Activity and Me<scp>CP</scp>2‐dependent regulation of <scp>nNOS</scp> levels in enteric neurons
Bibliographic record
Abstract
BACKGROUND: Rett syndrome (RTT) is a neurological disorder characterized by severe cognitive impairment, motor dyspraxia, and seizures. Rett syndrome arises predominantly from mutations in MECP2, the gene coding for methyl-CpG-binding protein 2 (MeCP2). MeCP2 is an important mediator of synaptic development and is essential in regulating homeostatic synaptic plasticity (HSP) in the brain. In addition to demonstrating central nervous system impairment, RTT patients also suffer from gastrointestinal (GI) dysmotility. We hypothesize that this is due to a similar impairment of plasticity-dependent synaptic function in the enteric nervous system (ENS). We recently reported that MeCP2 is expressed in the ENS, providing evidence that neuronal dysfunction may mediate the GI pathology. METHODS: Baseline measures of MeCP2-KO vs wild-type (WT) GI neuronal nitric oxide synthase (nNOS) were assessed in tissue samples and in vitro. Experiments were carried out to measure nNOS in baseline vs activated plasticity states in vitro. Functional in vivo studies were carried out to determine whether MeCP2-KO mice reproduced the RTT GI hypomotility. KEY RESULTS: Methyl-CpG-binding protein 2-KO mice reproduced the GI hypomotility seen in RTT. MeCP2-KO GI tissue demonstrated elevated nNOS levels. Cultured WT enteric neurons showed upregulation of nNOS following moderate, prolonged stimulation by hyperkalemia; neurons from MeCP2-KO mice failed to show this nNOS upregulation. CONCLUSIONS & INFERENCES: MeCP2 is required for proper GI motility and normal nNOS levels. Neuronal nitric oxide synthase imbalances could mediate the GI dysmotility seen in RTT. Disruption of MeCP2-dependent HSP may be the basis for aberrant nNOS levels and hence GI dysmotility in MeCP2-KO and RTT.
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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 | 0.001 |
| 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".