Common Hospital Ingredient Perfusate Equivalent to Standard Krebs–Henseleit Buffer with Serum Albumin Derived Perfusate in Negative Pressure Ventilation Ex Vivo Lung Perfusion
Bibliographic record
Abstract
Introduction Normothermic ex-vivo lung perfusion (EVLP) using negative pressure ventilation (NPV) and red blood cell-based perfusate solutions have been shown to decrease edema formation and pro-inflammatory cytokine production compared to positive pressure ventilation (PPV). We sought to develop a common hospital ingredient derived perfusate (CHIP) with equivalent functional and inflammatory characteristics to the standard Krebs–Henseleit buffer with 8% serum albumin derived perfusate (KHB-Alb) in order to improve access and reduce costs of ex vivo organ perfusion. Methods Porcine lungs were perfused using NPV-EVLP for 12 hours in a normothermic state, and were allocated to two groups: KHB-Alb (n=8) vs CHIP (n=4). Physiologic parameters, cytokine profiles, and edema formation were compared between treatment groups. Results Perfused lungs in both groups demonstrated equivalent oxygenation (partial pressure of arterial oxygen/ fraction of inspired oxygen ratio >350 mmHg) and physiologic parameters. There was equivalent generation of tumor necrosis factor-α, irrespective of perfusate solution used, when comparing CHIP vs KHB-Alb. Pig lungs developed equivalent edema formation between groups (CHIP: 15.7 ± 5.8%, STEEN 19.5 ± 4.4%, p>0.05). Conclusion A perfusate derived of common hospital ingredients provides equivalent results to standard Krebs–Henseleit buffer with 8% serum albumin based perfusate in NPV-EVLP. Canadian Institutes for Health Research - Canadian National Transplant Research Program (CIHR-CNTRP). University Hospital Foundation (UHF). Mazankowski Alberta Heart Institute - University Hospital Foundation Gerald Averback Award in Cardiovascular Gene Therapy / Genomics and Vascular Biology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".