An intestinal organoid–based platform that recreates susceptibility to T-cell–mediated tissue injury
Bibliographic record
Abstract
A goal in precision medicine is to use patient-derived material to predict disease course and intervention outcomes. Here, we use mechanistic observations in a preclinical animal model to design an ex vivo platform that recreates genetic susceptibility to T-cell-mediated damage. Intestinal graft-versus-host disease (GVHD) is a life-threatening complication of allogeneic hematopoietic cell transplantation. We found that intestinal GVHD in mice deficient in Atg16L1, an autophagy gene that is polymorphic in humans, is reversed by inhibiting necroptosis. We further show that cocultured allogeneic T cells kill Atg16L1-mutant intestinal organoids from mice, which was associated with an aberrant epithelial interferon signature. Using this information, we demonstrate that pharmacologically inhibiting necroptosis or interferon signaling protects human organoids derived from individuals harboring a common ATG16L1 variant from allogeneic T-cell attack. Our study provides a roadmap for applying findings in animal models to individualized therapy that targets affected tissues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".