Bibliographic record
Abstract
Intestinal transplantation has become an established therapeutic option that provides improved quality of life to patients with end-stage intestinal failure when total parenteral nutrition fails. Whereas this challenging life-saving intervention has shown exceptional growth over the past decade, illustrating the evolution of this complex and technical procedure from its preclinical origin in the mid-20th century to become a routine clinical practice today with several recent innovations, its success is hampered by multiple hurdles including technical challenges such as surgical manipulation during intestinal graft procurement, graft preservation and reperfusion damage, resulting in poor graft quality, graft rejection, post-operative infectious complications, and ultimately negatively impacting long-term recipient survival. Therefore, strategies to improve current intestinal transplantation protocol may have a significant impact on post-transplant outcomes. Carbon monoxide (CO), previously considered solely as a toxic gas, has recently been shown to be a physiological signaling molecule at low physiological concentrations with therapeutic potentials that could overcome some of the challenges in intestinal transplantation. This review discusses recent knowledge about CO in intestinal transplantation, the underlying molecular mechanisms of protection during intestinal graft procurement, preservation, transplantation and post-transplant periods. A section of the review also discusses clinical translation of CO and its challenges in the field of solid organ transplantation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".