Network pharmacology of JAK inhibitors
Bibliographic record
Abstract
Small-molecule inhibitors of the Janus kinase family (JAKis) are clinically efficacious in multiple autoimmune diseases, albeit with increased risk of certain infections. Their precise mechanism of action is unclear, with JAKs being signaling hubs for several cytokines. We assessed the in vivo impact of pan- and isoform-specific JAKi in mice by immunologic and genomic profiling. Effects were broad across the immunogenomic network, with overlap between inhibitors. Natural killer (NK) cell and macrophage homeostasis were most immediately perturbed, with network-level analysis revealing a rewiring of coregulated modules of NK cell transcripts. The repression of IFN signature genes after repeated JAKi treatment continued even after drug clearance, with persistent changes in chromatin accessibility and phospho-STAT responsiveness to IFN. Thus, clinical use and future development of JAKi might need to balance effects on immunological networks, rather than expect that JAKis affect a particular cytokine response and be cued to long-lasting epigenomic modifications rather than by short-term pharmacokinetics.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".