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Spirjakin</title> <meta name="description" content="Search results for: Denis Spirjakin"> <meta name="keywords" content="Denis Spirjakin"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Denis Spirjakin"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 94</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Denis Spirjakin</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Heat Transfer Phenomena Identification of a Non-Active Floor in a Stack-Ventilated Building in Summertime: Empirical Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Miguel%20Chen%20Austin">Miguel Chen Austin</a>, <a href="https://publications.waset.org/abstracts/search?q=Denis%20Bruneau"> Denis Bruneau</a>, <a href="https://publications.waset.org/abstracts/search?q=Alain%20Sempey"> Alain Sempey</a>, <a href="https://publications.waset.org/abstracts/search?q=Laurent%20Mora"> Laurent Mora</a>, <a href="https://publications.waset.org/abstracts/search?q=Alain%20Sommier"> Alain Sommier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An experimental study in a Plus Energy House (PEH) prototype was conducted in August 2016. It aimed to highlight the energy charge and discharge of a concrete-slab floor submitted to the day-night-cycles heat exchanges in the southwestern part of France and to identify the heat transfer phenomena that take place in both processes: charge and discharge. The main features of this PEH, significant to this study, are the following: (i) a non-active slab covering the major part of the entire floor surface of the house, which include a concrete layer 68 mm thick as upper layer; (ii) solar window shades located on the north and south facades along with a large eave facing south, (iii) large double-glazed windows covering the majority of the south facade, (iv) a natural ventilation system (NVS) composed by ten automatized openings with different dimensions: four are located on the south facade, four on the north facade and two on the shed roof (north-oriented). To highlight the energy charge and discharge processes of the non-active slab, heat flux and temperature measurement techniques were implemented, along with airspeed measurements. Ten “measurement-poles” (MP) were distributed all over the concrete-floor surface. Each MP represented a zone of measurement, where air and surface temperatures, and convection and radiation heat fluxes, were intended to be measured. The airspeed was measured only at two points over the slab surface, near the south facade. To identify the heat transfer phenomena that take part in the charge and discharge process, some relevant dimensionless parameters were used, along with statistical analysis; heat transfer phenomena were identified based on this analysis. Experimental data, after processing, had shown that two periods could be identified at a glance: charge (heat gain, positive values) and discharge (heat losses, negative values). During the charge period, on the floor surface, radiation heat exchanges were significantly higher compared with convection. On the other hand, convection heat exchanges were significantly higher than radiation, in the discharge period. Spatially, both, convection and radiation heat exchanges are higher near the natural ventilation openings and smaller far from them, as expected. Experimental correlations have been determined using a linear regression model, showing the relation between the Nusselt number with relevant parameters: Peclet, Rayleigh, and Richardson numbers. This has led to the determination of the convective heat transfer coefficient and its comparison with the convective heat coefficient resulting from measurements. Results have shown that forced and natural convection coexists during the discharge period; more accurate correlations with the Peclet number than with the Rayleigh number, have been found. This may suggest that forced convection is stronger than natural convection. Yet, airspeed levels encountered suggest that it is natural convection that should take place rather than forced convection. Despite this, Richardson number values encountered indicate otherwise. During the charge period, air-velocity levels might indicate that none air motion occurs, which might lead to heat transfer by diffusion instead of convection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat%20flux%20measurement" title="heat flux measurement">heat flux measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20ventilation" title=" natural ventilation"> natural ventilation</a>, <a href="https://publications.waset.org/abstracts/search?q=non-active%20concrete%20slab" title=" non-active concrete slab"> non-active concrete slab</a>, <a href="https://publications.waset.org/abstracts/search?q=plus%20energy%20house" title=" plus energy house"> plus energy house</a> </p> <a href="https://publications.waset.org/abstracts/81533/heat-transfer-phenomena-identification-of-a-non-active-floor-in-a-stack-ventilated-building-in-summertime-empirical-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81533.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Decrease in Olfactory Cortex Volume and Alterations in Caspase Expression in the Olfactory Bulb in the Pathogenesis of Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majed%20Al%20Otaibi">Majed Al Otaibi</a>, <a href="https://publications.waset.org/abstracts/search?q=Melissa%20Lessard-Beaudoin"> Melissa Lessard-Beaudoin</a>, <a href="https://publications.waset.org/abstracts/search?q=Amel%20Loudghi"> Amel Loudghi</a>, <a href="https://publications.waset.org/abstracts/search?q=Raphael%20Chouinard-Watkins"> Raphael Chouinard-Watkins</a>, <a href="https://publications.waset.org/abstracts/search?q=Melanie%20Plourde"> Melanie Plourde</a>, <a href="https://publications.waset.org/abstracts/search?q=Frederic%20Calon"> Frederic Calon</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Alexandre%20Castellano"> C. Alexandre Castellano</a>, <a href="https://publications.waset.org/abstracts/search?q=Stephen%20Cunnane"> Stephen Cunnane</a>, <a href="https://publications.waset.org/abstracts/search?q=Helene%20Payette"> Helene Payette</a>, <a href="https://publications.waset.org/abstracts/search?q=Pierrette%20Gaudreau"> Pierrette Gaudreau</a>, <a href="https://publications.waset.org/abstracts/search?q=Denis%20Gris"> Denis Gris</a>, <a href="https://publications.waset.org/abstracts/search?q=Rona%20K.%20Graham"> Rona K. Graham</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=APOE4" title=" APOE4"> APOE4</a>, <a href="https://publications.waset.org/abstracts/search?q=cognition" title=" cognition"> cognition</a>, <a href="https://publications.waset.org/abstracts/search?q=caspase" title=" caspase"> caspase</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20atrophy" title=" brain atrophy"> brain atrophy</a>, <a href="https://publications.waset.org/abstracts/search?q=neurodegenerative" title=" neurodegenerative"> neurodegenerative</a>, <a href="https://publications.waset.org/abstracts/search?q=olfactory%20dysfunction" title=" olfactory dysfunction"> olfactory dysfunction</a> </p> <a href="https://publications.waset.org/abstracts/74770/decrease-in-olfactory-cortex-volume-and-alterations-in-caspase-expression-in-the-olfactory-bulb-in-the-pathogenesis-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74770.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">258</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Antimicrobial and Antioxidant Activities of Actinobacteria Isolated from the Pollen of Pinus sylvestris Grown on the Lake Baikal Shore </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Denis%20V.%20Axenov-Gribanov">Denis V. Axenov-Gribanov</a>, <a href="https://publications.waset.org/abstracts/search?q=Irina%20V.%20Voytsekhovskaya"> Irina V. Voytsekhovskaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Evgenii%20S.%20Protasov"> Evgenii S. Protasov</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxim%20A.%20%20Timofeyev"> Maxim A. Timofeyev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Isolated ecosystems existing under specific environmental conditions have been shown to be promising sources of new strains of actinobacteria. The taiga forest of Baikal Siberia has not been well studied, and its actinobacterial population remains uncharacterized. The proximity between the huge water mass of Lake Baikal and high mountain ranges influences the structure and diversity of the plant world in Siberia. Here, we report the isolation of eighteen actinobacterial strains from male cones of Pinus sylvestris trees growing on the shore of the ancient Lake Baikal in Siberia. The actinobacterial strains were isolated on solid nutrient MS media and Czapek agar supplemented with cycloheximide and phosphomycin. Identification of actinobacteria was carried out by 16S rRNA gene sequencing and further analysis of the evolutionary history. Four different liquid and solid media (NL19, DNPM, SG and ISP) were tested for metabolite production. The metabolite extracts produced by the isolated strains were tested for antibacterial and antifungal activities. Also, antiradical activity of crude extracts was carried out. Strain Streptomyces sp. IB 2014 I 74-3 that active against Gram-negative bacteria was selected for dereplication analysis with using the high-yield liquid chromatography with mass-spectrometry. Mass detection was performed in both positive and negative modes, with the detection range set to 160–2500 m/z. Data were collected and analyzed using Bruker Compass Data Analysis software, version 4.1. Dereplication was performed using the Dictionary of Natural Products (DNP) database version 6.1 with the following search parameters: accurate molecular mass, absorption spectra and source of compound isolation. Thus, in addition to more common representative strains of Streptomyces, several species belonging to the genera Rhodococcus, Amycolatopsis, and Micromonospora were isolated. Several of the selected strains were deposited in the Russian Collection of Agricultural Microorganisms (RCAM), St. Petersburg, Russia. All isolated strains exhibited antibacterial and antifungal activities. We identified several strains that inhibited the growth of the pathogen Candida albicans but did not hinder the growth of Saccharomyces cerevisiae. Several isolates were active against Gram-positive and Gram-negative bacteria. Moreover, extracts of several strains demonstrated high antioxidant activity. The high proportion of biologically active strains producing antibacterial and specific antifungal compounds may reflect their role in protecting pollen against phytopathogens. Dereplication of the secondary metabolites of the strain Streptomyces sp. IB 2014 I 74-3 was resulted in the fact that a total of 59 major compounds were detected in the culture liquid extract of strain cultivated in ISP medium. Eight compounds were preliminarily identified based on characteristics described in the Dictionary of Natural Products database, using the search parameters Streptomyces sp. IB 2014 I 74-3 was found to produce saframycin A, Y3 and S; 2-amino-3-oxo-3H-phenoxazine-1,8-dicarboxylic acid; galtamycinone; platencin A4-13R and A4-4S; ganefromycin d1; the antibiotic SS 8201B; and streptothricin D, 40-decarbamoyl, 60-carbamoyl. Moreover, forty-nine of the 59 compounds detected in the extract examined in the present study did not result in any positive hits when searching within the DNP database and could not be identified based on available mass-spec data. Thus, these compounds might represent new findings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=actinobacteria" title="actinobacteria">actinobacteria</a>, <a href="https://publications.waset.org/abstracts/search?q=Baikal%20Lake" title=" Baikal Lake"> Baikal Lake</a>, <a href="https://publications.waset.org/abstracts/search?q=biodiversity" title=" biodiversity"> biodiversity</a>, <a href="https://publications.waset.org/abstracts/search?q=male%20cones" title=" male cones"> male cones</a>, <a href="https://publications.waset.org/abstracts/search?q=Pinus%20sylvestris" title=" Pinus sylvestris"> Pinus sylvestris</a> </p> <a href="https://publications.waset.org/abstracts/55755/antimicrobial-and-antioxidant-activities-of-actinobacteria-isolated-from-the-pollen-of-pinus-sylvestris-grown-on-the-lake-baikal-shore" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55755.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">232</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Multimodal Integration of EEG, fMRI and Positron Emission Tomography Data Using Principal Component Analysis for Prognosis in Coma Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Denis%20Jordan">Denis Jordan</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Golkowski"> Daniel Golkowski</a>, <a href="https://publications.waset.org/abstracts/search?q=Mathias%20Lukas"> Mathias Lukas</a>, <a href="https://publications.waset.org/abstracts/search?q=Katharina%20Merz"> Katharina Merz</a>, <a href="https://publications.waset.org/abstracts/search?q=Caroline%20Mlynarcik"> Caroline Mlynarcik</a>, <a href="https://publications.waset.org/abstracts/search?q=Max%20Maurer"> Max Maurer</a>, <a href="https://publications.waset.org/abstracts/search?q=Valentin%20Riedl"> Valentin Riedl</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefan%20Foerster"> Stefan Foerster</a>, <a href="https://publications.waset.org/abstracts/search?q=Eberhard%20F.%20Kochs"> Eberhard F. Kochs</a>, <a href="https://publications.waset.org/abstracts/search?q=Andreas%20Bender"> Andreas Bender</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruediger%20Ilg"> Ruediger Ilg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coma%20states%20and%20prognosis" title="coma states and prognosis">coma states and prognosis</a>, <a href="https://publications.waset.org/abstracts/search?q=electroencephalogram" title=" electroencephalogram"> electroencephalogram</a>, <a href="https://publications.waset.org/abstracts/search?q=entropy" title=" entropy"> entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20magnetic%20resonance%20imaging" title=" functional magnetic resonance imaging"> functional magnetic resonance imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=positron%20emission%20tomography" title=" positron emission tomography"> positron emission tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a> </p> <a href="https://publications.waset.org/abstracts/55193/multimodal-integration-of-eeg-fmri-and-positron-emission-tomography-data-using-principal-component-analysis-for-prognosis-in-coma-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55193.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">339</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Denis%20Spirjakin&page=3" 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