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Record W4295860542 · doi:10.1161/hyp.79.suppl_1.p317

Abstract P317: ANGIOTENSIN II INFUSION CAUSED EXPANSION OF ACTIVATED ð NATURAL KILLER T CELLS IN MESENTERIC VESSEL PERIVASCULAR ADIPOSE TISSUE OF MICE

2022· article· en· W4295860542 on OpenAlexaff
Olga Berillo, Kevin Comeau, Antoine Caillon, Séverine Leclerc, Brandon Shokoples, Ahmad Mahmoud, Grégor Andelfinger, Pierre Paradis, Ernesto L. Schiffrin

Bibliographic record

VenueHypertension · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineJewish General Hospital
Fundersnot available
KeywordsNatural killer T cellFlow cytometryCell sortingT cellMolecular biologyAdipose tissueCD28BiologyAngiotensin IICellImmunologyReceptorEndocrinologyImmune systemBiochemistry

Abstract

fetched live from OpenAlex

Introduction: The innate-like γδ T cells play a role in angiotensin II (AngII)-induced hypertension, vascular injury and T cell activation in perivascular adipose tissue (PVAT). Hypothesis: We hypothesized that single cell RNA sequencing (scRNA-seq) will reveal γδ T cell subpopulations in PVAT involved in hypertension, vascular injury and T cell activation. Methods: Male C57BL/6J mice were infused SC or not with 490 ng/kg/min AngII for 14 days (n=3). Hypertension was confirmed by tail cuff blood pressure measurement. Mesenteric vessels (MV) with PVAT were collected, lymph nodes removed, single cell suspension obtained and labeled with hashtag antibodies, T cells isolated by fluorescence-activated cell sorting, the 6 samples pooled in one tube, and scRNA libraries prepared with a Chromium Next GEM Single Cell 3’ Reagent Kit. Sequencing was done on an Illumina Novaseq 6000, and data analysed using Cell Ranger pipeline and Seurat tools. Cell subpopulations were validated by flow cytometry. Results: ScRNA-seq yielded 5,030 cells with 137,990 reads/cell and identified 11 T cell clusters. Subclustering of T cells expressing the T cell receptor (TCR) δ constant chain revealed 3 δ natural killer T (δNKT) (δNKT0, δNKT1 and activated δNKT cells) and 3 γδ T cell subpopulations ( Trgc1 low effector memory, TCR δ variable 4 + and apoptotic γδ T cells). AngII increased >2-fold the frequency of activated δNKT cells, and decreased by 74% δNKT0 cells. Gene expression profiling revealed that activated δNKT and δNKT0 cells could be identified using unique markers, Cd28 and Sell , respectively. Flow cytometry showed that TCRδ + CD28 + Sell - T cells were increased (393±57.2 vs 227±44.4 cells/MV-PVAT) and TCRδ + CD28 - Sell + T cells decreased (21.6±4.1 vs 45.3±4.10 cells/MV-PVAT) in MV-PVAT of AngII vs sham-treated mice. Conclusion: This study identified an activated δNKT cell subpopulation in MV-PVAT that may play a role in AngII-induced hypertension, vascular injury and T cell activation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.207
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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