Angiotensinogen Gene M235T and T174M Polymorphisms in Diabetic Nephropathy in a Bangladeshi Population
Bibliographic record
Abstract
Background: Marker gene polymorphisms linked with the renin-angiotensin-aldosterone system (RAAS) have been broadly studied in diabetic nephropathy (DN) patients considering that RAAS is a potential drug target to slow down kidney disease progression. Objectives: The aim of the present study was to determine the link between M235T and T174M variants of angiotensinogen (AGT) gene and DN. Methods: A total of 93 patients with DN, mean age of 56±8 years, systolic blood pressure (SBP) of 141±14, and diastolic blood pressure (DBP) of 84±7 mm Hg (mean±SD) were investigated, among whom 59 patients had a family history of type 2 diabetes mellitus. A total of 96 healthy subjects served as the control group with no family history of diabetic nephropathy (FHDN) and type 2 diabetes mellitus, a mean age of 47±10 years, SBP of 126±11, and DBP of 76±6 mm Hg. PCR–restriction fragment length polymorphism was employed for genotyping M235T and T174M molecular variants. Results: Genotype frequencies of the variants M235T (χ2=2.038, P=0.361) and T174M (χ2=2.952, P=0.229) did not show any statistically significant association with type 2 diabetic nephropathy (T2DN) compared to the control. Based on FHDN and family history of diabetes mellitus (FHDM), the frequency of genotypes of M235T marker (P=0.360) in FHDN, and (P=0.886) FHDM; T174M marker (P=0.641) in FHDN, and (P=0.425) FHDM also did not show any statistically significant association with T2DN compared to the controls. Conclusion: M235T and T174M variants were not associated with DN in a Bangladeshi population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".