Off-the-Shelf Engineered Liver Tissue Reverses Acute Liver Failure Without Immunosuppression
Bibliographic record
Abstract
Abstract There is an urgent need for effective solutions to replace liver functions in patients with acute liver failure (ALF). We describe here a human engineered liver tissue composed of induced pluripotent stem cell (iPSC)-derived liver organoids encapsulated within a non-degradable biomaterial. Unlike most stem cell–derived products, this encapsulated liver tissue (ELT) achieves functional maturation during manufacturing. When transiently implanted into the peritoneal cavity of immunocompetent mice with ALF, the human ELT improves survival, treats hepatic encephalopathy and promotes liver regeneration, without requiring immunosuppression. Based on robust processes and designed to overcome challenges such as foreign body reaction, loss of function and cryopreservation, the ELT does not require vascularization and provides immediate and long-lasting functional replacement. Once the liver regenerated, the ELT is explanted, leaving the subjects cured. Macroencapsulation prevents rejection by shielding the organoids from the host immune system, and minimizes the risk of tumorigenicity. The data shown demonstrate the ELT’s potential to be developed into a safe and effective off-the-shelf treatment that, if validated in upcoming clinical trials, could replace liver transplantation for many patients with ALF.
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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) | 0.002 | 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".