Molecular mechanisms underlying the synergistic induction of CXCL10 by LPS and IFN‐γ in human neutrophils
Bibliographic record
Abstract
The CXCL10 chemokine is a critical chemoattractant for the recruitment of activated Th1 and NK cells into inflammatory sites. CXCL10 is typically produced by myeloid cells in response to IFN-gamma, as well as by neutrophils, though the latter require a costimulation with IFN-gamma and LPS. In this study, we investigated the molecular mechanism(s) whereby IFN-gamma and TLR4 ligation synergize to induce CXCL10 expression in neutrophils. By primary transcript real-time PCR analysis, we demonstrate that the CXCL10 gene is transcriptionally induced by the LPS plus IFN-gamma combination in neutrophils, consistent with previous studies showing that increased CXCL10 gene expression does not reflect enhanced mRNA stability. The IFN-gamma-induced STAT1 activation and the lipopolysaccharide (LPS)-induced NF-kappaB activation were not enhanced if neutrophils were exposed to both stimuli, whereas both transcription factors were activated by IFN-gamma or LPS in monocytes. Finally, pharmacological inhibitors of NF-kappaB demonstrated its role in the induction of CXCL10 expression by LPS plus IFN-gamma in neutrophils, and by LPS or IFN-gamma in monocytes. Together, these results suggest that in neutrophils, the synergy observed between LPS and IFN-gamma toward CXCL10 gene expression likely reflects the cooperative induction of the NF-kappaB and STAT1 transcription factors by LPS and IFN-gamma, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".