Combinatorial Guidance by CCR7 Ligands for T Lymphocytes Migration in Co-Existing Chemokine Fields
Bibliographic record
Abstract
Chemokines mediate the trafficking and positioning of lymphocytes in lymphoid tissues that is crucial for immune surveillance and immune responses. In particular, a CCR7 ligand, CCL21, plays important roles in recruiting T cells to secondary lymphoid tissues (SLT). Furthermore, CCL21 together with another CCR7 ligand, CCL19, direct the navigation and compartmentation of T cells within SLT. However, the distinct roles of these two chemokines for regulating cell trafficking and positioning are not clear. In this study, we explore the effect of co-existing CCL19 and CCL21 concentration fields on guiding T cell migration. Using microfluidic devices that can configure single and superimposed chemokine fields we show that under physiological gradient conditions, human peripheral blood T cells chemotax to CCL21 but not CCL19. Furthermore, T cells migrate away from the CCL19 gradient in a uniform background of CCL21. This repulsive migratory response is predicted by mathematical modeling based on the competition of CCL19 and CCL21 for CCR7 signaling and the differential ability of the two chemokines for desensitizing CCR7. These results suggest a new combinatorial guiding mechanism by CCL19 and CCL21 for the migration and trafficking of CCR7 expressing leukocytes.
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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 | 0.001 |
| 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 | 0.001 | 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".