Factors affecting hepatocyte isolation, engraftment, and replication in an in vivo model
Bibliographic record
Abstract
We congratulate Kawahara et al.1 on their excellent study published in Liver Transplantation.We read about their experiences with human hepatocyte isolation and the subsequent application of the isolated cells with keen interest. Our group also has good experience with human hepatocyte isolation.2 We have 2 points to raise with respect to this excellent study. The authors used human hepatocytes isolated from resected normal liver tissue in their study (51 cancer specimens and 39 specimens of benign etiology). Our data show that such hepatocytes differ in their response to hypoxia and hypoxia/reoxygenation in comparison with hepatocytes isolated from normal livers.2 Did the authors note any phenotypic differences between hepatocytes isolated from cancer specimens and those isolated from benign livers? Moreover, did this have a bearing on transplant success? Kawahara et al.1 stated that their initial experiences with the isolation of human hepatocytes from cirrhotic livers was poor in terms of viable cell yields and transplant success. In our laboratory, we isolate human hepatocytes from all explanted livers after transplantation (for primary biliary cirrhosis, primary sclerosing cholangitis, alcoholic liver cirrhosis, or metabolic liver disease), from donor livers exceeding surgical requirements, and from normal tissue obtained from hepatic resections (for metastatic disease). We do not isolate the hepatocytes of patients with a viral hepatic disease. Although we have not published our results yet, we can state that our overall success rate for attempted human hepatocyte isolation is 54%. Because we use all liver tissue that is available to us, we have viable cell yields of 20,000 to 5,000,000 cells/mL. Therefore, we suggest that cirrhotic livers could be a valuable source of human hepatocytes for experimental use. We concur with Kawahara et al. that human hepatocytes isolated from extended criteria donors are suitable for cell transplantation, but we also stress that human hepatocytes isolated from diseased livers can be a valuable source of cells for functional studies.2 We again congratulate the authors on their excellent work within this challenging area, and we hope that with continuing research in human hepatocyte isolation, clear parameters and protocols can be established so that hepatocytes can be harvested from all available livers. Ricky H. Bhogal M.R.C.S.Ed [email protected]*, Simon C. Afford Ph.D., FRCPath*, * Centre for Liver Research Institute for Biomedical Research University of Birmingham Birmingham, United Kingdom.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.002 |
| 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 teacher head, 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".