRNA, after attaching with the activated mRNA, recruits CCR4-NOT and PAN2-PAN3 deadenylase complexes to target mRNAs via the GW182 protein. These deadenylated mRNAs are then oligouridylated by TUT4/7, thus starting the general mRNA decay in mammals. Apart from deadenylation, GW182 can also promote dissociation of PAPB (poly(A) binding protein). DDX6 (the de-capping activators) are then recruited onto the CCR4-NOT complex. This helps the DCP2 enzyme in removing the 5′ 7-methylated guanine cap. Finally, XRN1 acts on the uncapped uridylated mRNA strand by performing 5′-3′ exonucleolytic decay. (Modified from [<a href="#B127-ncrna-11-00001" class="html-bibr">127</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/11/1/1'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 8 pages, 253 KiB   </span> <a href="/2311-553X/10/6/62/pdf?version=1733994861" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The 2024 Nobel Prize in Physiology or Medicine: microRNA Takes Center Stage" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Editorial</span></div> <a class="title-link" href="/2311-553X/10/6/62">The 2024 Nobel Prize in Physiology or Medicine: microRNA Takes Center Stage</a> <div class="authors"> by <span class="inlineblock "><strong>George A. Calin</strong>, </span><span class="inlineblock "><strong>Florent Hubé</strong>, </span><span class="inlineblock "><strong>Michael R. Ladomery</strong>, </span><span class="inlineblock "><strong>Nicholas Delihas</strong>, </span><span class="inlineblock "><strong>Manuela Ferracin</strong>, </span><span class="inlineblock "><strong>Laura Poliseno</strong>, </span><span class="inlineblock "><strong>Luca Agnelli</strong>, </span><span class="inlineblock "><strong>Suresh K. Alahari</strong>, </span><span class="inlineblock "><strong>Ai-Ming Yu</strong> and </span><span class="inlineblock "><strong>Xiao-Bo Zhong</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 62; <a href="https://doi.org/10.3390/ncrna10060062">https://doi.org/10.3390/ncrna10060062</a> - 12 Dec 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The <i>Non-coding</i> Journal Editorial Board Members would like to congratulate Victor Ambros and Gary Ruvkun, who were jointly awarded the 2024 Nobel Prize in Physiology or Medicine for their groundbreaking discovery of microRNAs and the role of microRNAs in post-transcriptional gene regulation, uncovering <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/62/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The <i>Non-coding</i> Journal Editorial Board Members would like to congratulate Victor Ambros and Gary Ruvkun, who were jointly awarded the 2024 Nobel Prize in Physiology or Medicine for their groundbreaking discovery of microRNAs and the role of microRNAs in post-transcriptional gene regulation, uncovering a previously unknown layer of gene control in eukaryotes [...] <a href="/2311-553X/10/6/62">Full article</a> </div> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 885 KiB   </span> <a href="/2311-553X/10/6/61/pdf?version=1733128888" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Urinary miRNA Expression in Pre-Eclampsia During Early and Mid-Pregnancy" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/10/6/61">Urinary miRNA Expression in Pre-Eclampsia During Early and Mid-Pregnancy</a> <div class="authors"> by <span class="inlineblock "><strong>Roman A. Illarionov</strong>, </span><span class="inlineblock "><strong>Anastasia R. Maltseva</strong>, </span><span class="inlineblock "><strong>Olga V. Pachuliia</strong>, </span><span class="inlineblock "><strong>Tatiana B. Postnikova</strong>, </span><span class="inlineblock "><strong>Elena S. Vashukova</strong>, </span><span class="inlineblock "><strong>Anastasiia K. Popova</strong>, </span><span class="inlineblock "><strong>Yulia A. Nasykhova</strong>, </span><span class="inlineblock "><strong>Olesya N. Bespalova</strong> and </span><span class="inlineblock "><strong>Andrey S. Glotov</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 61; <a href="https://doi.org/10.3390/ncrna10060061">https://doi.org/10.3390/ncrna10060061</a> - 2 Dec 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background:</b> Pre-eclampsia (PE) is a serious condition affecting 2–8% of pregnancies worldwide, leading to high maternal and fetal morbidity and mortality. MicroRNAs (miRNAs), small non-coding RNA molecules, have emerged as potential biomarkers for various pregnancy-related pathologies, including PE. MiRNAs in plasma and serum <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/61/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background:</b> Pre-eclampsia (PE) is a serious condition affecting 2–8% of pregnancies worldwide, leading to high maternal and fetal morbidity and mortality. MicroRNAs (miRNAs), small non-coding RNA molecules, have emerged as potential biomarkers for various pregnancy-related pathologies, including PE. MiRNAs in plasma and serum have been extensively studied, but urinary miRNAs remain underexplored, especially during early pregnancy. This study aimed to investigate the urinary miRNA expression profiles in women with pre-eclampsia during the first and second trimesters. <b>Materials and Methods:</b> A prospective study was conducted using 48 urine samples from 24 pregnant women (n = 12 pre-eclampsia and n = 12 controls). Urine samples were collected in the first (9–13 weeks) and second (22–24 weeks) trimesters. MiRNA isolation, library preparation, and high-throughput sequencing were performed, followed by differential expression and enrichment analyses. <b>Results:</b> In the first trimester, five miRNAs were dysregulated in PE in comparison with the control group (hsa-miR-184, hsa-miR-203a-3p, hsa-miR-205-5p, hsa-miR-223-3p—downregulated; hsa-miR-1-3p—upregulated). In the second trimester, hsa-miR-205-5p and hsa-miR-223-3p were downregulated, and hsa-miR-9-5p, hsa-miR-1-3p, and hsa-miR-206 were upregulated. <b>Conclusions:</b> Our study identified differentially expressed miRNAs in the urine of pre-eclamptic patients during early pregnancy. These findings suggest that specific urinary miRNAs could serve as non-invasive biomarkers for the early detection and risk assessment of pre-eclampsia. The changes in the level of differential expression of miRNAs during gestation highlight their role in the progression of PE. Further research and validation with a larger cohort are needed to explore their clinical potential for improving maternal and fetal outcomes through early intervention. <a href="/2311-553X/10/6/61">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/61/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1534806"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1534806"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1534806" data-cycle-prev="#prev1534806" data-cycle-progressive="#images1534806" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1534806-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00061/article_deploy/html/images/ncrna-10-00061-g001-550.jpg?1733128971" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1534806" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1534806-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00061/article_deploy/html/images/ncrna-10-00061-g002-550.jpg?1733128973'><p>Figure 2</p></div></script></div></div><div id="article-1534806-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00061/article_deploy/html/images/ncrna-10-00061-g001-550.jpg?1733128971" title=" <strong>Figure 1</strong><br/> <p>Volcano plot (first trimester).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/61'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00061/article_deploy/html/images/ncrna-10-00061-g002-550.jpg?1733128973" title=" <strong>Figure 2</strong><br/> <p>Volcano plot (second trimester).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/61'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1533812" aria-controls="drop-supplementary-1533812" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1533812" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2311-553X/10/6/60/s1?version=1732955078"> Supplementary File 1 (ZIP, 1153 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 4653 KiB   </span> <a href="/2311-553X/10/6/60/pdf?version=1732955078" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Identification of Tumor-Suppressive miR-30a-3p Controlled Genes: ANLN as a Therapeutic Target in Breast Cancer" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/10/6/60">Identification of Tumor-Suppressive <i>miR-30a-3p</i> Controlled Genes: <i>ANLN</i> as a Therapeutic Target in Breast Cancer</a> <div class="authors"> by <span class="inlineblock "><strong>Reiko Mitsueda</strong>, </span><span class="inlineblock "><strong>Ayako Nagata</strong>, </span><span class="inlineblock "><strong>Hiroko Toda</strong>, </span><span class="inlineblock "><strong>Yuya Tomioka</strong>, </span><span class="inlineblock "><strong>Ryutaro Yasudome</strong>, </span><span class="inlineblock "><strong>Mayuko Kato</strong>, </span><span class="inlineblock "><strong>Yoshiaki Shinden</strong>, </span><span class="inlineblock "><strong>Akihiro Nakajo</strong> and </span><span class="inlineblock "><strong>Naohiko Seki</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 60; <a href="https://doi.org/10.3390/ncrna10060060">https://doi.org/10.3390/ncrna10060060</a> - 30 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Our recently created RNA-sequence-based microRNA (miRNA) expression signature in breast cancer clinical specimens revealed that some <i>miR-30</i> family members were significantly downregulated in cancer tissues. Based on TCGA database analyses, we observed that among the <i>miR-30</i> family members, <i>miR-30a-3p</i> (the passenger strand derived <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/60/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Our recently created RNA-sequence-based microRNA (miRNA) expression signature in breast cancer clinical specimens revealed that some <i>miR-30</i> family members were significantly downregulated in cancer tissues. Based on TCGA database analyses, we observed that among the <i>miR-30</i> family members, <i>miR-30a-3p</i> (the passenger strand derived from pre-<i>miR-30a</i>) was significantly downregulated in breast cancer (BC) clinical specimens, and its low expression predicted worse prognoses. Ectopic expression assays showed that <i>miR-30a-3p</i> transfected cancer cells (MDA-MB-157 and MDA-MB-231) had their aggressive phenotypes significantly suppressed, e.g., their proliferation, migration, and invasion abilities. These data indicated that <i>miR-30a-3p</i> acted as a tumor-suppressive miRNA in BC cells. Our subsequent search for <i>miR-30a-3p</i> controlled molecular networks in BC cells yielded a total of 189 genes. Notably, among those 189 genes, cell-cycle-related genes (<i>ANLN</i>, <i>MKI67</i>, <i>CCNB1</i>, <i>NCAPG</i>, <i>ZWINT</i>, <i>E2F7</i>, <i>PDS5A</i>, <i>RIF1</i>, <i>BIRC5</i>, <i>MAD2L1</i>, <i>CACUL1</i>, <i>KIF23</i>, <i>UBE2S</i>, <i>EML4</i>, <i>SEPT10</i>, <i>CLTC</i>, and <i>PCNP</i>) were enriched according to a GeneCodis 4 database analysis. Moreover, the overexpression of four genes (<i>ANLN</i>, <i>CCNB1</i>, <i>BIRC5</i>, and <i>KIF23</i>) significantly predicted worse prognoses for patients with BC according to TCGA analyses. Finally, our assays demonstrated that the overexpression of <i>ANLN</i> had cancer-promoting functions in BC cells. The involvement of <i>miR-30a-3p</i> (the passenger strand) in BC molecular pathogenesis is a new concept in cancer research, and the outcomes of our study strongly indicate the importance of analyzing passenger strands of miRNAs in BC cells. <a href="/2311-553X/10/6/60">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ncrna/special_issues/Q5376262D2 ">Non-coding RNA as Biomarker in Cancer</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/60/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1533812"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1533812"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1533812" data-cycle-prev="#prev1533812" data-cycle-progressive="#images1533812" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1533812-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g001-550.jpg?1732955218" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1533812" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g002-550.jpg?1732955220'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g003-550.jpg?1732955222'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g004-550.jpg?1732955224'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g005-550.jpg?1732955224'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g006-550.jpg?1732955231'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g007-550.jpg?1732955233'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g008-550.jpg?1732955236'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1533812-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g009-550.jpg?1732955239'><p>Figure 9</p></div></script></div></div><div id="article-1533812-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g001-550.jpg?1732955218" title=" <strong>Figure 1</strong><br/> <p>Expression levels of <span class="html-italic">miR-30a-5p</span> and <span class="html-italic">miR-30a-3p</span> in BC clinical specimens. (<b>A</b>) Volcano plot of the miRNA expression signature based on RNA sequencing (GEO accession number: GSE118539). The log<sub>2</sub> fold change (FC) in the expression is plotted on the <span class="html-italic">x</span>-axis and the log<sub>10</sub> <span class="html-italic">p</span>-value is on the <span class="html-italic">y</span>-axis. Blue and red dots represent the downregulated (log<sub>2</sub>FC &lt; −2.0 and <span class="html-italic">p</span> &lt; 0.05) and upregulated (log<sub>2</sub>FC &gt; 2.0 and <span class="html-italic">p</span> &lt; 0.05) miRNAs, respectively. (<b>B</b>) Chromosomal location of pre-<span class="html-italic">miR-30</span> within the human genome, showing mature sequences of <span class="html-italic">miR-30a-5p</span> (guide strand) and <span class="html-italic">miR-30a-3p</span> (passenger strand). (<b>C</b>) Expression levels of <span class="html-italic">miR-30a-5p</span> and <span class="html-italic">miR-30a-3p</span> were validated in BC clinical specimens. <span class="html-italic">miR-30a-3p</span> expression was significantly downregulated in cancer tissues (<span class="html-italic">p</span> &lt; 0.001). (<b>D</b>) The 10-year overall survival rate of breast cancer patients according to miRNA expression. Patients with a high expression of <span class="html-italic">miR-30a-5p</span> and <span class="html-italic">miR-30a-3p</span> show a preferable prognosis. (<b>E</b>) A positive correlation (Spearman’s rank test) between <span class="html-italic">miR-30a-5p</span> and <span class="html-italic">miR-30a-3p</span> expression levels in clinical specimens is shown (<span class="html-italic">r</span> = 0.833, <span class="html-italic">p</span> &lt; 0.001).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g002-550.jpg?1732955220" title=" <strong>Figure 2</strong><br/> <p>Effects of ectopic expression of <span class="html-italic">miR-30a-3p</span> in BC cells (MDA-MB-157 and MDA-MB-231). (<b>A</b>) Cell proliferation was assessed via the XTT assay 72 h after transient transfection of miRNAs. (<b>B</b>) Cell invasion was evaluated using Matrigel invasion assays 48 h after <span class="html-italic">miR-30a-3p</span>-transfected cells were seeded into the chambers. (<b>C</b>) Cell migration was evaluated using a membrane culture system 48 h after <span class="html-italic">miR-30a-3p</span>-transfected cells were seeded into chambers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g003-550.jpg?1732955222" title=" <strong>Figure 3</strong><br/> <p>Flowchart of <span class="html-italic">miR-30a-3p</span> target identification in BC cells. To identify putative targets of <span class="html-italic">miR-30a-3p</span> in BC cells, we integrated two datasets: the TargetScan Human database (release 8.0) and our original mRNA expression profile (<span class="html-italic">miR-30a-3p</span>-transfected MDA-MB-231 cells; GEO accession number: GSE118539). A total of 189 genes were identified as putative <span class="html-italic">miR-30a-3p</span> targets. According to a GeneCodis 4 database analysis, 17 genes were most frequently associated with the cell cycle. Of these 17 genes, 10 genes showed significant overexpression in BC specimens according to GEPIA2 (<a href="http://gepia2.cancer-pku.cn/#index" target="_blank">http://gepia2.cancer-pku.cn/#index</a>, accessed on 13 March 2024), and 4 genes showed a significantly low overall survival rate according to OncoLnc (<a href="http://www.oncolnc.org/" target="_blank">http://www.oncolnc.org/</a>, accessed on 13 March 2024). Finally, four oncogenic genes were selected as <span class="html-italic">miR-30a-3p</span> targets in BC.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g004-550.jpg?1732955224" title=" <strong>Figure 4</strong><br/> <p>The expression levels of 10 genes (<span class="html-italic">ANLN</span>, <span class="html-italic">MKI67</span>, <span class="html-italic">CCNB1</span>, <span class="html-italic">NCAPG</span>, <span class="html-italic">ZWINT</span>, <span class="html-italic">BIRC5</span>, <span class="html-italic">MAD2L1</span>, <span class="html-italic">KIF23</span>, <span class="html-italic">UBE2S</span>, and <span class="html-italic">CLTC</span>) in BC clinical specimens were analyzed using TCGA-BRCA datasets. These genes were upregulated in BC tissues (n = 1085) compared with normal tissues (n = 291) (<span class="html-italic">p</span> &lt; 0.01).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g005-550.jpg?1732955224" title=" <strong>Figure 5</strong><br/> <p>Clinical significance of 4 target genes in BC specimens. Kaplan–Meier curves of 10-year overall survival rates according to the levels of gene expression (<span class="html-italic">ANLN</span>, <span class="html-italic">CCNB1</span>, <span class="html-italic">BIRC5</span>, and <span class="html-italic">KIF23</span>). A total of 1006 patients were divided into high- and low-expression groups according to the median gene expression level. The red lines represent the high-expression group, and the blue lines represent the low-expression group. Expressing high levels of these genes was significantly correlated with a poorer prognosis in BC patients.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g006-550.jpg?1732955231" title=" <strong>Figure 6</strong><br/> <p>Expression control of four genes (<span class="html-italic">ANLN</span>, <span class="html-italic">CCNB1</span>, <span class="html-italic">BIRC5</span>, and <span class="html-italic">KIF23</span>) by <span class="html-italic">miR-30a-3p</span> in BC cells. (<b>A</b>) qRT-PCR showing significantly reduced expression of all four mRNAs 72 h after <span class="html-italic">miR-30a-3p</span> transfection in MDA-MB-157 and MDA-MB-231 cells compared to the control group. (<b>B</b>) Correlation analysis of four genes using TCGA-BRCA database. Expression levels of <span class="html-italic">miR-30a-3p</span> and four genes (<span class="html-italic">ANLN</span>, <span class="html-italic">CCNB1</span>, <span class="html-italic">BIRC5</span>, and <span class="html-italic">KIF23</span>) in BC clinical samples are negatively correlated.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g007-550.jpg?1732955233" title=" <strong>Figure 7</strong><br/> <p>TargetScan Human database (release 8.0) shows that the putative <span class="html-italic">miR-30a-3p</span> binding site is mapped in the 3′UTR of the <span class="html-italic">ANLN</span> gene. Dual-luciferase reporter assays revealed reduced luminescence activity after co-transfection of <span class="html-italic">miR-30a-3p</span> with a vector containing the <span class="html-italic">miR-30a-3p</span> binding site (wild-type) in MDA-MB-231 cells. In contrast, no luminescence activity was observed after co-transfection of <span class="html-italic">miR-30a-3p</span> with a vector lacking the <span class="html-italic">miR-30a-3p</span> binding site (deletion-type) in MDA-MB-231 cells.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g008-550.jpg?1732955236" title=" <strong>Figure 8</strong><br/> <p>Effects of knockdown of <span class="html-italic">ANLN</span> by siRNAs in BC cells. (<b>A</b>) Cell proliferation was assessed using XTT assays 72 h after siRNA transfection into BC cells. (<b>B</b>) Cell invasion was evaluated using Matrigel invasion assays 48 h after si<span class="html-italic">ANLN</span>-transfected cells were seeded into chambers. (<b>C</b>) Cell migration was evaluated using a membrane culture system 48 h after si<span class="html-italic">ANLN</span>-transfected cells were seeded into chambers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00060/article_deploy/html/images/ncrna-10-00060-g009-550.jpg?1732955239" title=" <strong>Figure 9</strong><br/> <p>Clinical significance of <span class="html-italic">ANLN</span> expression in BC. (<b>A</b>) Expression of ANLN in BC tissues. Immunohistochemical staining of ANLN was confined to cancer tissues, whereas weak staining was observed in the noncancerous area. Upper: 50-year-old woman, T1N0M0 invasive papillary carcinoma. Lower: 78-year-old woman, T4N0M0 invasive breast ductal carcinoma. (<b>B</b>) Forest plot showing the result of multivariate Cox proportional hazards regression analysis of the 10-year overall survival rate. Patients with high <span class="html-italic">ANLN</span> expression had a significantly lower overall survival rate. These data were obtained from TCGA-BRCA datasets. (<b>C</b>) Gene set enrichment analysis (GSEA) was applied to explore molecular pathways mediated by <span class="html-italic">ANLN</span> in BC cells. The top three pathways enriched in BC patients with high <span class="html-italic">ANLN</span> expression were E2F targets, G<sub>2</sub>M checkpoint, and Myc targets.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/60'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 1577 KiB   </span> <a href="/2311-553X/10/6/59/pdf?version=1732774956" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="SVALKA: A Long Noncoding Cis-Natural Antisense RNA That Plays a Role in the Regulation of the Cold Response of Arabidopsis thaliana" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/10/6/59"><i>SVALKA</i>: A Long Noncoding Cis-Natural Antisense RNA That Plays a Role in the Regulation of the Cold Response of <i>Arabidopsis thaliana</i></a> <div class="authors"> by <span class="inlineblock "><strong>Nicholas M. Kiger</strong> and </span><span class="inlineblock "><strong>Susan J. Schroeder</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 59; <a href="https://doi.org/10.3390/ncrna10060059">https://doi.org/10.3390/ncrna10060059</a> - 28 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> RNA plays important roles in the regulation of gene expression in response to environmental stimuli. <i>SVALKA</i>, a long noncoding cis-natural antisense RNA, is a key component of regulating the response to cold temperature in <i>Arabidopsis thaliana</i>. There are three mechanisms through <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/59/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> RNA plays important roles in the regulation of gene expression in response to environmental stimuli. <i>SVALKA</i>, a long noncoding cis-natural antisense RNA, is a key component of regulating the response to cold temperature in <i>Arabidopsis thaliana</i>. There are three mechanisms through which <i>SVALKA</i> fine tunes the transcriptional response to cold temperatures. <i>SVALKA</i> regulates the expression of the <i>CBF1</i> (C-Repeat Dehydration Binding Factor 1) transcription factor through a collisional transcription mechanism and a dsRNA and DICER mediated mechanism. <i>SVALKA</i> also interacts with Polycomb Repressor Complex 2 to regulate the histone methylation of <i>CBF3</i>. Both <i>CBF1</i> and <i>CBF3</i> are key components of the <i>COLD REGULATED</i> (<i>COR)</i> regulon that direct the plant’s response to cold temperature over time, as well as plant drought adaptation, pathogen responses, and growth regulation. The different isoforms of <i>SVALKA</i> and its potential to form dynamic RNA conformations are important features in regulating a complex gene network in concert with several other noncoding RNA. This review will summarize the three mechanisms through which <i>SVALKA</i> participates in gene regulation, describe the ways that dynamic RNA structures support the function of regulatory noncoding RNA, and explore the potential for improving agricultural genetic engineering with a better understanding of the roles of noncoding RNA. <a href="/2311-553X/10/6/59">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ncrna/special_issues/67RRTK6Z55 ">Non-Coding RNA and Their Regulatory Roles in Plant</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/59/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1531490"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1531490"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1531490" data-cycle-prev="#prev1531490" data-cycle-progressive="#images1531490" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1531490-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g001-550.jpg?1732775072" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1531490" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1531490-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g002-550.jpg?1732775074'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1531490-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g003-550.jpg?1732775076'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1531490-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g004-550.jpg?1732775076'><p>Figure 4</p></div></script></div></div><div id="article-1531490-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g001-550.jpg?1732775072" title=" <strong>Figure 1</strong><br/> <p>Illustration of the relative locations of the <span class="html-italic">CBF</span> cluster and <span class="html-italic">SVALKA</span> genes to each other. The two <span class="html-italic">SVALKA</span> isoforms, <span class="html-italic">SVK</span>-L and <span class="html-italic">SVK</span>-S, are shown. The transcription start sites (TSSs) for <span class="html-italic">CBF1</span> and <span class="html-italic">SVALKA</span> are given, and the numbers given are the nucleotides up/downstream of the TSS for <span class="html-italic">CBF1</span>, showing the location of the distal polyadenylation site (DPAS) and proximal polyadenylation site (PPAS) corresponding to <span class="html-italic">SVK</span>-L and <span class="html-italic">SVK</span>-S, respectively. The relative locations of the <span class="html-italic">svk</span>-1 and <span class="html-italic">uns-1</span> (uncoupling <span class="html-italic">SVALKA</span> 1) T-DNA inserts are indicated. Figure drawn approximately to scale. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/59'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g002-550.jpg?1732775074" title=" <strong>Figure 2</strong><br/> <p>The three different known mechanisms of <span class="html-italic">SVALKA</span> regulation. (<b>A</b>) Mechanism by which <span class="html-italic">SVK</span>-L adopts a dsRNA (double-stranded RNA) conformation with <span class="html-italic">CBF1</span> mRNA and regulates <span class="html-italic">CBF1</span> expression at 22 degrees Celsius. (<b>B</b>) <span class="html-italic">SVK</span>-S RNAPII collision-based mechanism of regulating <span class="html-italic">CBF1</span> in response to cold stress (4–8 h after freezing exposure). Sense/antisense collision of <span class="html-italic">CBF1/SVALKA</span> RNAPII occurs, resulting in premature transcript termination. Note that although they are shown on the same strand here, <span class="html-italic">SVALKA</span> is antisense to <span class="html-italic">CBF1</span>. Prior to Polycomb Repressive Complex 2 (PRC2) recruiting, <span class="html-italic">CBF3</span> is transcribed regularly. <span class="html-italic">SVALKA</span> lies between <span class="html-italic">CBF1</span> and <span class="html-italic">CBF3</span>, but antisense to them. (<b>C</b>) <span class="html-italic">SVALKA</span>-PRC2 mechanism for methylation of CBF3 (24 h after freezing exposure). <span class="html-italic">SVALKA</span> RNA recruits PRC2 to <span class="html-italic">CBF3</span>, where it methylates the gene, thereby making the chromatin inaccessible for transcription. (<b>D</b>) Timeline of the regulators of the cold response in Arabidopsis at 4 °C. <b>i</b>: <span class="html-italic">SVK</span>-S reaches a stable peak 8–12 h after initial cold exposure. <b>ii</b>: <span class="html-italic">CBF1</span> expression peaks 4 h after initial cold exposure (according to some studies). <b>iii</b>: <span class="html-italic">CBF3</span> expression peaks 3 h after initial cold exposure, then decreases. <b>iv</b>: Expression of <span class="html-italic">ICE</span>, a <span class="html-italic">CBF1</span> activator, reaches a steady peak 1–3 h after initial cold exposure. <b>v</b>: Expression of <span class="html-italic">CBF2</span>, a <span class="html-italic">CBF1</span> repressor, peaks three hours after initial cold exposure, then decreases to almost undetectable levels after 6 h. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/59'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g003-550.jpg?1732775076" title=" <strong>Figure 3</strong><br/> <p>Overview of the <span class="html-italic">ICE/CBF-SVALKA COR</span> signaling pathway. Acronyms are as follows: MAPK, mitogen-activated protein kinase; OST1, Open stomata 1; <span class="html-italic">ICE1/2</span> Inducer of <span class="html-italic">CBF</span> Expression; <span class="html-italic">CBF</span>, C-repeat Binding Factor; <span class="html-italic">COR</span>, Col regulated genes; CRT/DRE, C-repeat/Dehydration Responsive Element; GA, gibberellin; SA, salicylic acid; BR, brassinosteroids; DICER/AGO, Dicer enzyme ARGONAUTE enzyme; PRC2 Polycomb Repressor Complex 2. Figure is updated and adapted from reference [<a href="#B47-ncrna-10-00059" class="html-bibr">47</a>]. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/59'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00059/article_deploy/html/images/ncrna-10-00059-g004-550.jpg?1732775076" title=" <strong>Figure 4</strong><br/> <p>CBF is a master regulator of stress response. As shown by the blunt red arrows, <span class="html-italic">SVALKA</span> negatively regulates <span class="html-italic">CBF1</span> and <span class="html-italic">CBF3</span>, and CBF1 in turn negatively regulates biomass production. As shown by green arrows, CBF1 expression positively regulates genes in the cold response, drought response, biotic stress response, and circadian clock pathways. Created with BioRender.com.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/59'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 10 pages, 5690 KiB   </span> <a href="/2311-553X/10/6/58/pdf?version=1732603332" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Detection of miR-133a-5p Using a Molecular Beacon Probe for Investigating Postmortem Intervals" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/10/6/58">Detection of miR-133a-5p Using a Molecular Beacon Probe for Investigating Postmortem Intervals</a> <div class="authors"> by <span class="inlineblock "><strong>Eun Hye Lee</strong>, </span><span class="inlineblock "><strong>Mingyoung Jeong</strong>, </span><span class="inlineblock "><strong>Kwangmin Park</strong>, </span><span class="inlineblock "><strong>Dong Geon Lee</strong>, </span><span class="inlineblock "><strong>Eun Ju Lee</strong>, </span><span class="inlineblock "><strong>Haneul Lee</strong>, </span><span class="inlineblock "><strong>Ah Yeoung Kim</strong>, </span><span class="inlineblock "><strong>Jae Won Ahn</strong>, </span><span class="inlineblock "><strong>Hyun Jun Woo</strong>, </span><span class="inlineblock "><strong>Sunghyun Kim</strong>, </span><span class="inlineblock "><strong>Jaewon Lim</strong> and </span><span class="inlineblock "><strong>Jungho Kim</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 58; <a href="https://doi.org/10.3390/ncrna10060058">https://doi.org/10.3390/ncrna10060058</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background:</b> When a body is discovered at a crime or murder scene, it is crucial to examine the body and estimate its postmortem interval (PMI). Accurate estimation of PMI is vital for identifying suspects and providing clues to resolve the case. MicroRNAs (miRNAs <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/58/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background:</b> When a body is discovered at a crime or murder scene, it is crucial to examine the body and estimate its postmortem interval (PMI). Accurate estimation of PMI is vital for identifying suspects and providing clues to resolve the case. MicroRNAs (miRNAs or miRs) are small non-coding RNAs that remain relatively stable in the cell nucleus even after death-related changes occur. <b>Objective</b>: This study developed a molecular beacon probe for mmu-miR-133a-5p and assessed its use in mouse muscle tissue at temperatures of 4 °C and 21 °C to estimate the PMI. <b>Methods:</b> A total of 36 healthy adult male BALB/c mice were divided into 9 PMI time points (0, 2, 6, 8, and 10 days) with 3 mice per time point, and they were exposed to 4 °C and 21 °C. Next, the expression pattern of mmu-miR-133a in the skeletal muscle tissue over a 10-day PMI period was analyzed using the developed molecular beacon probe. <b>Results:</b> The molecular beacon (MB) probe was designed for optimal thermodynamic stability with a hairpin structure that opened in the presence of mmu-miR-133a-5p, thus separating the fluorophore from the quencher and resulting in a strong fluorescence signal at 495 nm. Fluorescence intensity increased with mmu-miR-133a-5p concentration from 1 ng/μL to 1000 ng/μL and exhibited a strong correlation (R<sup>2</sup> = 0.9966) and a detection limit of 1 ng/μL. Subsequently, the expression level of mmu-miR-133a-5p was observed to be stable in mouse skeletal muscle tissue at both 4 °C and 21 °C. <b>Conclusions:</b> This user-friendly assay can complete measurements in just 30 min after RNA extraction and is suitable for point-of-care testing, and it possesses the potential to improve existing complex and time-consuming methods for PMI estimation. <a href="/2311-553X/10/6/58">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/ncrna/sections/detection_and_biomarkers">Detection and Biomarkers of Non-Coding RNA</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/58/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529388"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529388"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529388" data-cycle-prev="#prev1529388" data-cycle-progressive="#images1529388" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529388-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g001-550.jpg?1732603574" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529388" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529388-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g002-550.jpg?1732603575'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529388-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g003-550.jpg?1732603576'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529388-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g004-550.jpg?1732603577'><p>Figure 4</p></div></script></div></div><div id="article-1529388-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g001-550.jpg?1732603574" title=" <strong>Figure 1</strong><br/> <p>Schematic illustration for detection of mmu-miR-133a-5p using MB to assess PMI. (<b>A</b>) Thirty-six healthy adult male BALB/c mice were randomly divided into six groups based on different PMI intervals (0, 1, 2, 6, 8, and 10 days), with each group containing three mice. The mice were exposed to two temperature conditions (4 °C and 21 °C). Skeletal muscle tissues were collected from each mouse, homogenized with TRIzol reagent, and total RNA was extracted. (<b>B</b>) The MB probe was engineered for optimal thermodynamic stability in its hairpin structure, but it unfolds in the presence of mmu-miR-133a. (<b>C</b>) Steps of the MB probe assay for quantifying mmu-miR-133a. Created in Biorender.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/58'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g002-550.jpg?1732603575" title=" <strong>Figure 2</strong><br/> <p>Analytical performance of molecular beacon probe assay for mmu-miR-133a-5p. (<b>A</b>) Melt curve of the molecular beacon probe for mmu-miR-133a-5p. (<b>B</b>) The fluorescence spectra of the molecular beacon probe in response to varying concentrations of synthetic mmu-miR-133a. (<b>C</b>) The standard curve between fluorescence intensity versus the target miRNA concentration. (<b>D</b>) Detection limits of the molecular beacon probe assay for mmu-miR-133a-5p using 10-fold serial dilutions of synthetic miR-133a-5p (from 1 ng/μL to 1000 ng/μL). The dotted line represents the limit of detection.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/58'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g003-550.jpg?1732603576" title=" <strong>Figure 3</strong><br/> <p>Specificity of the molecular beacon probe assay for mmu-miR-133a-5p. (<b>A</b>) A graphical comparison of wild-type and mutant miR-133a-5p used to assess the specificity of the molecular beacon probe assay for mmu-miR-133a-5p. (<b>B</b>) The fluorescence spectra of the molecular beacon probe in reactions with wild-type and mutant miR-133a-5p.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/58'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00058/article_deploy/html/images/ncrna-10-00058-g004-550.jpg?1732603577" title=" <strong>Figure 4</strong><br/> <p>Detection of mmu-miR-133a-5p using the MB probe at different time intervals at (<b>A</b>) 4 °C or (<b>B</b>) 21 °C in mouse skeletal muscle. Data are presented as mean ± standard error of the mean.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/58'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 9 pages, 591 KiB   </span> <a href="/2311-553X/10/6/57/pdf?version=1732102860" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="LNC-ing Genetics in Mitochondrial Disease" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Commentary</span></div> <a class="title-link" href="/2311-553X/10/6/57">LNC-ing Genetics in Mitochondrial Disease</a> <div class="authors"> by <span class="inlineblock "><strong>Rick Kamps</strong> and </span><span class="inlineblock "><strong>Emma Louise Robinson</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 57; <a href="https://doi.org/10.3390/ncrna10060057">https://doi.org/10.3390/ncrna10060057</a> - 15 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Primary mitochondrial disease (MD) is a group of rare genetic diseases reported to have a prevalence of 1:5000 and is currently without a cure. This group of diseases includes mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), maternally inherited diabetes and deafness (MIDD), <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/57/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Primary mitochondrial disease (MD) is a group of rare genetic diseases reported to have a prevalence of 1:5000 and is currently without a cure. This group of diseases includes mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), maternally inherited diabetes and deafness (MIDD), Leber’s hereditary optic neuropathy (LHON), Leigh syndrome (LS), Kearns–Sayre syndrome (KSS), and myoclonic epilepsy and ragged-red fiber disease (MERRF). Additionally, secondary mitochondrial dysfunction has been implicated in the most common current causes of mortality and morbidity, including cardiovascular disease (CVD) and cancer. Identifying key genetic contributors to both MD and secondary mitochondrial dysfunction may guide clinicians to assess the most effective treatment course and prognosis, as well as informing family members of any hereditary risk of disease transmission. Identifying underlying genetic causes of primary and secondary MD involves either genome sequencing (GS) or small targeted panel analysis of known disease-causing nuclear- or mitochondrial genes coding for mitochondria-related proteins. Due to advances in GS, the importance of long non-coding RNA (lncRNA) as functional contributors to the pathophysiology of MD is being unveiled. A limited number of studies have thus far reported the importance of lncRNAs in relation to MD causation and progression, and we are entering a new area of attention for clinical geneticists in specific rare malignancies. This commentary provides an overview of what is known about the role of lncRNAs as genetic and molecular contributors to disease pathophysiology and highlights an unmet need for a deeper understanding of mitochondrial dysfunction in serious human disease burdens. <a href="/2311-553X/10/6/57">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/57/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1521982-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00057/article_deploy/html/images/ncrna-10-00057-g001-550.jpg?1732102934" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1521982-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00057/article_deploy/html/images/ncrna-10-00057-g001-550.jpg?1732102934" title=" <strong>Figure 1</strong><br/> <p>The mitochondrial DNA (mtDNA) and location of ncRNAs. The mtDNA consists of 16,569 base pairs, which encode 22 tRNAs, 2 rRNAs, and the 13 core subunits of the OXPHOS complexes. Here, the complex I genes of interest are in yellow, the complex III genes are in blue, the complex IV genes are shown in orange, and the complex V genes are in green. The positions of the two rRNAs are in purple, and the 22 single tRNAs are colored in black. Known validated mt-lncRNAs are listed as dark orange regions. Here, as an example, the LIPCAR sequence maps to the two red segments as small arrows indicating the selected designed standard primers. Heavy indicates the H-chain, and the Light one is the L-chain. The image is reprinted/adapted with permission from Gerald W. Dorn. Circulation Research. LIPCAR, Volume: 114, Issue: 10, Pages: 1548–1550, DOI: (10.1161/CIRCRESAHA.114.304028), © 2014 American Heart Association, Inc. [<a href="#B11-ncrna-10-00057" class="html-bibr">11</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/57'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 547 KiB   </span> <a href="/2311-553X/10/6/56/pdf?version=1731422391" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Androgen Receptor and Non-Coding RNAs’ Interaction in Renal Cell Carcinoma" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/10/6/56">Androgen Receptor and Non-Coding RNAs’ Interaction in Renal Cell Carcinoma</a> <div class="authors"> by <span class="inlineblock "><strong>Manal A. Hussain</strong>, </span><span class="inlineblock "><strong>Noha M. Elemam</strong> and </span><span class="inlineblock "><strong>Iman M. Talaat</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 56; <a href="https://doi.org/10.3390/ncrna10060056">https://doi.org/10.3390/ncrna10060056</a> - 12 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Renal cell carcinoma (RCC), the most prevalent among the urogenital cancers, accounts for around 3% of new cancer cases worldwide. Significantly, the incidence of RCC has doubled in developed world countries, ranking it as the sixth most common cancer in males, who represent <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/56/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Renal cell carcinoma (RCC), the most prevalent among the urogenital cancers, accounts for around 3% of new cancer cases worldwide. Significantly, the incidence of RCC has doubled in developed world countries, ranking it as the sixth most common cancer in males, who represent two-thirds of RCC cases. Males with RCC exhibit a higher mortality rate and tend to develop a more aggressive form of the disease than females. Sex-related risk factors, including lifestyle and biological variations, explain this difference. The androgen receptor (AR) oncogenic signaling pathway has been extensively studied among the biological factors that affect RCC. Recent advancements in high-throughput RNA sequencing techniques have underscored the significant roles played by noncoding-RNAs (ncRNAs), previously dismissed as “junk”. The oncogenic potential of AR is manifested through its dysregulation of the ncRNAs’ availability and function, promoting RCC tumorigenesis. This review offers a summary of the most recent findings on the role and molecular mechanisms of the AR in dysregulating the ncRNAs that play a role in the progression of RCC and the possibility of utilizing ncRNAs to target AR as a potential therapeutic strategy. <a href="/2311-553X/10/6/56">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/56/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1519366-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00056/article_deploy/html/images/ncrna-10-00056-g001-550.jpg?1731422496" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1519366-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00056/article_deploy/html/images/ncrna-10-00056-g001-550.jpg?1731422496" title=" <strong>Figure 1</strong><br/> <p>Oncogenic effect of increased AR expression in RCC through the modulation of ncRNAs. AR: androgen receptor, ARE: androgen response element, ASS1: arginosuccinate synthase-1, HIF-1α: hypoxia-inducible factor-1α, VEGF: vascular endothelial growth factor, CSF1: colony-stimulating factor-1, CircHIAT1: hipocampus abundant transcript-1 circular RNA, TANAR: Twist1 associated long non-coding RNA, UPF1: regulated by AR, up-frameshift protein1, EMT: epithelial–mesenchymal transition.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/56'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-1517028" aria-controls="drop-supplementary-1517028" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-1517028" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2311-553X/10/6/55/s1?version=1731069345"> Supplementary File 1 (ZIP, 2285 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 3683 KiB   </span> <a href="/2311-553X/10/6/55/pdf?version=1731069344" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Comparison of Three Computational Tools for the Prediction of RNA Tertiary Structures" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <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> <a class="title-link" href="/2311-553X/10/6/55">Comparison of Three Computational Tools for the Prediction of RNA Tertiary Structures</a> <div class="authors"> by <span class="inlineblock "><strong>Frank Yiyang Mao</strong>, </span><span class="inlineblock "><strong>Mei-Juan Tu</strong>, </span><span class="inlineblock "><strong>Gavin McAllister Traber</strong> and </span><span class="inlineblock "><strong>Ai-Ming Yu</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 55; <a href="https://doi.org/10.3390/ncrna10060055">https://doi.org/10.3390/ncrna10060055</a> - 8 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Understanding the structures of noncoding RNAs (ncRNAs) is important for the development of RNA-based therapeutics. There are inherent challenges in employing current experimental techniques to determine the tertiary (3D) structures of RNAs with high complexity and flexibility in folding, which makes computational methods <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/55/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Understanding the structures of noncoding RNAs (ncRNAs) is important for the development of RNA-based therapeutics. There are inherent challenges in employing current experimental techniques to determine the tertiary (3D) structures of RNAs with high complexity and flexibility in folding, which makes computational methods indispensable. In this study, we compared the utilities of three advanced computational tools, namely RNAComposer, Rosetta FARFAR2, and the latest AlphaFold 3, to predict the 3D structures of various forms of RNAs, including the small interfering RNA drug, nedosiran, and the novel bioengineered RNA (BioRNA) molecule showing therapeutic potential. Our results showed that, while RNAComposer offered a malachite green aptamer 3D structure closer to its crystal structure, the performances of RNAComposer and Rosetta FARFAR2 largely depend upon the secondary structures inputted, and Rosetta FARFAR2 predictions might not even recapitulate the typical, inverted “L” shape tRNA 3D structure. Overall, AlphaFold 3, integrating molecular dynamics principles into its deep learning framework, directly predicted RNA 3D structures from RNA primary sequence inputs, even accepting several common post-transcriptional modifications, which closely aligned with the experimentally determined structures. However, there were significant discrepancies among three computational tools in predicting the distal loop of human pre-microRNA and larger BioRNA (tRNA fused pre-miRNA) molecules whose 3D structures have not been characterized experimentally. While computational predictions show considerable promise, their notable strengths and limitations emphasize the needs for experimental validation of predictions besides characterization of more RNA 3D structures. <a href="/2311-553X/10/6/55">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/ncrna/sections/Computational_Biology">Computational Biology</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/55/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1517028"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1517028"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1517028" data-cycle-prev="#prev1517028" data-cycle-progressive="#images1517028" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1517028-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g001-550.jpg?1731069493" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1517028" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g002-550.jpg?1731069494'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g003-550.jpg?1731069495'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g004-550.jpg?1731069496'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g005-550.jpg?1731069497'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g006-550.jpg?1731069498'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1517028-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g007-550.jpg?1731069498'><p>Figure 7</p></div></script></div></div><div id="article-1517028-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g001-550.jpg?1731069493" title=" <strong>Figure 1</strong><br/> <p>Malachite green aptamer (MGA) 3D structures predicted by different computational programs and compared with the crystal structure. (<b>A</b>) The 2.8 Å crystal structure of MGA with strontium ions (green) and tetramethylrosamine (TMR, red) (PDB ID: 1f1t). Segments are color coded as follows: base quadruple (G24∙A31∙G29:C7, blue) above TMR, two sets of base triples (A26∙U11:A22 and A27∙C10:G23, cyan) below the TMR, pair of stacking bases (magenta) adjacent to TMR, and U-turn bulge (U25, white). (<b>B</b>) The MGA 3D structure predicted by RNAComposer. Compared with the crystal structure (<b>A</b>) by using PyMOL 3.0, it shows the all-atom root mean square deviation (RMSD) difference of 2.558 Å. (<b>C</b>) The MGA 3D structure predicted by Rosetta FARFAR2 exhibits an RMSD value of 9.702 Å relative to the crystal structure (<b>A</b>). (<b>D</b>) The MGA 3D structure predicted by AlphaFold 3, with an RMSD of 5.745 Å relative to the crystal structure (<b>A</b>). Prediction confidence is illustrated by color in ribbon form as follows: blue for high confidence regions, yellow for low confidence regions, and orange for very low confidence regions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g002-550.jpg?1731069494" title=" <strong>Figure 2</strong><br/> <p>Comparison of human glycyl-tRNA-CCC (htRNA<sup>Gly-CCC</sup>) 3D structures determined experimentally (<b>A</b>) and predicted by RNAComposer (<b>B</b>), Rosetta FARFAR2 (<b>C</b>), and AlphaFold 3 (<b>D</b>). (<b>A</b>) The htRNA<sup>Gly-CCC</sup> 3D structure is extracted from the human glycyl-tRNA synthetase complex (hGlyRS–htRNA<sup>Gly-CCC</sup>) crystal structure (PDB ID: 5E6M, 2.93 Å resolution) and annotated according to its secondary structure prediction from RNAfold as follows: acceptor arm (wheat tint), D arm (cyan), T arm (yellow), and anticodon arm (orange). (<b>B</b>) The htRNA<sup>Gly-CCC</sup> 3D structure predicted by RNAComposer shows an RMSD of 16.077 Å as compared to the crystal structure (<b>A</b>). (<b>C</b>) The htRNA<sup>Gly-CCC</sup> 3D structure predicted by Rosetta FARFAR2, with an RMSD of 7.482 Å relative to the crystal structure (<b>A</b>). (<b>D</b>) The htRNA<sup>Gly-CCC</sup> 3D structure predicted by AlphaFold 3 exhibits an RMSD of 5.522 Å relative to the crystal structure (<b>A</b>) The degree of prediction confidence is displayed in ribbon form as follows: blue is relatively high, while yellow is relatively low.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g003-550.jpg?1731069495" title=" <strong>Figure 3</strong><br/> <p>Comparison of human glycyl-tRNA-GCC (htRNA<sup>Gly-GCC</sup>) 3D structures predicted computationally with RNAComposer (<b>A</b>), Rosetta FARFAR2 (<b>B</b>), and AlphaFold 3 (<b>C</b>). Acceptor arm (wheat tint), D arm (cyan), T arm (yellow), and anticodon arm (orange). The blue and yellow areas in the ribbon-form structure predicted by AlphaFold 3 indicate high and low confidence in its prediction, respectively. (<b>D</b>) Comparison of the primary sequences of the htRNA<sup>Gly-GCC</sup> examined herein and htRNA<sup>Gly-CCC</sup> isoacceptor shown in <a href="#ncrna-10-00055-f002" class="html-fig">Figure 2</a>. Note that the secondary structure predicted by CONTRAfold was used as inputs for RNAComposer and Rosetta FARFAR2, whereas its primary sequence was directly inputted for AlphaFold 3 prediction. The secondary structure predicted by RNAfold failed to offer unpaired anticodon GCC (<a href="#app1-ncrna-10-00055" class="html-app">Figure S1</a>), thus a common inverted “L” shape tRNA 3D structure (<a href="#app1-ncrna-10-00055" class="html-app">Figure S2</a>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g004-550.jpg?1731069496" title=" <strong>Figure 4</strong><br/> <p>Comparison of human precursor microRNA let-7a-1 (pre-let-7a) 3D structures predicted by RNAComposer (<b>B</b>), Rosetta FARFAR2 (<b>C</b>), and AlphaFold 3 (<b>D</b>) vs. the 3D structure (<b>A</b>) of its truncated version (pre-let-7a<sup>Trunc</sup>) determined experimentally. (<b>A</b>) The pre-let-7a<sup>Trunc</sup> 3D structure extracted from the human Dicer–TRBP complex determined by cryo–EM (PDB ID: 5ZAL, 3.1 Å resolution). Let-7a-1-5p strand (red), let-7a-1-3p (green), and distal loop (pink; orange in ribbon form), which has an undefined structure. Note that the 3D structure of the distal loop remains uncharacterized. (<b>B</b>) The pre-let-7a 3D structure predicted by RNAComposer, with an RMSD of 5.251 Å as compared to the cryo–EM structure (<b>A</b>). (<b>C</b>) The pre-let-7a 3D structure predicted by Rosetta FARFAR2 shows an RMSD of 6.037 Å relative to the crystal structure (<b>A</b>). (<b>D</b>) The pre-let-7a 3D structure predicted by AlphaFold 3, with an RMSD of 4.890 Å difference from the crystal structure (<b>A</b>). Prediction confidence is displayed in ribbon form as follows: blue relatively high, yellow relatively low, and orange very low. (<b>E</b>) Comparison of the primary sequences of the pre-let-7a<sup>Trunc</sup> and pre-let-7a. The secondary structure predicted by CONTRAfold was used as the input for RNAComposer and Rosetta FARFAR2 predictions, and its primary sequence was directly inputted for AlphaFold 3 prediction.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g005-550.jpg?1731069497" title=" <strong>Figure 5</strong><br/> <p>Comparison of the 3D structures of human tRNA<sup>Gly-GCC</sup>-fused hsa-pre-let-7a (BioRNA<sup>Gly</sup>/pre-let-7a) predicted computationally by RNAComposer (<b>A</b>), Rosetta FARFAR2 (<b>B</b>), and AlphaFold 3 (<b>C</b>). The tRNA segment is displayed as follows: acceptor arm (wheat tint), D arm (cyan), T arm (yellow); the pre-let-7a segment is displayed as follows: let-7a-1-5p (red), let-7a-1-3p (green), distal loop (pink; orange in ribbon form). The blue and yellow areas in the ribbon-form structure predicted by AlphaFold 3 indicate high and low confidence, respectively, while the orange denotes very low confidence in its prediction. The secondary structure predicted by CONTRAfold was used as the input for RNAComposer and Rosetta FARFAR2 predictions, and its primary sequence was directly inputted for AlphaFold 3 prediction. Note that the 3D structure of the distal loop within pre-let-7a (<a href="#ncrna-10-00055-f004" class="html-fig">Figure 4</a>A) was undefined in the cryo–EM study [<a href="#B12-ncrna-10-00055" class="html-bibr">12</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g006-550.jpg?1731069498" title=" <strong>Figure 6</strong><br/> <p>Predicted 3D structures of the siRNA drug nedosiran (<b>A</b>,<b>B</b>) and human leucyl-tRNA (htRNA<sup>Leu-UAA</sup>) (<b>C</b>,<b>D</b>) by AlphaFold 3. Sense (S, black) and antisense (AS, red) RNA strands are noted for the nedosiran, and the acceptor arm (wheat tint), D arm (cyan), anticodon arm (orange), variable arm (magenta), and T arm (yellow) are color coded for htRNA<sup>Leu-UAA</sup>. Panels <b>A</b> and <b>C</b> show unmodified RNAs, while panels <b>B</b> and <b>D</b> are respective RNAs with a few modifications supported by AlphaFold 3, including 2′-<span class="html-italic">O</span>-methylcytidine (Cm), 2′-<span class="html-italic">O</span>-methylguanosine (Gm), 2′-<span class="html-italic">O</span>-methyladenosine (Am), and 2′-<span class="html-italic">O</span>-methyluridine (Um), 5-methyluridine (m5U), and pseudouridine (ψ). See <a href="#app1-ncrna-10-00055" class="html-app">Table S2</a> for complete chemical modifications applied to nedosiran and conserved post-transcription modifications for htRNA<sup>Leu-UAA</sup>; many are currently not supported by AlphaFold 3. The blue and cyan regions in the ribbon structure represent very high and high prediction confidence, respectively, while yellow indicates low confidence. While overall 3D structures looked similar, a RMSD of 1.993 Å between unmodified and modified nedosiran siRNA (<b>A</b>,<b>B</b>) was observed, as well as 1.431 Å between modified and unmodified htRNA<sup>Leu-UAA</sup>. Interestingly, the inclusion of chemical modifications affected AlphaFold 3′s ability to perform local prediction confidence analysis and generate the complete ribbon structure for nedosiran siRNA (<b>B</b>), while incorporation of a few conserved post-transcriptional modifications improved the prediction confidence for surrounding regions (<b>D</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00055/article_deploy/html/images/ncrna-10-00055-g007-550.jpg?1731069498" title=" <strong>Figure 7</strong><br/> <p>The workflow for computational prediction of RNA 3D structures. It starts by retrieving primary sequences from relevant databases such as PDB, GtRNAdb, and miRBase. The RNA secondary structures are obtained by using RNAfold, Mfold, or CONTRAfold, and then used by conventional tools (RNAComposer and Rosetta FARFAR2) to generate 3D structures. By contrast, the primary sequence is fed directly into AlphaFold 3 for 3D structure prediction. The resultant structures are visualized and analyzed using PyMOL 3.0, facilitating a detailed comparison of specific structures.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/55'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 1428 KiB   </span> <a href="/2311-553X/10/6/54/pdf?version=1730796300" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Extracellular Vesicle lncRNAs as Key Biomolecules for Cell-to-Cell Communication and Circulating Cancer Biomarkers" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/10/6/54">Extracellular Vesicle lncRNAs as Key Biomolecules for Cell-to-Cell Communication and Circulating Cancer Biomarkers</a> <div class="authors"> by <span class="inlineblock "><strong>Panagiotis Papoutsoglou</strong> and </span><span class="inlineblock "><strong>Antonin Morillon</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 54; <a href="https://doi.org/10.3390/ncrna10060054">https://doi.org/10.3390/ncrna10060054</a> - 5 Nov 2024 </div> <a href="/2311-553X/10/6/54#metrics">Cited by 1</a> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Extracellular vesicles (EVs) are secreted by almost every cell type and are considered carriers of active biomolecules, such as nucleic acids, proteins, and lipids. Their content can be uptaken and released into the cytoplasm of recipient cells, thereby inducing gene reprogramming and phenotypic <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/54/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Extracellular vesicles (EVs) are secreted by almost every cell type and are considered carriers of active biomolecules, such as nucleic acids, proteins, and lipids. Their content can be uptaken and released into the cytoplasm of recipient cells, thereby inducing gene reprogramming and phenotypic changes in the acceptor cells. Whether the effects of EVs on the physiology of recipient cells are mediated by individual biomolecules or the collective outcome of the total transferred EV content is still under debate. The EV RNA content consists of several types of RNA, such as messenger RNA (mRNA), microRNA (miRNA), and long non-coding RNA (lncRNA), the latter defined as transcripts longer than 200 nucleotides that do not code for proteins but have important established biological functions. This review aims to update our insights on the functional roles of EV and their cargo non-coding RNA during cancer progression, to highlight the utility of EV RNA as novel diagnostic or prognostic biomarkers in cancer, and to tackle the technological advances and limitations for EV RNA identification, integrity assessment, and preservation of its functionality. <a href="/2311-553X/10/6/54">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ncrna/special_issues/Q78HGD8Q4E ">Extracellular Vesicles and ncRNA</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/54/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1514196"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1514196"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1514196" data-cycle-prev="#prev1514196" data-cycle-progressive="#images1514196" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1514196-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g001-550.jpg?1730796400" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1514196" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1514196-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g002-550.jpg?1730796402'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1514196-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g003-550.jpg?1730796405'><p>Figure 3</p></div></script></div></div><div id="article-1514196-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g001-550.jpg?1730796400" title=" <strong>Figure 1</strong><br/> <p>Different subtypes of lncRNAs and circRNA biogenesis. (<b>a</b>) Classification of lncRNAs based on their genomic location relative to protein-coding genes (PCG); (<b>b</b>) generation of circRNA from back-splicing of a precursor mRNA (pre-mRNA). Arrows in panel (<b>a</b>) show the direction of transcription and in panel (<b>b</b>) splicing events.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/54'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g002-550.jpg?1730796402" title=" <strong>Figure 2</strong><br/> <p>Biological effects of cancer-derived EVs on diverse cell types within TME. Cancer cells produce heterogenous EV populations consisting of different RNA cargo compositions and sizes, which are secreted in the extracellular space and shape the physiological responses of recipient non-tumorigenic cells of the TME, such as monocytes, dendritic cells, and fibroblasts. MVB: multivesicular body.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/54'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00054/article_deploy/html/images/ncrna-10-00054-g003-550.jpg?1730796405" title=" <strong>Figure 3</strong><br/> <p>Circulating lncRNAs within EVs as cancer biomarkers. Examples of lncRNAs demonstrated to be highly enriched in EVs from human biofluids derived from patients with breast, prostate, pancreatic, liver, bladder, and kidney cancer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/54'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 1045 KiB   </span> <a href="/2311-553X/10/6/53/pdf?version=1729679780" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Cardiomyopathies: The Role of Non-Coding RNAs" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/10/6/53">Cardiomyopathies: The Role of Non-Coding RNAs</a> <div class="authors"> by <span class="inlineblock "><strong>Nicole Carabetta</strong>, </span><span class="inlineblock "><strong>Chiara Siracusa</strong>, </span><span class="inlineblock "><strong>Isabella Leo</strong>, </span><span class="inlineblock "><strong>Giuseppe Panuccio</strong>, </span><span class="inlineblock "><strong>Antonio Strangio</strong>, </span><span class="inlineblock "><strong>Jolanda Sabatino</strong>, </span><span class="inlineblock "><strong>Daniele Torella</strong> and </span><span class="inlineblock "><strong>Salvatore De Rosa</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(6), 53; <a href="https://doi.org/10.3390/ncrna10060053">https://doi.org/10.3390/ncrna10060053</a> - 23 Oct 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Cardiomyopathies are the structural and functional disorders of the myocardium. Etiopathogenesis is complex and involves an interplay of genetic, environmental, and lifestyle factors eventually leading to myocardial abnormalities. It is known that non-coding (Nc) RNAs, including micro (mi)-RNAs and long non-coding (lnc) RNAs, <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/53/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Cardiomyopathies are the structural and functional disorders of the myocardium. Etiopathogenesis is complex and involves an interplay of genetic, environmental, and lifestyle factors eventually leading to myocardial abnormalities. It is known that non-coding (Nc) RNAs, including micro (mi)-RNAs and long non-coding (lnc) RNAs, play a crucial role in regulating gene expression. Several studies have explored the role of miRNAs in the development of various pathologies, including heart diseases. In this review, we analyzed various patterns of ncRNAs expressed in the most common cardiomyopathies: dilated cardiomyopathy, hypertrophic cardiomyopathy and arrhythmogenic cardiomyopathy. Understanding the role of different ncRNAs implicated in cardiomyopathic processes may contribute to the identification of potential therapeutic targets and novel risk stratification models based on gene expression. The analysis of ncRNAs may also be helpful to unveil the molecular mechanisms subtended to these diseases. <a href="/2311-553X/10/6/53">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2311-553X/10/6/53/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1504795"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1504795"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1504795" data-cycle-prev="#prev1504795" data-cycle-progressive="#images1504795" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1504795-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ncrna/ncrna-10-00053/article_deploy/html/images/ncrna-10-00053-g001-550.jpg?1729679906" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1504795" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1504795-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ncrna/ncrna-10-00053/article_deploy/html/images/ncrna-10-00053-g002-550.jpg?1729679908'><p>Figure 2</p></div></script></div></div><div id="article-1504795-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00053/article_deploy/html/images/ncrna-10-00053-g001-550.jpg?1729679906" title=" <strong>Figure 1</strong><br/> <p>Non-Coding RNAs and their sources in the analyzed studies on cardiomyopathies. Figure created with Biorender; echocardiographic images are part of our archive.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/53'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ncrna/ncrna-10-00053/article_deploy/html/images/ncrna-10-00053-g002-550.jpg?1729679908" title=" <strong>Figure 2</strong><br/> <p>Mechanisms of action of some well-known miRNAs in cardiomyopathies. Figure created with Biorender.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2311-553X/10/6/53'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 8 pages, 236 KiB   </span> <a href="/2311-553X/10/5/52/pdf?version=1728624988" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="MicroRNA Biogenesis, Gene Regulation Mechanisms, and Availability in Foods" data-journal="ncrna"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2311-553X/10/5/52">MicroRNA Biogenesis, Gene Regulation Mechanisms, and Availability in Foods</a> <div class="authors"> by <span class="inlineblock "><strong>Amilton S. de Mello</strong>, </span><span class="inlineblock "><strong>Bradley S. Ferguson</strong>, </span><span class="inlineblock "><strong>Erica L. Shebs-Maurine</strong> and </span><span class="inlineblock "><strong>Francine M. Giotto</strong></span> </div> <div class="color-grey-dark"> <em>Non-Coding RNA</em> <b>2024</b>, <em>10</em>(5), 52; <a href="https://doi.org/10.3390/ncrna10050052">https://doi.org/10.3390/ncrna10050052</a> - 11 Oct 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> MicroRNAs (miRNAs) are small, non-coding RNAs that control gene expression by degrading or repressing mRNA translation into proteins. Research recently suggested that food-derived miRNAs are bioavailable and may be absorbed in the gastrointestinal tract (GIT). Since these small RNAs may reach the circulation <a href="#" data-counterslink = "https://www.mdpi.com/2311-553X/10/5/52/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> MicroRNAs (miRNAs) are small, non-coding RNAs that control gene expression by degrading or repressing mRNA translation into proteins. Research recently suggested that food-derived miRNAs are bioavailable and may be absorbed in the gastrointestinal tract (GIT). Since these small RNAs may reach the circulation and organs, possible interactions with host genes will lead to epigenetic effects that alter metabolism. Therefore, from a precision nutrition standpoint, exogenous miRNAs may be essential in modulating health status. This review summarizes the process of miRNA biogenesis, the post-translational mechanisms of gene regulation, and their bioavailability in animal- and plant-derived foods. <a href="/2311-553X/10/5/52">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/ncrna/sections/Small_Non-Coding_RNA">Small Non-Coding RNA</a>)<br/> </div> </div> </div> </div> </div> <div class="generic-item last-item"> <a class="bold" href="/search?q=&journal=ncrna&sort=pubdate&page_count=50">More Articles...</a> </div> </div> </div> </div> <div id="left-column" class="content__column large-3 large-pull-6 medium-3 medium-pull-6 small-12 columns"> <div id="js-large-main-top-container"> <div id="js-main-top-container" class="content__container"> <a href="/journal/ncrna"> <img src="https://pub.mdpi-res.com/img/journals/ncrna-logo.png?8600e93ff98dbf14" alt="ncrna-logo" title="Non-Coding RNA" style="max-height: 60px; margin: 0 0 0 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Non-Coding RNA | An Open Access Journal from MDPI