The communal relation of <i>MTHFR</i>, <i>MTR</i>, <i>ACE</i> gene polymorphisms and hyperhomocysteinemia as conceivable risk of coronary artery disease
Bibliographic record
Abstract
, independently or in combination, are associated with CAD risk. A total of 504 participants were recruited (cases, n = 254; controls, n = 250, respectively). Tetra primer allele refractory mutation system polymerase chain reaction (PCR) was used for resolving the genotypes of 5'10' methylenetetrahydrofolate reductase 'MTHFR' polymorphisms (rs1801133, rs1801131), 5' methyl tetrahydrofolate homocysteine methyltransferase 'MTR' polymorphism (rs1805087), paroxanse1 'PON1' polymorphism (rs662), and cystathionine beta synthase 'CBS' polymorphism (rs5742905). Conventional PCR amplification was carried out for resolving angiotensin converting enzyme 'ACE' insertion/deletion (I/D) polymorphism (rs4646994). ANOVA analysis, adjusted for the covariates, revealed that rs1801133, rs1805087 polymorphisms and homocysteine levels were associated with CAD. Logistic regression analysis (adjusted) revealed similar findings. Logistic regression analysis after applying factorial design to the studied single nucleotide polymorphisms (SNPs) revealed that homocysteine levels and heterozygous and mutant alleles at rs1801133, rs1805087, along with mutant alleles at rs1801131, rs4646994, conferred higher risk for CAD. Our results provide insight into the multifactorial nature of coronary artery disease. We highlight that SNPs in folate pathway genes and homocysteine have role in disease causation and can be used in disease prediction strategies.
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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 | 0.001 |
| 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 | 0.000 |
| 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".