An In‐Vitro Model of T Cell Exit from the T Cell Zone Mediated by Sub‐Regional Co‐Existing CCL19 and CCL21 Fields in Lymph Nodes
Bibliographic record
Abstract
Chemokines CCL19, CCL21 and their receptor CCR7 are known key mediators for T lymphocyte recruitment to lymph nodes (LNs) and navigation within LNs. The current model of T cell exit from LNs requires additional guiding signals. However, a critical mechanism is missing to facilitate T cell exit from the T cell zone (TCZ). Based on our previous experimental and modeling studies, we propose that LNs sub‐regional CCL19 and CCL21 fields mediate T cell exit from the TCZ through CCR7 signaling. In the present study, we analyzed CCL19 and CCL21 distribution profiles in different LNs sub‐regions of mouse LNs sections by immuno‐fluorescent staining and confocal microscopy, and our results conceptually support the hypothesized LNs sub‐regional CCL19 and CCL21 fields. Furthermore, we established an in‐vitro model to quantitatively examine the migration of activated human blood T cells in simulated LNs sub‐regional CCL19 and CCL21 fields followed by cell surface CCR7 expression analysis using a previously described microfluidic system. Our results suggest that CCL19 and CCL21 mediate T cells migration in LNs sub‐regions. In particular, the results suggest the sequential actions by specific co‐existing CCL19 and CCL21 fields in the TCZ periphery and in the region further beyond for mediating T cell exit from TCZ, which is correlated with altered surface CCR7 expression. This research was funded by NSERC, CFI and MHRC.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".