Understanding the Mechanisms of Human Liver regeneration via Characterization of Circulating Extracellular Vesicles
Bibliographic record
Abstract
Purpose Liver transplantation is a life-saving intervention for end-stage liver disease. Improved understanding of normal liver regeneration is crucial to improving the lives of patients with liver disease. Our study aims to identify circulating extracellular vesicles associated with liver regeneration in humans and mice, explore their roles, and evaluate their potential as biomarkers of regeneration.Methods: Plasma samples from 28 humans and 22 mice were collected at regenerating and non-regenerating time points post-transplant. MicroRNA was extracted from small extracellular vesicles in plasma and analyzed using NanoString. MirDIP and STRING were used to analyze miRNA target genes involved in regenerative pathways like Hippo and cell cycle. Results: Twenty-five differentially expressed miRNAs were identified from human plasma and thirty in mouse plasma. Putative target genes of these miRNA overlap with genes involved in cell cycle and Hippo pathways. Conclusion: Small extracellular vesicle-associated miRNA can potentially serve as non-invasive biomarkers of liver regeneration.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".