Albumin-expressing hepatocyte-like cells develop in the livers of immune-deficient mice that received transplants of highly purified human hematopoietic stem cells
Bibliographic record
Abstract
Rodent bone marrow cells can contribute to liver. If these findings are applicable to humans, marrow stem cells could theoretically be harvested from a patient and used to repair his/her damaged liver. To explore this potential, CD34(+) or highly purified CD34(+)CD38(-)CD7(-) human hematopoietic stem cells from umbilical cord blood and bone marrow were transplanted into immunodeficient mice. One month after transplantation, carbon tetrachloride (CCl(4)) was administered into the mice to induce liver damage and hepatocyte proliferation. Mice were analyzed in comparison with CCl(4)-injured mice that did not receive transplants and noninjured controls that received transplants with the same stem cell populations, one month after liver damage. Human-specific albumin mRNA and protein were expressed in the mouse liver and human albumin was detected in the serum of mice that had received CCl(4) injury. Human alpha-fetoprotein was never expressed, but in some mice, human cytokeratin 19 was expressed, which may indicate bile duct development in addition to the albumin-secreting hepatocyte-like cells. Human albumin was not expressed in the starting stem cell populations in injured mice that did not receive transplants nor in noninjured mice that had received transplants of human stem cells. Human albumin expression was detected only in CCl(4)-treated mice that received transplants of human stem cells, and recovery was increased by administration of human hepatocyte growth factor 48 hours after the CCl(4)-mediated liver injury. Our studies provide evidence that human "hematopoietic" stem/progenitor cell populations have the capacity to respond to the injured liver microenvironment by inducing albumin expression.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".