Sigma-1 and N-Methyl-<smlcap>D</smlcap>-Aspartate Receptors: A Partnership with Beneficial Outcomes
Bibliographic record
Abstract
Sigma-1 receptors (σ-1R) are interorganelle signaling molecules, which have been implicated in synaptic plasticity, primarily by enhancing the function of N-methyl-d-aspartate receptors (NMDARs). On the other hand, excessive influx of calcium via activated NMDAR can cause excitotoxicity. Yet, despite their NMDAR-enhancing role, multiple lines of evidence suggest that σ-1Rs are involved in neuroprotection. The mechanism underlying these intriguing opposing effects is not known. Recent studies now suggest the possibility that σ-1Rs could exert neuroprotective effects via targeted disruption of protein-protein interactions between NMDARs and their associated intracellular signaling machinery, specifically the neuronal nitric oxide synthase (nNOS). This targeted disruption of protein-protein interactions between NMDARs and nNOS results in lower levels of nitric oxide generation, thus having a neuroprotective effect. Here, we briefly summarize aspects of σ-1R-mediated enhancement of NMDAR function and possible neuroprotection. In-depth mechanistic understanding of σ-1R modulation of NMDAR function, which preserves Ca(2+) homoeostasis while limiting excitotoxicity would provide valuable information for designing novel as well as improving prevailing therapeutic strategies.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".