Muscle and serum myostatin expression in type 1 diabetes
Bibliographic record
Abstract
Type 1 diabetes (T1D) has been reported to negatively affect the health of skeletal muscle, though the underlying mechanisms are unknown. Myostatin, a myokine whose increased expression is associated with muscle-wasting diseases, has not been reported in humans with T1D but has been demonstrated to be elevated in preclinical diabetes models. Thus, the purpose of this study was to determine if there is an elevated expression of myostatin in the serum and skeletal muscle of persons with T1D compared to controls. Secondarily, we aimed to explore relationships between myostatin expression and clinically important metrics (e.g., HbA1c, strength, lean mass) in women and men with (N = 31)/without T1D (N = 24) between 18 and 72 years old. Body composition, baseline strength, blood sample and vastus lateralis muscle biopsy were evaluated. Serum, but not muscle, myostatin expression was significantly elevated in those with T1D versus controls, and to a greater degree in T1D women than T1D men. Serum myostatin levels were not significantly associated with HbA1c nor disease duration. A significant correlation between serum myostatin expression and maximal voluntary contraction (MVC) and body fat mass was demonstrated in control subjects, but these correlations did not reach significance in those with T1D (MVC: R = 0.64 controls vs. R = 0.37 T1D; Body fat: R = −0.52 controls/R = −0.02 T1D). Collectively, serum myostatin was correlated with lean mass (R = 0.45), and while this trend was noted in both groups separately, neither reached statistical significance (R = 0.47 controls/R = 0.33 T1D). Overall, while those with T1D exhibited elevated serum myostatin levels (particularly females) myostatin expression was not correlated with clinically relevant metrics despite some of these relationships existing in controls (e.g., lean/fat mass). Future studies will be needed to fully understand the mechanisms underlying increased myostatin in T1D, with relationships to insulin dosing being particularly important to elucidate.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".