Tumour necrosis factor alpha -308G/A gene polymorphism: lack of association with knee osteoarthritis in a Turkish population.
Bibliographic record
Abstract
OBJECTIVE: To study the association between TNFalpha-308 G/A polymorphism and susceptibility to and severity of knee osteoarthritis in a Turkish population. METHODS: Genomic DNA was obtained from 151 patients with knee osteoarthritis and 84 ethnically matched healthy controls. Polymerase chain reaction-restriction fragment length analysis was used to identify G/A polymorphism at position -308 in the promoter region. Genotype distributions and allelic frequencies of TNFalpha-308 G/A polymorphism were compared between osteoarthritis patients and controls. Thereafter, this association was investigated between patients and controls of the same sex. In addition, the standard Kellgren-Lawrence grading score and the Turkish version of the Western Ontario and McMaster Universities Osteoarthritis Index were used to assess the radiological and functional severity of the disease and their relationship with the TNFalpha-308 gene polymorphism was investigated. RESULTS: Genotype distribution and allelic frequencies of -308 G/A polymorphism in the TNFalpha gene did not differ significantly between patients with knee osteoarthritis and controls (p>0.05). Moreover, there were no significant differences between patients and controls of the same sex (p>0.05). In addition, no association was observed between the radiological and functional severity of the disease and TNFalpha-308 G/A polymorphism (p>0.05). CONCLUSION: These findings suggest that the examined polymorphism in the TNFalpha gene does not contribute to susceptibility to or severity of knee osteoarthritis in the Turkish 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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".