Galantamine alleviates inflammation and insulin resistance in patients with metabolic syndrome in a randomized trial
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MetS) is an obesity-driven condition of pandemic proportions that increases the risk of type 2 diabetes and cardiovascular disease. Pathophysiological mechanisms are poorly understood, though inflammation has been implicated in MetS pathogenesis. The aim of this study was to assess the effects of galantamine, a centrally acting acetylcholinesterase inhibitor with antiinflammatory properties, on markers of inflammation implicated in insulin resistance and cardiovascular risk, and other metabolic and cardiovascular indices in subjects with MetS. METHODS: In this randomized, double-blind, placebo-controlled trial, subjects with MetS (30 per group) received oral galantamine 8 mg daily for 4 weeks, followed by 16 mg daily for 8 weeks or placebo. The primary outcome was inflammation assessed through plasma levels of cytokines and adipokines associated with MetS. Secondary endpoints included body weight, fat tissue depots, plasma glucose, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), cholesterol (total, HDL, LDL), triglycerides, BP, heart rate, and heart rate variability (HRV). RESULTS: Galantamine resulted in lower plasma levels of proinflammatory molecules TNF (-2.57 pg/ml [95% CI -4.96 to -0.19]; P = 0.035) and leptin (-12.02 ng/ml [95% CI -17.71 to -6.33]; P < 0.0001), and higher levels of the antiinflammatory molecules adiponectin (2.71 μg/ml [95% CI 1.93 to 3.49]; P < 0.0001) and IL-10 (1.32 pg/ml, [95% CI 0.29 to 2.38]; P = 0.002) as compared with placebo. Galantamine also significantly lowered plasma insulin and HOMA-IR values, and altered HRV. CONCLUSION: Low-dose galantamine alleviates inflammation and insulin resistance in MetS subjects. These findings support further study of galantamine in MetS therapy. TRIAL REGISTRATION: ClinicalTrials.gov, number NCT02283242. FUNDING: Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, and the NIH.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".