Pharmacological increases in circulating ketones fail to alleviate the hypertrophic cardiomyopathy present in the Tafazzin knockdown mouse model of Barth syndrome
Bibliographic record
Abstract
Objective Mutations in the tafazzin gene lead to impaired remodeling of cardiolipin, thereby impairing mitochondrial function and causing Barth syndrome (BTHS), a rare X-linked genetic disorder characterized by cardiomyopathy. Previous studies in a mouse model of BTHS, secondary to knockdown of Tafazzin (TazKD mice), also observed perturbations in mitochondrial substrate metabolism and a hypertrophic cardiomyopathy. BTHS may be characterized by increased cardiac ketone metabolism, as myocardial protein expression of the ketolytic enzyme, β-hydroxybutyrate dehydrogenase 1 (BDH1), was markedly increased in TazKD mice. We therefore determined whether increasing ketone supply in TazKD mice may have therapeutic utility against their cardiac abnormalities. Methods We treated TazKD mice and their wild-type littermates with either the sodium-glucose cotransporter-2 inhibitor, empagliflozin (10 mg/kg), or a ketone ester (KE; 1719 mg/kg) once daily for 7-week, and performed ultrasound echocardiography to assess cardiac structure and function. Results Treatment of TazKD mice with either empagliflozin or a KE increased circulating ketone levels. However, neither approach proved capable of alleviating the cardiac hypertrophy present in TazKD mice, as their increased left ventricular wall thickness and decreased left ventricular diameter remained comparable to that observed in vehicle control treated animals. We also observed that empagliflozin and KE treatment did not impact key markers of cardiac hypertrophy in TazKD mice. Conclusion Increasing circulating ketone levels did not alleviate the cardiac hypertrophy in TazKD mice, suggesting that such an approach would not improve outcomes in BTHS.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".