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27 results for “time of death”
Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022.
<p>Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022. These data were used to estimate the time-varying reproduction number (R) in South Africa, as described in https://www.medrxiv.org/content/10.1101/2022.07.22.22277932v1.full.</p>
Data for: "A high-throughput microscopy method for single-cell analysis of event-time correlations in nanoparticle-induced cell death"
<p>Data related to the publication Murschhauser <em>et al.</em>: <a href="https://doi.org/10.1038/s42003-019-0282-0">A high-throughput microscopy method for single-cell analysis of event-time correlations in nanoparticle-induced cell death</a>. It contains fluorescence time traces of single cells marked with cell-event markers and observed by time-lapse microscopy. The cells were treated with nanoparticles at different doses (NP25 and NP100), with staurosporine (sts) or were left untreated for control (ctrl). See the above-mentioned publication for more details.</p> <p>The format of the data is described below.</p> <p>The file <code>Data_A549.zip</code> contains data measured with A549 cells, and the file <code>Data_Huh7.zip</code> contains data measured with Huh7 cells. Both files have the same structure. Each file contains the directories <code>Raw</code> and <code>Fitted</code> as well as a checksum file. The <code>Raw</code> directory contains single-cell fluorescence time courses as obtained by time-lapse microscopy. The <code>Fitted</code> directory contains the results of fitting model functions as well as properties of identified events, such as event times. The checksum file contains SHA256 checksums of all files within these directories and can be used to check file integrity.</p> <p>Both directories contain measurement directories. Each measurement directory contains the data corresponding to one experiment. The name of the measurement directory is the measurement identifier. Each measurement directory contains condition directories. Each condition directory contains data corresponding to one condition measured in the measurement and is named after the condition. Each condition directory contains marker directories. They are named after the fluorescence markers measured and contain files with single-cell data corresponding to the respective markers.</p> <p>The names of those files consist of multiple parts separated by underscores. The first two parts identify a position of the microscope. Since pairs of markers were measured, each position is present in two marker directories. The third part is the measurement identifier. The other parts will be described below.</p> <p>The <code>Raw</code> directory contains only CSV files with the raw fluorescence time courses. The filenames contain no other parts and have the suffix “.txt”. The first row of each CSV file is the time (in units of 10 minutes), and the other rows are the fluorescence time courses of the cells observed at the corresponding position (in arbitrary units). Each file in the <code>Raw</code> directory corresponds to a group of files in the <code>Fitted</code> directory.</p> <p>The <code>Fitted</code> directory contains three types of CSV files. Their names have “ALL” as fourth part, a session identifier as sixth part and the suffix “.csv”. The fifth part indicates the type of file and is one of the following:</p> <ul> <li>“PARAMS” indicates the estimated values for the model parameters. Each row stands for one cell and each column for a parameter of the model function fitted to the data. The model functions are published with the <a href="https://doi.org/10.5281/zenodo.1418465">fitting software</a>.</li> <li>“SIMULATED” indicates the fitted traces. The traces are calculated using the model functions and the estimated parameters. The format is the same as for the raw traces, but the time is in units of hours and has a higher resolution.</li> <li>“STATE” indicates additional information extracted from the fitted traces. Each row stands for a cell and each column for a property. The first column is the number of the cell. The second column is the event time found (in hours); non-finite values indicate that no event time was found. The third and fourth columns contain the absolute and relative amplitude of the trace, respectively. The fifth column is the logarithmic likelihood of the best fit. The sixth column indicates an algorithm used for postprocessing, and the seventh column indicates the trace slope at the event. See the fitting software for details.</li> </ul> <p> </p>
Fig. 1 in Effect of four multiple nucleopolyhedrovirus isolates on the larval mortality and development of Spodoptera exigua (Lepidoptera: Noctuidae): determination of virus production and mean time to death
Fig. 1. Mean time of death calculated for third-instar larvae of Spodoptera exigua. The numbers above the columns indicate the values calculated for 3 replications. The columns headed by the same letter are not significantly different (Weibull analysis, α = 1.96).
Data for: Modeling the transition of death assemblages through the mixed layer predicts a downcore increase in time averaging
<p>Understanding how time averaging changes during the burial is essential for using Holocene and Anthropocene cores to analyze ecosystem change, given the many ways in which the time averaging affects biodiversity measures. Here, we use transition-rate matrices to explore how time averaging changes downcore when shells transit through a taphonomically-complex mixed layer into permanently-buried historical layers: this is a null model, without any temporal changes in rates of sedimentation or bioturbation, to contrast with downcore patterns that might be produced by human activity. Assuming stochastic burial and exhumation movements of shells between increments within the mixed layer and stochastic disintegration within increments, almost all combinations of net sedimentation, mixing, and disintegration produce a downcore increase in time averaging (interquartile range, IQR), typically associated with a decrease in kurtosis and skewness and with a shift from right-skewed to symmetrical age distributions. A downcore increase in time averaging is a null expectation wherever bioturbation generates an internally-structured mixed layer (i.e., a surface well-mixed layer is underlain by an incompletely-mixed layer), so that shells are mixed throughout the entire mixed layer at slower rate than they are buried below it by sedimentation. This downcore trend created by mixing is further amplified by the downcore decline in disintegration rate. Using data from the southern California shelf, we find that transition-rate matrices accurately reproduce the downcore changes in IQR, skewness, and kurtosis observed in sediment cores. The right-skewed distributions typical of surface death assemblages – the focus of most actualistic research – might be fossilized under exceptional conditions of episodic anoxia or sudden burial. However, such right-skewed assemblages will not typically transfer into subsurface historical layers and thus will be geologically transient. The deep-time fossil record will be dominated instead by more time-averaged assemblages with weakly skewed age distributions that form in the lower parts of the mixed layer.</p>
Data for: Modeling the transition of death assemblages through the mixed layer predicts a downcore increase in time averaging
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When death comes: Linking predator-prey activity patterns to timing of mortality to understand predation risk
<p>The assumption that activity and foraging are risky for prey underlies many predator-prey theories and has led to the use of predator-prey activity overlap as a proxy of predation risk. However, the simultaneous measures of prey and predator activity along with timing of predation required to test this assumption have not been available. Here, we used accelerometry data on snowshoe hares (<em>Lepus</em> <em>americanus</em>) and Canada lynx (<em>Lynx canadensis)</em> to determine activity patterns of prey and predators and match these to precise timing of predation. Surprisingly, we found that lynx kills of hares were as likely to occur during the day when hares were inactive as at night when hares were active. We also found that activity rates of hares were not related to the chance of predation at daily and weekly scales, whereas lynx activity rates positively affected the diel pattern of lynx predation on hares and their weekly kill rates of hares. Our findings suggest that predator-prey diel activity overlap may not always be a good proxy of predation risk, and highlight a need for examining the link between predation and spatiotemporal behavior of predator and prey to improve our understanding of how predator-prey behavioral interactions drive predation risk.</p>
When death comes: Linking predator-prey activity patterns to timing of mortality to understand predation risk
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Data from: Explaining high-diversity death assemblages: undersampling of the living community, out-of-habitat transport, time-averaging of rare taxa, and local extinction
Molluscan benthic assemblages provide unique opportunities for understanding both spatial and temporal patterns of biodiversity. Species richness in the shell remains found at a site (i.e. the death assemblage) is typically several times higher than in the counterpart living assemblage, reflecting a complex history of settlement, dissemination and decomposition post-mortem. We used high-density temporal and spatial sampling (>37'000 individuals representing 196 taxa) of a shallow (5-8 m) nearshore sandy habitat off the coast of south-east Sardinia (Italy, Mediterranean Sea) to study the factors responsible for differences in the relative diversity of living and death assemblages. We found that death assemblages at all sites were considerably more diverse than living communities (1.5-3.5x more dead than living taxa after sample-size standardization), with 78% of all taxa solely recovered as empty shells, resulting in low live-dead agreement. By carefully filtering the raw data and combining them with habitat information extracted from the literature, we disentangled the major causes of this discordance and quantified their individual effects. Increased dead diversities could not be attributed to undersampling of the living community, but instead resulted from three phenomena of decreasing importance: the post-mortem, out-of-habitat transport of non-indigenous taxa (57% of dead-only taxa were allochthonous), the time-averaged presence of rare indigenous taxa (40% of dead-only taxa), and the likely local extirpation of a small number of species (3% of dead-only taxa). Our approach demonstrates how ecological inferences based on death assemblages can be improved by restricting analyses to demonstrably indigenous taxa, and highlights how mollusc shell remains can be used to provide information over both ecological and evolutionary timescales.
The relation between deviation from the balanced time perspective and quality of life among older people. The mediating role of death anxiety and the moderating role of awareness of aging
<p><em><span>Objectives</span></em><span>. In the current study, one of the objectives was to check if the deviation from a balanced time perspective (DBTP) is a predictor of the quality of life of the elderly. Another objective investigated whether awareness of aging is a moderator and death anxiety a mediator of the relationship between PTSD and quality of life. <em>Method.</em> 436 elderly people participated in this research (M = 68.27; SD= 6.56; 66.7% female, 33.3% male). They completed 4 instruments to evaluate the variables included in the study: World Health Organization Quality of Life, Zimbardo Time Perspective Inventory - Short version, Death Anxiety Scale and Awareness of Age-Related Change 10-Item Short Form (awareness of aging). <em>Results</em>. Statistical analyzes highlighted the fact that DBTP is not a predictor of quality of life, but it can positively predict death anxiety. Also, awareness of aging does not moderate the relationship between DBTP and quality of life. Finally, death anxiety negatively predicts quality of life, but also mediates the relationship between DBTP and quality of life. <em>Discussion</em>. This study brought to the fore some concepts less addressed in the case of the elderly population in Romania, which could lead to the identification of some benefits for improving the quality of life of the elderly. Starting from the conclusions obtained, promotion and intervention plans can be developed to improve mental and physical health services. The inclusion process of the elderly in as many social activities as possible can also be considered.</span></p> <p><strong><span> </span></strong></p>
Vitamin A Liver Reserves and Serum Markers of Vitamin A in US Adults at Time of Death
ClinicalTrials.gov study NCT03305042. IPD Sharing: NO. Countries: 1. Publications: 1.
Canadian Study of Prediction of Risk and Evolution to Dialysis, Death and Interim Cardiovascular Events Over Time
ClinicalTrials.gov study NCT00826319. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Prediction on Time to Death in Potential Controlled Donation After Circulatory Death (cDCD) Donors (DCD III Study)
ClinicalTrials.gov study NCT04123275. IPD Sharing: NO. Countries: 1. Publications: 2.
Trends Over Time (1990-2010) of Diarrhoea-related Hospitalizations and Deaths in Children < 5 Years of Age in Brazil
ClinicalTrials.gov study NCT01175252. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Explaining high-diversity death assemblages: undersampling of the living community, out-of-habitat transport, time-averaging of rare taxa, and local extinction
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Data from: Live, dead, and fossil mollusks in Florida freshwater springs and spring-fed rivers: taphonomic pathways and the formation of multi-sourced, time-averaged death assemblages
Taphonomic processes are informative about the magnitude and timing of paleoecological changes but remain poorly understood with respect to freshwater invertebrates in spring-fed rivers and streams. We compared taphonomic alteration among freshwater gastropods in live, dead (surficial shell accumulations), and fossil (late Pleistocene-early Holocene in situ sediments) assemblages from two Florida spring-fed systems, the Wakulla and Silver/Ocklawaha Rivers. We assessed taphonomy of two gastropod species: the native <i>Elimia floridensis</i> (n=2504) and introduced <i>Melanoides tuberculata</i> (n=168). We quantified seven taphonomic attributes (aperture condition, color, fragmentation, abrasion, juvenile spire condition, dissolution, and exterior luster) and combined those attributes into a total taphonomic score (TT). Fossil <i>E. floridensis</i> specimens exhibited the greatest degradation (highest TT scores), whereas live specimens of both species were least degraded. Specimens of <i>E. floridensis</i> from death assemblages were less altered than fossil specimens of the same species. Within death assemblages, specimens of <i>M. tuberculata</i> were significantly less altered than specimens of <i>E. floridensis</i>, but highly degraded specimens dominated in both species. Radiocarbon dates on fossils clustered between 9792 and 7087 cal. BP, whereas death assemblage ages ranged from 10,692 to 1173 cal. BP. Possible explanations for the observed taphonomic patterns include: (1) rapid taphonomic shell alteration, (2) prolonged near-surface exposure to moderate alteration rates, and/or (3) introduction of reworked fossil shells into surficial assemblages. Combined radiocarbon dates and taphonomic analyses suggest that all these processes may have played a role in death assemblage formation. In these fluvial settings, shell accumulations develop as a complex mixture of specimens derived from multiple sources and characterized by multi-millennial time averaging. These findings suggest that, when available, fossil assemblages may be more appropriate than death assemblages for assessing pre-industrial faunal associations and recent anthropogenic changes in freshwater ecosystems.
Supplementary results for stroke, timing of atrial fibrillation diagnosis, and risk of death
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective:</b> To evaluate the prognosis of ischemic stroke patients according to the timing of an atrial fibrillation (AF) diagnosis, we created an inception cohort of incident stroke events and compared the risk of death between stroke patients with a) sinus rhythm; b) known atrial fibrillation (KAF); and c) AF diagnosed after stroke (AFDAS). </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Methods:</b> We utilized the Penn AF Free study to create an inception cohort of patients with incident stroke. Mortality events were identified after linkage with the National Death Index through June 30, 2017. We also evaluated initiation of anticoagulants and antiplatelets across the study duration. Cox proportional hazards models evaluated associations between stroke subtypes and death.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results</b>: We identified 1,489 individuals who developed an incident ischemic stroke event: 985 did not develop AF at any point during the study period, 215 had KAF before stroke, 160 had AF detected ≤6 months after stroke and 129 had AF detected >6 months after stroke. After a median follow-up of 4.9 [IQR 1.9, 6.8] years, 686 deaths occurred. The annualized mortality rate was 8.8% in the stroke, no AF group; 12.2% in the KAF group, 15.8% in the AFDAS ≤6 months; and 12.7% in the AFDAS > 6 months. Patients in the AFDAS ≤6 months had the highest independent risk of all-cause mortality even after multivariable adjustment for demographics, clinical risk factors and the use of antithrombotic therapies [HR 1.62 (1.22, 2.14)]. Compared to the stroke, no AF group, those with KAF had a higher mortality risk that was rendered non-significant after adjustment. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span class="MsoHyperlink"><span><span><span><span><span><span><span><span><span><b>Conclusions</b></span></span></span></span></span></span></span></span></span></span><span class="MsoHyperlink"><span><span><span><span><span><span><span><span><span>: The AFDAS group had the highest risk of death, which was not explained by comorbidities or use of antithrombotic therapies. </span></span></span></span></span></span></span></span></span></span></p>
Supplementary results for stroke, timing of atrial fibrillation diagnosis, and risk of death
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Data from: The effect of fossil sampling on the estimation of divergence times with the fossilised birth death process
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Data from: Live, dead, and fossil mollusks in Florida freshwater springs and spring-fed rivers: taphonomic pathways and the formation of multi-sourced, time-averaged death assemblages
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Regulatory inversion in NAC networks steers the timing of age-dependent cell death in plants [Nanostring]
GEO Series GSE92369. Arabidopsis thaliana. 434 samples. Type: Expression profiling by array.
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