Phase 2A Proof-of-Concept Double-Blind, Randomized, Placebo-Controlled Trial of Nicotinamide in Early Alzheimer Disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Nicotinamide is a coenzyme involved in cellular oxidation-reduction reactions that can inhibit Class III histone deacetylases (HDACs) or sirtuins. HDAC inhibition can affect numerous therapeutic pathways, including tau phosphorylation. We tested the hypothesis that nicotinamide treatment could reduce tau phosphorylation in early Alzheimer disease (AD). METHODS: in CSF and the clinical measures Alzheimer's Disease Assessment Scale (ADAS-cog13), Alzheimer's Disease Cooperative Study-Activities of Daily Living Scale-Mild Cognitive Impairment (ADCS-ADL-MCI), and Clinical Dementia Rating Summary of Boxes (CDR-SB). Participants were recruited at 2 academic clinical centers. Enrollment criteria included diagnosis of mild cognitive impairment or mild dementia with CSF biomarker confirmation of AD. The Holm-Bonferroni procedure was used to control type I error within biomarker and clinical domains. RESULTS: = 0.10) outcomes. DISCUSSION: Nicotinamide was safe but did not alter AD biomarkers. CLASSIFICATION OF EVIDENCE: . TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov: NCT03061474.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".