Mechanical ventilation-induced pneumoprotein CC-16 vascular transfer in rats: effect of KGF pretreatment
Bibliographic record
Abstract
After air-blood barrier injury, "pneumoproteins" specific to lung epithelial distal airspaces reaching the bloodstream are putative markers of lung hyperpermeability. The contribution of mechanical ventilation (MV) to this leakage is unknown. To explore this issue, 16-kDa Clara cell protein (CC-16) concentration was quantified in bronchoalveolar lavages (BALFs) and/or sera of rats first exposed either to ambient air or to 48 h of hyperoxia-induced acute lung injury and then ventilated for 2 h according to one of the following strategies: 1) spontaneous ventilation (SV), 2) very-low-volume high PEEP (VLVHP, where PEEP is positive end-expiratory pressure), 3) low-volume zero PEEP, 4) moderate-volume low PEEP, and 5) high-volume zero PEEP (HVZP). Results show that total proteins in BALFs increased with time and MV, with little impact from hyperoxia preexposure. CC-16 content decreased in BALFs but increased in the bloodstream during MV, suggesting intravascular leakage. Lung overdistension may result either from high-volume (HVZP) or high-PEEP (VLVHP) MV, and it was the most potent inducer of CC-16 leakage (P < 0.05 vs. SV). In the VLVHP group, pretreatment with keratinocyte growth factor was efficient in reducing blood CC-16 transfer.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".