Skin Metabolites Define a New Paradigm in the Localization of Skin Tropic Memory T Cells
Bibliographic record
Abstract
The localization of memory T cells to human skin is essential for long-term immune surveillance and the maintenance of barrier integrity. The expression of CCR8 during naive T cell activation is controlled by skin-specific factors derived from epidermal keratinocytes and not by resident dendritic cells. In this study, we show that the CCR8-inducing factors are heat stable and protease resistant and include the vitamin D3 metabolite 1α,25-dihydroxyvitamin D3 and PGE2. The effect of either metabolite alone on CCR8 expression was weak, whereas their combination resulted in robust CCR8 expression. Elevation of intracellular cAMP was essential because PGE2 could be substituted with the adenylyl cyclase agonist forskolin, and CCR8 expression was sensitive to protein kinase A inhibition. For effective induction, exposure of naive T cells to these epidermal factors needed to occur either prior to or during T cell activation even though CCR8 was only detected 4-5 d later in proliferating T cells. The importance of tissue environments in maintaining cellular immune surveillance networks within distinct healthy tissues provides a paradigm shift in adaptive immunity. Epidermal-derived vitamin D3 metabolites and PGs provide an essential cue for the localization of CCR8(+) immune surveillance T cells within healthy human 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".