Interferon‐γ amplifies airway smooth muscle‐mediated CD4+ T cell recruitment by promoting the secretion of C–X–C‐motif chemokine receptor 3 ligands
Bibliographic record
Abstract
Asthmatic airways feature increased ASM mass that is largely attributable to hyperplasia, and which potentially contributes to excessive airway narrowing. T cells induce ASMC proliferation via contact-dependent mechanisms in vitro that may have importance for asthmatic ASM growth, as CD4+ T cells infiltrate ASM bundles in asthmatic human airways. In this study, we used an in vitro migration assay to investigate the pathways responsible for the trafficking of human CD4+ T cells to ASM. ASMCs induced chemotaxis of activated CD4+ T cells, which was inhibited by the CXCR3 antagonist AMG487 and neutralizing antibodies against its ligands CXCL10 and 11, but not CCR3 or CCR5 antagonists. CXCR3 expression was upregulated among all T cells following anti-CD3/CD28-activation. CD4+ T cells upregulated CXCL9, 10, and 11 expression in ASMCs in an IFN-γ/STAT1-dependent manner. Disruption of IFN-γ-signaling resulted in reduced T cell migration, along with the inhibition of CD4+ T cell-mediated STAT1 activation and CXCR3 ligand secretion by ASMCs. ASMCs derived from healthy and asthmatic donors demonstrated similar T cell-recruiting capacities. In vivo CXCL10 and 11 expression by asthmatic ASM was confirmed by immunostaining. We conclude that the CXCL10/11-CXCR3 axis causes CD4+ T cell recruitment to ASM that is amplified by T cell-derived IFN-γ.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".