Partial Pancreatectomized Diabetic Rats Present with Altered Skeletal Muscle Contractility and Phenotype
Bibliographic record
Abstract
People with long‐term type 1 diabetes (T1D) often have skeletal muscle complications (myopathy). Studies on T1D and skeletal muscle are limited and often use animal models that induce T1D with streptozotocin, which causes myopathy independent of hyperglycemia. The objective of this study was to characterize diabetic myopathy in a partially pancreatectomized (Px) model of T1D. Male Sprague Dawley rats were randomly assigned to either Px or sham surgery groups. Following 8 weeks of diabetes, Px had significantly lower body and gastrocnemius‐plantaris‐soleus (GPS) mass compared to shams (349.1±21 vs 484.4±10 g; 1.8±0.1 vs 3.3±0.1 g/g mass, respectively). In situ muscle stimulation of the GPS revealed a lower maximal force (Fmax) in Px vs shams (12.1±1.3N vs 22.6±1.8N, p<0.01), but was similar when corrected for muscle mass. During a 2 minute fatigue protocol, stimulating the GPS at ~50% Fmax (3 sec stimulation, 3 sec rest), Px had a lower rate of decline in force than shams (52.8±3.4% vs 69.7±7.2%, p<0.05). Histochemical analysis of the GPS demonstrates that Px have reduced myofiber area irrespective of fiber type and an increase in type IIa fiber number. These data suggest that sustained hyperglycemia/hypoinsulinemia induced by Px is characterized by changes in the skeletal muscle phenotype that result in compromised function. This research was funded by NSERC.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".