Pathological Appearance of a Case of Preclinical Multiple System Atrophy: A Comparison With Advanced Cases
Bibliographic record
Abstract
We aimed to investigate the frequency of multiple system atrophy (MSA) in a large number of forensic autopsies and characterize the pathological appearance of preclinical MSA. We investigated a series of 1930 brains from forensic autopsies. In addition to performing immunohistochemistry for phosphorylated α-synuclein, the levels of 3 autonomic nervous system markers (catecholaminergic, serotonergic, and cholinergic) were used to assess the peripheral nerve (heart and superior cervical ganglion) and medulla oblongata. The results were compared to those of healthy control and Parkinson disease (PD) cases. Four cases (0.21%) were identified as having MSA. Cases 1-3 were symptomatic, and Case 4 was incipient; that is, although no neuronal loss was evident, the cerebellar dentate nucleus exhibited marked grumose degeneration. Immunohistochemistry revealed a marked reduction in autonomic nervous system marker levels expressed in the medulla; this reduction was more prominent in the 3 symptomatic MSA cases than in the PD case. The opposite occurred for the peripheral nerve. Case 4 exhibited mild cholinergic nerve reduction. Two cases showed possible significant pathological changes in the heart. Grumose degeneration, few oligodendroglial cytoplasmic inclusions without neuronal loss, and less reduction of autonomic nervous tissue were more prominent in the preclinical case than in symptomatic cases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".