A case-control study in NAT2 gene polymorphism studies in patients diagnosed with acute myeloid leukemia
Bibliographic record
Abstract
INTRODUCTION: Acute myeloid leukemia (AML) is a clinically defined heterogeneous disease whose pathophysiology is currently unknown. The association of NAT2 acetylation profiles with human cancer risks, particularly with AML, was investigated in molecular epidemiological studies. Additionally, the NAT2 gene was carried out with acute lymphoid leukemia and other cancers. AIM: In this case-control study, C481T (rs1799929) and G857A (rs1799931) polymorphism studies were investigated in diagnosed AML patients in the Saudi population. METHODS: This case-control study included 100 AML patients and 100 control subjects recruited in Saudi Arabia. The C481T and G857A polymorphisms were genotyped using specific primers and restriction enzymes. Statistical analysis was performed on the AML patients and controls using chi-square tests, genotyping, and allele frequencies (odds ratios, 95% of confidence intervals, and P-values). RESULTS: Hardy Weinberg Equilibrium was determined to be both within and outside of the G857A and C481T polymorphisms. The allele and genotyping frequencies in AML and control subjects were analyzed, and the results corroborated the unfavorable connection with C481T (CC vs CT+TT; OR-1.12; (95% CIs: 0.64-1.96); P=0.67 and T vs C; OR-0.89; (95% CIs: 0.59-1.35) and P=0.60) and G857A polymorphisms (GG vs GA+AA; OR-1.50; (95% CIs: 0.83-2.71); P=0.17 and A vs G; OR-0.71; (95%CIs: 0.43-1.19) and P=0.19) in the NAT2 gene. CONCLUSION: The study results revealed a negative correlation as well as a protective factor for AML with the C481T and G857A polymorphisms in the NAT2 gene.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".