Inhibition of Poly(Adenosine Diphosphate–Ribose) Polymerase Attenuates Ventilator-induced Lung Injury
Bibliographic record
Abstract
BACKGROUND: Mechanical ventilation can induce organ injury associated with overwhelming inflammatory responses. Excessive activation of poly(adenosine diphosphate-ribose) polymerase enzyme after massive DNA damage may aggravate inflammatory responses. Therefore, the authors hypothesized that the pharmacologic inhibition of poly(adenosine diphosphate-ribose) polymerase by PJ-34 would attenuate ventilator-induced lung injury. METHODS: Anesthetized rats were subjected to intratracheal instillation of lipopolysaccharide at a dose of 6 mg/kg. The animals were then randomly assigned to receive mechanical ventilation at either low tidal volume (6 ml/kg) with 5 cm H2O positive end-expiratory pressure or high tidal volume (15 ml/kg) with zero positive end-expiratory pressure, in the presence and absence of intravenous administration of PJ-34. RESULTS: The high-tidal-volume ventilation resulted in an increase in poly(adenosine diphosphate-ribose) polymerase activity in the lung. The treatment with PJ-34 maintained a greater oxygenation and a lower airway plateau pressure than the vehicle control group. This was associated with a decreased level of interleukin 6, active plasminogen activator inhibitor 1 in the lung, attenuated leukocyte lung transmigration, and reduced pulmonary edema and apoptosis. The administration of PJ-34 also decreased the systemic levels of tumor necrosis factor alpha and interleukin 6, and attenuated the degree of apoptosis in the kidney. CONCLUSION: The pharmacologic inhibition of poly(adenosine diphosphate-ribose) polymerase reduces ventilator-induced lung injury and protects kidney function.
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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) | 0.001 | 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".