Increased body fat in streptozotocin diabetic rats treated with intensive subcutaneous insulin therapy vs. islet transplantation
Bibliographic record
Abstract
The continued development of novel insulin treatment is predicated on the hypothesis that strict glycemic control is necessary to prevent the secondary complications of diabetes. Although dramatically successful in reducing selected secondary complications, intensive insulin therapy has consequences. These include hypoglycemia, weight gain, and body fat accumulation. In the present studies we compared a model of intensive insulin therapy in diabetic rats and contrasted weight gain and body fat accumulation with pancreatic islet transplantation. Female Wistar Furth rats (173 g) administered streptozotocin (55 mg x kg(-1), iv) remained diabetic (DB) for four or nine weeks. At week three, a third group was transplanted (TRAN) with islets of Langerhans (3519 +/- 838 150 microm islets); one week later group four began intensive subcutaneous insulin therapy (ISIT; 4 x 0.5-1.0 U regular insulin x day(-1)). Within one week ISIT rats had normalized plasma glucose; levels were not different from age matched controls (CN) or TRAN animals (ISIT 10.6 +/- 1.7, CN 7.2 +/- 0.4, TRAN 7.7 +/- 0.8 mmol x L(-1), P > 0.05). The cumulative occurrence of one episode of hypoglycemia (< 2.8 mmol x L(-1)) occurred in 50% of ISIT rats. At study termination, body weight of ISIT and CN rats did not differ (199 +/- 4 vs. 207 +/- 3, P > 0.05). While carcass protein content was similar for TRAN, ISIT, and CN animals, the body fat of ISIT animals was 24% greater than in CN rats and 21% greater than in TRAN rats (P < 0.05). Correlation of body fat vs. plasma glucose illustrated hypoglycemia contributed to the body fat gain of ISIT rats (n = 8, r = -0.70, P = 0.0535). These studies illustrate a disproportionate gain of body fat from ISIT, an effect not observed with islet transplantation. Thus, the metabolic benefit ascribed to islet transplantation appears related to the absence of hypoglycemia.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".