Use of Nucleoside Modified mRNA Encoding Regenerative Factors Encapsulated with Lipid Nanoparticles to Alleviate Acute and Chronic Murine Liver Diseases
Bibliographic record
Abstract
The remarkable ability of the liver to regenerate by proliferation of mature hepatocytes constitutes the first mechanism of repair commonly named the hepatocyte‐driven regeneration. Yet, during chronic liver injury or acute severe hepatocyte death, proliferation of mature cells becomes exhausted. In these cases, alternative precursors of hepatocytes that derive from cholangiocytes have been identified in both human and rodent diseased livers. They are presently growing evidence of conversion of these cholangiocytes into hepatocytes as defined as the cholangiocyte‐driven regeneration. Despite these two mechanisms of liver repair, end stage liver disease remains the 12 th most common cause of death in the United States, begging for therapeutic strategies to harness mechanisms of liver regeneration. Here we demonstrate that delivery via nucleoside modified mRNA complexed to lipid nanoparticles (mRNA‐LNP) to the liver of the key hepatocyte mitogen hepatocyte growth factor (HGF) and epidermal growth factor (EGF) enhance hepatocyte‐driven repair, while delivery of vascular endothelial growth factor A (VEGFA) mRNA‐LNP promotes cholangiocyte‐driven repair. We confirm specific hepatotropism of mRNA‐LNP via intravenous injection of firefly luciferase encoding mRNA‐LNP, with protein expression lasting about 3 days. In the liver, virtually all hepatocytes are transfected along with a subpopulation of endothelial and Kupffer cells. In homeostasis, HGF mRNA‐LNP efficiently induce hepatocyte proliferation. In a chronic liver injury mouse model recapitulating non‐alcoholic fatty liver disease, injections of both HGF and EGF mRNA‐LNP sharply reverse steatosis and accelerate restoration of liver function. Likewise, HGF and EGF mRNA‐LNP accelerate liver regeneration after acetaminophen‐induced acute liver injury with rapid return to baseline alanine transaminase (ALT) levels. Transient delivery of VEGFA in acute and chronic injured mouse livers via mRNA‐LNP induces robust cholangiocyte conversion to hepatocytes as well as reversion of steatosis and fibrosis. This study introduces mRNA‐LNP as a potentially translatable safe therapeutic intervention to harness both hepatocyte‐ and cholangiocyte‐driven liver regeneration to ultimately treat human acute and 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) | 0.001 | 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".