Sirtuin 3 overexpression preserves maximal sarco(endo)plasmic reticulum calcium ATPase activity in the skeletal muscle of mice subjected to high fat – high sucrose feeding
Bibliographic record
Abstract
Sarco(endo)plasmic reticulum calcium (Ca2+) ATPase (SERCA) transports Ca2+ in muscle. Impaired SERCA activity may contribute to diabetic myopathy. Sirtuin (SIRT) 3 regulates muscle metabolism and function; however, it is unknown if SIRT3 regulates muscle SERCA activity or acetylation. We determined if SIRT3 overexpression enhances SERCA activity in mouse gastrocnemius muscle and if SIRT3 overexpression preserves gastrocnemius SERCA activity in a model of type 2 diabetes, induced by high fat – high sucrose (HFHS) feeding. We also determined if the acetylation status of SERCA proteins in mouse gastrocnemius is altered by SIRT3 overexpression or HFHS feeding. Wild-type (WT) and SIRT3 transgenic (SIRT3TG) mice, overexpressing SIRT3 in skeletal muscle, were fed a standard or HFHS diet for 4 months. SIRT3TG and WT mice developed obesity and glucose intolerance after 4 months of HFHS feeding. SERCA Vmax was higher in gastrocnemius of SIRT3TG mice compared with WT mice. HFHS-fed mice had lower SERCA1a protein levels and lower SERCA Vmax in their gastrocnemius than control-fed mice. The decrease in SERCA Vmax in gastrocnemius muscle due to HFHS feeding was attenuated by SIRT3 overexpression in HFHS-fed SIRT3TG mice. SERCA1a and SERCA2a acetylation in mouse gastrocnemius was not altered by genotype or diet. These findings suggest SIRT3 overexpression improves SERCA function in mouse skeletal muscle.
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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 | 0.001 |
| 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".