LDLR C1725T Gene Polymorphism Frequency in Type 2 Diabetes Mellitus Patients With Dyslipidemia
Bibliographic record
Abstract
Background: Dyslipidemia has a substantial role in the development of cardiovascular diseases in patients with type 2 diabetes mellitus (T2DM). Determining the genetic profile of T2DM patients with dyslipidemia is important in order to reduce the risk of microvascular and macrovascular complications. Low-density lipoprotein receptor (LDLR) plays a critical role in plasma lipoprotein hemostasis. LDLR mutations/polymorphisms cause changes at the lipoprotein level. The objective of this study is to determine the frequency of LDLR (rs179989) polymorphisms in Turkish T2DM patients with dyslipidemia. Methods: The study group consisted of 217 T2DM patients with dyslipidemia including 28 cases with myocardial infarction and 212 healthy controls. Genomic DNA was isolated from venous blood samples and genotype analysis was carried out on the LightCycler ® 480 instrument. The chi 2 test was used to compare genotype distributions. Results: There were no significant differences in the frequency or allelic distribution of the LDLR C1725T (rs1799898) genotype between the type 2 diabetic dyslipidemia patients and the control group (P > 0.05). Conclusion: LDLR C1725T polymorphism was not associated with lipid parameters, and dyslipidemia in T2DM patients. J Clin Med Res. 2016;8(11):793-796 doi: http://dx.doi.org/10.14740/jocmr2739w
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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 | 0.000 | 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".