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16,682 results for “Lung”
Multiplexed histology of COVID-19 post-mortem lung samples - CONTROL CASE 1 FOV3
<p><strong>Image-based data set of a post-mortem lung sample from a non-COVID-related pneumonia donor (CONTROL CASE 1 FOV3)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - CHRONIC CASE 1 FOV3
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (CHRONIC CASE 1 FOV3)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 3 FOV1
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 3 FOV1)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 2 FOV1
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 2 FOV1)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 1 FOV2
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 1 FOV2)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - CONROL CASE 2 FOV2
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (CONTROL CASE 2 FOV2)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 3 FOV2
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 3 FOV2)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Altered nanoparticle uptake by lung carcinoma cells when stimulated with epidermal growth factor
<p>This dataset provides the raw data supporting the paper "Altered nanoparticle uptake by lung carcinoma cells when stimulated with epidermal growth factor". The focus of the study was to investigate the uptake of two different sizes of silica NPs and gold NPs in lung epithelial cells A549 in the presence of epidermal growth factor (EGF). </p> <p>The data set includes:</p> <ul> <li>Screening for EGF receptor using western blot and confocal microscopy (Figure 1 and Figure S1)</li> <li>Investigating expression of RAC1/CDC42 proteins upon EGF stimulation using Western blot (Figure 2)</li> <li>Investigating expression of RAC1 gene upon EGF stimulation using RT-qPCR (Figure S2)</li> <li>Evaluating uptake of endocytic markers upon EGF stimulation using confocal laser scanning microscopy (Figure 3, Figure S4) and flow cytometry (Figure 3)</li> <li>Nanoparticle characterization using TEM (Figure 4, Figure S6) and UV-Vis (Figure S5, Figure S6)</li> <li>Evaluating silica nanoparticle uptake upon EGF stimulation using confocal laser scanning microscopy (Figure 5, Figure S8) and flow cytometry (Figure 5)</li> <li>Evaluating gold nanoparticle uptake upon EGF stimulation using dark-field microscopy and ICP-AES (Figure 6)</li> <li>Investigating expression of c-MYC gene upon EGF stimulation using RT-qPCR (Figure 6)</li> <li>Cell viability results, analysed via lactate dehydrogenase assay (Figure S3) and MTS assay (Figure S9)</li> <li>Raw integrated density data from dark-field images (Figure S9)</li> </ul>
Increased egg shell temperature during incubation leads to changes in transcriptional and epigenetic profiles in chicken lungs
<p>These RDS files contain <strong>DESeqDataSet </strong>objects subsets per broiler age and treatment. These objects are the result of DESeq2::DESeq( … ,betaPrior=FALSE).The .txt-objects contain the normalized sequencing counts per broiler age and treatment group. These objects are the result of DESeq2::counts( … , normalized=TRUE). Data was generated using STAR v2.7.10a and DESeq2 v1.36. Metadata is included as Excel file.</p> <p>Sequencing data is deposited at NCBI-SRA under BioProject: PRJNA949139. </p> <p> </p> <p><strong>Study abstract</strong></p> <p>D. Schokker, J. de Vos, P.B. Stege, O. Madsen, H.J. Wijnen, S.K. Kar, and J.M.J. Rebel</p> <p>Health and resilience against respiratory diseases are important features for broiler chicken. In this study, epigenetic and transcriptomic changes in the lungs of broiler chickens of different ages during rearing that were either exposed to elevated egg shell temperature (HIGH) of 38.9°C during mid-incubation or normal egg shell temperature (control; CON). The objective was to better understand how environmental challenges, such as heat stress during egg incubation, affect the development of the immune system and health of broiler chicken at later age. To this end we generated both epigenetic and transcriptomic data of lung tissue of elevated HIGH and CON chicken, furthermore these chicken were challenged by introducing either an infectious E. coli or an IBV vaccination to monitor the respiratory response. Thousands of differential methylated sites were observed at days 15 and 33, when comparing HIGH vs. CON. Pathway enrichment analysis of HIGH vs. CON showed that differentially expressed genes were mainly involved in cilium, cytoskeleton, and immune processes. These findings provide insight into the underlying biological mechanisms of early life conditions, like elevated EST, and their potential role in health of broilers.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - Single-cell Mean Fluorescence Intensities
<p>Data table containing single-cell mean fluorescence intensities (MFI) of all markers analyzed by multiplexed histology in all COVID-19 post-mortem lung samples and non-COVID-related pneumonia controls (14 lung samples, stratified based on disease duration into control, acute, chronic and prolonged). It contains information at the single-cell level about approx 50 proteins in around 40.000 lung cells.</p> <p>Data shown has been arcsin(h) transformed with a co-factor of 0.2. Additionally, cells expressing less than 0.15 MFI of all markers have been labeled as non-defined and excluded from the data set.</p> <p>Seurat package 4.0.0 was used in R to perform mean centering and scaling, followed by PCA, and reduced the dimensions of the data to the top 11 principal components. UMAP was initialized in this PCA space to visualize the data on reduced UMAP dimensions. The cells were clustered on PCA space using the SNN algorithm implemented as <em>FindNeighbors</em> and <em>FindClusters </em>with <em>n.epochs = 500</em> and default parameters (<em>res = 0.8</em>). We obtained 26 clusters that we merged to get relevant populations for our analysis based on canonical lineage markers. We ended up with 8 cell clusters that were manually annotated based on cell-type-specific markers found to be differentially expressed.</p> <p> </p> <p> </p>
LungVis1.0: Active learning AI-powered 3D imaging ecosystem for spatial profiling of lung geometry and pulmonary nanoparticle delivery
<p>The imaging dataset was obtained by light sheet fluorescence microscopy on tissue cleared murine lungs. It includes whole lung autofluorence image, particle fluorescence image, and artifical intelligence nnU-Net generated lung airway segments. The dataset provides 78 healthy murine lung strucutre and airway geometry for C57BL/6 mice and offers comprehensive delivery features including qualitative and quantitative analysis on the temporal and spatial inter- and intra-acinar deposition patterns and NP regional dosimetry for four commonly-used routes of pulmonary delivery,namely intranasal liquid aspiration, intratracheal liquid instillation, ventilator-assisted and nose-only aerosol inhalation.</p> <p>Raw LSFM imaging data collection was carried out between 2017-2021, the AI code and generated airway segmention were performed in 2021-2022, the whole datasets were then compiled in 2023. </p> <p>Please ensure to cite our paper for any reuse or reanalysis. Yang, L., Liu, Q., Kumar, P. <em>et al.</em> LungVis 1.0: an automatic AI-powered 3D imaging ecosystem unveils spatial profiling of nanoparticle delivery and acinar migration of lung macrophages. <em>Nat Commun</em> <strong>15</strong>, 10138 (2024). https://doi.org/10.1038/s41467-024-54267-1</p> <p>For any inquiries, please feel free to contact us at lin.yang@helmholtz-munich.de </p>
Multiplexed histology of COVID-19 post-mortem lung samples - CHRONIC CASE 3 FOV1
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (CHRONIC CASE 3 FOV1)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Multiplexed histology of COVID-19 post-mortem lung samples - CHRONIC CASE 3 FOV2
<p><strong>Image-based data set of a post-mortem lung sample from a COVID-19 donor (CHRONIC CASE 3 FOV2)</strong></p> <p>Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.</p>
Free Breathing Lung MRI Dataset at 3T
<p> This is a free breathing lung MRI dataset. Data is acquired with 3D ultra-short te (UTE) radial sequence.</p>
Lung ultrasonography features and risk stratification in 80 patients with COVID-19: a prospective observational cohort study
<p><strong>Background</strong></p> <p>Point-of-care lung ultrasound (LUS) is a promising and pragmatic risk stratification tool in COVID-19. This study describes and compares early LUS characteristics across of range of clinical outcomes.</p> <p><strong>Method</strong></p> <p>Prospective observational study of PCR-confirmed COVID-19 patients in the emergency department (ED) of Lausanne University Hospital. A trained physician recorded LUS images using a standardized protocol. Two experts retrospectively reviewed images blinded to patient outcome. We describe and compare early LUS findings (acquired within 24hours of presentation at the ED) between patient groups based on their outcome at 7-days after inclusion: 1) self-resolving outpatients, 2) hospitalised and 3) intubated/death. The LUS score was used to discriminate between groups.</p> <p><strong>Findings</strong></p> <p>Between March 6 and April 3 2020, we included 80 patients (18 outpatients, 41 hospitalized and 21 intubated/dead). 73 patients (91%) had abnormal LUS (72% outpatients, 95% hospitalised and 100% intubated/death; p=0.004). The proportion of involved zones was lower in outpatients compared with other groups (median 30% [IQR 0-40%], 44% [33-70%] and 70% [50-88%], p<0.001). Predominant abnormal patterns were bilateral and multifocal spread thickening of the pleura with pleural line irregularities (77%), confluent B lines (66%) and pathologic B lines (55%). Posterior inferior zones were more often affected. Median LUS score had a good level of discrimination between outpatients and others with area under the ROC of 0.80 (95% CI 0.66-0.95).</p> <p><strong>Interpretation</strong></p> <p>Systematic LUS is a reliable, cheap and easy-to-use triage tool for the early stratification of risk in COVID-19 patients presenting at emergency departments.</p> <p><strong>Funding</strong></p> <p>Leenaards Foundation</p>
Free-Breathing Self-Gated 4D-Lung MRI using wave-CAIPI
<p>MRI raw data set of a volunteer examination for the project "Free-Breathing Self-Gated 4D-Lung MRI using wave-CAIPI". The upload includes the measured k-space for 8 different breathing phases, the respective image reconstructions and the coil sensitivity maps required for the Conjugate Gradient SENSE reconstruction.</p> <p>C++ source code for image reconstruction can be downloaded at <a href="https://github.com/expRad/4d_lung">https://github.com/expRad/4d_lung</a>.</p> <p> </p>
Data and scripts for SCLC_CellMiner: Integrated Genomics and Therapeutics Predictors of Small Cell Lung Cancer Cell Lines based on their genomic signatures
<p>This is the repository of data and scripts for the analysis of the CellminerCDB-SCLC manuscript and website (<a href="https://discover.nci.nih.gov/SclcCellMinerCDB/">https://discover.nci.nih.gov/SclcCellMinerCDB/</a>)</p> <p> </p> <p>CellMiner-SCLC (https://discover.nci.nih.gov/SclcCellMinerCDB) integrates 118 patient-derived cell lines with drug sensitivity and genomic datasets, including high resolution methylome and RNAseq data. CellMiner-SCLC provides a new resource for SCLC research for this “recalcitrant cancer”. Of fundamental importance, we demonstrate the reproducibility and stability of the cell line datasets from different institutions (CCLE, GDSC, CTRP, NCI and UTSW). We validate the classification based on four master transcription factors: NEUROD1, ASCL1, POU2F3 and YAP1 and show transcription networks connecting them with the MYC genes (MYC, MYCL1 and MYCN) and the NOTCH and HIPPO pathways. We find that the 4 subsets express specific surface markers for antibody-targeted therapies. The YAP1-driven (SCLC-Y) cell lines differ from the other subsets by expressing the NOTCH pathway, epithelial-mesenchymal-transition (EMT) and antigen-presenting machinery (APM) genes, and by responding to mTOR and AKT inhibitors, suggesting the potential of NOTCH modulators, YAP1 inhibitors and immune checkpoint inhibitors for SCLC-Y tumors.</p>
Figures 20. Silba fumosa, a lunge taking about 1 in Diverse mechanisms of feeding and movement in Cyclorrhaphan larvae (Diptera)
Figures 20. Silba fumosa, a lunge taking about 1 sec. (A) Start of a lunge, ventral view, from Film 8; (B) start of a lunge, lateral view from Film 9; (C–E) mandible positions at the limit of extension: (C) ventral view; (D) mandibles starting to depress and separate, ventral view; (E) on the substrate, lateral view.
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>
Dataset - A lung-on-chip model reveals an essential role for alveolar epithelial cells in controlling bacterial growth during early M. tuberculosis infection
<p>Description of the sub-folders<br> Name, type of data, corresponding Figure in the manuscript<br> 3D view of the LoC model - .tiff image stack, Figure 1.</p> <p>Bacterial Growth Rate Data - .tiff image stacks, .csv files and MATLAB code to extract the fluorescence intensity over time, Figure 2, Figure 2 - figure supplement 2, Figure 2 - figure supplement 4, Figure 3, Figure 3 - figure supplement 2, Figure 4.</p> <p>AT Characterization - .tiff image stacks and MATLAB code to extract the number and volume of lamellar bodies from the stack of confocal images, Figure 1, Figure 1 - figure supplement 1, Figue 1 - figure supplement 2.</p> <p>AT Infection in LoC model - .tiff image stacks, Figure 2 - figure supplement 1.</p> <p>AT Infection in vivo - .tiff image stacks, Figure 1 - figure supplement 3.</p> <p>Simulations of in vivo infections - .dat files of growth rates in macrophages for the WT and ESX-1 deficient populations and MATLAB code to simulate an infection from this data, Figure 4.</p> <p> </p>
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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.