Chemoattractant Receptors and Lymphocyte Egress from Extralymphoid Tissue: Changing Requirements during the Course of Inflammation
Bibliographic record
Abstract
Memory/effector T cells traffic efficiently through extralymphoid tissues, entering from the blood and leaving via the afferent lymph. During inflammation, T cell traffic into the affected tissue dramatically increases; however, the dynamics and mechanisms of T cell exit from inflamed tissues are poorly characterized. In this study, we show, using both a mouse and a sheep model, that large numbers of lymphocytes leave the chronically inflamed skin. Many T cells capable of producing IFN-γ and IL-17 also entered the draining afferent lymph, demonstrating that memory/effector T cells egress from sites of inflammation. Whereas efficient egress from acutely inflamed skin required lymphocyte-expressed CCR7, chronic inflammation promoted significant CCR7-independent exit as well. Lymphocyte exit at late time points of inflammation was sensitive to pertussis toxin but was only partially affected by the drug FTY720, implying the contribution of alternative chemoattractant receptors other than spingosine 1-phosphate receptor 1. Our data show that CCR7 is an important receptor for lymphocyte egress from both resting and inflamed extralymphoid tissues, but that alternative exit receptors come into play during chronic inflammation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".