High Levels of Autoantibodies against Drug-metabolizing Enzymes in SLA/LP-positive AIH-1 Sera
Bibliographic record
Abstract
Autoimmune hepatitis type 1 (AIH-1) is characterized by the detection of smooth muscle autoantibodies, antinuclear antibodies and antineutrophil cytoplasmic autoantibodies, and AIH-2 is characterized by the presence of autoantibodies against LKM, which contain drug-metabolizing enzymes. In this study, we measured the levels of drug-metabolizing enzymes in AIH-1 patients (ANA-positive). We exhaustively investigated the level of autoantibodies against major CYPs and UDP-glucuronosyltransferases of typical phase II drug-metabolizing enzymes, a transporter (MDR1), and NADPH-cytochrome P450 reductase in 4 patients with AIH-1 and 6 controls, as a case report. Two (Patients 3 and 4) of the AIH patients exhibited high levels of autoantibodies, while two (Patients 1 and 2) of the patients and the controls did not. The levels of autoantibodies against CYP2C19, CYP2D6, CYP2E1, UGT1A6 and human liver microsomes in Patients 3 and 4 sera were over 2(3) times the levels in Patient 1, Patient 2 and the control sera. Meanwhile, the levels of autoantibodies against CYP1A2, CYP2A6, CYP2C9, UGT2B7, MDR1 and NADPH-cytochrome P450 reductase were 2-2(2) higher in Patients 3 and 4 than in the other subjects. We found that the pattern of elevation in the Patient 3 serum was not parallel with that in Patient 4. Thus, we found high levels of autoantibodies against drug-metabolizing enzymes in AIH-1 patients.
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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) | 0.001 | 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) | 0.000 | 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".