Three-Dimensional Collagen Matrix Scaffold Implantation as a Liver Regeneration Strategy
Bibliographic record
Abstract
Liver diseases are the leading cause of death worldwide. Excessive alcohol consumption, a high-fat diet, and hepatitis C virus infection promote fibrosis, cirrhosis, and/or hepatocellular carcinoma. Liver transplantation is the clinically recommended procedure to improve and extend the life span of patients in advanced disease stages. However, only 10% of transplants are successful, with organ availability, presurgical and postsurgical procedures, and elevated costs directly correlated with that result. Extracellular matrix (ECM) scaffolds have emerged as an alternative for tissue restoration. Biocompatibility and graft acceptance are the main beneficial characteristics of those biomaterials. Although the capacity to restore the size and correct function of the liver has been evaluated in liver hepatectomy models, the use of scaffolds or some kind of support to replace the volume of the extirpated liver mass has not been assessed. Partial hepatectomy was performed in a rat liver with the xenoimplantation of a collagen matrix scaffold (CMS) from a bovine condyle. Left liver lobe tissue was removed (approximately 40%), and an equal proportion of CMS was surgically implanted. Liver function tests were evaluated before and after the surgical procedure. After days 3, 14, and 21, the animals were euthanized, and macroscopic and histologic evaluations were performed. On days 3 and 14, adipose tissue was observed surrounding the CMS, with no clinical evidence of rejection or infection, as was vessel neoformation and CMS reabsorption at day 21. There was histologic evidence of an insignificant inflammation process and migration of adjacent cells to the CMS, observed with the hematoxylin and eosin (H&E) and Masson's trichrome staining. The CMS was shown to perform well in liver tissue and could be a useful alternative for studying tissue regeneration and repair in chronic liver diseases.
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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) | 0.000 | 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".