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3,329 results for “heterogeneity”
Heterogeneous Habenular Neuronal Ensembles during Selection of Defensive Behaviors
<p>Optimal selection of threat-driven defensive behaviors is paramount to an animal's survival. The lateral habenula (LHb) is a key neuronal hub coordinating behavioral responses to aversive stimuli. Yet, how individual LHb neurons represent defensive behaviors in response to threats remains unknown. Here, we show that in mice, a visual threat promotes distinct defensive behaviors, namely runaway (escape) and action-locking (immobile-like). Fiber photometry of bulk LHb neuronal activity in behaving animals reveals an increase and a decrease in calcium signal time-locked with runaway and action-locking, respectively. Imaging single-cell calcium dynamics across distinct threat-driven behaviors identify independently active LHb neuronal clusters. These clusters participate during specific time epochs of defensive behaviors. Decoding analysis of this neuronal activity reveals that some LHb clusters either predict the upcoming selection of the defensive action or represent the selected action. Thus, heterogeneous neuronal clusters in LHb predict or reflect the selection of distinct threat-driven defensive behaviors.</p>
Heterogeneous environmental seascape across a biogeographic break influences the thermal physiology and tolerances to ocean acidification in an ecosystem engineer
<p>Dataset for the metabolic rates of limpets under two different pCO2/pH conditions</p> <p>MR are in O2 mg h−1g−1</p>
Clonal heterogeneity of endocrine therapy resistance in breast cancer
<p>We barcoded endocrine therapy sensitive cell lines (MCF7 and T47D) and rendered them resistant to commonly applied first line endocrine therapeutics (Tamoxifen and estrogen deprivation). Next, we isolated single cell clones of endocrine therapy resistant populations and subjected clonal cell lines to RNA-Seq and Phosphoproteomics profiling.</p>
High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas
<p>We present the design of a digital phantom that tries to overcome the problems of the current PET digital brain phantoms, particularly for the simulation of simultaneous PET-MRI data sets. We propose a new brain digital brain phantom based on the BigBrain atlas, a free, publicly available tool that provides considerable neuroanatomical insight into the human brain with an ultrahigh-resolution 3D model of a human brain at nearly cellular resolution of 20 micrometers. We used the histology maps, the classified tissue maps and the MRI image of the BigBrain atlas, as well as the Hammersmith atlas and a PET [18F]FDG template as inputs to create an instance of this ultra high-resolution heterogeneous PET-MRI phantom.</p> <p>Full details of this phantom in Medical Physics: "Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas", <a href="https://doi.org/10.1002/mp.14218">10.1002/mp.14218.</a></p> <p>You can find codes examples for reading the data at https://github.com/mabelzunce/PETBrainPhantoms </p> <p>Please cite this paper if you use this phantom in your work:</p> <p>Belzunce, M.A. and Reader, A.J. (2020), Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas. Med. Phys., 47: 3356-3362. doi:<a href="https://doi.org/10.1002/mp.14218">10.1002/mp.14218</a></p>
Supplementary Movies and Source Data for: Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation
<p>Supplementary Movies and raw data for the manuscript: "Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation":</p> <p>Source_Data.zip: Supplementary Code, Supplementary Data and Weka Analysis</p> <p>Lan_supplementary_movies_AVI.zip: Supplementary movies as AVI</p> <p>Lan_supplementary_movies_MP4.zip: Supplementary movies as MP4</p> <p>Lan_raw_movies.zip: Raw TIFF stacks of the movies.</p> <p>Lan_supplementary_movies.zip: Old version of the movies.</p>
Code and data for manuscript: Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.
<p>This is the source code and data required to reproduce data analysis and figures from the manuscript, "Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir". </p>
Data from Citizen science data reveal regional heterogeneity in phenological response to climate in the large milkweed bug, Oncopeltus fasciatus
These data include annotations for life stage, mating behavior, and plant part occupancy of large milkweed bug observations in North America as well as information about climate and environment.
Temporal heterogeneity increases with spatial heterogeneity in ecological communities
Heterogeneity is increasingly recognized as a foundational characteristic of ecological systems. Indeed, spatial heterogeneity is commonly used in alternative state theory as an early indicator of regime shifts. To evaluate if spatial heterogeneity of communities is a predictor of temporal heterogeneity, we used mixed effects models to synthesize 68 community datasets spanning freshwater and terrestrial systems where measures of species abundance were replicated over space and time. Overall, we found a significant positive relationship between spatial and temporal heterogeneity across all ecosystems. In addition, lifespan and successional stage were related to temporal heterogeneity. Therefore we found evidence that spatial heterogeneity is a potential tool to predict temporal heterogeneity in ecological communities. This data package consists of six files. First we used a (1) R script to derive community dynamic metrics from source files to calculate (2) spatial and temporal heterogeneity over time as well as other measures of the community. We used this derived dataset to run analyses (3) with a R script to study the relationship between spatial and temporal heterogeneity communities. These analyses resulted in three figures, (4) the overall relationship between spatial and temporal heterogeneity, (5) output of mixed models investigating how experimental and biological factors affect this relationship, and (6) figures exploring how lifespan of the study organism affects the relationship between spatial and temporal datasets.
Fig. 5 in Fish beta diversity responses to environmental heterogeneity and flood pulses are different according to reproductive guild
Fig. 5. Relationship between beta diversity (mean distance to centroid), environmental heterogeneity and period of the hydrological cycle. a. Beta diversity of non-migratory fish species with external fertilization and parental care (NEFC); b. beta diversity of non-migratory fish species with internal fertilization (NIF).
Fig. 4 in Fish beta diversity responses to environmental heterogeneity and flood pulses are different according to reproductive guild
Fig. 4. Beta diversity variation among the guilds. The boxes represent the interquartile ranges, the horizontal lines indicate the medians, the bars indicate the minimum and maximum values, and the closed diamonds represent the mean beta diversity of each guild. LMEF: long-distance migratory and external fertilization; NEFC: non-migratory with external fertilization and parental care; NEFW: nonmigratory with external fertilization without parental care; NIF: non-migratory with internal fertilization; DET: detritivorous; HER: herbivorous; INS: insectivorous; INV: invertivorous; ONI: omnivorous; and PIS: piscivorous.
Fig. 2 in Fish beta diversity responses to environmental heterogeneity and flood pulses are different according to reproductive guild
Fig. 2. Hydrometric-level (a) and environmental heterogeneity (b) variation between 2000 and 2012 in the Paraná River. The horizontal black dashed line indicates the flood level of the floodplain. Source: ANA - Estação Fluviométrica of Porto São José, PR.
Data for "Plasmon excitations in chemically heterogeneous nanoarrays"
<p>The data includes atomic structures, photoabsorption spectra, and noninteracting spectra of the systems modeled in the article "Plasmon excitations in chemically heterogeneous nanoarrays" by Kevin Conley <em>et al</em>.</p> <p>See <em>README.md</em> in the archive for a detailed description.</p>
Data from: Using genetic relatedness to understand heterogeneous distributions of urban rat-associated pathogens
<p>Urban Norway rats (<i>Rattus norvegicus</i>) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape, and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada and used 1,495 genome-wide single nucleotide polymorphisms to identify parent-offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens <i>Leptospira interrogans</i>, <i>Bartonella tribocorum</i>, and <i>Clostridium difficile</i>, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. <span>Our findings also highlight the utility of evolutionary tools to understand movement and rat-associated health risks in urban landscapes.</span></p>
Figure 3 in Genetic and morphological heterogeneity within Eucyclops serrulatus (Fischer, 1851) (Crustacea: Copepoda: Cyclopidae)
Figure 3. Eucyclops serrulatus (Fischer) from the Dniester Liman (A, C, E) and Zakarpattia regions (B, D, F) of Ukraine. (A, B) P4, caudal side with feature abbreviations used; (C, D) antenna, caudal side; (E, F) caudal ramus with abbreviations.
Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq
<p><strong><a href="https://gitlab.com/bu_cnio/Beyondcell">Beyondcell</a> </strong>is a methodology for the identification of drug vulnerabilities in single cell RNA-seq data. To this end, <strong>Beyondcell</strong> focuses on the analysis of drug-related commonalities between cells by classifying them into distinct therapeutic clusters. We have validated the tool in a population of MCF7-AA cells exposed to 500nM of bortezomib and collected at different time points: t0 (before treatment), t12, t48 and t96 (72h treatment followed by drug wash and 24h of recovery) obtained from <a href="https://www.nature.com/articles/s41586-018-0409-3"><strong><em>Ben-David U, et al., Nature, 2018</em></strong></a>. Here, you can find the integrated Seurat object obtained from this analysis. This object is meant to help users follow <strong>Beyondcell's</strong> <a href="https://gitlab.com/bu_cnio/Beyondcell/-/tree/master/tutorial/analysis_workflow">analysis workflow</a>.</p> <p> </p>
The imprint of crustal density heterogeneities on regional seismic wave propagation - dataset
<p>This dataset should provide complete synthetic seismograms and software</p> <p>(python tools for random media generation, signal comparison and histogram stacking)</p> <p>that were used in the publication:</p> <p>Płonka, A., Blom, N., and Fichtner, A.: The imprint of crustal density heterogeneities on regional seismic wave propagation, Solid Earth, 7, 1591-1608, doi:10.5194/se-7-1591-2016, 2016.</p>
Single-cell mouse and PC9 data for "TP53 loss with whole genome doubling mediates heterogeneous intra-patient therapy response through Chromosomal Instability"
<p>This repository includes the processed data (including copy number profiles and related analysis) for the E/EP mouse tumors and for the PC9 resistance cell lines for all the analyses of the manuscript "TP53 loss with whole genome doubling mediates heterogeneous intra-patient therapy response through Chromosomal Instability".</p><p>The code for the related analyses is available in GitHub at https://github.com/zaccaria-lab/TP53loss_WGD</p>
Quantification of soil organic carbon: the challenge of biochar-induced spatial heterogeneity
<p>R-script and output from model on spatially discrete biochar application and its influence on representative SOC sampling. An additional document to explain the data curation is also available ("Comment on Data curation").</p><p> </p>
Heterogeneity of synaptic connectivity in the fly visual system
<p>Source data of the paper Cornean, Molina-Obando et al. 2024, Nature Communications. This work contains an analysis of synaptic connectivity in the Drosophila system, focusing on the presynaptic circuitry of three medulla interneurons, Tm9, Tm1, and Tm2.<br>Synaptic connectivity was analyzed using the FAFB dataset (Zheng et al. 2018 Cell) and the Flywire connectome (Schlegel et al. 2023 bioRxiv, Dorkenwald et al. 2023 bioRxiv), as well as expansion microscopy. This analysis is supplement by some functional analysis using in vivo 2-photon calcium imaging. <br><br>Connectomics data used for this study are provided as .xlsx and .text files containing raw and processed data. <br>Expansion microscopy are uploaded as .tiff files containing raw data, as well as .nrrd and .csv files containing processed data.<br>Calcium imaging data are provided at .mat files containing both raw and processed data, as well as .xml files with information about the experimental protocol.</p><p>Please find all relevant information to use the code in the README files.</p><p>The code to analyze the data, either written in Matlab or Python, is found at https://github.com/silieslab/Cornean_Molina-Obando_etal_2024.git</p>
Local grafting heterogeneities control water intrusion and extrusion in nanopores
<p>Datasets and scripts used to generate data.</p>
ScienceDex guides
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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.