C-reactive protein, vitamin B12 and C677T polymorphism of N-5,10-methylenetetrahydrofolate reductase gene are related to insulin resistance and risk factors for metabolic syndrome in Chinese population
Bibliographic record
Abstract
PURPOSE: Metabolic syndrome (MS) and type 2 diabetes mellitus (T2DM) are complex diseases affected by both dietary intake and genetic background. Whether N-5, 10-methylenetetrahydrofolate reductase (MTHFR) C677T gene polymorphism, high-sensitivity C-reactive protein (hs-CRP) and dietary components folate and vitamin B12 are associated with MS in Asian has not been determined. METHODS: We hypothesized that MTHFR gene C677T, folate, vitamin B12 and hs-CRP are associated with MS and factors related to MS in northern Han Chinese. To test this hypothesis, MTHFR C677T gene polymorphism was determined by PCR-RFLP, serum insulin, folate and vitamin B12 levels by radioimmunoassay, and hs-CRP by immunoturbidimetry in newly diagnosed T2DM patients with MS (118) and without MS (40), and in 55 healthy subjects. RESULTS: Results indicated that MS-associated T2DM accounts for 75% of newly diagnosed T2DM in Han Chinese. Serum hs-CRP was higher and serum vitamin B12 was lower in subjects with TT genotype in comparison with those with CC or CT genotypes. Total T frequency was significantly higher in MS-associated T2DM patients (45.3%) compared to 26.3% in non-MS-associated T2DM patients. MTHFR C677T gene polymorphism and vitamin B12 levels were associated with MS-associated T2DM. CONCLUSION: MTHFR C677T gene polymorphism may contribute to insulin resistance in Han Chinese with MS by increasing hs-CRP and decreasing vitamin B12, and consequently play an important role in development of MS-associated T2DM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".