Distinctive phenotypic, metabolic and contractile properties of <i> Ins2 <sup>Akita+/−</sup> </i> and streptozotocin‐induced diabetic skeletal muscles.
Bibliographic record
Abstract
The impact of type 1 diabetes on skeletal muscle (diabetic myopathy) during adolescence is largely unknown. Diabetic myopathy studies commonly use streptozotocin‐induced diabetic (STZ) rodents; however, streptozotocin has known detrimental effects on muscle cell growth. Here, we examined mechanisms of diabetic myopathy in adolescent Akita and STZ mice following 8 weeks of diabetes. Both models exhibited reduced muscle mass (Akita: 0.124 ± 0.008g; STZ: 0.124 ± 0.024g; Con: 0.162 ± 0.015g) and IIB/D fiber area (Akita: 57.7 ± 4.2% and STZ: 78.9 ± 7.3% of Con). Intramyocellular lipid was increased in STZ (122.9 ± 3.6% of Con) but not Akita muscle, resulting from lower citrate synthase and β‐HAD activities in STZ muscle. Functional analyses revealed lower absolute peak force in Akita (70.2 ± 8.2% of Con) but not STZ muscle (87.6 ± 7.9% of Con). Corrected for muscle mass, no relative force difference was observed between Akita and Con, while STZ relative force was significantly elevated. STZ muscle exhibits contractile, metabolic and phenotypic properties distinct from Akita, despite similarity in hyperglycemia, furthering concerns of toxic effects of streptozotocin on muscle. In Akita mice, muscle atrophy and specific fiber type loss did not affect contractile properties (relative to muscle mass), suggesting that pathological metabolic changes within diabetic muscle precede alteration of contractile properties.
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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 | 0.001 | 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) | 0.002 | 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".