Influence of bone mineral density in circulating adipokines among postmenopausal Arab women
Bibliographic record
Abstract
Osteoporosis and osteopenia has a significant link with substantial fracture risk. Epidemiological data revealed a protective role of adipose tissue on bone biology in postmenopausal osteoporosis. The current study assessed the associations between select adipokines and bone mineral density (BMD) in postmenopausal women. A total of 175 Saudi postmenopausal women were selected and categorized based on their BMD (normal & low-BMD). Circulating levels of select adipokines (adiponectin, resistin, leptin, and adipsin), insulin, 25(OH)D and RANKl were determined using commercially available assay kits. BMD was measured by dual-energy X-ray absorptiometry (DXA). Overall and among low-BMD subjects, adiponectin consistently showed a significant inverse association with BMD (overall -0.34, p < 0.01; low BMD group -0.34, p < 0.01). In multiple regression, adiponectin (-0.29 ± 0.06, p < 0.00) and resistin (-0.08 ± 0.04, p < 0.05) were inversely significant with BMD overall, but after stratification the significance was lost for resistin (-0.05 ± 0.04, p < 0.224) whereas adiponectin remained (-0.22 ± 0.07, p < 0.02) in low-BMD subjects. Adipsin, leptin and lipocalin-2 showed no significant associations. Findings of the present study revealed that only adiponectin showed a significantly strong inverse association with low BMD, suggesting that insulin sensitivity may influence bone health in Arab 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 | 0.001 |
| 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) | 0.001 | 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".