Urinary chiro-Inositol and myo-inositol Excretion is Elevated in the Diabetic db/db Mouse and Streptozotocin Diabetic Rat
Bibliographic record
Abstract
Inositol phosphoglycan molecules containing either D-chiro-inositol or myo-inositol have been isolated from various mammalian tissues and are putative mediators of insulin action. Urinary excretion of inositols appears to be altered in diabetes mellitus; however, the relationships with different types of diabetes are unclear. The objective of this study was to determine the urinary excretion of chiro- and myo-inositol in diabetic animal models, including streptozotocin (STZ) rats, db/db mice, and fa/fa Zucker rats. In STZ rats (type 1 diabetes), 12-hr urinary excretion of chiro-inositol was elevated 336-fold and myo-inositol excretion was elevated 47-fold compared with their nondiabetic counterparts. When corrected for creatinine, chiro-inositol excretion was 259-fold higher and myo-inositol excretion was 36-fold higher in STZ rats than in normal rats. The same pattern was observed in db/db mice (type 2 diabetes), where 12-hr urinary chiro-inositol excretion was elevated 247-fold compared with normal mice. When corrected for creatinine, chiro-inositol excretion was 2455-fold higher and urinary myo-inositol excretion was elevated 8.5-fold in db/db mice compared with normal mice. The fa/fa Zucker rats (impaired glucose tolerance) had a pattern of urinary inositol excretion that was similar to the nondiabetic animals (lean Zucker rats, C57BL/6 mice, and Sprague-Dawley rats). In summary, urinary chiro-inositol and myo-inositol excretion was elevated in animal models of type 1 and type 2 diabetes mellitus, concomitant with hyperglycemia and glucosuria.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".