Adipose-Specific Deficiency of Fumarate Hydratase in Mice Protects Against Obesity, Hepatic Steatosis, and Insulin Resistance
Bibliographic record
Abstract
Obesity and type 2 diabetes are associated with impaired mitochondrial function in adipose tissue. To study the effects of primary deficiency of mitochondrial energy metabolism in fat, we generated mice with adipose-specific deficiency of fumarate hydratase (FH), an integral Krebs cycle enzyme (AFHKO mice). AFHKO mice have severe ultrastructural abnormalities of mitochondria, ATP depletion in white adipose tissue (WAT) and brown adipose tissue, low WAT mass with small adipocytes, and impaired thermogenesis with large unilocular brown adipocytes. AFHKO mice are strongly protected against obesity, insulin resistance, and fatty liver despite aging and high-fat feeding. AFHKO white adipocytes showed normal lipolysis but low triglyceride synthesis. ATP depletion in normal white adipocytes by mitochondrial toxins also decreased triglyceride synthesis, proportionally to ATP depletion, suggesting that reduced triglyceride synthesis may result nonspecifically from adipocyte energy deficiency. At thermoneutrality, protection from insulin resistance and hepatic steatosis was diminished. Taken together, the results show that under the cold stress of regular animal room conditions, adipocyte-specific FH deficiency in mice causes mitochondrial energy depletion in adipose tissues and protects from obesity, hepatic steatosis, and insulin resistance, suggesting that in cold-stressed animals, mitochondrial function in adipose tissue is a determinant of fat mass and insulin sensitivity.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".