CTLA-4 Gene Haplotypes and the Risk of Chronic Hepatitis C Infection; a Case Control Study.
Bibliographic record
Abstract
BACKGROUND: and HCV infection. METHODS: Restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) was performed as the genotyping assay at four different positions (+49 A>G, -318 C>T, -1722 T>C, and - 1661 A>G). Haplotypes were analyzed using PHASE software. Sixty-five HCV patients and 65 healthy individuals as controls who were referred to the hepatitis clinic in Mashhad, Iran, were recruited. Genomic DNA was extracted from whole blood of participants. RESULTS: In a dominant analysis model of the -1661 position (GG vs. AA+AG), the AA genotype was more common in controls than in patients (adjusted P = 0.0003; OR = 0.15, 95% CI = 0.051 -0.42). The GCAT haplotype was also more prevalent in controls than in patients (adjusted P = 0.01; OR = 0.40, 95% CI = 0.20-0.81). Furthermore, the ACGT/ACGT diplotype was more common in controls than in patients (P = 0.0037; OR = 0.15, 95% CI = 0.04-0.54). In addition, the ACGT/ACAT diplotype was more frequent in patients than controls (adjusted P =0.003; OR = 2.48, 95% CI = 1.37- 4.50). CONCLUSION: and certain haplotypes may affect the risk of HCV infection in our population, although a larger sample size may be required to confirm this association.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".