DEPTOR in POMC neurons affects liver metabolism but is dispensable for the regulation of energy balance
Bibliographic record
Abstract
We have recently demonstrated that specific overexpression of DEP-domain containing mTOR-interacting protein (DEPTOR) in the mediobasal hypothalamus (MBH) protects mice against high-fat diet-induced obesity, revealing DEPTOR as a significant contributor to energy balance regulation. On the basis of evidence that DEPTOR is expressed in the proopiomelanocortin (POMC) neurons of the MBH, the present study aimed to investigate whether these neurons mediate the metabolic effects of DEPTOR. Here, we report that specific DEPTOR overexpression in POMC neurons does not recapitulate any of the phenotypes observed when the protein was overexpressed in the MBH. Unlike the previous model, mice overexpressing DEPTOR only in POMC neurons 1) did not show differences in feeding behavior, 2) did not exhibit changes in locomotion activity and oxygen consumption, 3) did not show an improvement in systemic glucose metabolism, and 4) were not resistant to high-fat diet-induced obesity. These results support the idea that other neuronal populations are responsible for these phenotypes. Nonetheless, we observed a mild elevation in fasting blood glucose, insulin resistance, and alterations in liver glucose and lipid homeostasis in mice overexpressing DEPTOR in POMC neurons. Taken together, these results show that DEPTOR overexpression in POMC neurons does not affect energy balance regulation but could modulate metabolism through a brain-liver connection.
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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 | 0.000 |
| 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".