Gamma-Aminobutyrate Transaminase Protects against Lipid Overload-Triggered Cardiac Injury in Mice
Bibliographic record
Abstract
Lipid overload contributes to cardiac complications of diabetes and obesity. However, the underlying mechanisms remain obscure. This study investigates the role of gamma-aminobutyrate transaminase (ABAT), the key enzyme involved in the catabolism of γ-aminobutyric acid (GABA), in lipid overload-induced cardiac injury. Microarray revealed a down-regulation of ABAT mRNA expression in high fat diet (HFD)-fed mouse hearts, which correlated with a reduction in ABAT protein level and its GABA catabolic activity. Transgenic mice with cardiomyocyte-specific ABAT over-expression (Tg-ABAT/tTA) were generated to determine the role of ABAT in lipid overload-induced cardiac injury. Feeding with a HFD to control mice for 4 months reduced ATP production and the mitochondrial DNA copy number, and induced myocardial oxidative stress, hypertrophy, fibrosis and dysfunction. Such pathological effects of HFD were mitigated by ABAT over-expression in Tg-ABAT/tTA mice. In cultured cardiomyocytes, palmitate increased mitochondrial ROS production, depleted ATP production and promoted apoptosis, all of which were attenuated by ABAT over-expression. With the inhibition of ABAT's GABA catabolic activity, the protective effects of ABAT remained unchanged in palmitate-induced cardiomyocytes. Thus, ABAT protects the mitochondrial function in defending the heart against lipid overload-induced injury through mechanisms independent of its GABA catabolic activity, and may represent a new therapeutic target for lipid overload-induced cardiac injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".