Neuropathology of Speech Network Distinguishes Bulbar From Nonbulbar Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Bulbar amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative subtype affecting speech and swallowing motor functions as well as associated with the burden of cognitive deficits. The neuroanatomical underpinnings of bulbar ALS are not well understood. The aim of this study was to compare neuropathology of the speech network (SpN) between 3 cases of bulbar-onset ALS (bALS), 3 cases of spinal-onset ALS (sALS) with antemortem bulbar ALS (sALSwB) against 3 sALS without antemortem bulbar ALS (sALSnoB) and 3 controls. Regional distribution and severity of neuronal loss, TDP-43 (transactive response DNA-binding protein of 43 kDa), and tau proteinopathy were examined. All 3 bALS cases showed marked neuronal loss and severe proteinopathy across most SpN regions; sALSwB cases showed no neuronal loss but mild and variable TDP-43 pathology in focal regions; sALSnoB cases demonstrated an absence of pathology. Two bALS cases had coexisting tauopathy in SpN regions, which was not noted in any sALS cases. The findings suggested that bALS may have a distinct neuropathological signature characterized by marked neuronal loss and polypathology in the SpN. Milder TDP-43 pathology in the SpN for sALSwB cases suggested a link between severity of bulbar ALS and SpN damage. Findings support a clinicopathologic link between bulbar symptoms and pathology in the SpN.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".