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2,079 results for “prognostics”
Dataset for the paper "Prolonged prothrombin time as an early prognostic indicator of severe acute respiratory distress syndrome in patients with COVID-19 related pneumonia"
<p>The dataset contains the data on ICU-transferred (N=100) and Stable (N=131) patients with COVID-19 (N=156) and Non-COVID-19 viral pneumonia (N=75). Among COVID-19 patients of this study, 82 patients developed Refractory Respiratory Failure (RRF) or Severe Acute Respiratory Distress Syndrome (SARDS) and were transferred to Intensive Care Unit (ICU), 74 patients had a Stable course of disease and were not transferred to ICU. Collected data are presented as a table with columns:<br> - Gender;<br> - Age (years);<br> - SARS-CoV-2 RT-PCR testing results;<br> - Time between the disease onset and admission to the hospital (days);<br> - Time between admission to the hospital and transfer to ICU (days);<br> - Artificial lung ventilation in ICU needed;<br> - C-reactive protein (CRP) upon admission (mg/L);<br> - International Normalized Ratio (INR) upon admission;<br> - Prothrombin Time (PT) upon admission (sec.);<br> - Fibrinogen upon admission (mg/L);<br> - Chest Computed Tomography (CT) upon admission: lung tissue affected (%);<br> - Platelet count upon admission (10^9/L);<br> - Chest CT, 1 week after admission: lung tissue affected (%);<br> - CRP, 1 week after admission (mg/L);<br> - Platelet count, 1 week after admission (10^9/L).</p>
Supplementary files for Molecular Differences Between Squamous Cell Carcinoma and Adenocarcinoma Cervical Cancer Subtypes: Potential Prognostic Biomarkers
<p>Supplementary files for Molecular Differences Between Squamous Cell Carcinoma and Adenocarcinoma Cervical Cancer Subtypes: Potential Prognostic Biomarkers</p>
Data from: External validation of prognostic and predictive gene signatures in 1097 European head and neck squamous cell carcinoma patients
<p><span>Anonymized data containing survival endpoints and gene signature scores for head and neck cancer patients.</span></p> <p><span>File <strong>data_os_gs.csv</strong> : data linking overall survival and gene signature scores</span></p> <p><span>File <strong>data_dfs_gs.csv</strong> : data linking disease-free survival and gene signature scores</span></p> <p><span><strong>Variables</strong>:</span></p> <ul> <li><span><em>supertreat_id</em>: patient ID</span></li> <li><span><em>GS_score_172GS</em>: gene signature score for the <em>172-GS</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_3clustersHPV</em>: gene signature score for the <em>3 clusters HPV</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_RSI</em>: gene signature score for the <em>radiosenstivity index (RSI) </em>signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_pancancerCisplatin</em>: gene signature score for the <em>pancancer-cisplatin</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_cl3Hypoxia</em>: gene signature score for the <em>Cl3-hypoxia</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span>Variables only available in <strong>data_os_gs.csv: </strong></span> <ul> <li><span><em>overall_survival_days_2years</em>: Overall survival censored at 2 years since diagnosis. Number of days from diagnosis to death or censoring.</span></li> <li><span><em>overall_survival_days_5years</em>: Overall survival censored at 5 years since diagnosis. Number of days from diagnosis to death or censoring.</span></li> <li><span><em>overall_survival_status_2years</em>: Overall survival status when censored at 2 years since diagnosis. Coded as 0 if censored, and 1 if dead. </span></li> <li><span><em>overall_survival_status_5years</em>: Overall survival status when censored at 5 years since diagnosis. Coded as 0 if censored, and 1 if dead. </span></li> </ul> </li> </ul> <ul> <li><span>Variables only available in <strong>data_dfs_gs.csv:</strong></span> <ul> <li><span><em>disease_free_survival_days_2years</em>: Disease-free survival censored at 2 years since diagnosis. Number of days from diagnosis to an event (death or cancer recurrence) or censoring.</span></li> <li><span><em>disease_free_survival_days_5years</em>: Disease-free survival censored at 5 years since diagnosis. Number of days from diagnosis to an event (death or cancer recurrence) or censoring.</span></li> <li><span><em>disease_free_survival_status_2years</em>: Disease-free survival status when censored at 2 years since diagnosis. Coded as 0 if censored, and 1 if an event (death or recurrence). </span></li> <li><span><em>disease_free_survival_status_5years</em>: Disease-free survival status when censored at 5 years since diagnosis. Coded as 0 if censored, and 1 if an event (death or recurrence). </span></li> </ul> </li> </ul>
Meta analysis of prognostic scoring systems for pancreatitis
Open the record for dataset details and reuse information.
Identification of Genes Regulating Dexamethasone Resistance and Prognostic Model Development in Acute Lymphoblastic Leukemia
<p>This study investigates the mechanisms of dexamethasone resistance in acute lymphoblastic leukemia (ALL) and presents a prognostic model to predict patient outcomes and immunotherapy responses. By analyzing gene expression data, we identified autophagy-related genes associated with dexamethasone resistance, particularly focusing on STK38L’s role in modulating autophagy via ULK1. Our results reveal that high STK38L expression enhances dexamethasone resistance by promoting autophagy markers LC3II/LC3I and beclin-1. This study provides valuable insights into the molecular basis of dexamethasone resistance and highlights STK38L as a potential biomarker and therapeutic target for improving ALL treatment strategies.</p>
Data for the "Does prognostic seeding along flight tracks produce the desired effects of cirrus cloud thinning?" manuscript
<p>Tar file of the data used to prepare the plots and write the text in: "Does prognostic seeding along flight tracks produce the desired effects of cirrus cloud thinning?" manuscript for submission to ACP.</p> <p>A description of each netcdf file is provided in the README file. The format of each file is in netcdf4</p>
Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment
<p>We uploaded the raw data related to extracted features of the manuscript "Granata V, Fusco R, De Muzio F, Brunese MC, Setola SV, Ottaiano A, Cardone C, Avallone A, Patrone R, Pradella S, Miele V, Tatangelo F, Cutolo C, Maggialetti N, Caruso D, Izzo F, Petrillo A. Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment. Radiol Med. 2023 Nov;128(11):1310-1332. doi: 10.1007/s11547-023-01710-w. Epub 2023 Sep 11. PMID: 37697033."</p>
Dataset: Sera Prognostics, Inc. (SERA) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset for "Validation of a Prognostic Staging for Metastatic Uveal Melanoma: A Collaborative Study of the European Ophthalmic Oncology Group"
<p>Raw data corresponding to the paper entitled: "<strong>Validation of a Prognostic Staging for Metastatic Uveal Melanoma: A Collaborative Study of the European Ophthalmic Oncology Group</strong><strong>" </strong>published in <em>Am. J. Ophthalmol.</em> 2016 Aug;168:217-226 by Kivelä <em>et al.</em></p>
Spatially Resolved Transcriptomics Deconvolutes Prognostic Histological Subgroups in Patients with Colorectal Cancer and Synchronous Liver Metastases
<p>Spatial transcriptomic data (counts.csv) derived using the Nanostring GeoMx digital spatial profiler platform to analyse matched colonic primary and liver metastases from 4 patients with metastatic colorectal cancer. 48 AOIs of cancer transcriptome atlas data. Normalised using Q3 normalisation. In addition, normalised data (Counts - ncounter.csv) from ncounter bulk experiment comparing matched colonic primary and liver metastases</p>
"PROGNOSTIC ROLE OF TUMOR BUDDING IN ORAL SQUAMOUS CELL CARCINOMA"
<p>Master Data Sheet</p>
Data for the publication "Significant Increase in Graupel and Lightning Occurrence in a Warmer Climate Simulated by Prognostic Graupel Parameterization"
<p>This dataset includes a set of 11yr simulations using the MIROC6 global aerosol-climate model under the pre-industrial (PI, aerosol emission at the year 1850), present-day (PD, aerosol emission at the year 2000), and future warming (SST+4K, a uniform 4 K increase in sea surface temperature) conditions.</p> <p>The data are used in the manuscript entitled "Significant Increase in Graupel and Lightning Occurrence in a Warmer Climate Simulated by Prognostic Graupel Parameterization".</p>
Dataset on prognostic factors in patients with metastatic castration-resistant prostate cancer undergoing radioligand therapy with [177Lu]Lu-PSMA-617
<p>This upload provides Open Data associated with the publication "Prognostic value of the De Ritis ratio for overall survival in patients with metastatic castration-resistant prostate cancer undergoing [<sup>177</sup>Lu]Lu-PSMA-617 radioligand therapy" by Gaal S <em>et al.</em> (2023).</p> <p>The upload contains the anonymized dataset of 91 patients analyzed in this publication with all variables that are required to reproduce the results.</p> <p>However, to fully comply with requirements for data anonymization, the patients' age was categorized into groups spanning 5 years each. A dataset with the age variable in exact years can be obtained from the corresponding author (julian.rogasch@charite.de) upon reasonable request.</p> <p>Besides the dataset, this upload provides a dictionary to explain all variables and their categories.</p>
Data from: Validation of serum neurofilaments as prognostic & potential pharmacodynamic biomarkers for ALS
<p><span><span><span><span><span><span><span><span><span><span><span><u>Objective</u>. Identify preferred neurofilament assays, and clinically validate serum NfL and pNfH as prognostic and potential pharmacodynamic biomarkers relevant to ALS therapy development. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><u>Methods</u>. Prospective, multi-center, longitudinal observational study of patients with ALS (n=229), primary lateral sclerosis (PLS, n=20) and progressive muscular atrophy (PMA, n=11). Biological specimens were collected, processed and stored according to strict standard operating procedures (SOPs) <sup>1</sup>. Neurofilament assays were performed in a blinded manner by independent contract research organizations (CROs). </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><u>Results</u>. For serum NfL and pNfH measured using the Simoa assay, there were no missing data (i.e. both technical replicates below the lower limit of detection were not encountered). For the Iron Horse and Euroimmun pNfH assays, such missingness was encountered in ~4% and ~10% of serum samples respectively. Mean coefficients of variation (CVs) for pNfH in serum and CSF were ~4-5% and ~2-3% respectively in all assays. Baseline NfL concentration, but not pNfH, predicted the future ALSFRS-R slope and survival. Incorporation of baseline serum NfL into mixed effects models of ALSFRS-R slopes yields an estimated sample size saving of ~8%. Depending on the method used to estimate effect size, use of serum NfL (and perhaps pNfH) as pharmacodynamic biomarkers, instead of the ALSFRS-R slope, yields significantly larger sample size savings.</span></span></span></span></span></span></span></span></span></span></span></p> <p><u>Conclusions</u><span><span><span><span><span><span><span><span><span><span><span>. Serum NfL may be considered a clinically validated prognostic biomarker for ALS. Serum NfL (and perhaps pNfH), quantified using the Simoa assay, have potential utility as pharmacodynamic biomarkers of treatment effect. </span></span></span></span></span></span></span></span></span></span></span></p>
Dataset - PONE-D-20-09507 - Usefulness of circulating miR-146a and miR-16-5p microRNAs as prognostic biomarkers in community-acquired pneumonia
<p>This dataset shows a prospective observational study performed in a cohort of 153 patients admitted to hospital with CAP.</p> <p>Clinical and analytical variables were collected, and the main outcome variable was 30-day mortality.</p> <p>Small RNA was purified from patients´ plasma samples by column-based protocol, and retrotranscribed to cDNA (Exiqon's miRCURY ™ series kits), adding synthetic RNA controls (spike-in). The quality of the process was evaluated (QC control) and only 117 samples passed the test.</p> <p>FIRST STEP: Eight samples paired by age and gender were selected (4 patients who had suffered a cardiovascular event or death during follow-up and 4 who had not) and a panel of 752 human miRNAs was tested (miRCURY LNA ™ Universal - Ready-to-Use Human Panel , Exiqon), in order to determine a preliminary pattern of differential miRNA expression between patients with different CAP evolution.</p> <p>SECOND STEP: According to the preliminary data obtained, 25 candidate miRNAs were selected: 5 intended to be used as normalizers, 5 selected by statistical criteria (univariate association with mortality) and 15 selected from an exhaustive bibliographic search on miRNAs, sepsis, inflammation and / or cardiovascular disease, prioritizing those that appeared in a greater number of publications and those related to respiratory diseases. RT-PCR was carried out by hybridization with double-stranded flurochrome (ExiLENT SYBR® Green Master Mix) using the C1000 Touch CFX384 thermocycler (Bio-Rad).</p> <p>The relative amount of each miRNA was calculated with ∆Ct = CtmiRNA - CtUniSp2, and it was later normalized using the GeNorm algorithm. The final data was calculated with the formula 2<sup>-∆Ct</sup> and the values were expressed as the fold change (FC) of each miRNA with respect to UniSP2<em>.</em></p>
2DVD dataset for GMD publication - Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign
<p>This archive contains the 2DVD measurement of graupel particles used in the GMD paper "Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign".</p><p>For each identified graupel particle, the following are included:</p><ul><li>Volume-equivalent diameter (mm)</li><li>Density (g cm-3)</li><li>Fall velocity (m s-1)</li></ul>
Data accompanying the paper "Stable Numerical Implementation of a Turbulence Scheme with Two Prognostic Turbulence Energies".
<p>Data accompanying the paper <strong>"Stable Numerical Implementation of a Turbulence Scheme with Two Prognostic Turbulence Energies",</strong> submitted to Monthly Weather Review.</p> <p>This repository contains results from the idealized simulations of GABLS1 case,<br> obtained by the OpenIFS single column model version with the TOUCANS two-energy<br> turbulence scheme.</p> <p>Each simulation has its own folder, containing single NetCDF file 'progvar.nc'.<br> Experimental settings, explained in the paper, are following:</p> <pre><code>----------------------------------------------------------------- folder timestep delta beta beta_tau [s] [1] [1] [1] ----------------------------------------------------------------- GABLS1_2TE-R_dt001s_delta00_bt15/ 1 0.00 1.0 1.5 GABLS1_2TE-R_dt045s_delta00_bt15/ 45 0.00 1.0 1.5 GABLS1_2TE-R_dt090s_delta00_bt15/ 90 0.00 1.0 1.5 ----------------------------------------------------------------- GABLS1_2TE-R_dt090s_delta25_bt15/ 90 0.25 1.0 1.5 GABLS1_2TE-R_dt090s_delta25_bt10/ 90 0.25 1.0 1.0 GABLS1_2TE-R_dt180s_delta25_bt10/ 180 0.25 1.0 1.0 -----------------------------------------------------------------</code></pre> <p>Names of the NetCDF fields examined in the paper are:</p> <pre><code>tke - turbulence kinetic energy [J/kg] tte - turbulence total energy [J/kg] efb3 - turbulent heat flux [W/m^2] t - thermodynamic temperature [K] </code></pre> <p>They are all 2D fields, indexed by the timestep number and the model level.<br> Turbulent heat flux is given on the model half levels, remaining quantities<br> on the model full levels. Heights of the model levels are stored in the<br> NetCDF fields:</p> <pre><code>height_f - full level heights [m] height_h - half level heights [m] </code></pre> <p>Simulation time in seconds is stored in the NetCDF field 'time'.</p> <p><strong>CAUTION:</strong><br> Since the simulations were run with the prescribed forcings and only with<br> the turbulence scheme activated, some fields in NetCDF files are meaningless<br> (e.g. skin temperature).</p>
PD1+CD8+ cells are an independent prognostic marker in patients with head and neck cancer
<p><strong>Data open:</strong> file with parametres used for the multivariate evaluation. </p>
Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia
<p><span><strong>Background</strong>:</span><span> Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. Although the treatment landscape for CLL is rapidly evolving, there are still some patients who remain drug resistance or disease refractory. Ferroptosis is a type of lipid peroxidation-induced cell death and has been suggested with a prognostic value in several cancers. Our research aims to build a prognostic model to improve risk stratification in CLL patients and facilitate more accurate assessment for clinical management.</span></p> <p><span><strong>Methods</strong>: </span><span>The differentially expressed ferroptosis-related genes (</span><span>FRGs) in CLL were filtered through univariate Cox regression analysis based on public databases. Least Absolute Shrinkage and Selection Operator (LASSO) Cox algorithms were performed to construct a prognostic risk model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were performed to estimate the immune infiltration score and immune-related pathways. A total of thirty-six CLL patients in our center were enrolled in this study as a validation cohort. Moreover, a nomogram model was established to predict the prognosis.</span></p> <p><span><strong>Results</strong>: </span><span>A total of differentially expressed 15 FRGs with prognostic significance were screened out. After minimizing the potential risk of overfitting, we constructed a novel ferroptosis-related prognostic score (FPS) model with nine FRGs (AKR1C3, BECN1, CAV1, CDKN2A, CXCL2, JDP2, SIRT1, SLC1A5 and SP1), and stratified patients into low-risk and high-risk groups. Kaplan–Meier analysis showed that patients with high FPS had worse overall survival (OS) (P<0.0001) and treatment-free survival (TFS) (P<0.0001). ROC curves evaluated the prognostic prediction ability of the FPS model. Additionally, the immune cell types and immune-related pathways were correlated with the risk scores in CLL patients. In the validation cohort, the results confirmed </span><span>that the </span><span>high</span><span>-</span><span>risk group was related to worse OS (P<0.0001), progress-free survival (PFS) (P=0.0140) and TFS (P=0.0072). </span><span>In</span><span> the multivariate analysis, only FPS (P=0.011) and CLL-IPI (P=0.010) were independent risk indicators for OS. Furthermore, we established a nomogram including FPS and CLL-IPI which could strongly and reliably predict individual prognosis.</span></p> <p><span><strong>Conclusion</strong>: </span><span>A novel FPS model could be used in CLL for prognostic prediction. The model index may also facilitate the development of new clinical ferroptosis-targeted therapies in patients with CLL.</span></p>
An ssGSEA Based Immune-related Gene Prognostic Signature Combining Immune Infiltration and Immune Checkpoint for Breast Cancer Patients
<p>This is the gene expression and related clinical data of breast cancer patients obtained from TCGA. Original codes and data from GEO database could be found in GitHub via link "https://github.com/Grevilblois/R-codes-for-manuscript".</p>
ScienceDex guides
Understand access before you commit
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.