D-Serine in Neurobiology: CNS Neurotransmission and Neuromodulation
Bibliographic record
Abstract
Homochirality is fundamental for life. L-Amino acids are exclusively used as substrates for the polymerization and formation of peptides and proteins in living systems. However, D- amino acids were recently detected in various living organisms, including mammals. Of these D-amino acids, D-serine has been most extensively studied. D-Serine was found to play an important role as a neurotransmitter in the human central nervous system (CNS) by binding to the N-methyl- D-aspartate receptor (NMDAr). D-Serine binds with high affinity to a co-agonist site at the NMDAr and, along with glutamate, mediates several vital physiological and pathological processes, including NMDAr transmission, synaptic plasticity and neurotoxicity. Therefore, a key role for D-serine as a determinant of NMDAr mediated neurotransmission in mammalian CNS has been suggested. In this context, we review the known functions of D-serine in human physiology, such as CNS development, and pathology, such as neuro-psychiatric and neurodegenerative diseases related to NMDAr dysfunction.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".