Bibliographic record
Abstract
At central synapses, glutamate is the main excitatory neurotransmitter. Once released from presynaptic terminals, glutamate activates a number of different glutamatergic receptors one of which is the ligand gated ionophore glutamatergic subtype N-methyl-D-aspartate receptors (NMDARs). NMDARs play a crucial role in controlling various determinants of synaptic function. N-acetylaspartylglutamate (NAAG) is the most prevalent peptide transmitter in the mammalian central nervous system. NAAG is released upon neuronal depolarization by a calcium-dependent process from glutamatergic and GABAergic neurons. It is cleaved by a specific peptidase located on astrocytes, glutamate carboxypeptidase type II (GCP-II), to N-acetylaspartate (NAA) and glutamate. Current evidence supports the hypothesis that NAAG is an endogenous agonist at G protein coupled mGluR3 receptors and an antagonist at NMDAR. In several disorders and animal models of human diseases, the levels of NAAG and the activity of GCP-II are altered in ways that are consistent with NAAG's role in regulation of glutamatergic neurotransmission. Several lines of evidence suggest that a dysfunction in glutamatergic via the NMDAR might be involved in schizophrenia. This hypothesis has evolved from findings that NMDAR antagonists such as phencyclidine (PCP or "angel dust"), produces a syndrome in normal individuals that closely resembles schizophrenia and exacerbates psychotic symptoms in patients with chronic schizophrenia. Recent postmortem, metabolic and genetic studies have provided evidence that hypofunction of discrete populations of NMDAR can contribute to the symptoms of schizophrenia, at least in some patients. The review outlines the role of endogenous NAAG at NMDAR neurotransmission and its putative role in the pathophysiology of schizophrenia.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".