Loss of glutamatergic signalling from <scp>MCH</scp> neurons reduced anxiety‐like behaviours in novel environments
Bibliographic record
Abstract
Melanin-concentrating hormone (MCH) neurons within the hypothalamus are heterogeneous and can coexpress additional neuropeptides and transmitters. The majority of MCH neurons express vesicular transporters to package glutamate for synaptic release, and MCH neurons can directly innervate downstream neurons via glutamate release. Although glutamatergic signalling from MCH neurons may support physiological and behavioural roles that are independent of MCH (e.g., in glucose homeostasis and nutrient-sensing), it can also mediate similar roles to MCH in the regulation of energy balance. In addition to energy balance, the MCH system has also been implicated in mood disorders, as MCH receptor antagonists have anxiolytic and anti-depressive effects. However, the contribution of glutamatergic signalling from MCH neurons to mood-related functions have not been investigated. We crossed Mch-cre mice with floxed-Vglut2 mice to delete the expression of the vesicular glutamate transporter 2 (Vglut2) and disable glutamatergic signalling specifically from MCH neurons. The resulting Mch-Vglut2-KO mice showed Vglut2 deletion from over 75% of MCH neurons, and although we did not observe changes in depressive-like behaviours, we found that Mch-Vglut2-KO mice displayed anxiety-like behaviours. Mch-Vglut2-KO mice showed reduced exploratory activity when placed in a new cage and were quicker to consume food placed in the centre of a novel open arena. These findings showed that Vglut2 deletion from MCH neurons resulted in anxiolytic actions and suggested that the anxiogenic effects of glutamate are similar to those of the MCH peptide. Taken together, these findings suggest that glutamate and MCH may synergize to regulate and promote anxiety-like behaviour.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".