Topiramate Enhances <scp>GABAergic</scp> Tone to Orexigenic Neuropeptide Y/Agouti‐Related Peptide ( <scp>NPY</scp> / <scp>AgRP</scp> ) Neurons
Bibliographic record
Abstract
ABSTRACT Objective Topiramate is a medication used off‐label, or in combination with phentermine, for the management of obesity. However, its mechanism of action remains elusive. As many obesity medications target the brain, we aimed to determine if topiramate influences the activity of hypothalamic melanocortin neurons known to regulate energy balance. Methods Transgenic mice expressing a fluorescent protein in either “orexigenic” neuropeptide Y/agouti‐related peptide (NPY/AgRP) or “anorexigenic” pro‐opiomelanocortin (POMC) neurons were used to perform whole‐cell patch clamp electrophysiology experiments in the arcuate nucleus (ARC) of the hypothalamus. Results Topiramate (1 μM) strongly inhibited NPY/AgRP neuron electrical excitability. Despite topiramate's well‐known actions at GABA A receptors, we demonstrate that the topiramate‐induced inhibition of NPY/AgRP neurons does not involve GABA A receptors. The effects of topiramate on NPY/AgRP neurons were suppressed by inhibitors of synaptic transmission and after blockade of GABA B receptors or potassium channels. In contrast, topiramate had negligible influence on the activity of POMC neurons. Conclusions This study is the first demonstration that topiramate strongly inhibits the activity of ARC NPY/AgRP neurons and suggests that enhanced GABAergic tone to these neurons mediates this effect. The ability of topiramate to inhibit the orexigenic NPY/AgRP neurons may underlie some of its weight‐lowering properties.
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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) | 0.003 | 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".