LMO4 Is Essential for Paraventricular Hypothalamic Neuronal Activity and Calcium Channel Expression to Prevent Hyperphagia
Bibliographic record
Abstract
The dramatic increase in the prevalence of obesity reflects a lack of progress in combating one of the most serious health problems of this century. Recent studies have improved our understanding of the appetitive network by focusing on the paraventricular hypothalamus (PVH), a key region responsible for the homeostatic balance of food intake. Here we show that mice with PVH-specific ablation of LIM domain only 4 (Lmo4) become rapidly obese when fed regular chow due to hyperphagia rather than to reduced energy expenditure. Brain slice recording of LMO4-deficient PVH neurons showed reduced basal cellular excitability together with reduced voltage-activated Ca(2+) currents. Real-time PCR quantification revealed that LMO4 regulates the expression of Ca(2+) channels (Cacna1h, Cacna1e) that underlie neuronal excitability. By increasing neuronal activity using designer receptors exclusively activated by designer drugs technology, we could suppress food intake of PVH-specific LMO4-deficient mice. Together, these results demonstrate that reduced neural activity in LMO4-deficient PVH neurons accounts for hyperphagia. Thus, maintaining PVH activity is important to prevent hyperphagia-induced obesity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".