Dysregulated skeletal muscle myosin super-relaxation and energetics in male participants with type 2 diabetes mellitus
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Disrupted energy balance is critical for the onset and development of type 2 diabetes mellitus. Understanding of the exact underlying metabolic mechanisms remains incomplete, but skeletal muscle is thought to play an important pathogenic role. As the super-relaxed state of its most abundant protein, myosin, regulates cellular energetics, we aimed to investigate whether it is altered in individuals with type 2 diabetes. METHODS: We used vastus lateralis biopsy specimens (obtained from patients with type 2 diabetes and control participants with similar characteristics), and ran a combination of structural and functional assays consisting of loaded 2'- (or 3')-O-(N-methylanthraniloyl)-ATP (Mant-ATP) chase experiments, x-ray diffraction and LC-MS/MS proteomics in isolated muscle fibres. RESULTS: Our studies revealed a greater muscle myosin super-relaxation and decreased ATP demand in male participants with type 2 diabetes than in control participants. Subsequent proteomic analyses indicated that these (mal)adaptations probably originated from remodelled sarcomeric proteins and greater myosin glycation levels in patients than in control participants. CONCLUSIONS/INTERPRETATION: Overall, our findings indicate a complex molecular dysregulation of myosin super-relaxed state and energy consumption in male participants with type 2 diabetes. Ultimately, pharmacological targeting of myosin could benefit skeletal muscle and whole-body metabolic health through enhancement of ATP consumption. DATA AVAILABILITY: The raw MS data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD053022.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".