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970 results for “risk assessment”
Appendices to the Roadmap for action for the project More Welfare: towards new risk assessment methodologies and harmonised animal welfare data in the EU
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Data and code for publication: Advancing Maternal Transfer of Organic Pollutants across Reptiles for Conservation and Risk Assessment Purposes
<p>Dataset and r code to prepare the dataset, in support of the publication:</p> <p>"Advancing maternal transfer of organic pollutants across reptiles for conservation and risk assessment purposes"</p> <p>Munoz, C.C., Charles, S., Vermeiren, P. (2024) Environmental Science and Technology, https://doi.org/10.1021/acs.est.4c04668</p> <p>contact email: munozc.cynthia@gmail.com</p>
Dataset in support of an AI-aided chronic mixture risk assessment along a small European river
<p>Here, we make available a dataset to perform an AI-aided multi-scenario chronic mixture risk assessment. In 2021, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. The dataset of the chemical analysis was already published and can be found at DOI: 10.5281/zenodo.10892038. Furthermore, a detailed description of the dataset can be found at DOI: 10.1016/j.dib.2024.110510.</p> <p> </p>
Drug-Induced TdP Risk Assessment
<p>A manually collected dataset that investigates the proarrhythmic risk of 109 drugs using parameters obtained from biophysical models. The dataset provides 4 torsade de pointes (TdP) risk categories. For all 109 drugs, IC50 values and Hill coefficients (h) for INa, INaL, IKr, Ito, ICaL, IK1, and IKs and human effective free therapeutic plasma concentration (EFTPC) were obtained (Llopis-Lorente et al., 2020).</p> <p> </p> <p><strong>Task: </strong>The dataset can be used to study causal discovery methods aiming to infer ion channels selection for the drug-induced TdP risk.</p> <p> </p> <p><strong>Summary: </strong></p> <ul> <li><strong>Size of dataset</strong>: 109 x 16</li> <li><strong>Task:</strong> Causal Discovery Problem</li> <li><strong>Data Type:</strong> Mixed Data</li> <li><strong>Dataset Scope:</strong> Standalone Dataset</li> <li><strong>Ground Truth:</strong> Unknown Graph</li> <li><strong>Temporal Structure:</strong> Static Data</li> <li><strong>License:</strong> CC BY-NC 4.0 (see https://pubs.acs.org/page/policy/authorchoice_termsofuse.html)</li> <li><strong>Missing Values:</strong> Existing Missing Values</li> </ul> <p> </p> <p><strong>Missingness Statement: </strong>A dash in the dataset means that no value was found publicly available, thus it was considered that the drug effect on that current was negligible (Llopis-Lorente et al., 2020).</p> <p> </p> <p><strong>Features:</strong></p> <ul> <li><strong>Class</strong>: Torsadogenic risk characterization. Class 1 (known risk of TdP), class 2 (possible risk of TdP), class 3 (conditional risk of TdP), and class 4 (drugs with a lack of evidence of TdP).</li> <li><strong>EFTPC</strong>: Effective free therapeutic plasma concentration. EFTPC is the minimum concentration of the unbound form of a drug in plasma required to produce the intended therapeutic effect in the body.</li> <li><strong>IC50[...]</strong>: Value that represents the minimal concentration of a drug that is required for 50% inhibition in vitrovalues (given in nm). Drugs are in the set {Kr, INa,INaL, ICaL, IKs, IK1, Ito}.</li> <li><strong>h[...]</strong>: Hill coefficients of the currents. Drugs are in the set {Kr, INa,INaL, ICaL, IKs, IK1, Ito}.</li> </ul> <p> </p> <p><strong>Files: </strong></p> <ul> <li><strong>med_file.csv</strong>: dataset</li> </ul>
Assessment of Potential Risk Factors for COVID-19 among Health Care Workers in a Health Care Setting in Delhi, India
<p><strong><em>Executive summary</em></strong></p> <p>The novel coronavirus SARS-CoV2 (COVID-19), first detected by Wuhan Municipal Health Commission, China, in Wuhan, Hubei Province in December 2020 and eventually the disease became pandemic. It was declared as Public Health Emergency of International Concern (PHEIC) by WHO in January 2020. The COVID-19 disease primarily spreads through droplets of saliva or discharge from the nose when an infected person coughs or sneezes. People infected with the COVID-19 virus experiences mild, moderate or serious respiratory illness. </p> <p>Health workers play a critical role in the clinical management of patients with COVID-19 and hence are likely to be the most vulnerable for contracting the disease. Therefore, investigating the extent of infection in health care settings and identifying risk factors for infection among health workers along with follow-up within a facility in which a confirmed case of COVID-19 infection is receiving care can provide useful information on virus transmissibility and routes of transmission, and will bear important step in limiting amplification events in health care facilities. </p> <p> </p> <p><strong>Objectives:</strong></p> <p>1. To find out the extent of human-to-human transmission of the SARS-CoV-2 infection among health workers<br> 2. To study the clinical presentations of COVID-19 infection and the risk factors for infection among health workers.<br> 3 To evaluate the effectiveness of infection prevention and control measures among health workers in protecting against COVID-19.<br> 4. To evaluate the effectiveness of infection prevention and control programmes at health facility level <br> 5. To determine the serological response of health workers with symptomatic and possibly asymptomatic COVID-19 infection.</p> <p> </p> <p><strong>Materials and Methods:</strong></p> <p>This was a prospective cohort study conducted over a period of seven months, from December 2020 to June 2021, the period covering India’s deadly second wave of COVID-19 pandemic. This was done among the health care workers working in HIMSR & HAHC hospital, a tertiary health care setting (Dedicated COVID-19 Hospital) providing care to patients with a laboratory-confirmed COVID-19 infection. This hospital located in South East Delhi has 200 bedded COVID-19 Care Hospital and 1050 registered healthcare workers who come in contact with COVID-19-infected persons. The study population (sampling frame) included all the health personnel like doctors, nurses, paramedical staff, housekeeping staff, security staff, students of medical, nursing and paramedical sciences and other front office staff who come in contact with the patients. In this study, the first visit / interview (Baseline) was done when the staff came in contact with a confirmed COVID-19 case. The second visit / interview (Endline) was done between 22-28 days. During each of these two visits, biological sample in the form of serum was collected to check the presence of anti-COVID-19 antibodies</p> <p> </p> <p><strong>Results:</strong></p> <p>A total of 192 HCW were recruited in this study. All of them were interviewed and blood was collected for serology at the baseline visit as well as at endline. Out of 192 participants, 119 (61.97%) were detected with SARS-CoV2 antibodies at baseline whereas 73 (38.02%) were seronegative. Again, on22-28 days of follow-up, the seropositivity was 77.7% at the endline. We found that seropositivity was significantly and negatively associated with doctor as profession [OR:0.353, CI:0.176-0.710], COVID-19 symptoms [OR:0.210, CI:0.054-0.820], comorbidities [OR:0.139 , CI: 0.029 - 0.674], recent IPC Training [OR:0.250, CI:0.072 -0.864] , while positively associated with Partially [OR:3.303,CI: 1.256-8.685], as well as fully Vaccinated for COVID-19 [OR:2.428, CI:1.118-5.271]. We also observed seroconversion among 36.7% while 64.0% had increase in titre of antibodies during our follow-up period. The seroconversion was 63.2% in doctors, 42.9% in nurses and 13.0% in paramedics staff. Seroconversion was positively associated with doctor as profession [OR:11.43, CI:2.47 - 52.79] and with partially, as well as fully vaccinated for COVID-19 [OR: 32.63, CI: 5.11 - 208.49]. None of the HCW who were smokers and with any comorbidity did not found to have been seroconversion. We observe a negative and significant relationship of increase in titre of antibodies with recent any ILI symptoms [OR:0.17, 0.13 - 0.94], smokers[OR: 0.35, 95%CI: 0.13 - 0.94], HCW with comorbidities [OR:0.08,95CI: 0.01 - 0.71],, recent full IPC Training [OR:0.07, CI:0.01 -0.63] , while positively associated with partially [OR: 7.87, 95CI: 2.18 - 28.40)], as well as fully Vaccinated for COVID-19 [OR: 3.59, 95CI: 1.46 - 8.87]. Majority of the health care worker enrolled in our study had close contact exposure with COVID-19 patients while 5 had indirect exposure. It was observed that almost all (100% in both) doctors and nurses as well as almost all paramedical staff (99%) were wearing some kind of personal protective equipment (PPE) when they were exposed to a COVID-19 patient. We did not found adherences to any of the infection prevention measure adopted by the enrolled HCW during the recent contact with COVID-19 patients to be significantly associated with seroconversion. </p> <p><strong>Conclusion:</strong></p> <p>Majority of the health care worker (67% doctor, 80% nurses & 55% paramedics) enrolled in our study had close contact exposure with COVID-19 patient. The results show that among 192 HCW enrolled, 62% were seropositive at the baseline. At end line the seropositivity was increased to 77.7%. The seroconversion rate was also studied. It was found to be 36.7% in our study population (63.2% in doctors, 42.9% in nurses and 13.0% in paramedic’s staff.). Adherence to the recommended IPC measures was reported by most participants. About two third (63%) of the HCW in our study were not vaccinated against COVID-19; nurses and paramedics were higher in proportion among those who were unvaccinated. Fifteen percentage were partially vaccinated and 22% were fully vaccinated against COVID-19, with doctors comprising majority among them. We also found that vaccination had the strongest association with seropositivity, seroconversion as well as serial rise of titre.</p>
IUCLID templates for PPP Risk Assessment - Template 7.2 - Template for presenting the results of the OECD 106 evaluators checklist
<p>This word file contains the template for <strong>presenting the results of the OECD 106 evaluators checklist</strong>. The template has been draft based on the Technical report on the outcome of the pesticides peer review meeting on the OECD 106 evaluators checklist (EFSA, 2017).<br> The filled-in template shall be pasted in the "<strong>Any other information on results incl. tables</strong> " field of IUCLID document “<strong>Adsorption and desorption in soil</strong>”<strong> </strong>endpoint study record (Section 7.1.3.1 of active substance dataset).</p>
An epidemiological Study to Assess Household Transmission & Associated Risk Factors for COVID-19 Disease amongst Residents of Delhi, India.
<p><strong><em>Executive summary</em></strong>: Studying the spread and epidemiological characteristics of COVID-19 virus specially in household settings are needed to prepare our self-better in preventing and controlling this epidemic. In this study we proposed a conceptual framework of four level of determinates and tried to understand the transmission dynamics of COVID-19 among household contacts along with clinical, epidemiological and virologic characteristics of the infection. </p> <p><strong>Aims & Objectives:</strong></p> <ol> <li>the proportion of asymptomatic cases and symptomatic cases;</li> <li>the incubation period of COVID-19 and the duration of infectiousness and of detectable shedding;</li> <li>the serial interval of COVID-19 infection; </li> <li>clinical risk factors for COVID-19, and the clinical course and severity of disease; </li> <li>high-risk population subgroups;</li> <li>the secondary infection rate and secondary clinical attack rate of COVID-19 infection among household contacts; and</li> <li>the associations of various factors across four dimensions interaction associated with risk of transmission</li> </ol> <p><strong>Methodology:</strong> This was a case-ascertained study where all susceptible contacts of a laboratory confirmed COVID-19 case were studied prospective for four weeks after their enrolment. It was done in New Delhi, during the end of first wave as well as whole second wave from December 2020 to July 2021. The study team collected the key information by questionnaire along with blood and oro-nasal swab during the household visits. Follow-up was done on day 7, 14 and 28 for observing the disease characteristic and symptomatology along with confirmation by serum and oro-nasal swab testing. Daily characteristics of the infection were noted by the participants on symptoms diary.</p> <p><strong>Results: </strong>We enrolled 99 households, each having one laboratory-confirmed COVID-19 index case along with their 318 susceptible contacts. By the end of the follow-up, secondary infection rate was seen at 55.5%, while seroconversion in 46.6%. Hospitalization and case fatality rate was 3.83% and 1.7% respectively. Among epidemiological characteristics we observed serial interval of 8.0 ± 6.7 days, generation time 3.8 ± 6.4, while secondary attack rate was 54.9%. The predictors of secondary infection among individual contact level were being female (OR:2.13, 95% CI:1.27 - 3.57), age of the household contact (1.01;1.00 - 1.03), symptoms at baseline (3.39; 1.61- 7.12) and during follow-up (3.18; 1.64 - 6.19), while only symptoms during follow-up (3.81: 1.43 - 10.14) and being RT-PCR positive (8.32; 3.22 -21.54) was significantly and independently associated with seroconversion among household contacts. Among index case-level age of the primary case (1.03; 1.01 -1.04) and any symptoms during follow-up (6.29; 1.83-21.63) significantly and independently associated with secondary infection while any symptoms during follow-up was associated with seroconversion among household contacts. Among household-level characteristics having more rooms (4.44; 2.16 - 9.13) independently associated with secondary infection, while more rooms (3.98; 1.23 -12.90) along with overcrowding (0.37; 0.16 - 0.82) associated with seroconversion. Among contact pattern only taking care of the index case (2.02;1.21- 3.38) was significantly and independently associated with secondary infection, while none was associated with seroconversion.</p> <p><strong>Conclusion: </strong>A high secondary cases and secondary attack rate was seen in our study. This highlights the need to adopts strict measure and advocate COVID appropriate behaviours in order to break the transmission chain at household level. The targeted approach at household contacts with higher risk would be efficient in limiting the development of infection among susceptible contacts. </p>
Datasets and R-codes complementing the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen"
<p>These datasets complement the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen". They contain:</p> <p>i) data on concentration of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>) in commercially available sunscreens,</p> <p>ii) data on amount sunscreen used, and</p> <p>iii) data on dermal absorption of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>).</p> <p>The data are used in the probabilistic exposure estimations in the Opinion. The data were retrieved from open sources.</p> <p>In addition, the R-codes used to perform the exposure estimation, are included.</p>
Risk of bias assessments for the Cochrane review 'SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19'
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19.</p>
Simulation file for "Titanium dioxide and silver nanoparticles air emissions risk assessment for spray coating processes in Witek, Italy – A case study"
<p>Underlying data for “Nanosized titanium dioxide particle emission potential from a commercial indoor air purifier photocatalytic surface – A case study”</p>
Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: Janus kinase inhibitors for the treatment of COVID-19
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: Janus kinase inhibitors for the treatment of COVID-19.</p>
Risk of bias assessments for version 5 of the Cochrane review 'Convalescent plasma for people with COVID-19'
<p>Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Living Systematic Review: Convalescent plasma for people with COVID-19 (Version 5). </p>
Supplementary material 1 from: Yemshanov D, Koch F, Ducey M, Haack R, Siltanen M, Wilson K (2013) Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker's perspective. NeoBiota 18: 193-218. https://doi.org/10.3897/neobiota.18.4002
Risk of out-of-state (out-of-province) locations to be the source of forest pests transported in firewood carried by campers. The risk rank values are based on the delineation of nested non-dominant sets via the first-degree stochastic dominance rule (FSD). The ranks close to 1.0 denote the highest risk of pest arrival and the ranks close to 0 denote the lowest risk. (doi: 10.3897/neobiota.18.4002.app1) File format: Adobe PDF File (pdf).:
Supplementary material 4 from: Yemshanov D, Koch F, Ducey M, Haack R, Siltanen M, Wilson K (2013) Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker's perspective. NeoBiota 18: 193-218. https://doi.org/10.3897/neobiota.18.4002
Summary of differences between risk rank classes, 0–0.05, 0.05–0.25, 0.25–0.5, 0.5–0.75, 0.75–0.95 and 0.95–1 in the delineations based on the FSD and SSD rules. (doi: 10.3897/neobiota.18.4002.app4) File format: Adobe PDF File (pdf).:
Risk Assessment of Extreme Precipitation on to Low- and Medium-Voltage Electrical Infrastructure Under the Influence of Climate Change
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Exposure and fragility of a virtual oil refinery testbed for seismic risk assessment
<p><span>Α</span><span> </span><span>virtual mid-size oil refinery, located in a high-seismicity region of Greece, is offered as a testbed for developing and testing system-level assessment methods. The dataset includes (a) a full geolocated exposure model with all pertinent critical assets, namely tanks, pressure vessels, process towers, chimneys, equipment-supporting buildings, and a flare; (b) the corresponding record-wise asset demands and summarized fragilities derived via nonlinear dynamic analyses on reduced-order numerical models.</span></p>
Figure 3 in America's Most Wanted Fishes: cataloging risk assessments to prioritize invasive species for management action
Figure 3. The proportion of risk statuses of fish families with four or more species assessed at the extent of Florida. Panel (A) shows the proportion of species with high, moderate, low, multiple, and undetermined risk statuses of assessed species (total number of species evaluated in a family). Panel (B) shows the ratio of assessed to unassessed species in a given family (total species in a family). Total species in a family were obtained from FishBase (Froese and Pauly 2023).
Figure 1 in America's Most Wanted Fishes: cataloging risk assessments to prioritize invasive species for management action
Figure 1. The proportion of risk statuses of fish families with four or more species assessed at the extent of the conterminous U.S. Panel (A) shows the proportion of species with high, moderate, low, multiple, and undetermined risk statuses of assessed species (total number of species evaluated in a family). Panel (B) shows the ratio of assessed to unassessed species in a given family (total species in a family). Total species in a family were obtained from FishBase (Froese and Pauly 2023).
Figure 2 in America's Most Wanted Fishes: cataloging risk assessments to prioritize invasive species for management action
Figure 2. The proportion of risk statuses of fish families with four or more species assessed at the extent of the Great Lakes region. Panel (A) shows the proportion of species with high, moderate, low, multiple, and undetermined risk statuses of assessed species (total number of species evaluated in a family). Panel (B) shows the ratio of assessed to unassessed species in a given family (total species in a family). Total species in a family were obtained from FishBase (Froese and Pauly 2023).
Data from: In vitro to in vivo extrapolation from three-dimensional hiPSC-derived cardiac microtissues and physiologically based pharmacokinetic modeling to inform next-generation arrythmia risk assessment
<p>Proarrhythmic cardiotoxicity remains a substantial barrier to drug development as well as a major global health challenge. <em>In vitro</em> human pluripotent stem cell-based new approach methodologies have been increasingly proposed and employed as alternatives to existing <em>in vitro</em> and <em>in vivo</em> models that do not accurately recapitulate human cardiac electrophysiology or cardiotoxicity risk. In this study, we expanded the capacity of our previously established three-dimensional human cardiac microtissue model to perform quantitative risk assessment by combining it with a physiologically based pharmacokinetic model, allowing a direct comparison of potentially harmful concentrations predicted <em>in vitro</em> to <em>in vivo</em> therapeutic levels. This approach enabled the measurement of concentration responses and margins of exposure for two physiologically relevant metrics of proarrhythmic risk (<em>i.e.</em>, action potential duration and triangulation assessed by optical mapping) across concentrations spanning three orders of magnitude. The combination of both metrics enabled accurate proarrhythmic risk assessment of four compounds with a range of known proarrhythmic risk profiles (<em>i.e., </em>quinidine, cisapride, ranolazine, and verapamil) and demonstrated close agreement with their known clinical effects. Action potential triangulation was found to be a more sensitive metric for predicting proarrhythmic risk associated with the primary mechanism of concern for pharmaceutical-induced fatal ventricular arrhythmias, delayed cardiac repolarization due to inhibition of the rapid delayed rectifier potassium channel, or hERG channel. This study advances human induced pluripotent stem cell-based three-dimensional cardiac tissue models as new approach methodologies that enable <em>in vitro</em> proarrhythmic risk assessment with high precision of quantitative metrics for understanding clinically relevant cardiotoxicity.</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.