Exercise training alleviates MCT1 and MCT4 reductions in heart and skeletal muscles of STZ-induced diabetic rats
Bibliographic record
Abstract
We compared the changes in monocarboxylate transporter 1 (MCT1) and 4 (MCT4) proteins in heart and skeletal muscles in sedentary control and streptozotocin (STZ)-induced diabetic rats (3 wk) and in trained (3 wk) control and STZ-induced diabetic animals. In nondiabetic animals, training increased MCT1 in the plantaris (+51%; P < 0.01) but not in the soleus (+9%) or the heart (+14%). MCT4 was increased in the plantaris (+48%; P < 0.01) but not in the soleus muscles of trained nondiabetic animals. In sedentary diabetic animals, MCT1 was reduced in the heart (-30%), and in the plantaris (-31%; P < 0.01) and soleus (-26%) muscles. MCT4 content was also reduced in sedentary diabetic animals in the plantaris (-52%; P < 0.01) and soleus (-25%) muscles. In contrast, in trained diabetic animals, MCT1 and MCT4 in heart and/or muscle were similar to those of sedentary, nondiabetic animals (P > 0.05) but were markedly greater than in the sedentary diabetic animals [MCT1: plantaris +63%, soleus +51%, heart +51% (P > 0.05); MCT4: plantaris +107%, soleus +17% (P > 0.05)]. These studies have shown that 1) with STZ-induced diabetes, MCT1 and MCT4 are reduced in skeletal muscle and/or the heart and 2) exercise training alleviated these diabetes-induced reductions.
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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 | 0.000 | 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".