Lack of association polymorphisms of the IL1RN, IL1A, and IL1B genes with knee osteoarthritis in Turkish patients
Bibliographic record
Abstract
PURPOSE: To examine whether polymorphisms of the interleukin 1 receptor antagonist (IL1RN), interleukin 1 alpha (IL1A) and interleukin 1 beta (IL1B) genes are markers of genetic susceptibility to knee osteoarthritis in Turkish patients. METHODS: One hundred and seven patients with knee osteoarthritis and 67 controls were studied. Three polymorphisms of IL1A, IL1B, and IL1RN genes were typed from genomic DNA. Allelic frequencies were compared between patients and control subjects. RESULTS: No significant differences were observed in genotype and allele frequencies of the IL1RN VNTR, IL1A+4845, IL1B+3953 genes polymorphisms between patients and controls. Furthermore, we did not detect any association genotypes of the polymorphisms with the clinical, radiological, and laboratory profiles of patients. CONCLUSIONS: The present study suggest that the IL1RN VNTR, IL1A+4845, IL1B+3953 genes polymorphisms are not genetic markers of susceptibility to knee osteoarthritis in Turkish patients, and are unrelated to the clinical, radiological, and laboratory characteristics of knee osteoarthritis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".