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169
datasets available to search
ShareScore release 0.9.0
Dataset results
169 results for “timing of detection”
Comparison of Adenoma Detection Miss Rates at Colonoscopy Associated With Different Withdrawal Times
ClinicalTrials.gov study NCT01802008. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Surveillance of High-risk Early Postsurgical Patients for Real-time Detection of Complications
ClinicalTrials.gov study NCT02957825. IPD Sharing: NO. Countries: 1. Publications: 1.
Real-time Early Detection of Nephrotoxicity by Urinary Biomarker Analysis With SeroFlow Technology
ClinicalTrials.gov study NCT06124885. IPD Sharing: NO. Countries: 1. Publications: 1.
AIDI - Research & Development of a Multisensor-Based Machine Learning Technology for Real-Time Automated Detection of COVID-19 Decompensation
ClinicalTrials.gov study NCT05220306. IPD Sharing: NO. Countries: 1. Publications: 1.
Setting the Shortest Examination Time of Gastroscopy to Improve the Detection Rate of Upper Gastrointestinal Tumors
ClinicalTrials.gov study NCT04602299. IPD Sharing: NO. Countries: 1. Publications: 1.
Impact of Real-time Automatic Quality Control System on Colorectal Adenoma Detection
ClinicalTrials.gov study NCT04901130. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Supporting information for: A pilot experiment on infrasonic lahar detection at Mount Adams, Cascades: Ambient infrasound and wind-noise characterization at a quiescent stratovolcano: time-lapse camera images
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Data from: Detection of airborne genetically modified maize pollen by real-time PCR
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Data from: Detecting selection on temporal and spatial scales: a genomic time-series assessment of selective responses to devil facial tumor disease
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Data from: Ready to detect a reversal of time’s arrow: a psychophysical study using short video clips in daily scenes
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Data from: Functional antibodies against Plasmodium falciparum sporozoites are associated with a longer time to qPCR-detected infection among schoolchildren in Burkina Faso
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Data from: Hide and seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence
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Selection and exploitation of prevalent, tandemly repeated genomic targets for improved real-time PCR-based detection of Wuchereria bancrofti and Plasmodium falciparum in mosquitoes
<p><b>Background</b></p> <p>Optimization of polymerase chain reaction (PCR)-based diagnostics requires the careful selection of molecular targets that are both highly repetitive and pathogen-specific. Advances in both next-generation sequencing (NGS) technologies and bioinformatics-based analysis tools are facilitating this selection process, informing target choices and reducing labor. Once developed, such assays provide disease control and elimination programs with an additional set of tools capable of evaluating and monitoring intervention successes. The importance of such tools is heightened as intervention efforts approach their endpoints, as accurate and complete information is an essential component of the informed decision-making process. As global efforts for the control and elimination of both lymphatic filariasis and malaria continue to make significant gains, the benefits of diagnostics with improved analytical and clinical/field-based sensitivities and specificities will become increasingly apparent.</p> <p><b>Methodology/Principal Findings </b></p> <p>Coupling Illumina-based NGS with informatics approaches, we have successfully identified the tandemly repeated elements in both the <i>Wuchereria bancrofti </i>and <i>Plasmodium falciparum </i>genomes of putatively greatest copy number. Utilizing these sequences as quantitative real-time PCR (qPCR)-based targets, we have developed assays capable of exploiting the most abundant tandem repeats for both organisms. For the detection of <i>P. falciparum</i>, analysis and development resulted in an assay with improved analytical and field-based sensitivity vs. an established ribosomal sequence-targeting assay. Surprisingly, analysis of the <i>W. bancrofti </i>genome predicted a ribosomal sequence to be the genome's most abundant tandem repeat. While resulting cycle quantification values comparing a qPCR assay targeting this ribosomal sequence and a commonly targeted repetitive DNA sequence from the literature supported our finding that this ribosomal sequence was the most prevalent tandemly repeated target in the <i>W. bancrofti </i>genome, the resulting assay did not significantly improve detection sensitivity in conjunction with field sample testing. </p> <p><b>Conclusions/Significance </b></p> <p>Examination of pathogen genomes facilitates the development of PCR-based diagnostics targeting the most abundant and specific genomic elements. While in some instances currently available tools may deliver equal or superior performance, systematic analysis of potential targets provides confidence that the selected assays represent the most advantageous options available and that informed assay selection is occurring in the context of a particular study's objectives.</p>
Data from: Effect of detection heterogeneity in occupancy-detection models: an experimental test of time-to-first-detection methods
Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time-to-first-detection (TTD) occupancy models have been proposed as a cost-effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy-detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala (Phascolarctos cinereus) populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness-of-fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy-detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness-of-fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy-detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.
Data from: Computer assisted detection of axonal bouton structural plasticity in in vivo time-lapse images
The ability to measure minute structural changes in neural circuits is essential for long-term in vivo imaging studies. Here, we propose a methodology for detection and measurement of structural changes in axonal boutons imaged with time-lapse two-photon laser scanning microscopy (2PLSM). Correlative 2PLSM and 3D electron microscopy (EM) analysis, performed in mouse barrel cortex, showed that the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18), and that 2PLSM-based bouton weights are correlated with their volumes measured in EM (r=0.93). Next, the method was applied to a set of axons imaged in quick succession to characterize measurement uncertainty. The results were used to construct a statistical model in which bouton addition, elimination, and size changes are described probabilistically, rather than being treated as deterministic events. Finally, we demonstrate that the model can be used to quantify significant structural changes in boutons in long-term imaging experiments.
Data from: Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys
Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9–20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.
Data from: Genomic data detect corresponding signatures of population size change on an ecological time scale in two salamander species
Understanding the demography of species over recent history (e.g., < 100 years) is critical in studies of ecology and evolution, but records of population history are rarely available. Surveying genetic variation is a potential alternative to census-based estimates of population size, and can yield insight into the demography of a population. However, to assess the performance of genetic methods it is important to compare their estimates of population history to known demography. Here, we leveraged the exceptional resources from a wetland with 37 years of amphibian mark-recapture data to study the utility of genetically-based demographic inference on salamander species with documented population declines (Ambystoma talpoideum) and expansions (A. opacum); patterns that have been shown to be correlated with changes in wetland hydroperiod. We generated ddRAD data from two temporally sampled populations of A. opacum (1993, 2013) and A. talpoideum (1984, 2011) and used coalescent-based demographic inference to compare alternate evolutionary models. For both species, demographic model inference supported population size changes that corroborated mark-recapture data. Parameter estimation in A. talpoideum was robust to our variations in analytical approach, while estimates for A. opacum were highly inconsistent, tempering our confidence in detecting a demographic trend in this species. Overall, our robust results in A. talpoideum suggest that genome-based demographic inference has utility on an ecological scale, but researchers should also be cognizant that these methods may not work in all systems and evolutionary scenarios. Demographic inference may be an important tool for population monitoring and conservation management planning.
Data from: Residual eDNA detection sensitivity assessed by quantitative real-time PCR in a river ecosystem
Several studies have demonstrated that environmental DNA (eDNA) can be used to detect the presence of aquatic species, days to weeks after the target species has been removed. However, most studies used eDNA analysis in lentic systems (ponds or lakes), or in controlled laboratory experiments. While eDNA degrades rapidly in all aquatic systems, it also undergoes dilution effects and physical destruction in flowing systems, complicating detection in rivers. However, some eDNA (i.e. residual eDNA) can be retained in aquatic systems, even those subject to high flow regimes. Our goal was to determine residual eDNA detection sensitivity using quantitative real-time polymerase chain reaction (qRT-PCR), in a flowing, uncontrolled river after the eDNA source was removed from the system; we repeated the experiment over two years. Residual eDNA had the strongest signal strength at the original source site and was detectable there up to 11.5 hours after eDNA source removal. Residual eDNA signal strength decreased as sampling distance downstream from the eDNA source site increased, and was no longer detectable at the source site 48 hours after the eDNA source water was exhausted in both experiments. This experiment shows that residual eDNA sampled in surface water can be mapped quantitatively using qRT-PCR, which allows a more accurate spatial identification of the target species location in lotic systems, and relative residual eDNA signal strength may allow the determination of the timing of the presence of target species.
Analysis of the performance of Faster R-CNN and YOLOv8 in detecting fishing vessels and fishs in real time
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Detecting periodicities in time-series (for exoplanet detection)
<p>Recording of the presentation given at the Summer School</p>
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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.