<scp>CD4</scp> <sup>+</sup> T cell‐derived <scp>IFN</scp> ‐γ and <scp>LIGHT</scp> synergistically upregulate chemokine production from airway smooth muscle cells
Bibliographic record
Abstract
Abstract Airway smooth muscle (ASM) remodeling in asthmatic airways may contribute to persistent airflow limitation and airway hyperresponsiveness. CD4 + T cells infiltrate the ASM layer where they may induce a proliferative and secretory ASM cell phenotype. We studied the interaction between activated CD4 + T cells and ASM cells in co‐culture in vitro and investigated the effects of CD4 + T cells on chemokine production by ASM cells. CD4 + T cells induced marked upregulation of C‐X‐C motif chemokine ligands (CXCL) 9, 10, and 11 in ASM cells. Blockade of the IFN‐γ receptor on ASM cells prevented this upregulation. Furthermore, T cell‐derived IFN‐γ and LIGHT (lymphotoxin, exhibits inducible expression and competes with HSV glycoprotein D for binding to herpesvirus entry mediator, a receptor expressed on T lymphocytes) synergize in a dose‐dependent manner to coordinately enhance CXCL9, 10, and 11 expression. The synergistic property of LIGHT was mediated exclusively through the lymphotoxin‐β receptor (LTBR), but not herpes virus entry mediator (HVEM). Disruption of LTBR signaling in ASM cells reduced CXCL9, 10, and 11 production and ASM cell‐mediated CD4 + T cell chemotaxis. We conclude that the LIGHT‐LTBR signaling axis acts together with IFN‐γ to regulate chemokines that mediate lymphocyte infiltration in asthmatics.
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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) | 0.005 | 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".