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11,852 results for “liver”
Four lipidomics datasets (mouse liver, mouse pancreatic islets, mouse soleus muscle and mouse visceral adipose tissue), generated for the publication Mehl et al., "A multiorgan map of metabolic, signalling, and inflammatory pathways that coordinately control fasting glycemia in mice"
<p>Mehl, Thorens et al present a multiomics study aimiing to<span> identify the pathways that are coordinately regulated in pancreatic </span><span>b</span><span>-cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2 and Balb/c mice a regular chow or a high fat diet for 3, 10 and 30 days. We measured fasted glycemia, insulinemia and whole-body insulin resistance. Transcriptomic and lipidomic analysis were used in a data fusion approach to identify organ-specific pathways related to the glycemic levels across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels were associated with reduced expression of mRNAs encoding hormone and neurotransmitter receptors as well as OXPHOS, cadherins, integrins and gap junction proteins. Higher glycemia and whole-body insulin resistance were associated, in muscle, with reduced expression of mRNAs encoding insulin signaling proteins and enzymes of the glycolysis, Krebs’ cycle and OXPHOS pathways, as well as endocytosis and exocytosis proteins; in hepatocytes, with lower expression of mRNAs of the insulin signaling pathway, of branched chain amino acid catabolism and of OXPHOS; in adipose tissue, with increased expression of mRNAs of innate immunity and lipid catabolism. These data provide a map of the pathways that are coordinately recruited in the investigated tissues to control fasting glycemia and a resource for further studies of interorgan communication in glucose homeostasis. </span></p>
SEAL Substudy dataset on psychosocial consequences of liver screening
<p><strong>Background:</strong></p> <p>This data set comprises responses from n=487 patients who took part in a screening program for liver cirrhosis and fibrosis from January 2018 to February 2021 which was implemented as SEAL liver prevention program in Rhineland-Palatinate and Saarland, Germany. The project was funded by the Innovation Fund of Federal Joint Committee of Germany, provided by Deutsches Zentrum für Luft- und Raumfahrt (Funding ID: 01NVF16026).</p> <p>The SEAL program is a prospective study that aimed at evaluating a newly introduced medical screening method for early diagnosis of liver cirrhosis or fibrosis. Within this screening, patients who visited collaborating clinics or doctor's offices for a general health check-up (Check-Up 35), underwent a multistep screening (step 1: blood sample test and determination of risk score, step 2: enhanced laboratory diagnostics and ultrasound, step 3: liver biopsy and enhanced diagnostics in a specialized clinic). Inclusion criteria for study participation were a minimum age of 35 years and no known previous cirrhosis of liver.</p> <p><strong>Data collection:</strong></p> <p>In August 2019, we contacted all participants who had been included in the SEAL program so far. A total of n=5,935 patients were contacted via postal mailing which included a self-administered paper questionnaire, a patient information and an informed consent form. In sum, n=487 processsable questionnaires were returned. The data set contains processed data, so that used instruments were transformed according to guidelines, where available. The data set is completely anonymized.</p> <p><strong>Content:</strong></p> <p>The data set encompasses a context-adapted German version of the Psychological Consequences of Screening Questionnaire (PCQ) (Cockburn et al. 1992, Fichtner et al., 2022), the short form of the State-Trait Anxiety Inventory (STAI) (Marteau et al. 1992), a multimorbidity score (KOMO) (Glattacker et al. 2007), a health literacy instrument (HELP) (Farin et al. 2013), the Oslo Social Support Scale (OSSS-3) (Kocalevent et al. 2018), items to measure communication competences (KoKo) (Farin et al. 2014), the MacArthur Scale on Subjective Social Status (Adler et al. 2000) and items on satisfaction with healthcare (ZAP) (Bitzer et al. 1999). Furthermore, background information was collected: Household size, education, occupational status, age, sex, existence of a steady partnership, professional education, future screening attitudes, reception of test result and satisfaction with screening procedure and information on risk factors.</p>
RNA sequencing dataset for prediction of liver hepatocellular carcinoma using SIMON analysis
<p>The LIHC dataset was used for data mining and for the generation of machine learning model for the detection of liver hepatocellular carcinoma cells (LIHC) using the SIMON platform as described in the "SIMON: open-source knowledge discovery platform" publication (<a href="https://doi.org/10.1101/2020.08.16.252767">https://doi.org/10.1101/2020.08.16.252767</a>). The LIHC dataset was obtained from the <em>GSEABenchmarkeR</em> package ( <a href="https://doi.org/10.1093/bib/bbz158">https://doi.org/10.1093/bib/bbz158</a>) and it contains RNA expression data from 374 liver hepatocellular carcinoma (LIHC) cells and 50 adjacent normal cells.</p>
Liver Micrometastases area quantification using QuPath and pixel classifier
<p><strong>Sample</strong>: Mouse (NSG) liver slices with human colorectal cancer cells metastases, stained with Hematoxylin & Eosin. </p> <p><strong>Image Acquisition</strong>: Images were acquired on an Olympus VS120 Whole Slide Scanner, using a 20x objective (UPLSAPO, N.A. 0.75) and a color camera (Pike F505 Color) with an image pixel size of 0.345 microns.</p> <p><strong>Image Processing and Analysis</strong>: Obtained images were analyzed using the software QuPath [1] (version 0.3.2) using groovy scripts, making use of a pixel classifier to segment and measure cancer cell clusters.</p> <p><strong>Files</strong> :</p> <p><em>Detailed_worflow.pdf</em> : contains a detailed description of how pixel classifier was created</p> <p><em>images_for_classifier_training.zip</em> : contains all the vsi file obtained from the microscope and used for the training</p> <p><em>project_for_classifier_training.zip</em> : contains the QuPath project, with Training Image, annotations, classifiers and scripts for analysis</p> <p><em>PythonCode.txt</em> : code ran to transform output results from QuPath to final results</p> <p> </p> <p>[1] Bankhead, P. et al. <strong>QuPath: Open source software for digital pathology image analysis</strong>. <em>Scientific Reports</em> (2017). <a href="https://doi.org/10.1038/s41598-017-17204-5">https://doi.org/10.1038/s41598-017-17204-5</a></p>
Dataset of B-mode fatty liver ultrasound images
<p>The dataset used and described in: M. Byra, G. Styczynski, C. Szmigielski, P. Kalinowski. Ł. Michałowski4. R. Paluszkiewicz. B. Ziarkiewicz-Wróblewska, K. Zieniewicz. P. Sobieraj, A. Nowicki. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images. International Journal of Computer Assisted Radiology and Surgery, 2018. DOI: 10.1007/s11548-018-1843-2. </p> <p>Please refer to the above work if you use the dataset in your research. </p> <p>Contact:<br> Michal Byra<br> Department of Ultrasound<br> Institute of Fundamental Technological Research<br> Polish Academy of Sciences, Warsaw, Poland<br> mbyra@ippt.pan.pl<br> byra.michal@gmail.com</p>
Mice infected with High shedder S. mansoni parasites from cross A - cage 1 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> High shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 2/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Mice infected with High shedder S. mansoni parasites from cross A - cage 2 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with S. mansoni High shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 3/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p> <p> </p>
Mice infected with High shedder S. mansoni parasites from cross B - cage 1 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> High shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 6/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Mice infected with Low shedder S. mansoni parasites from cross A - cage 2 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> Low shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 5/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Mice infected with Low shedder S. mansoni parasites from cross A - cage 1 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> Low shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 4/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Control mice (non-infected with S. mansoni parasites) - cage 2 - Liver histopathology data (mouse ID 2C.1 / 2C.2 / 2C.3).
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas in liver of mice (non-infected with S. mansoni parasite). These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 11.1/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area (_TRICH.czi) and (_HE.czi) files.</p>
Control mice (non-infected with S. mansoni parasites) - cage 2 - Liver histopathology data (mouse ID 2C.4 / 2C.5).
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas in liver of mice (non-infected with S. mansoni parasite). These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 11.2/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area (_TRICH.czi) and (_HE.czi) files.</p>
Mice infected with High shedder S. mansoni parasites from cross B - cage 2 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> High shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 7/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Mice infected with Low shedder S. mansoni parasites from cross B - cage 2 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> Low shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 9/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Mice infected with Low shedder S. mansoni parasites from cross B - cage 1 - Liver histopathology data.
<p>The present dataset contains all the histopathology images used to quantify fibrotic areas, parasite egg counts and to quantify granuloma areas in liver of mice infected with <em>S. mansoni</em> Low shedder line. These data are presented in the manuscript entitled "No evidence for schistosome parasite fitness trade-offs in the intermediate and definitive host" (dataset # 8/11).<br> Each folder corresponds to one mouse sample and contain, along with a readme file, all the files used to quantify fibrotic area and egg counts (_TRICH.czi), to quantify granuloma area (_HE.czi), and the annotation file (.annotations) containing all the annotated granuloma areas.</p>
Data from Time since liver transplantation and immunosuppression withdrawal outcomes: a systematic review with individual patient data meta-analysis
<p>This record provides one CSV file containing anonymized individual patient data (IPD) of pre-withdrawal times (in days) of liver transplant recipients that underwent immunosuppression (IS) withdrawal. Collection and publication of anonymized data was approved by the Ethics Committee Northwest and Central Switzerland. Patients of 15 primary studies are stratified by successfully reaching the state of IS-free operational tolerance (OT) or by developing signs of immunological rejection (non-OT).</p>
Multiplexed Staining Dataset - OMAP 5 - Liver-Lanthanides-conjugated antibodies and C60-secondary ion mass spectrometry imaging
<p>This dataset contains images of multiplexed antibody panel on a human pediatric liver section including the nuclear marker and antibodies conjugated with lanthanides tags. The dataset is one example of serial experiments of multiplexed antibody staining and imaging. The antibody panel targets the major cell types and tissue structures in the liver tissue. Data acquisition was performed using single multiplexing imaging by C60-secondary ion mass spectrometry.</p> <p> </p>
Raw data accompanying the manuscript "Multiscale and multimodal optical imaging of the human liver"
<p>These are the raw datasets used to generate the figures for the manuscript entitled "Multiscale and multimodal optical imaging of the human liver". The file CARS_SRS.zip contains folders with all raw CARS and SRS data (TIFF format). The file CLSM.zip contains confocal laser scanning microscopy data using the manufacturers data format (Zeiss). The file LSFM.zip contains light sheet fluorescence microscopy data files using the manufacturers data format (LaVision Biotec). The file OPT.zip contains raw optical projection tomography data at different excitation wavelengths (TIFF format). The file SRSIM.zip contains reconstructed structured illumination microscopy data files (TIFF format).</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>
F I G U R E 2 in Effects of dietary hydrolysate supplementation on growth, body composition, hematological responses, and liver histology of juvenile giant trevally (Caranx ignobilis Forsskal, 1775)
F I G U R E 2 Somatic indexes and condition factor of giant trevally fed experimental diets for 8 weeks. ns, nonsignificant. Different subscript letters indicate differences among treatments.
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