Reviewer #3 (Public Review): Smith-Magenis syndrome protein Rai1 regulates body weight homeostasis through hypothalamic Bdnf-producing neurons and TrkB signalling
Bibliographic record
Abstract
Retinoic acid-induced 1 (RAI1) haploinsufficiency causes Smith-Magenis syndrome (SMS), a genetic disorder with symptoms including hyperphagia, hyperlipidemia, severe obesity, and autism phenotypes. Rai1 is a transcriptional regulator with a pan-neural expression pattern and hundreds of downstream targets. The mechanisms linking neural Rai1 to body weight regulation remain unclear. Here we find that hypothalamic brain-derived neurotrophic factor (Bdnf)-TrkB signalling is disrupted in SMS (Rai1+/-) mice. Selective Rai1 loss from all Bdnf-producing cells or from Bdnf-producing neurons in the paraventricular nucleus of the hypothalamus (PVH) induced obesity in mice. Electrophysiological recordings revealed that Rai1 ablation increased inhibitory synaptic transmission to PVHBdnf neurons and decreased intrinsic neuronal excitability. Chronic treatment of SMS mice with a partial agonist of tropomyosin receptor kinase B (TrkB), the cognate Bdnf receptor, delayed obesity onset. This treatment also partially rescued disrupted lipid profiles, insulin intolerance, and stereotypical repetitive behaviour in SMS mice. These data argue that Rai1 regulates body weight and metabolic function through hypothalamic Bdnf-producing neurons and that targeting TrkB signalling might improve associated SMS phenotypes.
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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 | 0.020 | 0.132 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.016 | 0.006 |
| Insufficient payload (model declined to judge) | 0.083 | 0.045 |
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".