Disc degeneration and bone density in monozygotic twins discordant for insulin‐dependent diabetes mellitus
Bibliographic record
Abstract
The effects of insulin-dependent diabetes mellitus on bone density and connective tissue degeneration have theoretical interest and practical relevance. Several experimental studies in animals have demonstrated the harmful effects of insulin deficiency on connective tissues. However, clinical studies in humans have produced somewhat contradictory results, most likely due to difficulties controlling for general degeneration and factors associated with diabetes. In nine pairs of monozygotic twins discordant for insulin-dependent diabetes mellitus, we compared femoral and lumbar bone mineral density (assessed by dual-energy x-ray absorptiometry) and spinal degeneration (assessed by magnetic resonance imaging). The bone densities were, on average, 0.1-0.3% lower (p = 0.87-0.96) in diabetic patients. However, after controlling for smoking, we found that the bone density in the femoral neck was 2.5% (0.025 g/cm2) lower in diabetic individuals than in their twins (p = 0.09). The five magnetic resonance imaging parameters used to evaluate disc degeneration did not differ between diabetic patients and their twins. In conclusion, our results provide no evidence that insulin-dependent diabetes mellitus has any major effect on bone density or disc degeneration.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".