Abstract 11465: Ultrafast Cooling With Total Liquid Ventilation Attenuates Multi-organ Failure and Sepsis-like Response After Experimental Shock Induced by Aortic Cross Clamping
Bibliographic record
Abstract
Introduction: Total liquid ventilation (TLV) provides ultrafast cooling and potent neuro- and cardioprotection after experimental cardiac arrest. Hypothesis: We determined whether it could also mitigate multi-organ failure and sepsis-like response after abdominal ischemia/reperfusion and subsequent shock. Methods: Anesthetized rabbits were submitted to 30 min of supracoeliac aortic cross-clamping and 300 min of reperfusion. They underwent a normothermic procedure (Control group) or rapid cooling toward 32-33°C with TLV started either before, during or after aortic clamping (PRE, PER and POST groups, respectively). TLV was maintained during 75 min after which rabbits were rapidly rewarmed and switched to conventional mechanical ventilation. Results: Control animals elicited a dramatic shock state with a low cardiac output, high demand in norepinephrine, liver failure and acute kidney injury. Cardiac output was gradually improved in POST, PER and PRE groups as compared to Control (53±3, 64±5, 90±10 and 36±8 ml/min/kg after 300 min, respectively; all p<0.05). A significant protection was also observed in the TLV groups regarding liver enzymes (ASAT, ALAT, L-FABP), acute kidney injury markers (nNAG, KIM-1, NGAL, β2-microglobulin) and renal function parameters (creatinine clearance and fractional Na+ excretion). The protection was maximal in the PRE group and achieved a lower extent in PER and POST groups when compared to Control. As example, urinary clearance of creatinine achieved 4.8±1.2, 1.3±0.9, 0.9±1.4 in PRE, PER and POST groups vs 0.5±0.4 ml/kg/min in Control (all p<0.05), respectively. Importantly, multi-organ failure was associated with elevated blood transcripts of inflammatory markers (e.g., IL-1β, IL-8, IL-10). This was attenuated in all groups submitted to TLV with no difference between PRE, PER and POST groups. As example, changes in IL-1β achieved 2.7±0.4, 3.8±0.4 and 3.2±1.1 in PRE, PER and POST groups vs 5.6±0.7 in Control (fold-change from baseline; p<0.05), respectively. Conclusions: Ultra-fast cooling with TLV attenuates shock and multi-organ failure in a model of abdominal ischemia/reperfusion. The cardiac, liver and renal protections but not anti-inflammatory effects depend upon the window of application.
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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 | 0.000 |
| 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) | 0.003 | 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".