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30,948 results for “Profile”
Supplementary information to the article by van Beijnum et al. "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment"
<p>Supplementary information to the article "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment".</p> <p><strong>Judy R. van Beijnum<sup>1</sup>, Andrea Weiss<sup>2, 3</sup>, Robert H. Berndsen<sup>1,2 </sup>, Tse J. Wong<sup>1</sup>, Louise C. Reckman<sup>1</sup>, Sander R. Piersma<sup>4,5</sup>, Marloes Zoetemelk<sup>2,3</sup>, Richard de Haas<sup>1,4,5</sup>, Olivier Dormond<sup>6</sup>, Axel Bex<sup>7,8</sup>, Alexander A. Henneman<sup>4,5</sup>, Connie R. Jimenez<sup>4,5</sup>, Arjan W. Griffioen<sup>1</sup>, Patrycja Nowak-Sliwinska<sup>2,3,9</sup>*</strong></p> <p> </p> <p><sup>1</sup> Angiogenesis Laboratory, Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands;</p> <p><sup>2</sup> Molecular Pharmacology Group, School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland*;</p> <p><sup>3 </sup>Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland</p> <p><sup>4 </sup>Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands</p> <p><sup>5</sup> OncoProteomics Laboratory, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</p> <p><sup>6</sup> Department of Visceral surgery, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland<sup> </sup> </p> <p><sup>7</sup> Royal Free London NHS Foundation Trust, Renal Cancer Centre, UCL Division of Surgical and Interventional Science, London, UK</p> <p><sup>8</sup> Netherlands Cancer Institute, Amsterdam, The Netherlands</p> <p><sup>9 </sup> Translational Research Centre in Oncohaematology, Geneva, Switzerland</p> <p> Correspondence: <a href="mailto:Patrycja.Nowak-Sliwinska@unige.ch">Patrycja.Nowak-Sliwinska@unige.ch</a></p>
Empirical shapes for the publication "Modifications of the K-Profile parameterization with nondiffusive fluxes for wave effects"
<p>This dataset contains data for the reproduction of the empirical shape functions G_l and g_s introduced in the publication "Modifications of the K-Profile parameterization with nondiffusive fluxes for wave effects".</p>
Supplementary data (simulated metagenome set 3) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of SSU rRNA read extraction and targeted assembly from simulated shotgun metagenome of closely related Bacteorides strains.</p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
3D metabolic profiles acquired by a Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS)
<p>Dataset for "Spatially resolved 3D metabolomic profiling in tissues"</p> <p>The Dataset has 6 subdata of TOF-SIMS signal raw data:<br> * Inside germinal center dataset separate into 2<br> * Outside germinal center dataset<br> * Border germinal center dataset<br> * Unlabeled dataset separate into 2<br> * Labeled tonsil tissue dataset<br> * Unlabeled tonsil tissue dataset</p> <p>1 processed data for python numpy version: 3D metabolites npy Data.zip</p> <p>Each dataset is a folder that has 191 txt files corresponding to the signal of 189 mass channels, the sum of all signals and the rest of signals not captured. <br> In each folder, the signal corresponding to a channel is named: name - molecular compound<br> </p>
Dataset Profil Toko
<p><em>Dataset</em> dalam laman ini adalah <em>dataset</em> yang digunakan dalam <em>paper</em> "Analisis Pengaruh Profil Toko Resmi <em>Smartphone</em> (Merk Samsung, Xiaomi, Realme, Oppo, dan Vivo) di 3 Situs <em>E-Commerce</em> (Tokopedia, Shopee, dan BliBli) terhadap Tingkat Penjualan". <em>Dataset</em> tersedia dalam format .csv</p>
Longitudinal proteomic profiling of high-risk patients with COVID-19 reveals markers of severity and predictors of fatal disease
<p>End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We performed dense serial blood sampling in hospitalised and non-hospitalised ESKD patients with COVID-19 (n=256 samples from 55 patients) and used Olink immunoassays to measure 436 circulating proteins. Comparison to 51 non-infected ESKD patients revealed 221 proteins differentially expressed in COVID-19, of which 69.7% replicated in an independent cohort of 46 COVID-19 patients. 203 proteins were associated with clinical severity scores, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g proteinase-3) and epithelial injury (e.g. KRT19). Random Forests machine learning identified predictors of current or future severity such as KRT19, PARP1, PADI2, CCL7, and IL1RL1 (ST2). Survival analysis with joint models revealed 69 predictors of death including IL22RA1, CCL28, and the neutrophil-derived chemotaxin AZU1 (Azurocidin). Finally, longitudinal modelling with linear mixed models uncovered 32 proteins that display different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. Our findings point to aberrant innate immune activation and leucocyte-endothelial interactions as central to the pathology of severe COVID-19. The data from this unique cohort of high-risk individuals provide a valuable resource for identifying drug targets in COVID-19.</p>
FIG. 2. — Profil taphonomique des principaux assemblages fauniques d in Exploitation animale à l'Ancien Empire en Égypte: les apports d'Ayn Asil (oasis de Dakhla)
FIG. 2. — Profil taphonomique des principaux assemblages fauniques d'Ayn Asil.
Microgrid Profiles
<p>This dataset has been used for validating the technology solution developed during eDREAM project in the Italian pilot site (GA n. 774478).</p>
Input data of manuscript "CACTUS: integrating clonal architecture with genomic clustering and transcriptome profiling of single tumor cells"
<p>This is the directory containing input data necessary to reproduce analyses presented in the manuscript:</p> <blockquote> <p><strong>CACTUS: integrating clonal architecture with genomic clustering and transcriptome profiling of single tumor cells</strong><br> Shadi Darvish Shafighi, Szymon M Kiełbasa, Julieta Sepúlveda Yáñez, Ramin Monajemi, Davy Cats, Hailiang Mei, Roberta Menafra, Susan Kloet, Hendrik Veelken, Cornelis A.M. van Bergen, Ewa Szczurek</p> </blockquote>
A specific IL6 polymorphic genotype modulates the risk of T. cruzi parasitemia while IL18, IL17A and IL1B variant profiles and HIV infection protect against cardiomyopathy in Chagas disease
<p><strong>Background:</strong> Chagas disease caused by Trypanosoma cruzi (T. cruzi) affects approximately six million individuals worldwide. Clinical manifestations are expected to occur due to the parasite persistence and host immune response. Herein we investigated potential associations between IL1B, IL6, IL17A or IL18 polymorphism profiles and cardiomyopathy or T. cruzi parasitemia, as well as the impact of HIV infection on cardiopathy.</p> <p><strong>Methods:</strong> 206 patients and 90 control individuals were analyzed. IL1B rs1143627 T>C, IL6 rs1800795 C>G, IL17A rs2275913 G>A, IL18 rs187238 C>G, and IL18 rs1946518 C>A SNVs were analyzed by real-time PCR and T. cruzi parasitemia by PCR.</p> <p><strong>Results: </strong>Our data revealed association between a cytokine gene polymorphism and parasitemia never previously reported. The IL6 rs1800795 CG genotype lowered the risk of positive parasitemia (OR=0.45, 95% CI 0.24–0.86, P=0.015). Original findings included associations between IL17A rs2275913 AA and IL18 s1946518 AA genotypes with decreased risk of developing cardiomyopathy (OR=0.27, 95% CI 0.07-0.97, P=0.044; and OR=0.35, 95% CI 0.14-0.87, P=0.023, respectively). IL18 rs1946518 AA and IL1B rs1143627 TC were associated with reduced risk for cardiomyopathy severity, including NYHA (New York Heart Association) class≥ 2 (OR=0.21, 95% CI 0.06-0.68, P=0.009; and OR=0.48, 95% CI 0.24-0.95, P=0.036, respectively) and LVEF (Left Ventricular Ejection Fraction) <45% for IL18 rs1946518 AA (OR=0.22, 95% CI 0.05-0.89, P=0.034). A novel, unexpected protective effect of HIV infection against development/progression of cardiomyopathy was identified, based on a lower risk of developing cardiopathy (OR=0.48, 95% CI 0.23‐0.96, P=0.039), NYHA class≥2 (OR=0.15, 95% CI 0.06‐0.39, P<0.001) and LVEF<45% (OR=0.03, 95% CI 0.00‐0.25, P=0.001). Digestive involvement was negatively associated with NYHA ≥2 and LVEF<45% (OR=0.20, 95% CI 0.09‐0.47, P<0.001; and OR=0.24, 95% CI 0.09-0.62, P=0.004, respectively).</p> <p><strong>Conclusions: </strong>Our data support a protective role of IL17A AA, IL18 AA and IL1B TC genotypes against development/progression of cardiomyopathy and a modulatory effect of the IL6 CG genotype on the risk of parasitemia in Chagas disease. Notably, HIV infection was shown to protect against development/progression of cardiopathy, potentially associated with a synergistic effect of HIV and HAART, attenuating a Th1-mediated response in the myocardium. This proposed hypothesis requires confirmation, however, in larger and more comprehensive future studies.</p>
Random Profile Data
<p>Sine wave + Random noise</p>
Public opinion about management strategies for a low-profile Species across multiple jurisdictions: whitebark pine in the northern Rockies
<p>1. As public land managers seek to adopt and implement conservation measures aimed at reversing or slowing the negative effects of climate change, they are looking to understand public opinion regarding different management strategies.</p> <p>2. This study explores drivers of attitudes toward different management strategies (i.e., no management, protection, and restoration) for a low-profile but keystone tree species, the whitebark pine (<i>Pinus albicaulis</i>), in the Greater Yellowstone Ecosystem. Since the whitebark pine species has a range that traverses different federal land designations, we examine whether attitudes toward management strategies differ by jurisdiction (i.e., wilderness or federal lands more generally).</p> <p>3. We conducted a web and mail survey of residents from Montana, Idaho, and Wyoming, with 1,617 valid responses and a response rate of 16%. <a name="_Hlk36455244"></a></p> <p>4. We find that active management strategies have substantially higher levels of support than does no management, with relatively little differentiation across protection and restoration activities or across different land designations. We also find that support for management strategies is not influenced by values (political ideology) but is influenced by beliefs (about material vs. post-material environmental orientation, global climate change, and federal spending for public lands) and some measures of experience (e.g., knowledge of threats).</p> <p>5. This study helps land managers understand that support for active management of the whitebark pine species is considerable and nonpartisan and that beliefs and experience with whitebark pine trees are important for support</p>
Data from: Transcriptome profiles of sunflower reveal the potential role of microsatellites in gene expression divergence
The mechanisms by which natural populations generate adaptive genetic variation are not well understood. Some studies propose that microsatellites can function as drivers of adaptive variation. Here we tested a potentially adaptive role for transcribed microsatellites with natural populations of the common sunflower (Helianthus annuus L.) by assessing the enrichment of microsatellites in genes that show expression divergence across latitudes. Seeds collected from six populations at two distinct latitudes in Kansas and Oklahoma were planted and grown in a common garden. Morphological measurements from the common garden demonstrated that phenotypic variation among populations is largely explained by underlying genetic variation. An RNA–Seq experiment was conducted with 96 of the individuals grown in the common garden and differentially expressed (DE) transcripts between the two latitudes were identified. A total number of 825 DE transcripts were identified. DE transcripts and non-differentially expressed (NDE) transcripts were then scanned for microsatellites. The abundance of different motif lengths and types in both groups were estimated. Our results indicate that DE transcripts are significantly enriched with mononucleotide repeats and significantly depauperate in trinucleotide repeats. Further, the standardized mononucleotide repeat motif A and dinucleotide repeat motif AG were significantly enriched within DE transcripts while motif types, C, AT, ACC, and AAC in DE transcripts are significantly differentiated in microsatellite tract length between the two latitudes. The tract length differentiation at specific microsatellite motif types across latitudes and their enrichment within DE transcripts indicate a potential functional role for transcribed microsatellites in gene expression divergence in sunflower.
Soil inoculation alters leaf metabolic profiles in genetically identical plants
<p> Abiotic and biotic properties of soil can influence growth and chemical composition of plants. Although it is well-known that soil microbial composition can vary greatly spatially, how this variation affects plant chemical composition is poorly understood. We grew genetically identical <em>Jacobaea vulgaris</em> in sterilized soil inoculated with live soil collected from four natural grasslands and in 100% sterilized soil. Within each grassland we sampled eight plots, totalling 32 different inocula. Two samples per plot were collected, leading to three levels of spatial variation: within plot, between and within grasslands. The leaf metabolome was analysed with <sup>1</sup>H Nuclear magnetic resonance spectroscopy (NMR) to investigate if inoculation altered the metabolome of plants and how this varied between and within grasslands. Inoculation led to changes in metabolomics profiles of J. vulgaris in two out of four sites. Plants grown in sterilized and inoculated soils differed in concentrations of malic acid, tyrosine, trehalose and two pyrrolizidine alkaloids (PA). Metabolomes of plants grown in inoculated soils from different sites varied in glucose, malic acid, trehalose, tyrosine and in one PA. The metabolome of plants grown in soils with inocula from the same site was more similar than with inocula from distant sites. We show that soil influences leaf metabolomes. Performance of aboveground insects often depends on chemical composition of plants. Hence our results imply that soil microbial communities, via affecting aboveground plant metabolomes, can impact aboveground plant-insect food chains but that it is difficult to make general predictions due to spatial variation in soil microbiomes.</p> <div> <div> <div class="msocomtxt"> </div> </div> </div>
Data from: Profile of and risk factors for post-stroke cognitive impairment in diverse ethno-regional groups
OBJECTIVE: To address the variability in prevalence estimates and inconsistencies in potential risk factors for post-stroke cognitive impairment (PSCI) using a standardised approach and individual participant data (IPD) from international cohorts in the STROKOG consortium. METHODS: We harmonised data from thirteen studies based in eight countries. Neuropsychological test scores 2 to 6 months after stroke or TIA and appropriate normative data were used to calculate standardised cognitive domain scores. Domain-specific impairment was based on percentile cut-offs from normative groups, and associations between domain scores and risk factors were examined using one-stage IPD meta-analysis. RESULTS: In a combined sample of 3,146 participants admitted to hospital for stroke (97%) or TIA (3%), 44% were impaired in global cognition and 30–35% in individual domains 2 to 6 months after the index event. Diabetes and a history of past stroke were strongly associated with poorer cognitive function after covariate adjustments; hypertension, smoking and atrial fibrillation had weaker domain-specific associations. While there were no significant differences in domain impairment among ethno-racial groups, some inter-ethnic differences were found in the effects of risk factors on cognition. CONCLUSIONS: This paper confirms the high prevalence of PSCI in diverse populations, highlights common risk factors, in particular diabetes, and points to ethno-racial differences which warrant attention in the development of prevention strategies.
Data from: Ecological factors influence balancing selection on leaf chemical profiles of a wildflower
<div> <div> <div> <div> <p>Balancing selection is frequently invoked as a mechanism to maintain variation within and across populations. However, rigorous tests demonstrating balancing selection operating in nature are scarce, particularly on complex traits, which frequently display high levels of variation. Leveraging a focal polymorphism, leaf chemical profile in a perennial wildflower (<em>Boechera stricta</em>, Brassicaceae), we investigated the ecological and genetic mechanisms that may influence the maintenance of variation in this trait. A suite of common garden and greenhouse experiments showed that the alleles underlying variation in chemical profile have contrasting fitness effects across environments, implicating two ecological drivers of selection on chemical profile: herbivory and drought. Phenotype-environment associations and molecular genetic analyses revealed additional evidence of past selection by these drivers. Together, these data are consistent with balancing selection on chemical profile, likely caused by pleiotropic effects of genes that influence secondary chemical biosynthesis on herbivore defense and drought response.</p> </div> </div> </div> </div>
Profiling protocols example datasets for mOTUs v3
<p>Example dataset for the profiling protocols</p>
Intaglio. Oval intaglio in rose-coloured garnet engraved with the bust of a woman in profile; before her a brāhmī inscription in three characters.
<p>Intaglio. Oval intaglio in rose-coloured garnet engraved with the bust of a woman in profile; before her a brāhmī inscription in three characters. British Museum 1892,1103.121.</p>
Intaglio. Oval intaglio in garnet with a concave back; engraved with a bust of a woman in profile; before her a brāhmī inscription in four characters.
<p>Intaglio. Oval intaglio in garnet with a concave back; engraved with a bust of a woman in profile; before her a brāhmī inscription in four characters. British Museum 1892,1103,140.</p>
Intaglio. Oval intaglio in garnet with a flat back; engraved with a bust of a man in profile; above him a brāhmī inscription in five characters.
<p>Intaglio. Oval intaglio in garnet with a flat back; engraved with a bust of a man in profile; above him a brāhmī inscription in five characters. British Museum 1892,1103.141.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.