GLP-1 receptor stimulation preserves primary cortical and dopaminergic neurons in cellular and rodent models of stroke and Parkinsonism
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) is an endogenous insulinotropic peptide secreted from the gastrointestinal tract in response to food intake. It enhances pancreatic islet beta-cell proliferation and glucose-dependent insulin secretion, and lowers blood glucose and food intake in patients with type 2 diabetes mellitus (T2DM). A long-acting GLP-1 receptor (GLP-1R) agonist, exendin-4 (Ex-4), is the first of this new class of antihyperglycemia drugs approved to treat T2DM. GLP-1Rs are coupled to the cAMP second messenger pathway and, along with pancreatic cells, are expressed within the nervous system of rodents and humans, where receptor activation elicits neurotrophic actions. We detected GLP-1R mRNA expression in both cultured embryonic primary cerebral cortical and ventral mesencephalic (dopaminergic) neurons. These cells are vulnerable to hypoxia- and 6-hydroxydopamine-induced cell death, respectively. We found that GLP-1 and Ex-4 conferred protection in these cells, but not in cells from Glp1r knockout (-/-) mice. Administration of Ex-4 reduced brain damage and improved functional outcome in a transient middle cerebral artery occlusion stroke model. Ex-4 treatment also protected dopaminergic neurons against degeneration, preserved dopamine levels, and improved motor function in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of Parkinson's disease (PD). Our findings demonstrate that Ex-4 can protect neurons against metabolic and oxidative insults, and they provide preclinical support for the therapeutic potential for Ex-4 in the treatment of stroke and PD.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".