Involvement of T Helper 17 Cells in D-Penicillamine–Induced Autoimmune Disease in Brown Norway Rats
Bibliographic record
Abstract
Idiosyncratic drug reactions (IDRs) are poorly understood, but their clinical characteristics suggest that they are immune mediated. Penicillamine-induced autoimmunity in Brown Norway rats has been utilized as an animal model for mechanistic studies of one type of IDR because it closely mimics the autoimmune syndromes that it causes in humans. Our previous work suggested that it is T-cell mediated. It has been shown that T helper 17 (Th17) cells play a central role in many types of autoimmune diseases. This study was designed to test whether Th17 cells are involved in the pathogenesis of penicillamine-induced autoimmunity and to establish an overall serum cytokine/chemokine profile for this IDR. In total, 24 serum cytokines/chemokines were determined and revealed a dynamic process. In sick animals, interleukin (IL) 6 and transforming growth factor-β1, known to be driving forces of Th17 differentiation, were consistently increased at both early and late stages of penicillamine treatment; however, no significant changes in these cytokines were observed in animals that did not develop autoimmunity. IL-17, a characteristic cytokine produced by Th17 cells, was increased in sick animals at both the messenger RNA and serum protein level. In addition, serum concentrations of IL-22, another characteristic cytokine produced by Th17 cells, were found to be elevated. Furthermore, the percentage of IL-17-producing CD4 T cells was significantly increased but only in sick animals. These data strongly suggest that Th17 cells are involved in penicillamine-induced autoimmunity. Such data provide important mechanistic clues that may help to predict which drug candidates will cause a relatively high incidence of such autoimmune IDRs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".