Locus coeruleus neuromelanin, cognitive dysfunction, and brain metabolism in multiple system atrophy
Bibliographic record
Abstract
BACKGROUND: Cognitive dysfunction is increasingly recognized in multiple system atrophy (MSA). Locus coeruleus (LC) integrity is associated with cognitive performance both in healthy controls (HC) and neurodegenerative conditions such as Parkinson's disease (PD). Furthermore, cortical glucose hypometabolism is associated with impaired cognitive performance in MSA. However, knowledge about LC sub-regional degeneration and its association with cognitive dysfunction and cortical glucose metabolism is lacking. OBJECTIVE: To investigate LC sub-regional involvement and its association with cognitive impairment and brain metabolism in MSA. METHODS: F]Fluorodeoxyglucose PET (FDG-PET). The Montreal Cognitive Assessment (MoCA) was used as a measure of global cognition. RESULTS: Middle LC neuromelanin signal was significantly reduced in MSA [t(43) = 3.70, corrected-p = 0.004] and PD [t(43) = 2.63, corrected-p = 0.041] compared to HC, while caudal LC was only reduced in MSA [t(43) = 2.82, corrected-p = 0.030]. In MSA, decreased rostral LC neuromelanin was associated with lower MoCA scores (ρ = 0.760, p = 0.006) which, in turn, were associated with lower frontal cortex glucose metabolism. An association between rostral LC neuromelanin signal and frontal cortex glucose metabolism was found in exploratory analyses. CONCLUSION: Loss of LC neuromelanin signal was found in MSA, the middle and caudal parts being targeted. Rostral LC neuromelanin signal loss was associated with both frontal cortex hypometabolism and lower MoCA scores. This pathophysiological link should be further investigated as the noradrenergic system transmission is amenable to pharmacological manipulation.
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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 | 0.000 | 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 | 0.000 |
| 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".