Glucose-loading reduces bone remodeling in women and osteoblast function in vitro
Bibliographic record
Abstract
Aging is associated with a reduction in osteoblast life span and the volume of bone formed by each basic multicellular unit. Each time bone is resorbed, less is deposited producing microstructural deterioration. Aging is also associated with insulin resistance and hyperglycemia, either of which may cause, or be the result of, a decline in undercarboxylated osteocalcin (ucOC), a protein produced by osteoblasts that increases insulin sensitivity. We examined whether glucose-loading reduces bone remodeling and ucOC in vivo and osteoblast function in vitro, and so compromises bone formation. We administered an oral glucose tolerance test (OGTT) to 18 pre and postmenopausal, nondiabetic women at rest and following exercise and measured serum levels of bone remodeling markers (BRMs) and ucOC. We also assessed whether increasing glucose concentrations with or without insulin reduced survival and activity of cultured human osteoblasts. Glucose-loading at rest and following exercise reduced BRMs in pre and postmenopausal women and reduced ucOC in postmenopausal women. Higher glucose correlated negatively, whereas insulin correlated positively, with baseline BRMs and ucOC. The increase in serum glucose following resting OGTT was associated with the reduction in bone formation markers. D-glucose (>10 mmol L(-1)) increased osteoblast apoptosis, reduced cell activity and osteocalcin expression compared with 5 mmol L(-1). Insulin had a protective effect on these parameters. Collagen expression in vitro was not affected in this time course. In conclusion, glucose exposure reduces BRMs in women and exercise failed to attenuate this suppression effect. The suppressive effect of glucose on BRMs may be due to impaired osteoblast work and longevity. Whether glucose influences material composition and microstructure remains to be determined.
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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 | 0.000 |
| 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".