Hepatocyte Transplantation in the Long Evans Cinnamon Rat Model of Wilson's Disease
Bibliographic record
Abstract
Wilson's disease (WD), caused by a mutation in the P-type copper transporting ATPase (Atp7b) gene, results in excessive accumulation of copper in the liver. Long Evans Cinnamon rats (LEC) bear a mutation in the atp7b gene and share clinical characteristics of human WD. To explore hepatocyte transplantation (HT) as therapy for metabolic liver diseases, 8-week-old LEC rats (n = 12) were transplanted by intrasplenic injection of hepatocytes from donor Long Evans (LE) rats. Immunosuppression was maintained with intraperitoneal tacrolimus. The success of HT was monitored at 24 weeks of life. Serum aminotransferases and bilirubin peaked at 14-21 weeks in both HT rats and nontransplanted controls, but at 24 weeks, survival was 97% in LEC-HT versus 63% in controls. All transplanted rats showed restored biliary copper excretion and reduced liver iron concentration associated with increased ceruloplasmin oxidase activity. Liver tissue expressed atp7b mRNA (11.9 +/- 13.6%) indicative of engraftment of normal cells in 7 of 12 HT rats, associated with a reduced liver copper concentration compared to untreated LEC rats. Periportal islets of normal appearing hepatocytes, recognized by atp7b antibody, were observed in transplanted livers while lobular host cells showed persistent pleomorphic changes and inflammatory infiltrates. In conclusion, transplantation of normal hepatocytes prevented fulminant hepatitis, reduces chronic inflammation, and improved 6-month survival in LEC rats. Engraftment of transplanted cells, which express atp7b mRNA, repopulated the recipient liver with normal functional capacity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".