Cerebrospinal Fluid Neurotransmitters, Cytokines, and Chemokines in Alzheimer’s and Lewy Body Diseases
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) and Lewy body disease (LBD) are complex neurodegenerative disorders that have been associated with brain inflammation and impaired neurotransmission. OBJECTIVE: We aimed to determine concentrations of multiple cytokines, chemokines, and neurotransmitters previously associated with brain inflammation and synapse function in cerebrospinal fluid (CSF) from AD and LBD patients. METHODS: We examined a panel of 50 analytes comprising neurotransmitters, cytokines, chemokines, and hormones in CSF in a cohort of patients diagnosed with mild cognitive impairment (MCI), AD, LBD, or non-demented controls (NDC). RESULTS: Among neurotransmitters, noradrenaline (NA) was increased in AD CSF, while homovanillic acid (HVA), a dopamine metabolite, was reduced in both AD and LBD CSF relative to NDC. Six cytokines/chemokines out of 30 investigated were reliably detected in CSF. CSF vascular endothelial growth factor (VEGF) was significantly reduced in LBD patients relative to NDC. CONCLUSIONS: CSF alterations in NA, HVA, and VEGF in AD and LBD may reflect pathogenic features of these disorders and provide tools for improved diagnosis. Future studies are warranted to replicate current findings in larger, multicenter cohorts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".