Reverse transcriptase activity in patients with primary biliary cirrhosis and other autoimmune liver disorders
Bibliographic record
Abstract
BACKGROUND: Patients with biliary disease make retroviral antibodies and the Human Betaretrovirus has been characterized in patients with primary biliary cirrhosis. AIM: To screen patients with autoimmune liver disease for evidence of retroviral infection. METHODS: Real-time reverse transcriptase polymerase chain reaction was used to detect Human Betaretrovirus, and a reverse transcriptase assay to measure reverse transcriptase activity in plasma. RESULTS: Using reverse transcriptase polymerase chain reaction, 24% of primary biliary cirrhosis samples were positive for Human Betaretrovirus when compared to 13% with autoimmune hepatitis, 5% of other liver diseases and 3% of the non-liver disease control subjects. Reverse transcriptase activity was found in 73% of patients with autoimmune hepatitis, 42% with primary biliary cirrhosis, 22% of liver patients without viral or autoimmune disease and 7% of subjects without liver disease. In patients with autoimmune liver disease, detection of reverse transcriptase activity was related to higher ALT levels, whereas others stabilized on immunosuppressive therapy either preliver or postliver transplantation were less likely to be reverse transcriptase-positive. CONCLUSIONS: Most patients with autoimmune hepatitis have detectable reverse transcriptase activity. Investigations will be required to assess whether this represents the expression of endogenous retroviruses and retrotransposable elements in inflamed tissue, or signifies the presence of exogenous retroviral infection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".