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68 results for “cause of death”
A human Y334C mutation in selenocysteine synthase causes cardio-respiratory failure and perinatal death in mice which can be rescued by selenium-independent GPX4
GEO Series GSE181852. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing.
Excessive O-GlcNAcylation causes heart failure and sudden death
GEO Series GSE134121. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) study: Causes of death and associated factors over a decade of follow-up in a cohort of HIV-infected adults in rural Tanzania
<p>These are a subset of pseudo-anonymised data from the Kilombero and Ulanga Antiretroviral Cohort (KIULARCO), which were used to analyse causes of death and associated factors among adults. The dataset contains one row for each of the 9871 participants included in this analysis, described further in the data dictionary. KIULARCO has been described in detail previously (see references).</p>
FIGURE 5 in A new species of Podosphaera sect. Sphaerotheca subsect. Sphaerotheca from India-first report of powdery mildew causing wilting and ultimately death of leaves of Filipendula vestita
FIGURE 5. Phylogenetic analysis of the ITS region for 26 sequences from the genus Podosphaera and Cystotheca. Bootstrap values for ML above 50% and Bayesian posterior probabilities support above 0.50 are indicated. Sequence from the collection reported in this study is shown in red.
Loss of cardiomyocyte CYB5R3 impairs redox equilibrium and causes sudden cardiac death
GEO Series GSE206121. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Dataset: Online Learning Module of the "Training Course on Underlying Cause-of-Death Coding – ICD-10'" of the Virtual Learning Environment of the Brazilian Health System
<p><strong>README</strong></p> <p> </p> <p><strong>Dataset name:</strong><em> avasus_dataset.csv </em></p> <p><strong>Version: </strong>1.0 </p> <p><strong>Dataset period:</strong> July 24, 2018 - February 22, 2024</p> <p><strong>Dataset Characteristics: </strong>Multivalued </p> <p><strong>Number of Instances: </strong>1533</p> <p><strong>Number of Attributes: 5</strong></p> <p><strong>Missing Values: </strong>Yes</p> <p><strong>Area(s): </strong>Health and education<strong> </strong></p> <p><strong>Sources: </strong></p> <ul> <li>Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2024a);</li> <li>Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2024d). </li> </ul> <p><strong>Description</strong>:<strong> </strong>The "avasus_dataset.csv" dataset (see Table 1) originates from participants of the "Training Course on Underlying Cause-of-Death Coding – ICD-10". The course was available on the Brazilian National Health System - AVASUS (Brasil, 2024a). This dataset provides elementary data to analyze the course's scope and participant profiles.</p> <p><br><strong>Note</strong>: The dataset's content is provided in Brazilian Portuguese (pt-br), originating from native speakers.</p> <p><strong>Table 1: </strong>Description of AVASUS dataset features. </p> <div> <table> <tbody> <tr> <td> <p><strong>Attributes </strong></p> </td> <td> <p><strong>Description </strong></p> </td> <td> <p><strong>Datatype </strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p><strong>certificate</strong></p> </td> <td> <p>The period in which the course participant obtained the right to a certificate.</p> </td> <td> <p>Datetime</p> </td> <td> <p>year-month-day hours, minutes, and seconds.</p> </td> </tr> <tr> <td> <p><strong>gender </strong></p> </td> <td> <p>Gender of the course participant. </p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Female;</p> </li> <li> <p>Male; or</p> </li> <li> <p>Not informed.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>region</strong></p> </td> <td> <p>Brazilian region in which the participant resides.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>North;</p> </li> <li> <p>Northeast;</p> </li> <li> <p>Central-West;</p> </li> <li> <p>Southeast;</p> </li> <li> <p>South;</p> </li> <li> <p>Abroad; or</p> </li> <li> <p>Not reported.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>course_evaluation</strong></p> </td> <td> <p>A score given to the course by the participant. </p> </td> <td> <p>Numerical</p> </td> <td> <p>0, 1, 2, 3, 4, 5, or NaN.</p> </td> </tr> <tr> <td> <p><strong>evaluation_commentary</strong></p> </td> <td> <p>Comment made by the participant about the course.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Free text or NaN.</p> </td> </tr> </tbody> </table> </div> <p> </p> <p><strong>Dataset name:</strong><em> cbo_dataset.csv </em></p> <p><strong>Version: </strong>1.0 </p> <p><strong>Dataset period:</strong> July 24, 2018 - February 22, 2024</p> <p><strong>Dataset Characteristics: </strong>Multivalued </p> <p><strong>Number of Instances: </strong>1135</p> <p><strong>Number of Attributes: 6</strong></p> <p><strong>Missing Values: </strong>Yes</p> <p><strong>Area(s): </strong>Health and education<strong> </strong></p> <p><strong>Sources: </strong></p> <ul> <li>Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2024a);</li> <li>Brazilian Occupational Classification (CBO) (Brasil, 2024b);</li> <li>National Registry of Health Establishments (CNES) (Brasil, 2024c); </li> <li>Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2024d). </li> </ul> <p><strong>Description</strong>:<strong> </strong>The "cbo_dataset.csv" dataset (see Table 2) originates from participants of the "Training Course on Underlying Cause-of-Death Coding – ICD-10". The course was available on the Brazilian National Health System - AVASUS (Brasil, 2024a). This dataset provides elementary data to analyze the course's scope and the participants' professional profiles.</p> <p><br><strong>Note</strong>: The dataset's content is provided in Brazilian Portuguese (pt-br), originating from native speakers.</p> <p><strong>Table 1: </strong>Description of AVASUS dataset features. </p> <div> <table> <tbody> <tr> <td> <p><strong>Attributes </strong></p> </td> <td> <p><strong>Description </strong></p> </td> <td> <p><strong>Datatype </strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p><strong>gender </strong></p> </td> <td> <p>Gender of the course participant. </p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Female;</p> </li> <li> <p>Male; or</p> </li> <li> <p>Not informed.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>region</strong></p> </td> <td> <p>Brazilian region in which the participant resides.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>North;</p> </li> <li> <p>Northeast;</p> </li> <li> <p>Central-West;</p> </li> <li> <p>Southeast;</p> </li> <li> <p>South;</p> </li> <li> <p>Abroad; or</p> </li> <li> <p>Not reported.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>course_evaluation</strong></p> </td> <td> <p>A score given to the course by the participant. </p> </td> <td> <p>Numerical</p> </td> <td> <p>0, 1, 2, 3, 4, 5, or NaN.</p> </td> </tr> <tr> <td> <p><strong>evaluation_commentary</strong></p> </td> <td> <p>Comment made by the participant about the course.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Free text or NaN.</p> </td> </tr> <tr> <td> <p><strong>CBO_Code</strong></p> </td> <td> <p>Participant's occupation code.</p> </td> <td> <p>Numerical</p> </td> <td> <p>Participant's professional occupation code.</p> </td> </tr> <tr> <td> <p><strong>CBO_Description</strong></p> </td> <td> <p>Textual description of the participant's professional occupation.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Text coded according to the Brazilian Classification of Occupations.</p> </td> </tr> </tbody> </table> </div> <p> </p> <p><strong>REFERENCES</strong></p> <p>Brasil (2024a). AVASUS - Virtual Learning Environment of the Brazilian Health System. Available from: <a href="https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php">https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php</a>. Accessed Jul 8, 2024.</p> <p>Brasil (2024b). CBO - classificação brasileira de ocupações. Available from: <a href="https://cbo.mte.gov.br/cbosite/pages/home.jsf">https://cbo.mte.gov.br/cbosite/pages/home.jsf</a>. Accessed Oct 23, 2024.</p> <p>Brasil (2024c). CNES - cadastro nacional de estabelecimentos de saúde. Available from: <a href="https://cnes.datasus.gov.br/">https://cnes.datasus.gov.br/</a>. Accessed Oct 23, 2024.</p> <p>Brasil (2024d). IBGE - Instituto Brasileiro de Geografia e Estatística. Estimativas da População. Available from: <a href="https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica">https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica</a>. Accessed Jun 19, 2024.</p> <p> </p> <p><strong>ARTICLE:</strong></p> <p>Data Report: Online Learning Module of the ``Training Course on Underlying Cause-of-Death Coding – ICD-10'' of the Virtual Learning Environment of the Brazilian Health System<br> </p> <p><strong>AUTHORS:</strong></p> <p>Aldiney J. Doreto<sup>1,2</sup>, António M. Teixeira<sup>3</sup>, Janaina L. R. S. Valentim<sup>1,4</sup>, João P. Q. Santos<sup>1,4</sup>, Talita K. de B. Pinto<sup>1</sup>, Yluska M. M. B. Mendes<sup>5</sup>, Aline P. Dias<sup>1</sup>, Karla M. D. Coutinho<sup>1,6</sup>, Ednara N. Gonçalves<sup>1</sup>, Andréa S. Pinheiro<sup>1</sup>, Felipe Fernandes<sup>1</sup>, Natalia A. N. Batista<sup>1,7</sup>, Karilany D. Coutinho<sup>1,8</sup>, and Ricardo A. M. Valentim<sup>1,8</sup></p> <p> </p> <p><sup>1</sup>Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil </p> <p><sup>2</sup>University of Minho (UMinho)/Open University of Portugal (UAb), Lisbon, Portugal</p> <p><sup>3</sup>Department of Education and Distance Learning, Open University of Portugal (UAb), Lisbon, Portugal</p> <p><sup>4</sup>Advanced Nucleus for Technological Innovation (NAVI), Federal Institute of Rio Grande do Norte (IFRN), Natal, RN, Brazil</p> <p><sup>5</sup>Secretariat of Health Surveillance and Environment of the Brazilian Ministry of Health, Brasilia, Federal District, Brazil</p> <p><sup>6</sup>Health Sciences Graduate Program, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>7</sup>Social Sustainability and Development Graduate Program, Open University of Portugal, Lisbon, Portugal</p> <p><sup>8</sup>Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, RN, Brazil</p>
The cell death negative regulator, CaRLK1 gene, causes metabolic alterations of pyruvate and alanine via the glyoxylate cycle under hypoxia
GEO Series GSE47671. Nicotiana tabacum. 12 samples. Type: Expression profiling by array.
Pigment Epithelium Derived Factor (PEDF) secreted from iPSC derived-RPE facilitates apoptotic causes cell death, not the differentiation, of iPSCs
GEO Series GSE43257. Homo sapiens. 2 samples. Type: Expression profiling by array.
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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.