Transient growth factor expression via mRNA in lipid nanoparticles promotes hepatocyte cell therapy in mice
Bibliographic record
Abstract
Primary human hepatocyte (PHH) transplantation is a promising alternative to liver transplantation, whereby liver function could be restored by partial repopulation of the diseased organ with healthy cells. However, currently PHH engraftment efficiency is low and benefits are not maintained long-term. Here we refine two male mouse models of human chronic and acute liver diseases to recapitulate compromised hepatocyte proliferation observed in nearly all human liver diseases by overexpression of p21 in hepatocytes. In these clinically relevant contexts, we demonstrate that transient, yet robust expression of human hepatocyte growth factor and epidermal growth factor in the liver via nucleoside-modified mRNA in lipid nanoparticles, whose safety was validated with mRNA-based COVID-19 vaccines, drastically improves PHH engraftment, reduces disease burden, and improves overall liver function. This strategy may overcome the critical barriers to clinical translation of cell therapies with primary or stem cell-derived hepatocytes for the treatment of 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 | 0.001 |
| 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".