CXCL10 contributes to p38-mediated apoptosis in primary T lymphocytes in vitro
Bibliographic record
Abstract
CXCL10 is part of the group of interferon-stimulated genes and it plays an important role during different viral infections by inducing cell activation, chemotaxis and lymphocyte priming toward the Th1 phenotype. In this study, we investigated in vitro the effects of CXCL10 in activated human primary T lymphocytes in terms of apoptosis or survival, and delineated the signaling pathways that are involved. CXCL10, in combination with IL-2 and/or IFNα, induces apoptosis in T lymphocytes. Moreover, CXCL10-induced activation of CXCR3 also triggers pro-survival signals that can be blocked by pertussis toxin. The analysis of the downstream signaling kinases shows that apoptosis is p38 MAPK-dependent and the pro-survival signals rely on the sustained activation of PI3K and the transient activation of Akt. On the other hand, the transient activation of p44/p42 ERK did not have an impact on T lymphocyte survival. We propose an immunological model in which CXCL10, together with other co-stimulating cytokines, participates in the activation of T lymphocytes, promotes survival and expansion of certain lymphocyte subsets, and induces chemotaxis toward the infected tissues. On the other hand, CXCL10 might contribute to the triggering of apoptosis in other subsets of T lymphocytes, including those lymphocytes that were transiently activated but later lacked the appropriate sets of specific co-stimulating signals to ensure their survival.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 |
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".