High-fructose feeding of streptozotocin-diabetic rats is associated with increased cataract formation and increased oxidative stress in the kidney
Bibliographic record
Abstract
We examined the effects of high-fructose (FR) feeding on the development of diabetic complications in the lens and the kidney of streptozotocin (STZ)-diabetic rats. Male Wistar Furth rats were treated with one of two doses of STZ (HIGH STZ, 55 mg/kg body weight; MOD STZ, 35 mg/kg body weight) or vehicle alone (SHAM) and were then assigned to a control (CNTL) or 400 g FR/kg diet for 12 weeks. At the end of the study, body weight, plasma glucose and insulin concentrations differed among STZ groups (HIGH v. MOD v. SHAM, P < 0.001) but did not differ due to diet. Plasma FR concentrations were significantly higher in FR-fed v. CNTL-fed groups (P < 0.0001) and in HIGH-STZ groups v. MOD-STZ and SHAM groups (P < 0.0004 and P < 0.0001 respectively). Focal length variability of the lens, a quantitative measure of cataract formation, was increased in the HIGH STZ, FR group compared with the HIGH STZ, CNTL group (P < 0.01). The concentration of H2O2 in kidney microsomes was significantly higher in HIGH STZ, FR rats v. HIGH STZ, CNTL rats (P < 0.01). Micro-albuminuria was not observed in any of the groups examined, and there was no evidence of extensive histological damage in the kidney from any rats. Under conditions of severe hyperglycaemia, high FR intake promotes the development of cataracts in the lens of the eye, and results in increased concentrations of substances indicative of oxidative stress in the kidney. Although FR has been suggested as a carbohydrate source for diabetics, a high FR diet coupled with hyperglycaemia produces effects that may promote some of the complications associated with diabetes.
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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 | 0.001 | 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 | 0.001 |
| 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".