Effects of glucose and its modulation by insulin and estradiol on BMSC differentiation into osteoblastic lineages
Bibliographic record
Abstract
It is well known that diabetes affects bone in human and animal models, and leads to osteopenia and osteoporosis. Bone-mineral density and other biochemical markers of bone turnover are very much affected in people with diabetes. Reduced bone mass, occurring with increased frequency in diabetes mellitus, has been attributed to poor glycemic control, but the pathogenic mechanisms remain unknown. High concentrations of glucose (hyperglycemia) in diabetics leads to this complication. Very few in vitro studies using bone-cell lines have been carried out to address this problem. In this study, we examined the effects of different doses of glucose concentration (5.5, 16.5, and 49.4 mmol/L), alone, with insulin (0.6 microg/mL), or with 17beta-estradiol (E2) (10 nmol/L), on rat bone-marrow stromal cells (BMSCs) in the presence of an osteogenic medium. BMSC proliferation and alkaline phosphatase (ALP) were studied after 3 and 7 d of culture, respectively; the area stained for collagen and mineralized nodules was studied after 28 d of culture. With high concentrations of glucose, BMSC proliferation, ALP activity, the number of nodules formed, and the area stained for collagen were greatly reduced. Insulin treatment alone was able to increase [3H]-thymidine uptake or ALP activity, whereas both insulin and estradiol were able to increase the number of mineralized nodules and the area stained for collagen and mineralization. In conclusion, this study suggests that insulin and estradiol are able to contain the deleterious effect of high concentrations of glucose on BMSC-derived osteoblast proliferation and function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".