Autoantibodies to Ganglionic Acetylcholine Receptors in Autoimmune Autonomic Neuropathies
Bibliographic record
Abstract
BACKGROUND: Idiopathic autonomic neuropathy is a severe, subacute disorder with a presumed autoimmune basis. It is indistinguishable from the subacute autonomic neuropathy that may accompany lung cancer or other tumors. Autoantibodies specific for nicotinic acetylcholine receptors in the autonomic ganglia are potentially pathogenic and may serve as serologic markers of various forms of autoimmune autonomic neuropathy. METHODS: We tested serum from 157 patients with a variety of types of dysautonomia. Immunoprecipitation assays with iodine-125-labeled epibatidine and solubilized human neuroblastoma acetylcholine receptors were used to detect autoantibodies that bound to or blocked ganglionic receptors. RESULTS: Ganglionic-receptor-binding antibodies were found in 19 of 46 patients with idiopathic or paraneoplastic autonomic neuropathy (41 percent), in 6 of 67 patients with postural tachycardia syndrome, idiopathic gastrointestinal dysmotility, or diabetic autonomic neuropathy (9 percent), and in none of 44 patients with other autonomic disorders. High levels of the binding antibodies correlated with more severe autonomic dysfunction (including the presence of tonic pupils). Levels of these antibodies decreased in patients who had clinical improvement. All seven patients with ganglionic-receptor-blocking antibodies had ganglionic-receptor-binding antibodies and had idiopathic or paraneoplastic autonomic neuropathy. CONCLUSIONS: Seropositivity for antibodies that bind to or block ganglionic acetylcholine receptors identifies patients with various forms of autoimmune autonomic neuropathy and distinguishes these disorders from other types of dysautonomia. The positive correlation between high levels of ganglionic-receptor antibodies and the severity of autonomic dysfunction suggests that the antibodies have a pathogenic role in these types of neuropathy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".