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Dataset results
63 results for “lung pathology”
The spatial landscape of lung pathology during COVID-19 progression - raw IMC data
<p>Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19). However thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking. We use high parameter imaging mass cytometry9 targeting the expression of 36 proteins, to investigate at single cell resolution, the cellular composition and spatial architecture of human acute lung injury including SARS-CoV-2. This spatially resolved, single-cell data unravels the disordered structure of the infected and injured lung alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyper-inflammatory cell state associated with lung damage. By leveraging the temporal range of COVID-19 severe fatal disease in relation to the time of symptom onset, we observe increased macrophage extravasation, mesenchymal cells, and fibroblasts abundance concomitant with increased proximity between these cell types as the disease progresses, possibly as an attempt to repair the damaged lung tissue. This spatially resolved single-cell data allowed us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. This spatial single-cell landscape enabled the pathophysiological characterization of the human lung from its macroscopic presentation to the single-cell, providing an important basis for the understanding of COVID-19, and lung pathology in general.</p>
Minimizing Pathologic Aspiration in Patients Undergoing Esophageal and Lung Resections for Cancer
ClinicalTrials.gov study NCT04251312. IPD Sharing: NO. Countries: 1. Publications: 3.
Data and code from: Wide-Angle Lung Experiment Segmentation (WALES): A novel methodology for quantitative assessment of lung pathology in model systems
Open the record for dataset details and reuse information.
Disease trajectories in hospitalized COVID-19 patients are predicted by clinical and peripheral blood signatures representing distinct lung pathologies
<p><span>COVID-19 is characterized by a broad range of symptoms and disease trajectories. Understanding the correlation between clinical biomarkers and lung pathology over the course of acute COVID-19 is necessary to understand its diverse pathogenesis and inform more precise and effective treatments. Here, we present an integrated analysis of longitudinal clinical parameters, peripheral blood biomarkers, and lung pathology in COVID-19 patients from the Brazilian Amazon. We identified core clinical and peripheral blood signatures differentiating disease progression between recovered patients from severe disease and fatal cases. Signatures were heterogenous among fatal cases yet clustered into two patient groups: “early death” (< 15 days of disease until death) and “late death” (> 15 days). Progression to early death was characterized systemically and in lung histopathology by rapid, intense endothelial and myeloid activation/chemoattraction and presence of thrombi, associated with SARS-CoV-2<sup>+</sup> macrophages. In contrast, progression to late death was associated with fibrosis, apoptosis and abundant SARS-CoV-2<sup>+</sup> epithelial cells in post-mortem lung, with cytotoxicity, interferon and Th17 signatures only detectable in the peripheral blood 2 weeks into hospitalization. Progression to recovery was associated with higher lymphocyte counts, Th2 and anti-inflammatory-mediated responses. By integrating ante-mortem longitudinal systemic and spatial single-cell lung signatures, we defined an enhanced set of prognostic clinical parameters predicting disease outcome for guiding more precise and optimal treatments.</span><span> Finally, this study represents a major advance in the investigation of acute respiratory infections by integrating serial clinical data and peripheral blood samples with histopathological and </span><span>spatially-resolved single-cell </span><span>analyses of post-mortem lung samples.</span></p>
The CCUS Based Characteristic of Hemodynamic and Lung Pathology in Early Stage of Shock in ICU: The Epidemic and Prognostic Value
ClinicalTrials.gov study NCT03082326. IPD Sharing: NO. Countries: 1. Publications: 8.
Analysis of the Incidence of Expression of Tumor Antigens in Pathologically Proven Stage I, II and III Non-Small Cell Lung Cancer(NSCLC) in Asiatic Patients
ClinicalTrials.gov study NCT01837511. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Postoperative Pembrolizumab for the Patients Who Have Solid Predominant or Micropapillary Lung Adenocarcinoma With Pathologic Stage I and Primary Tumor Than 4 cm
ClinicalTrials.gov study NCT03254004. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Primary Hemostasis Pathology in Patients on ECMO During Lung Transplantation
ClinicalTrials.gov study NCT04456894. IPD Sharing: NO. Countries: 1. Publications: 10.
Dielectric Property Test Compared With Frozen Pathological Section in the Rapid Diagnosis of Lung Nodules/Mass
ClinicalTrials.gov study NCT03339479. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
Pathological Comparisons of Surgical Open Lung Biopsies and Cryobiopsies in Non-IPF ILD
ClinicalTrials.gov study NCT02763540. IPD Sharing: Not stated. Countries: 2. Publications: 6.
The Efficacy of Medical Students to Identify Pathological Lung Sound Over a Period of Time
ClinicalTrials.gov study NCT05731180. IPD Sharing: NO. Countries: 1. Publications: 7.
Detection of Lung Pathologies Among Dialysis Patients Using Pulsenmore MC™ Device - Feasibility Study
ClinicalTrials.gov study NCT07028060. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Intraoperative Frozen Section Pathology to Guide Surgical Treatment for Lung Adenocarcinoma (ECTOP-1015)
ClinicalTrials.gov study NCT05794711. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The spatial landscape of lung pathology during COVID-19 progression - processed IMC data
<p>Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19). However thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking. We use high parameter imaging mass cytometry9 targeting the expression of 36 proteins, to investigate at single cell resolution, the cellular composition and spatial architecture of human acute lung injury including SARS-CoV-2. This spatially resolved, single-cell data unravels the disordered structure of the infected and injured lung alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyper-inflammatory cell state associated with lung damage. By leveraging the temporal range of COVID-19 severe fatal disease in relation to the time of symptom onset, we observe increased macrophage extravasation, mesenchymal cells, and fibroblasts abundance concomitant with increased proximity between these cell types as the disease progresses, possibly as an attempt to repair the damaged lung tissue. This spatially resolved single-cell data allowed us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. This spatial single-cell landscape enabled the pathophysiological characterization of the human lung from its macroscopic presentation to the single-cell, providing an important basis for the understanding of COVID-19, and lung pathology in general.</p>
Pathological images of non-small cell lung cancer
<p>The dataset comprises lung cancer patient information and pathology images utilized for the analysis of our study. These are anonymized data from cases in our cohort for which patient consent was obtained for public deposition. </p> <p>Patient information for original cohort and validation cohort is described in the Excle files, "original_cohort_patient_info.xlsx" and "validation_cohort_patient_info.xlsx", respectively. </p> <p>These Excel files contain information on sex, age, smoking history, pathological stage, histology, lymphovascular invasion, pleural invasion, lymph node metastasis, adjuvant treatment, survival outcomes and file names for pathological images of each patient. Each patient has two files of Whole Slide Images files (format: .npdi) including hematoxylin & eosin staining ("XXX_h.ndpi") and immunohistochemistry stainig for PD-L1 ("XXX_p.ndpi").</p>
Cross Spatio-Temporal Pathology-based Lung Nodule Dataset
<p>We introduce a novel cross spatio-temporal lung nodule dataset based on pathological information, which effectively integrates rich multimodal information within the spatio-temporal dimension.</p>
Cross Spatio-Temporal Pathology-based Lung Nodule Dataset
<p>We introduce a novel cross spatio-temporal lung nodule dataset based on pathological information, which effectively integrates rich multimodal information within the spatio-temporal dimension.</p>
Cellular and molecular heterogeneities and signatures, and pathological trajectories of fatal COVID-19 lungs defined by spatial single-cell transcriptome analysis
<p>Spatial in-situ data analysis.</p>
CT Scan Guide Percutaneous Biopsy of Lytic Bone Metastases of Lung Cancer : Contribution in Pathology Diagnosis and Molecular Biology
ClinicalTrials.gov study NCT03386916. IPD Sharing: Not stated. Countries: 0. Publications: 5.
Blood Sample Collection in Subjects With Pulmonary Nodules or CT Suspicion of Lung Cancer or Pathologically Diagnosed Lung Cancer
ClinicalTrials.gov study NCT03633006. IPD Sharing: YES. Countries: 1. Publications: 0.
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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.