Calcium-sensing receptor gene polymorphism is not associated with bone mineral density in Italian postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: Calcium-sensing receptor (CaR) is a candidate gene for osteoporosis susceptibility. Several CaR polymorphisms have been identified and an association between the A986S genotype and serum calcium levels has been found in Canadian postmenopausal women. We investigated whether the presence of 986S allele was associated with bone mineral density (BMD) and osteoporotic fractures. DESIGN: The study group consisted of 164 Italian postmenopausal women without fragility fracture (Fx(-)) and 55 women with fracture (Fx(+)). METHODS: A fragment of exon 7 of CaR gene containing three polymorphisms (A986S, R990G and Q1011E) was amplified by PCR and sequenced. Anthropometric characteristics and BMD were evaluated. RESULTS: The A986S polymorphism was the most commonly observed (27.9%), whereas the other two CaR polymorphisms, R990G and Q1011E, occurred in a minority of cases (8.8 and 5.5% respectively). There was no significant difference in the frequency distribution of any CaR allele between Fx(-) and Fx(+) patients. Body mass index was found to predict BMD at the lumbar spine and femoral neck. The A986S polymorphism and Years since menopause were not independent predictors of BMD at any site. As far as fracture occurrence, there was no statistically significant difference in the prevalence of fractures between women carrying or not carrying the 986S allele. CONCLUSIONS: Our data do not support a role of A986S CaR polymorphism in BMD and in the prevalence of fragility fractures in Italian postmenopausal women.
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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 | 0.002 |
| 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".