Elevated locus coeruleus metabolism provides resilience against cognitive decline in preclinical Alzheimer's disease
Bibliographic record
Abstract
Abstract INTRODUCTION Alterations in locus coeruleus’ (LC) metabolic turnover are associated with Alzheimer's disease (AD)‐pathology and cognitive impairment. However, the evolution of these changes across disease stages and their functional relevance remains unknown. METHODS We examined associations of [ 18 F]‐fluorodeoxyglucose positron emission tomography (FDG‐PET) ‐derived LC metabolism with clinical diagnostic status, cerebrospinal fluid (CSF) ‐based AD biomarkers of AD pathology, and cognitive decline in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants ( n = 604). RESULTS FDG‐PET‐derived LC metabolism was elevated in the earliest preclinical stages and lower in later disease stages. Higher LC metabolism was associated with attenuated memory decline in preclinical stages, particularly in those with low CSF Aβ 42, but not in AD patients with cognitive impairment. DISCUSSION Higher locus coeruleus [ 18 F]‐FDG‐PET‐derived signal in the early preclinical stages of AD can confer cognitive resilience and may reflect increased metabolic activity, whereas later stages are characterized by lower LC FDG‐PET‐derived signal, possibly due to neurodegeneration. Highlights LC FDG‐PET signal is lower in Alzheimer's disease (AD) patients. LC FDG‐PET signal is higher in the preclinical stage of AD. We observed less memory decline in those with higher LC FDG‐PET signal. Higher LC FDG‐PET signal conferred cognitive resilience in preclinical AD.
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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 | 0.001 | 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".