Non-neuronal cholinergic activity is potentiated in myasthenia gravis
Bibliographic record
Abstract
BACKGROUND: Non-neuronal acetylcholine (ACh) restricts autoimmune responses and attenuates inflammation by cholinergic anti-inflammation pathway. To date, the implication of ACh in myasthenia gravis (MG) remained unexplored. This study aimed to investigate the possible relationship between ACh levels, anti-muscle-specific tyrosine kinase (MuSK) antibody titers, main clinical features and outcomes of MG patients. METHODS: We successfully measured ACh levels in human peripheral blood mononuclear cells (PBMCs) from 125 MG patients and 50 matched healthy controls by using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). We assessed the quantitative MG (QMG) scores for each patient and titered anti-MuSK antibody. RESULTS: We found that PBMC-derived ACh level was significantly higher in MG patients, especially in patients of class III, IV-V, compared with that in controls (0.142 ± 0.108 vs. 0.075 ± 0.014 ng/million cells, p = 0.0003) according to the Myasthenia Gravis Foundation of America clinical classification. Importantly, we also found that ACh levels were positively correlated with QMG scores (r = 0.83, p < 0.0001) and anti-MuSK Ab levels (r = 0.85, p < 0.0001). CONCLUSIONS: Our demonstration of elevated ACh levels in PBMCs of MG patients foreshadows potential new avenues for MG research and treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".