Mechanical ventilation during experimental sepsis increases deposition of advanced glycation end products and myocardial inflammation
Bibliographic record
Abstract
INTRODUCTION: Increasing evidence links advanced glycation end products (AGE) including Nepsilon-(carboxymethyl)lysine (CML) to the development of heart failure. Accumulation of AGE leads to myocardial inflammation, which is considered as one of the possible mechanisms underlying sepsis-induced cardiac dysfunction. We hypothesized that mechanical ventilation (MV) augmented sepsis-induced myocardial CML deposition and inflammation. METHODS: Sepsis was induced using a modified cecal ligation and perforation (CLP) technique in 36 male adult Sprague Dawley rats. Rats were randomized to four hours of MV with low tidal volume (LTV: 6 ml/kg, PEEP 5 cmH2O, n = 10) or high tidal volume (HTV: 15 ml/kg, PEEP 3 cmH2O, n = 10) 24 hours after the induction of sepsis. Eight rats served as septic, non-ventilated controls and eight as non-septic, non-ventilated controls. After 28 hours all rats were killed. The number of extravascular polymorphonuclear (PMN) leucocytes, macrophages, and lymphocytes was measured as the number of positive cells/mm2. The number of CML positive endothelial cells were semi-quantified based upon an intensity score. The CML intensity score was correlated with the number of inflammatory cells to study the association between CML depositions and inflammation. RESULTS: Gas exchange was comparable between the ventilated groups. Sepsis induced a significant increase in CML deposition in both ventricles that was significantly augmented by MV compared with non-ventilated septic controls (left ventricle 1.1 +/- 1.0 vs 0.7 +/- 0.1, P = 0.030; right ventricle 2.5 +/- 0.5 vs 0.6 +/- 0.1, P = 0.037), irrespective of ventilatory strategy. In the right ventricle there was a non-significant tendency towards increased CML deposition in the HTV group compared with septic, non-ventilated controls (1.0 +/- 0.1 vs 0.7 +/- 0.09, P = 0.07). Sepsis induced a significant increase in the number of macrophages and PMNs compared with non-ventilated septic controls that was augmented by MV, irrespective of ventilatory strategy. CML deposition was significantly correlated with the number of macrophages and PMNs in the heart. CONCLUSIONS: Sepsis induces CML deposition in the heart with a predominant right ventricular inflammation that is significantly augmented by MV, irrespective of the ventilatory strategy.
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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".