Experimental evidence on the efficacy of two new metabolic modulators on mitochondrial biogenesis and function in mouse cardiomyocytes
Bibliographic record
Abstract
Proper maintenance of mitochondrial homeostasis is essential for cell health, and mitochondrial dysfunction underlies several metabolic and heart diseases. Stimulation of mitochondrial biogenesis represents a valuable therapeutic tool for the prevention and treatment of disorders characterized by a deficit in energy metabolism. The present study aimed to potentiate the mitochondrial biogenetic efficacy of an amino acid (AA) mixture, enriched in branched-chain amino acids (BCAAs), which we previously showed to boost mitochondrial biogenesis, leading to life span extension and reducing of muscle and liver damage. Hence, we designed and studied several innovative mixtures. Here, we report on two new AA formulas, α5 and E7, created on the BCAA-enriched amino acid mixture (BCAAem) template and enriched with Krebs cycle substrates, including succinate, malate, and citrate. Cardiomyocytes in culture exposed to either mixture showed increased mitochondrial DNA amount, mitochondrial biogenesis markers, and oxygen consump-tion. Furthermore, α5 and E7 also increased the expression of BCAA catabolic genes. Most importantly, all of these effects of α5 and E7 were more pronounced than those observed with BCAAem, confirming the higher mitochondrial biogenesis potential of these new formulas. Therefore, α5 and E7 could represent a more efficient tool for the nutritional treatment of diseases in which energy production is defective.
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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 | 0.001 | 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".