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7,518 results for “screenings”
Data from: Wide range screening of algorithmic bias in word embedding models using large sentiment lexicons reveals underreported bias types
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Raw sequence of: Field investigation- and dietary metabarcoding-based screening of arthropods that prey on primary tea pests
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Chemical screening in an estrogen receptor transactivation assay with metabolic competence
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Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens
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Mitochondrial and ER membrane protein trafficking CRISPR screens
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Data from: Screening test for neutralizing antibodies against yellow fever virus, based on a flavivirus pseudotype
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Data from: Systematic review on barriers and enablers for access to diabetic retinopathy screening services in different income settings
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Screening of 6000 compounds for uncoupling activity: input parameters, the predicted uncoupling activity, as well as the results in respect to structural alerts
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Data for: Screening of stapled peptides for inhibition of calcium-triggered exocytosis
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Data from: Descriptive multi-agent epidemiology via molecular screening on Atlantic salmon farms in the northeast Pacific Ocean
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Screening the Sigma LOPAC®1280 library of compounds for protective effects against cisplatin-induced oto- and nephrotoxicity
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Respirometric screening and characterization of mitochondrial toxicants within the ToxCast phase I and II chemical libraries
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Peloton baseline screening post-ride survey
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APSiC: Analysis of Perturbation Screens for the Identification of Novel Cancer Genes
<p>Systematic perturbation screens provide comprehensive resources for the elucidation of cancer driver genes. The perturbation of many genes in relatively few cell lines in such functional screens necessitates the development of specialized computational tools with sufficient statistical power. Here we developed APSiC (<em>A</em>nalysis of <em>P</em>erturbation <em>S</em>creens for <em>i</em>dentifying novel <em>C</em>ancer genes) to identify genetic and non-genetic drivers in perturbation screens even with few samples. Applying APSiC to the shRNA screen Project DRIVE, APSiC identified well-known, pan-cancer genetic drivers, novel putative genetic drivers known to be dysregulated in specific cancer types and the context dependency of mRNA-splicing between cancer types. Additionally, APSiC discovered a median of 28 and 35 putative non-genetic oncogenes and tumor suppressor genes, respectively, for individual cancer types, including genes involved in genome stability maintenance and cell cycle. We functionally demonstrated that <em>LRRC4B, </em>a putative novel non-genetic tumor suppressor gene, suppresses proliferation by delaying cell cycle and modulates apoptosis in breast cancer. We demonstrate APSiC is a robust statistical framework for discovery of novel cancer genes through analysis of large-scale perturbation screens. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes.</p>
Trust and Acceptance of Lung Cancer Screening Strategies Questionnaire and Data
<p>Lung cancer is one of the deadliest cancers today. Despite the widespread knowledge that early detection is crucial for cancer treatment, the majority of patients are diagnosed in an advanced stage with a significantly shorter 5-year survival rate. Lung cancer screening allows for early detection of cancer before symptoms arise. Currently, there are plans to introduce a lung cancer screening program in the Netherlands. The goal of this study is to gain knowledge about the effect of an individual's degree of trust on the acceptance level for different Lung Cancer Screening Strategies among people living in the Netherlands. This knowledge helps healthcare providers and professionals as well as the developers of screening software. Also, it supports the development of the best possible patient experience in the future. This survey consists of 30<strong> </strong>questions and should not take longer than 10 minutes to complete.</p>
SATURN: an inexpensive, freely-available, and fully self-administered cognitive screening test
<p>Cognitive screening tests improve detection of dementia in the outpatient setting, and are helpful in select inpatient settings. Barriers to widespread screening include provider time investment and variability in test administration and scoring. We therefore developed Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN) for inexpensive (<$100) computer tablets. This submission to Dryad accompanies an abstract for the 2020 American Academy of Neurology conference, and is likely to referenced in a later manuscript. This Dryad data submission was updated on 31-MAY-2020. The updated version of SATURN ("SATURN_0-4-0_ENGLISH.py") revises the score summary screen with the latest normative data, and now permits the operator to set their state (for orientation questions). The updated Dryad submission also includes a better video of normal operation of SATURN, draft foreign language versions, and an Excel spreadsheet with de-identified participant-level data on demographics, MoCA scores, and SATURN scores. As before, we include instructions for installing SATURN on a computer tablet, and the IRB-approved protocol for the validation study. The latter includes a description of scoring each item within SATURN. Our hope is that by sharing the protocol, it will be easier for others to implement studies that use SATURN.</p> <p> </p> <p>An older file, SATURN.rar, is retained for completeness, but is outdated as of the 31-MAY-2020 upload.</p>
A live screen capture of the AVA360VR prototype being used to annotate camerawork training video data
<p>In this 2D video clip, we see a live screen capture of the AVA360VR prototype being used to annotate camerawork training data. This clip was recorded in January 2018 with an alpha version of the prototype. The functions shown do not necessarily reflect those in the final software tool.</p> <p><em>AVA360VR </em>(Annotate, Visualise, Analyse 360° video in VR) is a VR software tool developed by the BigSoftVideo team at Aalborg University. The aim is to support ‘inhabiting’ 360-degree video data – that is, to explore complex spatial video and audio recordings of a scene in which social interaction took place through a tangible interface in virtual reality.</p> <p> </p> <p> </p> <p> </p>
Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni
<p><span><span><span><span><span><span><span><span><span><span><span>Schistosomes kill 250,000 people every year. Treatment of schistosomiasis relies on a single drug (praziquantel). Unfortunately, a scarcity of molecular tools has hindered the discovery of new drug targets. Here, we describe a large-scale RNA interference screen in adult Schistosoma mansoni examining the function of 2,216 genes. We discovered 250 genes with phenotypes affecting neuromuscular function, tissue integrity, stem cell maintenance, and parasite survival. Leveraging these data, we prioritize compounds with activity against the parasites and uncover a pair of protein kinases (TAO and STK25) that cooperate to maintain muscle-specific mRNA transcription. Loss of either of these kinases results in paralysis and worm death in a mammalian host. These studies will expedite therapeutic development and invigorate studies of these neglected parasites. Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni.</span></span></span></span></span></span></span></span></span></span></span></p> <p> </p>
Ultraviolet photodissociation for non-target screening based identification of organic micro-pollutants in water samples
<p>Raw LC-HRMS data that was used for demonstrating the the use of the fragmentation technique ultraviolet photodissociation (UVPD) for the structural elucidation of organic micropollutants (OMPs) in water samples in combination with the 'uvpd' R-package (<a href="https://github.com/cpanse/uvpd/">https://github.com/cpanse/uvpd/</a>). The dataset consists of HCD and UVPD fragmentation data of reference standard samples acquired at various collision energies and reaction times, respectively. The analyses were performed with a Vanquish Horizon UHPLC system coupled to an Orbitrap Fusion Lumos Tribrid instrument with positive and negative ESI ionization. More analytical details are in Panse et al., Molecules, submitted.</p>
Raw in vitro screening data and R scripts for: A Bayesian method for population-wide cardiotoxicity hazard and risk characterization using an in vitro human model
<p>Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes are an established model for testing potential chemical hazards. Inter-individual variability in toxicodynamic sensitivity has also been demonstrated <i>in vitro</i>; however, quantitative characterization of the population-wide variability has not been fully explored. We sought to develop a method to address this gap by combining a population-based iPSC-derived cardiomyocyte model with Bayesian concentration-response modeling. A total of 136 compounds, including 44 pharmaceuticals and 82 environmental chemicals, were tested in iPSC-derived cardiomyocytes from 43 non-diseased humans. Hierarchical Bayesian population concentration-response modeling was conducted for five phenotypes reflecting cardiomyocyte function or viability. Toxicodynamic variability was quantified through the derivation of chemical- and phenotype-specific variability factors (TDVF). Toxicokinetic modeling was used for probabilistic <i>in vitro</i>-to-<i>in vivo </i>extrapolation in order to derive population-wide margins of safety (MOS) for pharmaceuticals and margins of exposure (MOE) for environmental chemicals. Pharmaceuticals were found to be active across all phenotypes. Over half of tested environmental chemicals showed activity in at least one phenotype, most commonly positive chronotropy. TDVF estimates for the functional phenotypes were greater than those for cell viability, usually exceeding the generally-assumed default of ~3. Population variability-based MOS for pharmaceuticals were correctly predicted to be relatively narrow, between 10-100; however, MOE for environmental chemicals, based on population exposure estimates, generally exceeded 1000, suggesting they pose little risk at general population exposures even to sensitive sub populations. This study represents a first of its kind human <i>in vitro</i> model that can be used to characterize toxicodynamic population variability in cardiotoxic risk.</p>
ScienceDex guides
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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.