A Systematic Review of the Effects of N-Methyl-D-Aspartate Receptor Antagonists on Pancreatic Islets
Bibliographic record
Abstract
Background: N-methyl-D-aspartate receptors (NMDARs) are widely distributed in the brain and pancreas. Preliminary evidence indicates that aberrant NMDAR-mediated glutamatergic signaling may disrupt pancreatic islet function and glucose-insulin homeostasis. The frequent comorbidity of depression and diabetes underscores the potential role of NMDAR signaling in pancreatic function as a shared pathophysiological mechanism. Herein, this systematic review aims to evaluate the effects of NMDAR antagonism on pancreatic cells (i.e., alpha, beta, delta) viability and function (i.e., activation, hormone production, and release). METHODS: We performed a systematic search on PubMed and Ovid databases from inception to September 11, 2024. A manual search was also conducted on Google Scholar and Scopus databases. Eligible studies were primary, controlled in vitro or in vivo studies investigating the effects of NMDAR antagonism on pancreatic islet function and viability. Results were synthesized and presented descriptively. Risk of bias was assessed independently by two reviewers using a modified SYRCLE risk of bias tool. RESULTS: We reviewed 14 studies evaluating NMDA receptor antagonism in whole islets, beta and alpha cells; however, no studies evaluated delta cells. Within beta cells, NMDAR antagonism improved glucose-stimulated insulin secretion and increased cell proliferation and viability. Similarly, alpha cells were protected against stress-induced apoptosis. CONCLUSION: Our results suggest that NMDAR antagonism improves alpha and beta cell function and viability, which may have translational relevance to comorbid metabolic dysfunction in depression. These mechanisms may subserve the antidepressant effects of select NMDA antagonists (e.g., ketamine/esketamine, dextromethorphan). Further research should aim to investigate the effects of subanesthetic doses of ketamine/esketamine on pancreatic function and on delta cells. .
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".