The JAK-STAT Pathway Is Critical in Ventilator-Induced Diaphragm Dysfunction
Bibliographic record
Abstract
Mechanical ventilation (MV) is one of the lynchpins of modern intensive-care medicine and is life saving in many critically ill patients. Continuous ventilator support, however, results in ventilation-induced diaphragm dysfunction (VIDD) that likely prolongs patients' need for MV and thereby leads to major associated complications and avoidable intensive care unit (ICU) deaths. Oxidative stress is a key pathogenic event in the development of VIDD, but its regulation remains largely undefined. We report here that the JAK-STAT pathway is activated in MV in the human diaphragm, as evidenced by significantly increased phosphorylation of JAK and STAT. Blockage of the JAK-STAT pathway by a JAK inhibitor in a rat MV model prevents diaphragm muscle contractile dysfunction (by ~85%, p < 0.01). We further demonstrate that activated STAT3 compromises mitochondrial function and induces oxidative stress in vivo, and, interestingly, that oxidative stress also activates JAK-STAT. Inhibition of JAK-STAT prevents oxidative stress-induced protein oxidation and polyubiquitination and recovers mitochondrial function in cultured muscle cells. Therefore, in ventilated diaphragm muscle, activation of JAK-STAT is critical in regulating oxidative stress and is thereby central to the downstream pathogenesis of clinical VIDD. These findings establish the molecular basis for the therapeutic promise of JAK-STAT inhibitors in ventilated ICU patients.
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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) | 0.002 | 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 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".