CD28-expressing δ T cells are increased in perivascular adipose tissue of hypertensive mice and in subcutaneous adipose tissue of obese humans
Bibliographic record
Abstract
OBJECTIVES: γδ T-lymphocytes play a role in angiotensin II (AngII)-induced hypertension, vascular injury and T-cell infiltration in perivascular adipose tissue (PVAT) in mice. Mesenteric arteries of hypertensive mice and subcutaneous arteries from obese humans present similar remodeling. We hypothesized that γδ T-cell subtypes in mesenteric vessels with PVAT (MV/PVAT) from hypertensive mice and subcutaneous adipose tissue (SAT) from obese humans, who are prone to develop hypertension, would be similar. METHODS: Mice were infused with AngII for 14 days. MV/PVAT T-cells were used for single-cell RNA-sequencing (scRNA-seq). scRNA-seq data (GSE155960) of SAT CD45 + cells from three lean and three obese women were downloaded from the Gene Expression Omnibus database. RESULTS: δ T-cell subclustering identified six δ T-cell subtypes. AngII increased T-cell receptor δ variable 4 ( Trdv4 ) + γδ T-effector memory cells and Cd28high δ T EM -cells, changes confirmed by flow cytometry. δ T-cell subclustering identified nine δ T-cell subtypes in human SAT. CD28 expressing δ T-cell subclustering demonstrated similar δ T-cell subpopulations in murine MV/PVAT and human SAT. Cd28+ γδ NKT EM and Cd28high δ T EM -cells increased in MV/PVAT from hypertensive mice and CD28high δ T EM -cells in SAT from obese women compared to the lean women. CONCLUSION: Similar CD28 + δ T-cells were identified in murine MV/PVAT and human SAT. CD28 high δ T EM -cells increased in MV/PVAT in hypertensive mice and in SAT from humans with obesity, a prehypertensive condition. CD28 + δ T-lymphocytes could have a pathogenic role in human hypertension associated with obesity, and could be a potential target for therapy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".