Making sense of IL‐6 signalling cues in pathophysiology
Bibliographic record
Abstract
Unravelling the molecular mechanisms that account for functional pleiotropy is a major challenge for researchers in cytokine biology. Cytokine-receptor cross-reactivity and shared signalling pathways are considered primary drivers of cytokine pleiotropy. However, reports epitomized by studies of Jak-STAT cytokine signalling identify interesting biochemical and epigenetic determinants of transcription factor regulation that affect the delivery of signal-dependent cytokine responses. Here, a regulatory interplay between STAT transcription factors and their convergence to specific genomic enhancers support the fine-tuning of cytokine responses controlling host immunity, functional identity, and tissue homeostasis and repair. In this review, we provide an overview of the signalling networks that shape the way cells sense and interpret cytokine cues. With an emphasis on the biology of interleukin-6, we highlight the importance of these mechanisms to both physiological processes and pathophysiological outcomes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".