BDNF Serum Levels with Respect to Multidimensional Assessment in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
BACKGROUND: The clinical presentation of amyotrophic lateral sclerosis (ALS) is characterized by high heterogeneity, the greatest part of which still remains unexplained. OBJECTIVE: To assess serum levels of brain-derived neurotrophic factor (BDNF) in ALS patients, implementing a multidimensional characterization focused on four a priori chosen elements of phenotypic variability: ALS bulbar/spinal subtype, cognitive impairment, mood dysfunction and disease progression speed. METHODS: Serum samples were obtained from 45 ALS outpatients (16% bulbar onset) and 22 healthy controls. Each patient underwent the Montreal Cognitive Assessment (MoCA) and the Beck Depression Inventory (BDI), and disease progression speed was estimated by calculating the decay of the ALSFRS-R score over time. RESULTS: BDNF serum levels did not differ between patients and controls, although ∼25% lower levels characterized those patients carrying a depressive trait. Finally, BDNF serum levels were significantly lower in ALS patients expressing lower ALSFRS-R scores (r = 0.39, p < 0.01). No differences were found when considering cognitive impairment, disease progression speed and site of onset. CONCLUSION: BDNF serum levels might mark and possibly contribute in part to ALS phenotypic variability.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".