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126,115 results for “Patients”
Identification of immune-related candidate biomarkers in plasma of patients with sporadic vestibular schwannoma
<p>Vestibular schwannoma (VS) is an intracranial tumor arising from neoplastic Schwann cells, and typically presenting with hearing loss. The traditional belief that hearing deficit is caused by physical expansion of the VS, compressing the auditory nerve, does not explain the common clinical finding that patients with small tumors can have profound hearing loss, suggesting that tumor-secreted factors could influence hearing ability in VS patients. We conducted profiling of patients' plasma for 66 immune-related factors in patients with sporadic VS (N>170) and identified and validated candidate biomarkers associated with tumor size (S100B) and hearing (MCP-3). We further identified a 9-biomarker panel (TNR-R2, MIF, CD30, MCP-3, IL-2R, BLC, TWEAK, eotaxin, S100B) with outstanding discriminatory ability for VS. These findings revealed possible therapeutic targets for VS, providing a unique diagnostic tool that may predict hearing change and tumor growth in VS patients, and may inform the timing of tumor resection to preserve hearing.</p>
Host biomarkers and combinatorial scores for the detection of serious and invasive bacterial infection in pediatric patients with fever without source
<h3><span>Background </span></h3> <p><span>Improved tools are required to detect bacterial infection in children with fever without source (FWS), especially when younger than 3 years old. The aim of the present study was to investigate the diagnostic accuracy of a host signature combining for the first time two viral-induced biomarkers, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and interferon </span><span>γ</span><span>-induced protein-10 (IP-10), with a bacterial-induced one, C-reactive protein (CRP), to reliably predict bacterial infection in children with fever without source (FWS) and to compare its performance to routine individual biomarkers (CRP, procalcitonin (PCT), white blood cell and absolute neutrophil counts, TRAIL, and IP-10) and to the Labscore.</span></p> <h3><span>Methods</span></h3> <p><span>This was a prospective diagnostic accuracy study conducted in a single tertiary center in children aged less than 3 years old presenting with FWS. Reference standard etiology (bacterial or viral) was assigned by a panel of three independent experts. Diagnostic accuracy (AUC, sensitivity, specificity) of host individual biomarkers and combinatorial scores was evaluated in comparison to reference standard outcomes (expert panel adjudication and microbiological diagnosis). </span></p> <h3><span>Results </span></h3> <p><span>241 patients were included. 68 of them (28%) were diagnosed with a bacterial infection and 5 (2%) with invasive bacterial infection (IBI). Labscore, ImmunoXpert, and CRP attained the highest AUC values for the detection of bacterial infection, respectively 0.854 (0.804–0.905), 0.827 (0.764–0.890), and 0.807 (0.744–0.869). Labscore and ImmunoXpert outperformed the other single biomarkers with higher sensitivity and/or specificity and showed comparable performance to one another although slightly reduced sensitivity in children < 90 days of age.</span></p> <h3><span>Conclusion </span></h3> <p><span>Labscore and ImmunoXpert demonstrate high diagnostic accuracy for safely discriminating bacterial infection in children with FWS aged under and over 90 days, </span><span>supporting their adoption in the assessment of febrile patients. </span></p>
Multi-breath 4DCT images of lung cancer patients
<p><strong>Multi-breath 4DCT images of six non-small cell lung cancer (NSCLC) patients.</strong></p><p>Breathing motion has been transferred across longitudinal imaging to generate new 4DCT images sampling five consecutive breaths.</p><p>This dataset is the result of processing six subjects selected from the 4D-Lung dataset published in The Cancer Imaging Archive: <a href="https://doi.org/10.7937/K9/TCIA.2016.ELN8YGLE">https://doi.org/10.7937/K9/TCIA.2016.ELN8YGLE </a>Hugo et al. (2016).</p><p>Data generated within the project "New concept for adaptive real time tumour tracking" funded by the Swiss National Science Foundation (SNSF) under grant agreement 200021_185082: <a href="https://data.snf.ch/grants/grant/185082">https://data.snf.ch/grants/grant/185082</a> </p><p> </p>
IMBALANCED MACHINE LEARNING CLASSIFICATION MODELS FOR REMOVAL BIOSIMILAR DRUGS AND INCREASED ACTIVITY IN PATIENTS WITH RHEUMATIC DISEASES
<p>Objective: Predict long-term disease worsening and the removal of biosimilar medication in patients with rheumatic diseases.</p><p>Methodology: Observational, retrospective, and descriptive study. Review of a database of patients with immune-mediated inflammatory rheumatic diseases. Disease worsening and removing biosimilars are imbalanced variables, that require using imbalanced machine learning models selected based on their superior f1-scores and great accuracy. Previously, we selected the most important variables using mutual information tests.</p><p>Results: The best imbalanced machine learning models to predict disease worsening and the removal of the biosimilar obtained f1-scores of 0.52 and 0.63, respectively. Both models are decision trees. In the first one, two important factors are switching of biosimilar and age, and in the second, the relevant variables are optimization and the value of the initial CRP. </p><p>Conclusions: Biosimilar drugs do not always work well for rheumatic diseases. We obtained two imbalanced machine learning models to detect those cases, where the drug should be removed or where the activity of the disease increases from low to high. Our decision trees use variables, such as age or switching, not considered in previous studies.</p>
Quality of life for patients with cutaneous leishmaniasis: a comparative analysis of the EQ-5D-3L and CLIQ questionnaires.
<p>This dataset contains quality of life surveillance results for patients with cutaneous leishmaniasis, Brazil, focusing in a comparative analysis of the EQ-5D-3L and CLIQ questionnaires.</p>
Effect of Digoxin on clusters of circulating tumor cells in patients with metastatic breast cancer: a phase 1 trial
<p>This repository contains processed transcriptomics data, large data sets and additional files required to reproduce the code available at the repository https://github.com/TheAcetoLab/dicct-trial</p>
A potential patient stratification biomarker for Parkinson´s disease based on LRRK2 kinase-mediated centrosomal alterations in peripheral blood-derived cells
<p>Annotated WES VCF file and phenotype file used in Gene burden analysis of Naaldijk et al., "A potential patient stratification biomarker for Parkinson´s disease based on LRRK2 kinase-mediated centrosomal alterations in peripheral blood-derived cells", 2023. </p><p> </p>
Single-cell RNA sequencing reveals dysregulated cellular programs in the inflamed epithelium of Crohn's disease patients.
<p><strong>Crohn’s disease (CD) is a complex inflammatory disorder of incompletely understood molecular aetiology. We generated a large single-cell RNA sequencing dataset from the terminal ileal biopsies of two independent cohorts comprising a total of 50 CD patients and 71 healthy controls. We performed transcriptomic analyses to reveal genes, cell types and mechanisms perturbed in CD, leveraging the power of the two cohorts to confirm our findings and assess replicability. In addition to mapping widespread alterations in cytokine signalling, we provide evidence of pan-epithelial upregulation of MHC class I genes and pathways in CD. Using non-negative matrix factorization we revealed intra- and inter-cellular upregulation of expression programs such as G-protein coupled receptor signalling and interferon signalling, respectively, in CD. We observed an enrichment of CD heritability among marker genes for various activated T cell types and myeloid cells, supporting a causal role for these cell-types in CD aetiology. Comparisons between our discovery and replication cohort revealed significant variation in differential gene-expression replicability across cell types. B, T and myeloid cells showed particularly poor replicability, suggesting caution should be exercised when interpreting unreplicated differential gene-expression result in these cell types. Overall, our results provide a rich resource for identifying cell-type specific biomarkers of Crohn’s disease and identifying genes, cell types and pathways that are causally and replicably associated with disease.</strong></p>
Predictors of hypertension among diabetic patients in the Ejisu Municipality of Ghana
<p><strong>Introduction: </strong>The co-existence of hypertension with diabetes mellitus among diabetic patients is a setback to public health. About 40–75% of diabetic patients present with hypertension. The co-existence of hypertension and diabetes can accelerate complications such as stroke, myocardial infarction, nephropathy, and mortality. Available data indicate the devastating effects of hypertension and diabetes on individuals, families, and the economy as catastrophic. Therefore, knowing the predictors of hypertension among diabetic patients would inform the lifestyle and management of the two conditions.</p> <p><strong>Objective:</strong> The study focused on predictors of hypertension among diabetic patients in the Ejisu Municipality of Ghana.</p> <p><strong>Methods: </strong>The study employed a quantitative approach with a sample size of 120. Data were collected on sociodemographic characteristics, family history, 24-hour dietary recall, blood pressure, fasting blood glucose, glycated haemoglobin, total lipid profile, and anthropometrics. Data were analyzed using SPSS version 27.</p> <p><strong>Results:</strong> Out of 120 respondents, 85% were females with 77.5% above 50 years of age. A majority (66.7%) had a family history of diabetes with 76.7% having hypertension as a comorbidity. Fasting blood glucose was found to be 8.519 times more likely to present with hypertension. Systolic blood pressure, carbohydrate, and sodium intakes were 6.1%, 2.9%, and 0.1% respectively. However, diabetic patients with high HbA1c were 97% less likely not to present with hypertension.</p> <p><strong>Conclusion:</strong> Hypertension was found to be the most common comorbidity among diabetic patients in Ghana. Glycaemic control, systolic blood pressure, and dietary factors specifically carbohydrate and sodium intake were significant predictors of hypertension among the study participants.</p>
Data from: Pre- and post- treatment fold change plasma proteomics in metastatic NSCLC patients
<p>Blood plasma samples were collected from advanced-stage NSCLC patients as part of a clinical study (PROPHETIC; NCT04056247). All clinical sites received IRB approval for the study protocol. Patient blood samples were drawn at baseline (referred to as T0) and, on average, 4 weeks after the treatment commenced, prior to the second dose of treatment (referred to as T1). Blood samples were drawn into tubes containing EDTA as an anticoagulant, and plasma was separated from the whole blood. The protocol adheres to the Clinical and Laboratory Standards Institute (CLSI) guidelines.</p>
Prediction of mechanistic subtypes of Parkinson's using patient-derived stem cell models
<p>Data and pipelines used to predict mechanistic subtypes of Parkinson's disease using patient-derived stem cell model.</p> <p><strong>Lists of files included;</strong></p> <ul> <li>chemPredPD2022_Imaging process pipelines: pipelines to extract tabular data in Columbus Image Data Storage and Analysis System</li> <li>demo_data_images: a set of data for the Demo</li> <li>ImageData</li> <li>TabularData</li> <li>New test data_PINK1_isoCTRL</li> <li>New test data_SNCA_isoCTRL</li> <li>Tabular_demo_data</li> </ul>
In silico database of ~500 000 virtual patients with diverse cardiovascular disease
<p>The presented dataset contains a large virtual cohort of more than 50'000 heart failure patients characterized by realistic traces of volumes, pressures, flows, and regional mechanics. We used the well-established CircAdapt model <a href="https://www.circadapt.org/">(https://www.circadapt.org/</a> , <a href="http://framework.circadapt.org/">http://framework.circadapt.org/</a>) of the human heart and circulation to simulate a large cohort of virtual patients, covering a wide range of HF-related disease heterogeneity and severity. <br>In the construction of virtual patients, generating a variety of parameter sets for the initial population is essential and can be accomplished using various sampling techniques. In our investigation, we utilized the Sobol-low discrepancy sequence to ensure uniformity across the high-dimensional parameter space. For a more detailed explanation please refer to the document <em>"MARCIUS_deliverable_D1.5_VirtualDatabase.pdf"</em></p> <p><strong>Acknowledgments:</strong> This work was supported by the European Union's Horizon 2020 Research and Innovation program under the Marie Skłodowska-Curie grant agreement No. 86074, <strong>"MARCIUS - MARie Curie Intelligent UltraSound"(<a href="https://www.marcius-project.com/">https://www.marcius-project.com/</a>)</strong>. MARCIUS rationale was to develop a comprehensive in silico simulation platform comprising both the generation of virtual patients (<em>presented dataset</em>) and their associated realistic image data. Such approach would make it possible to learn the most relevant patterns within a wide representative set of patients to lead the training of ML-based image processing algorithms in order to analyze real-world clinical data.</p> <p> </p>
Figure 1. A in Prevalence and density of Demodex mites (Acari: Demodecidae) in patients with seborrheic dermatitis
Figure 1. A. Demodex spp. (at 40x magnification), B. D. folliculorum (at 40x magnification.
Diagnostic and prediction value of synthetic magnetic resonance imaging in acute ischemic stroke patients
<p>This is the supplementary tables for the above paper, mainly including original statistical analysis data.</p>
A Dataset for Inertial Measurements of Scoliotic Patients during Timed-Up and Go Tests in Unbraced and Braced Scenarios
<p>Repository composition:</p> <p>*** Dataset ***</p> <p>Anonymous data pertaining to each participant is stored in a single folder, named S##. </p> <p>Each of these folders contains the following:</p> <p>1) Raw IMU data from the G-Walk sensor (3-axis acceleration, 3-axis gyroscope, 3-axis magnetometer) recorded during the Timed-Up and Go tests in .txt files. Specifically, the 3 experimental conditions are "Unbraced", "Conventional" and "3DPrinted". Each condition was recorded three times (01, 02, 03).</p> <p>2) A .xlsx file named "TUG_Metrics" with the values of the TUG metrics for each condition.</p> <p>3) A .xlsx file named "Segmentation_Times" with the start and end timepoints of the TUG phases for each condition.</p> <p>*** Boxplot ***</p> <p>This is a folder containing boxplots in .png files for each TUG metric, comparing the three experimental conditions.</p> <p>*** Histogram ***</p> <p>This is a folder containing histograms in .png files for each TUG metric, comparing the three experimental conditions.</p> <p>*** QQ Plot ***</p> <p>This is a folder containing qq-plots in .png files for each TUG metric, comparing the three experimental conditions.</p>
Effectiveness of Mannitol Use on Clinical Outcomes of Severe Traumatic Brain Injury Patients
<p>Dataset for manuscript entitled: </p> <p><span>Effectiveness of Mannitol Use on Clinical Outcomes of Severe Traumatic Brain Injury Patients</span></p>
Processed OLINK serum proteomics data MIS-C patients versus healthy controls
<p>This dataset contains processed OLINK serum proteomics data MIS-C patients versus healthy controls. Data was generated by Diorio et al. (Diorio, C., Shraim, R., Vella, L.A. <em>et al.</em> Proteomic profiling of MIS-C patients indicates heterogeneity relating to interferon gamma dysregulation and vascular endothelial dysfunction. <em>Nat Commun</em> <strong>12</strong>, 7222 (2021). https://doi.org/10.1038/s41467-021-27544-6). Processing in format provided here was done by dr. Levi Hoste. This table is used in the MultiNicheNet package (https://github.com/saeyslab/multinichenetr) and mentioned in the updated corresponding manuscript. </p>
Determinants of Disease Progression in Bangladeshi COVID-19 Patients: A Cross-sectional Survey
<p>This was a nationwide study of COVID-19 patients who were diagnosed and confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) from Nov 2020 to April 2021. The list of available COVID-19 positive patients was obtained, after formal written approval, from Civil Surgeon’s (CS) offices in Bangladesh. </p>
Raw data for Figures 1-4 for journal article: "Transcutaneous and percutaneous bone conduction sound propagation in single-sided deaf patients and cadaveric human whole heads"
<p>This is a data set containing the raw data for figures 1-4 from the journal article:</p> <p>"Transcutaneous and percutaneous bone conduction sound propagation in single-sided deaf patients and cadaveric human whole heads"</p> <p>Original article DOI: 10.1080/14992027.2021.1903586</p> <p>Original article link: https://pubmed.ncbi.nlm.nih.gov/34097554/</p> <p> </p> <p>The data is contained within plots in word files, created with Microsofft Office (v18).</p>
Splicing-Aware Patient Stratification Using Different Biclustering Methods
<div> <div> <div> <p>Patient stratification refers to the process of categorizing patients into specific groups based on whether they exhibit certain characteristics of a disease. In this research, we investigated the feasibility of splicing-aware measurements for patient stratification in complex diseases like breast cancer and dilated cardiomyopathy.</p> <p>Splicing-aware patient stratification integrates the intricate dynamics of RNA splicing with the stratification of patients in clinical settings. The significance of this approach lies in its potential to revolutionize personalized medicine by offering more precise and effective treatment strategies. To execute our research, we collected datasets at three levels: genomic, transcrip- tomic, and isoform-specific expressions for both breast cancer and dilated cardiomyopathy. We applied network-constrained (BiCoN) and unconstrained (MoSBi) biclustering algorithms to classify individuals into subtypes. Here, we show that working not just with transcripts but with dominant isoforms of transcripts and different measurements can unveil new information. We took the dominant isoform of transcripts by a median of expression into account to examine the splicing effect. Despite various factors, we included in our research, both BiCoN and MoSBi appeared more efficient on the gene level. We observed that different biclustering methods or approaches work differently in both diseases and also on different levels in each disease.</p> <p>With our results, we aim to shed light on the potential applications of alternative splicing analysis for disease subtyping.</p> </div> </div> </div>
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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.