Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4,004
datasets available to search
ShareScore release 0.9.0
Dataset results
4,004 results for “In vivo”
Figure 1 in Transmission of Induced Chromosomal Aberrations through Successive Mitotic Divisions in Human Lymphocytes after In Vitro and In Vivo Radiation
Figure 1. – Photograph of the proximal (left) and distal (right) sides of the brown meagre sagittae (LT = 497 mm). Scale bar = 1 cm.
HIV-1 control in vivo is related to the number but not the fraction of infected cells with viral unspliced RNA
<p>In the absence of antiretroviral therapy (ART), a subset of individuals, termed HIV controllers, have levels of plasma viremia that are orders of magnitude lower than non-controllers who are at higher risk for HIV disease progression. In addition to having fewer infected cells resulting in fewer cells with HIV RNA, it is possible that lower levels of plasma viremia in controllers is due to a lower fraction of the infected cells having HIV-1 unspliced RNA (HIV usRNA) compared with non-controllers. To directly test this possibility, we used sensitive and quantitative single cell sequencing methods to compare the fraction of infected cells that contain one or more copies of HIV usRNA in peripheral blood mononuclear cells (PBMC) obtained from controllers and non-controllers. The fraction of infected cells containing HIV usRNA did not differ between the two groups. Rather, the levels of viremia were strongly associated with the total number of infected cells that had HIV usRNA, as reported by others, with controllers having 34-fold fewer infected cells per million PBMC. These results reveal for the first time that viremic control is not associated with a lower fraction of proviruses expressing HIV usRNA, unlike what is reported for elite controllers, but is only related to having fewer infected cells overall, maybe reflecting greater immune clearance of infected cells. Our findings show that proviral silencing is not a key mechanism for viremic control and will help to refine strategies towards achieving HIV remission without ART.</p>
supporting files for "What to Choose for Estimating Leaf Water Status - Spectral Reflectance or in vivo Chlorophyll Fluorescence?"
<p><strong><span>Fig. 1 </span></strong><span>Workflow and parameters used for comparative analysis.</span></p> <p><strong><span>Fig. 2</span></strong><span> Representative spectra of diffusive reflectance measured on the adaxial side (R<sub>D</sub>) of fresh (RWC = 98%), partially desiccated (RWC = 52% or 54%) and severely desiccated leaves (RWC = 5%) of tobacco (A) and barley (E). Comparison of R<sub>D</sub> and R<sub>B</sub> (R from the abaxial leaf side) in fresh and severely desiccated leaves of tobacco (B) and barley (F). Water index (WI = R<sub>900</sub>/R<sub>970</sub>) and relative decrease of R in the 800-1100 nm region (ΔR) estimated from R<sub>D</sub> (indexed by "D") and R<sub>B</sub> (indexed by "B") in desiccating leaves of tobacco (C, D) and barley (G, H).</span></p> <p><strong><span>Fig. 3</span></strong><span> Water index (WI<sub>SWIR </sub>= R<sub>1000</sub>/R<sub>1450</sub>) estimated from measurement of directional R from adaxial side of desiccating leaf samples of tobacco (A) and barley (B). </span></p> <p><strong><span>Fig. 4 </span></strong><span>Equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples within the RWC interval 100-50%.</span></p> <p><strong><span>Fig. 5 </span></strong><span>Normalized difference vegetation index</span><span> </span><span>(NDVI</span><span> </span><span>=</span><span> </span><span>(R<sub>780</sub>-R<sub>630</sub>)/(R<sub>780</sub>+R<sub>630</sub>)) estimated from measurement of diffusive R from the </span><span>abaxial (</span><span>NDVI</span><sub><span>B</span></sub><span>) and </span><span>adaxial side (NDVI</span><sub><span>D</span></sub><span>) of desiccating leaves of tobacco (A) and barley (D). SPAD-value</span><span>s</span><span> of desiccating leaves of tobacco (B) and barley </span><span>(E)</span><span>. Relative SPAD and NDVI</span><span>΄<sub>D</sub> (estimated from measurement of directional R from the adaxial side</span><span>)</span><span> </span><span>of a representative leaf of tobacco </span><span>(C)</span><span> and barley (F) during its desiccation (in % of the value measured immediately after leaf detachment). For selected data points, the time after the leaf detachment is indicated. </span></p> <p><strong><span>Fig. 6</span></strong><span> Chlorophyll fluorescence parameters of desiccating tobacco and barley leaf samples. (A, D) The maximum quantum yield of PSII photochemistry in the dark-adapted state (F<sub>V</sub>/F<sub>M</sub>) and the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSII<sub>st</sub>). (B, E) The non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ<sub>1</sub>). (C, F) The non-photochemical quenching of chlorophyll fluorescence at steady state (NPQ<sub>st</sub>).</span></p> <p><strong><span>Fig. 7 </span></strong><span>Coefficient of reliability (<em>CR</em>), coefficient of sensitivity (<em>CS</em>) and coefficient of inaccuracy (<em>CI</em>) of parameters measured in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%. The parameters have been divided into 5 groups according to the type of leaf characteristics they reflect. A horizontal line in <em>CR</em> plot indicates the reliability threshold (<em>CR</em> = 0.4).</span></p> <p><strong><span>Table 1 </span></strong><span>Parameters measured on desiccating tobacco and barley leaves ranked according to the value of their coefficient of reliability (<em>CR</em>) within the RWC interval 100-50% and the corresponding values of the coefficient of determination (<em>R<sup>2</sup></em>).</span></p> <p><strong><span>Fig. S1 </span></strong><span>Decrease in relative water content (RWC) of leaf samples of tobacco and barley with time after their detachment</span></p> <p><strong><span>Fig. S2 </span></strong><span>Micrographs of leaf structure of fresh tobacco (A) and barley (B) leaves.</span></p> <p><strong><span>Fig. S3</span></strong><span> </span><span>WI<sub>SWIR</sub> images </span><span>o</span><span>f representative desiccating tobacco and barley leaf samples</span><strong><span>. </span></strong><span>Numbers above the samples indicate their RWC in %.</span></p> <p><strong><span>Fig. S4 </span></strong><span>(A)</span><strong><span> </span></strong><span>Leaf area (in % of the area of fresh leaves) and (B) equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples.</span></p> <p><strong><span>Fig. S5 </span></strong><span>Imaging of chlorophyll fluorescence parameters of representative desiccating tobacco and barley leaf samples. The maximum quantum yield of PSII photochemistry (F<sub>V</sub>/F<sub>M</sub>), the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSII<sub>st</sub>), the non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ<sub>1</sub>), and the non-photochemical quenching of Chl fluorescence at steady state (NPQ<sub>st</sub>).</span></p> <p><strong><span>Fig. S6</span></strong><span> Dependencies of</span><strong><span> </span></strong><span>measured parameters on RWC (in interval 100-50%) in desiccating tobacco leaves and segments. The parameters are ranked from most to least reliable according to their coefficient of reliability (<em>CR</em>). All parameters are normalized to their mean value (<em>ȳ</em>).</span></p> <p><strong><span>Fig. S7</span></strong><span> Dependencies of</span><strong><span> </span></strong><span>measured parameters on RWC (in interval 100-50%) in desiccating barley leaves and segments. The parameters are ranked from most to least reliable according to their coefficient of reliability (<em>CR</em>). All parameters are normalized to their mean value (<em>ȳ</em>).</span></p> <p><strong><span>Fig. S8 </span></strong><span>Leaf water potential measured by psychrometry </span><span>(Ψ<sub>psy</sub>) and by pressure chamber (Ψ<sub>press</sub>) in desiccating leaves of tobacco (A) and barley (B).</span></p> <p><strong><span>Table S1 </span></strong><span>Parameters measured on desiccating leaf samples ranked according to their coefficient of sensitivity (<em>CS</em>) within the RWC interval 100-50% in tobacco and barley.</span></p> <p><strong><span>Table S2 </span></strong><span>Parameters measured on desiccating leaf samples ranked according to their coefficient of inaccuracy (<em>CI</em>) within the RWC interval 100-50% in tobacco and barley.</span></p> <p><strong><span>Table S3 </span></strong><span>Ranking of measured parameters according to their coefficient of reliability (<em>CR</em>), sensitivity (<em>CS</em>) and inaccuracy (<em>CI</em>) in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%. The parameters have been divided into 5 groups (the first column) according to the type of leaf characteristics they reflect.</span></p> <p><strong><span>Table S4</span></strong><span> Approximate </span><span>time required for the measurement of the parameters used in the study and the destructiveness/non-destructiveness of the measurement. The parameters that were used for the comparison according to their coefficients of reliability (<em>CR</em>), sensitivity (<em>CS</em>) and inaccuracy (<em>CI</em>) are written in bold.</span></p> <p><strong><span>Fig. 2_spectra of diffusive reflectance </span></strong><span>- source data for each panel (A-H) of Fig. 2: </span><span>Representative spectra of diffusive reflectance measured on the adaxial side (R<sub>D</sub>) of fresh (RWC = 98%), partially desiccated (RWC = 52% or 54%) and severely desiccated leaves (RWC = 5%) of tobacco (A) and barley (E). Comparison of R<sub>D</sub> and R<sub>B</sub> (R from the abaxial leaf side) in fresh and severely desiccated leaves of tobacco (B) and barley (F). Water index (WI = R<sub>900</sub>/R<sub>970</sub>) and relative decrease of R in the 800-1100 nm region (ΔR) estimated from R<sub>D</sub> (indexed by "D") and R<sub>B</sub> (indexed by "B") in desiccating leaves of tobacco (C, D) and barley (G, H).</span></p> <p><strong><span>Fig.3_water index WISWIR</span></strong><span> - source data for each panel (A+B) of Fig. 3: Water index (WISWIR = R1000/R1450) estimated from measurement of directional R from adaxial side of desiccating leaf samples of tobacco (A) and barley (B).</span></p> <p><strong><span>Fig.4_equivalent water thickness</span></strong><span> - source data for Fig. 4: Equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples within the RWC interval 100-50%.</span></p> <p><strong><span>Fig.5_NDVI</span></strong><span> - source data for each panel (A-F) of Fig. 5: Normalized difference vegetation index (NDVI = (R780-R630)/(R780+R630)) estimated from measurement of diffusive R from the abaxial (NDVIB) and adaxial side (NDVID) of desiccating leaves of tobacco (A) and barley (D). SPAD-values of desiccating leaves of tobacco (B) and barley (E). Relative SPAD and NDVI΄D (estimated from measurement of directional R from the adaxial side) of a representative leaf of tobacco (C) and barley (F) during its desiccation (in % of the value measured immediately after leaf detachment).</span></p> <p><strong><span>Fig.6_chlorophyll fluorescence parameters</span></strong><span> - source data for each panel (A-F) of Fig. 6: Chlorophyll fluorescence parameters of desiccating tobacco and barley leaf samples. (A, D) The maximum quantum yield of PSII photochemistry in the dark-adapted state (FV/FM) and the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSIIst). (B, E) The non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ1). (C, F) The non-photochemical quenching of chlorophyll fluorescence at steady state (NPQst).</span></p> <p><strong><span>Fig.7_coefficients of reliability, sensitivity, inaccuracy</span></strong><span> - Coefficient of reliability (CR), coefficient of sensitivity (CS) and coefficient of inaccuracy (CI) of parameters measured in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%.</span></p> <p><strong><span>Fig.S1_relative water content</span></strong><span> - source data for supplementary Fig. 1: Relative water content (RWC) of leaf samples of tobacco and barley with time after their detachment.</span></p> <p><strong><span>Fig.S4_leaf area and equivalent water thickness</span></strong><span> - source data for supplementary Fig. 4: Leaf area (A) and equivalent water thickness (EWT; B) during desiccation of tobacco and barley leaf samples.</span></p> <p><strong><span>Fig.S6_dependencies of parameters on RWC in tobacco</span></strong><span> - source data for each panel (A-N) of supplementary Fig.6: Dependencies of measured parameters (water potential, NPQ, NDVI, reflectance, SPAD, Fv/Fm, water indexes) on RWC (in interval 100-50%) in desiccating tobacco leaves and segments.</span></p> <p><strong><span>Fig.S7_dependencies of parameters on RWC in barley</span></strong><span> - source data for each panel (A-N) of supplementary Fig.7: Dependencies of measured parameters (water potential, NPQ, NDVI, reflectance, SPAD, Fv/Fm, water indexes) on RWC (in interval 100-50%) in desiccating barley leaves and segments.</span></p> <p><strong><span>Fig.S8_leaf water potential</span></strong><span> - source data for supplementary Fig. 8: Leaf water potential measured by psychrometry (Ψpsy) and by pressure chamber (Ψpress) in desiccating leaves of tobacco (A) and barley (B).</span></p>
Synthesis and biological evaluation of a radiolabeled PET probe for visualization of in vivo -fucosidase expression - esi
<p>Supplementary data for paper titled: <strong>Synthesis and biological evaluation of a radiolabeled PET probe for visualization of <em>in vivo</em> </strong><strong>a</strong><strong>-fucosidase expression</strong></p>
Valproic Acid Synergizes With Cisplatin and Cetuximab in vitro and in vivo in Head and Neck Cancer by Targeting the Mechanisms of Resistance - Unpublished data
<p>Antitumor effects of valproic acid (VPA) in combination with Cisplatin/Cetuximab doublet in head and neck squamous cell carcinoma (HNSCC) models. We reported unpublished data of the effects of this combination on cell cycle and 3D cell cultures</p>
Images, graphs and tables from the article: Biological performance of a bioabsorbable Poly (L-Lactic Acid) produced in polymerization unit: in vivo studies -
<p>The images, graphs and tables attached correspond to the study performed in the thesis project on the in vivo biocompatibility of the PLLA polymer produced.</p>
Biological performance of a bioabsorbable Poly (L-Lactic Acid) produced in polymerization unit: in vivo studies - HEMATOXYLIN&EOSIN, MASSON AND CT SCAN IMAGES
<p>CT, hematoxylin & eosin and masson staining images of the animals in the experimental biocompatibility study.</p> <p>Groups at 6 months post implantation and groups at 9 months post implantation.</p> <p>In addition to the subgroups lesion with PLLA and lesion without PLLA</p>
Real-time Automatic Temperature Regulation During In Vivo MRI-guided Laser Induced Thermotherapy (MR-LITT)
<p>This dataset is associated with the article.</p> <p>For each example (in vitro/in vivo), two matrices are provided, each containing :</p> <p>- coefficients estimation curves ;</p> <p>- automatic regulation curves and recontructed data (thermometry, phase, module) of the MRI sequence.</p>
Data used in the paper (Two-point optical manipulation reveals mechanosensitive remodeling of cell-cell contacts in vivo)
<p>Data used in the paper (Two-point optical manipulation reveals mechanosensitive remodeling of cell-cell contacts in vivo)</p>
Supporting material for "Scientists should not increase the overall n by default when including both sexes in in vivo studies: evidence from statistical simulations"
<p>Supporting material for manuscript "Scientists should not increase the overall n by default when including both sexes in in vivo studies: evidence from statistical simulations"</p> <p>Includes underlying data and scripts to enable reproducible analysis. </p>
Design, construction, and in vivo augmentation of a complex gut microbiome
<p>Please cite: <a href="https://doi.org/10.1016/j.cell.2022.08.003">10.1016/j.cell.2022.08.003</a></p> <blockquote> <p>Cheng AG, Ho PY, Aranda-Díaz A, Jain S, Yu FB, Meng X, Wang M, Iakiviak M, Nagashima K, Zhao A, Murugkar P, Patil A, Atabakhsh K, Weakley A, Yan J, Brumbaugh AR, Higginbottom S, Dimas A, Shiver AL, Deutschbauer A, Neff N, Sonnenburg JL, Huang KC, Fischbach MA. Design, construction, and in vivo augmentation of a complex gut microbiome. Cell. 2022 Sep 15;185(19):3617-3636.e19. doi: 10.1016/j.cell.2022.08.003. Epub 2022 Sep 6. PMID: 36070752; PMCID: PMC9691261.</p> </blockquote> <p>Original raw sequencing data is available in the BioProject: <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA746600">PRJNA746600</a></p> <p><strong>Article summary:</strong></p> <blockquote> <p>Efforts to model the human gut <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/microbiome">microbiome</a> in mice have led to important insights into the mechanisms of host-microbe interactions. However, the model communities studied to date have been defined or complex, but not both, limiting their utility. Here, we construct and characterize <em>in vitro</em> a defined community of 104 bacterial species composed of the most common taxa from the human <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/intestine-flora">gut microbiota</a> (hCom1). We then used an iterative experimental process to fill open niches: germ-free mice were colonized with hCom1 and then challenged with a human fecal sample. We identified new species that engrafted following fecal challenge and added them to hCom1, yielding hCom2. In <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/gnotobiotics">gnotobiotic mice</a>, hCom2 exhibited increased stability to fecal challenge and robust <a href="https://www.sciencedirect.com/topics/immunology-and-microbiology/colonisation-resistance">colonization resistance</a> against pathogenic <em>Escherichia coli</em>. Mice colonized by either hCom2 or a human fecal community are phenotypically similar, suggesting that this consortium will enable a mechanistic interrogation of species and genes on microbiome-associated phenotypes.</p> </blockquote> <p><strong>File Descriptions:</strong></p> <ul> <li><strong>hCom2.tar.gz:</strong> This dataset contains genomic sequences and <a href="https://github.com/oschwengers/bakta">bakta</a> annotations of members of the hCom2 community. Please note that these may not be identical to the ones used in the publication. For the exact versions used in the publication, please reach out to the authors. </li> <li> <p><strong>hCom2_20221117.ninjaIndex.tar.gz:</strong> This tarball contains the ninjamap index and the source files used to create this index. Please use this tarball if you wish to run <a href="https://github.com/FischbachLab/ninjaMap">NinjaMap</a> against the hCom2 community.</p> </li> </ul>
In vivo screening of Lrp-type transcription factors in Escherichia coli
<p>This dataset contains the raw data that lie at the basis of the results discussed in <strong>Chapter 4: <em>In vivo</em> screening of Lrp-type transcription factors in <em>Escherichia coli</em></strong><strong> </strong>of the PhD thesis of Amber Bernauw. The README.txt file provides more information on the different data files.</p>
Ex vivo [18F]Fenoprofen PET imaging
<p>Coronal slice, maximum intensity projection (MIP) static PET image, and CT image of representative TPA-treated ear (A, C and E) or normal ear (B, D and F) harvested from the mice injected intravenously with [<sup>18</sup>F]Fenoprofen. (G) Dynamic PET time-activity curve (tac) of organ ROIs in nude mice injected with a rapid intravenous bolus of [<sup>18</sup>F]Fenoprofen, imaged for 30 minutes post-injection. (H) Uptake of [<sup>18</sup>F]Fenoprofen in TPA-treated or normal ear measured by ROIs hand-drawn on static <em>ex vivo</em> PET images. (I) Uptake of [<sup>18</sup>F]Fenoprofen in TPA-treated or normal ear measured by gamma counting.</p>
In Vivo Effects of Fibrinogen Concentrate (FC) Versus Cryoprecipitate on the Neonatal Fibrin Network Structure After Cardiopulmonary Bypass (CPB)
ClinicalTrials.gov study NCT03932240. IPD Sharing: YES. Countries: 1. Publications: 1.
Data and code from: Deep learning-based autonomous retinal vein cannulation in ex vivo porcine eyes
Open the record for dataset details and reuse information.
Comparison of physiologically based pharmacokinetic modeling platforms for developmental neurotoxicity in vitro to in vivo extrapolation
Open the record for dataset details and reuse information.
Recovery of the full in vivo firing range in post-lesion surviving DA SN neurons associated with Kv4.3-mediated pacemaker plasticity
Open the record for dataset details and reuse information.
Data from: Residues neighboring an SH3-binding motif participate in the interaction in vivo
Open the record for dataset details and reuse information.
In vivo and in vitro electrochemical impedance spectroscopy analysis of acute and chronic intracranial electrodes
Open the record for dataset details and reuse information.
In vivo expression of VCAM1 precedes nephron loss following kidney tubular necrosis
Open the record for dataset details and reuse information.
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.