Paradoxical roles of serine racemase and <scp>d</scp>‐serine in the G93A mSOD1 mouse model of amyotrophic lateral sclerosis
Bibliographic record
Abstract
D-serine is an endogenous neurotransmitter that binds to the NMDA receptor, thereby increasing the affinity for glutamate, and the potential for excitotoxicity. The primary source of D-serine in vivo is enzymatic racemization by serine racemase (SR). Regulation of D-serine in vivo is poorly understood, but is thought to involve a combination of controlled production, synaptic reuptake by transporters, and intracellular degradation by D-amino acid oxidase (DAO). However, SR itself possesses a well-characterized eliminase activity, which effectively degrades D-serine as well. D-serine is increased two-fold in spinal cords of G93A Cu,Zn-superoxide dismutase (SOD1) mice--the standard model of amyotrophic lateral sclerosis (ALS). ALS mice with SR disruption show earlier symptom onset, but survive longer (progression phase is slowed), in an SR-dependent manner. Paradoxically, administration of D-serine to ALS mice dramatically lowers cord levels of D-serine, leading to changes in the onset and survival very similar to SR deletion. D-serine treatment also increases cord levels of the alanine-serine-cysteine transporter 1 (Asc-1). Although the mechanism by which SOD1 mutations increases D-serine is not known, these results strongly suggest that SR and D-serine are fundamentally involved in both the pre-symptomatic and progression phases of disease, and offer a direct link between mutant SOD1 and a glial-derived toxic mediator.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".