Liraglutide Activates mTORC1 Signaling and AMPA Receptors in Rat Hippocampal Neurons Under Toxic Conditions
Bibliographic record
Abstract
The aim of the present study was to determine whether treatment with liraglutide, a glucagon-like peptide 1 (GLP-1) receptor agonist, would alter mammalian target of rapamycin complex 1 (mTORC1) signaling and/or α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptor activity under dexamethasone-induced toxic conditions. Western blot analyses were performed to assess changes in mTORC1-mediated proteins, brain-derived neurotrophic factor (BDNF), and various synaptic proteins (PSD-95, synapsin I, and GluA1) in rat hippocampal cultures under toxic conditions induced by dexamethasone, which causes hippocampal cell death. Hippocampal dendritic outgrowth and spine formation were measured using immunostaining procedures. Dexamethasone significantly decreased the phosphorylation levels of mTORC1 as well as its downstream proteins. However, treatment with liraglutide prevented these reductions and significantly increased BDNF expression. The increase in BDNF expression was completely blocked by rapamycin and 2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzo[f]quinoxaline-7-sulfonamide (NBQX). Liraglutide also recovered dexamethasone-induced decreases in the total length of hippocampal dendrites and reductions in spine density in a concentration-dependent manner. However, the positive effects of liraglutide on neural plasticity were abolished by the blockade of mTORC1 signaling and AMPA receptors. Furthermore, liraglutide significantly increased the expression levels of PSD-95, synapsin I, and GluA1, whereas rapamycin and NBQX blocked these effects. The present study demonstrated that liraglutide activated mTORC1 signaling and AMPA receptor activity as well as increased dendritic outgrowth, spine density, and synaptic proteins under toxic conditions in rat primary hippocampal neurons. These findings suggest that GLP-1 receptor (GLP-1R) activation by liraglutide may affect neuroplasticity through mTORC1 and AMPA receptors.
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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) | 0.001 | 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".