A novel T<sub>H</sub>17-type cell is rapidly increased in the liver in response to acetaminophen-induced liver injury: T<sub>H</sub>17 cells and the innate immune response
Bibliographic record
Abstract
Helper T (T(H)) cells are an important part of the adaptive immune system. It is hypothesized that one type of helper T-cell, T(H)17 cells, play an important role in idiosyncratic drug-induced liver failure, and it was found that interleukin (IL)-17, the signature cytokine of T(H)17 cells, was elevated in most patients with idiosyncratic drug-induced liver failure. However, it was also found that IL-17 was elevated in some patients with acetaminophen (APAP)-induced liver failure. It is unlikely that APAP-induced liver failure is mediated by the adaptive immune system, but there are other cells such as macrophages and natural killer (NK) cells that also produce IL-17. Therefore, the phenotype of cells that produce IL-17 was studied in a mouse model of APAP-induced liver toxicity. To the authors' surprise, it was found that most of the IL-17 producing cells in the liver were T(H)17 cells, and they were increased within hours of APAP treatment. This is too fast for a response of the adaptive immune system. These data suggest that T(H)17 cells can be part of the innate immune response; however, it is unclear what role they play in the pathogenesis of APAP-induced hepatotoxicity.
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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) | 0.003 | 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".