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1,545 results for “microenvironment”
Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease
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Data from: Vascular plants promote moss crust restoration by softening the microenvironment near soil surface in dryland ecosystems
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Tree diversity drives multiple facets of bee diversity via microenvironment
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Data from: Development of an adrenocortical cancer humanized mouse model to characterize anti-PD1 effects on tumor microenvironment
Context: While the development of immune checkpoint inhibitors has transformed treatment strategies of several human malignancies, research models to study immunotherapy in ACC are lacking. Objective: To explore the effect of anti-PD1 immunotherapy on the alteration of the immune milieu in ACC in a newly generated preclinical model and correlate with the response of the matched patient. Design, Setting and Intervention: To characterize the CU-ACC2-M2B patient-derived xenograft in a humanized mouse model, evaluate the effect of a PD-1 inhibitor therapy and compare to the CU-ACC2 patient with metastatic disease. Results: Characterization of the CU-ACC2-hu-CB-BRGS model confirmed ACC origin and match with the original human tumor. Treatment of the mice with pembrolizumab demonstrated significant tumor growth inhibition (TGI = 60%) compared to controls, which correlated with increased tumor infiltrating lymphocyte activity, with an increase of human CD8+ T cells (p<0.05), HLA-DR+ T cells (p<0.05) as well as Granzyme B+ CD8+ T cells (<0.001). In parallel, treatment of the CU-ACC2 patient, who had progressive disease, demonstrated a partial response with 79%-100% reduction in the size of target lesions, and no new sites of metastasis. Pre-treatment analysis of the patient's metastatic liver lesion demonstrated abundant intra-tumoral CD8+ T cells by immunohistochemistry. Conclusions: Our study reports the first humanized ACC PDX mouse model which may be useful to define mechanisms and biomarkers of response and resistance to immune-based therapies, to ultimately provide more personalized care for patients with ACC.
Data from: Epiphytes improve host plant water use by microenvironment modification
1. Epiphytes have the potential to modify the canopy environments in which they grow. Accurately evaluating the impact of epiphytes can be challenging, since plants without epiphytes may also otherwise differ from host plants, and experimental removal is impractical and difficult to replicate in many forests. 2. We studied the impacts of epiphytes (primarily fruticose lichens and Tillandsia spp.) on host plants (Eulychnia saint-pieana and Caesalpinia spinosa) in two fog ecosystems in Chile (Pan de Azucar) and Peru (Atiquipa). These desert ecosystems sustain very high epiphyte loads and depend heavily on fog-water inputs. Using a combination of artificial substrates and epiphyte removals we show significant impacts of epiphytes on their host plants. 3. The presence of epiphytes reduced throughfall volumes, reducing fog and rainfall inputs to the soil beneath host plant canopies. 4. Soil moisture loss rate was increased below cacti after removal of epiphytes from sun-facing but not shade-facing branches. This suggests epiphyte effects on hosts are microclimatic. 5. Epiphytes also buffered temperature fluctuations and reduced daytime vapour pressure deficit (VPD). 6. Epiphytes can have strong effects on host plant ecophysiology and forest ecosystem processes, making them an important component for models and studies of canopy environments.
Characterizing Spatially Continuous Variations in Tissue Microenvironment through Niche Trajectory Analysis - Dataset
<p><span>Recent technological developments have made it possible to map the spatial organization of a tissue at the single-cell resolution. However, computational methods for analyzing spatially continuous variations in tissue microenvironment are still lacking. Here we present ONTraC as a strategy that constructs niche trajectories using a graph neural network-based modeling framework. Our benchmark analysis shows that ONTraC performs more favorably than existing methods for reconstructing spatial trajectories. Applications of ONTraC to public spatial transcriptomics datasets successfully recapitulated the underlying anatomical structure, and further enabled detection of tissue microenvironment-dependent changes in gene regulatory networks and cell-cell interaction activities during embryonic development. Taken together, ONTraC provides a useful and generally applicable tool for the systematic characterization of the structural and functional organization of tissue microenvironments.</span></p>
MIHIC: A multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification
<p>A cohort of 47 TMA sections from 114 patients was collected from Liaoning cancer hospital \& Institute, where each TMA section has the size of 188,416$\times$110,080 pixels (i.e., 42660.87um$\times$24924.15um) at 40$\times$ magnification. TMA sections contain different number of tissue cores, ranging from 28 to 48. After excluding poor quality TMA sections with tissue folding, missing or contamination, there are totally 114 patients. Each patient has tissue cores with 12 different IHC stains, including CD3, CD20, CD34, CD38, CD68, CDK4, cyclin-D1, D2-40, FAP, Ki67, P53, and SMA. Two pathologists have manually labeled clear tissue regions (i.e., without controversy) in TMA sections based on visual examination via Qupath software, where six tissue types including Alveoli, Immune cells, Nerosis, Other, Stroma, Tumor were annotated. Besides the annotated six tissue types, we added one more Background type.</p> <p>To build histological classification models, we split 309,698 image patches in MIHIC dataset into three sets: training, validation and test. Note that image patches extracted from the same annotated tissue region are distributed into the same set, which avoids data leakage during classification model optimization. According to the number of extracted ROIs, train, val and test accounted for 64\%, 16\% and 20\%.</p> <h1>if you use this dataset, please cite:</h1> <pre>@article{wang2024mihic, title={MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification}, author={Wang, Ranran and Qiu, Yusong and Wang, Tong and Wang, Mingkang and Jin, Shan and Cong, Fengyu and Zhang, Yong and Xu, Hongming}, journal={Frontiers in Immunology}, volume={15}, year={2024}, publisher={Frontiers Media SA} }</pre>
Microenvironment characteristics and molecular classification in pheochromocytoma patients
<p>Pheochromocytomas (PCCs) are rare neuroendocrine tumors that originate from chromaffin cells in the adrenal gland. However, the cellular molecular characteristics and immune microenvironment of PCCs are incompletely understood. Here, we performed single-cell RNA sequencing (scRNA-seq) on 16 tissues from 4 sporadic unclassified PCC patients and 1 hereditary PCC patient with Von Hippel-Lindau (VHL) syndrome. We found that intra-tumoral heterogeneity was less extensive than the inter-individual heterogeneity of PCCs. Further, the unclassified PCC patients were divided into two types, metabolism-type (marked by NDUFA4L2 and COX4I2) and kinase-type (marked by RET and PNMT), validated by immunohistochemical staining. Trajectory analysis of tumor evolution revealed that metabolism-type PCC cells display phenotype of consistently active metabolism and increased metastasis potential, while kinase-type PCC cells showed decreased epinephrine synthesis and neuron-like phenotypes. Cell-cell communication analysis showed activation of the annexin pathway and a strong inflammation reaction in metabolism-type PCCs and activation of FGF signaling in the kinase-type PCC. Although multispectral immunofluorescence staining showed a lack of CD8<sup>+</sup> T cell infiltration in both metabolism-type and kinase-type PCCs, only the kinase-type PCC exhibited downregulation of <em>HLA-Ⅰ</em> molecules that possibly regulated by <em>RET</em>, suggesting the potential of combined therapy with kinase inhibitors and immunotherapy for kinase-type PCCs; in contrast, the application of immunotherapy to metabolism-type PCCs (with antigen presentation ability) is likely unsuitable. Our study presents a single-cell transcriptomics-based molecular classification and microenvironment characterization of PCCs, providing clues for potential therapeutic strategies to treat PCCs.</p>
Spatial Transcriptomics in Breast Cancer Reveals Tumour Microenvironment-Driven Drug Responses and Clonal Therapeutic Heterogeneity
<p>We acquired 10x Visium spatial transcriptomics (ST) data from 9 patients with invasive adenocarcinomas [1–5] to explore the role of the tumour microenvironment (TME) on intratumor heterogeneity (ITH) and drug response in breast cancer. By leveraging a new version of Beyondcell [6] (<a href="https://github.com/cnio-bu/beyondcell" target="_blank" rel="noopener">cnio-bu/beyondcell</a>), a tool for identifying tumour cell subpopulations with distinct drug response patterns, we predicted sensitivity to over 1,200 drugs while accounting for the spatial context and interaction between the tumour and TME compartments. Moreover, we also used Beyondcell to compute spot-wise functional enrichment scores and identify niche-specific biological functions.</p> <p>Here, you can find:</p> <p>In signatures folder:</p> <ul> <li><strong>SSc breast:</strong> Collection of gene signatures used to predict sensitivity to > 1,200 drugs derived from breast cancer cell lines.</li> <li><strong>Functional signatures:</strong> Collection of gene signatures used to compute enrichment in different biological pathways.</li> </ul> <p>In visium folder:</p> <ul> <li><strong>Visium objects:</strong> Processed ST Seurat objects with deconvoluted spots, SCTransform-normalised counts, and clonal composition predicted with SCEVAN [7]. These objects, together with the signatures, were used to compute the Beyondcell objects.</li> </ul> <p>In single-cell folder:</p> <ul> <li><strong>Single-cell objects:</strong> Raw and filtered merged single-cell RNA-seq (scRNA-seq) Seurat objects with unnormalised counts used as a reference for spot deconvolution.</li> </ul> <p>In beyondcell folder:</p> <ul> <li><strong>Beyondcell </strong><strong>sensitivity </strong><strong>objects</strong> with prediction scores for all drug response signatures in SSc breast.</li> <li><strong>Beyondcell functional objects </strong>with enrichment scores for all functional signatures.</li> </ul>
Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer
<p>The datasets included in the manuscript 'Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer'</p>
An uncommon garden experiment: microenvironment has stronger influence on phenotypic variation than epigenetic memory in the clonal Lombardy poplar
<p>Phenotypic and bioclimatic data for manuscript "An uncommon garden experiment: microenvironment has stronger influence on phenotypic variation than epigenetic memory in the clonal Lombardy popla<strong>r"</strong></p>
Supplementary Materials for Evaluation role of ferroptosis long non-coding RNAs for immune microenvironment and microsatellite instability in colon cancer
<p>Supplementary Materials for "Evaluation role of ferroptosis long non-coding RNAs for immune microenvironment and microsatellite instability in colon cancer"</p>
Engineering Micro Oxygen Factories to Slow Tumour Progression via Hyperoxic Microenvironments
<p>Imaging data of the paper</p>
A Riskscore Model for Predicting Survival, Tumor Microenvironment, Immunotherapy and drug sensitivity of Lung Squamous Cell Carcinoma Based on PI3K/AKT/MTOR Pathway-Related Genes
<p>Firstly, the data we provide is the raw data downloaded from the TCGA database. Secondly, we provide the following explanations for the raw data, taking Figure 1 as an example:</p> <p>First, we selected a LUSC dataset from the TCGA database that includes RNA-seq data (FPKM values) and clear clinical information, consisting of 51 normal samples and 501 LUSC samples. The raw data <span>can be found in</span> the "mRNA" document in the "Fig.1" file<span>, and t</span>he data includes TCGA <span>id</span> information.</p> <p>Next, the data was imported into "mRNA_edgeR" to analyze whether the RNA-seq data from these 552 samples meet the criteria of |logFC| > 0.585 and FDR < 0.05, <span>and the results are shown in</span> the "diffSig" table. Subsequently, the genes in the "diffSig" table were intersected with 105 PAGs, <span>and</span> 44 key PAGs <span>were identified, </span>as shown in Figure 1.</p> <p>The <span>other</span> figures can <span>also </span>be reproduced sequentially based on the methods described <span>above</span>.</p> <p>Furthermore, due to the limited number of LUSC patients, the clinical information in the database is relatively incomplete. Hence, the clinical information that we provide constitutes the entire content available in the database.</p>
Transcriptome profiling associated with CARD11 overexpres-sion in Colorectal Cancer implicates a potential role for Tumour Immune Microenvironment and Cancer pathways modulation via NF-κB
<p>tables for CARD11</p>
Dataset for the paper "Analyses of tumor microenvironment in patients with advanced renal cell carcinoma receiving immunotherapy(Meet-URO 18 study)."
<p>Dataset for the paper "Analyses of tumor microenvironment in patients with advanced renal cell carcinoma receiving immunotherapy(Meet-URO 18 study)."</p>
Transcriptome profiling associated with CARD11 overexpres-sion in Colorectal Cancer implicates a potential role for Tumour Immune Microenvironment and Cancer pathways modulation via NF-κB
<p>Images for CARD11 study in IJMS</p>
Single-cell transcriptome analysis reveals evolving tumor microenvironment induced by immunochemotherapy in nasopharyngeal carcinoma
<p>18 bulks and 11 single-cell RNA sequencing samples from paired before anti-PD-1 contained treatment and on treatment in patients with treatment-naive high-risk metastatic locally advanced NPCs were obtained. We aim to explore the mechanism of response heterogeneity for locally advanced NPCs underwent immunochemotherapy.</p>
Data from: Microenvironment and functional-trait context dependence predict alpine plant community dynamics
Predicting the structure and dynamics of communities is difficult. Approaches linking functional traits to niche boundaries, species co‐occurrence and demography are promising, but have so far had limited success. We hypothesized that predictability in community ecology could be improved by incorporating more accurate measures of fine‐scale environmental heterogeneity and the context‐dependent function of traits. We tested these hypotheses using long term whole‐community demography data from an alpine plant community in Colorado. Species distributions along microenvironmental gradients covaried with traits important for below‐ground processes. Positive associations between species distributions across life stages could not be explained by abiotic microenvironment alone, consistent with facilitative processes. Rates of growth, survival, fecundity and recruitment were predicted by the direct and interactive effects of trait, microenvironment, macroenvironment and neighbourhood axes. Synthesis. Context‐dependent interactions between multiple traits and microenvironmental axes are needed to predict fine‐scale community structure and dynamics.
IL-2 inside tumor microenvironment is essential and sufficient to reinvigorate CD8+ T cells
<p>The single-cell RNA seq data of day 10 and day 20. </p>
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.