Regulatory T Cells Control Vascular Adhesion Molecule Expression in Skin Under Inflammatory and Homeostatic Conditions
Bibliographic record
Abstract
OBJECTIVE: During skin inflammation, inhibition of adhesion of regulatory T cells (Tregs) to the dermal microvascular endothelium leads to exacerbation of inflammation, evidence that the dermal endothelium is a key target of the anti-inflammatory actions of Tregs. The aim of this study was to investigate the capacity of Tregs to control the expression of endothelial adhesion molecules in inflamed and resting skin. METHODS: mice. RESULTS: CHS induced upregulation of E-selectin and ICAM-1 but not P-selectin and VCAM-1. Elimination of Tregs following CHS challenge resulted in exacerbated skin inflammation and enhanced expression of E-selectin, P-selectin and ICAM-1 in the dermal microvasculature. Multiphoton imaging revealed that at this phase of the response, Tregs were enriched near blood vessels and underwent dynamic migration adjacent to the microvasculature. Additionally, in skin that was not undergoing hapten challenge, absence of Tregs also resulted in upregulation of E-selectin and ICAM-1 in skin vessels. CONCLUSIONS: These observations demonstrate that the microvascular endothelium is a target of the anti-inflammatory actions of Tregs in the skin, both during CHS and in steady-state skin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".