Neuroprotection through adiponectin receptor agonist: an updated meta-analysis of preclinical Alzheimer’s disease studies
Bibliographic record
Abstract
BACKGROUND: Alzheimer’s disease (AD) is a leading cause of dementia, imposing a substantial burden on individuals and society. While existing therapies can reduce the symptoms of AD, they do not offer genuine therapeutic effectiveness. Adiponectin Receptor Agonist (ADN-R Ag) has been proposed as a novel therapeutic agent for AD. This study aims to evaluate its efficacy in treating AD model mice. METHODS: A systematic search of PubMed, Scopus, Cochrane Library, and Web of Science was conducted up to May 3, 2025. Research investigating the impact of ADN-R Ag on cognitive performance and associated molecular pathways in Alzheimer’s disease models, specifically APP/PS1, P301S, and 5XFAD mice, was incorporated. The Alzheimer’s disease models in the study were male and ranged in age from 5.5 to 8 months. Studies evaluating the effect of ADN-R Ag on AD model mice through cognitive function tests and related molecular mechanisms were included. Methodological quality assessment was performed using the CAMARADES tool for animal studies. The meta-analysis was performed following Cochrane guidelines. RESULTS: Six articles were included for the review. ADN-R Ag significantly improved cognitive function in the meta-analysis. The weighted mean difference of ADN-R Ag was 21.75 (95% CI: 16.61–26.88; p < 0.001) for alternation rate percentage in the Y-maze, 20.46 (95% CI: 11.41–29.51, p < 0.001) for novel object exploration time percentage in the novel object recognition (NOR) test, -15.83 (95% CI: -23.33 to -8.32, p < 0.001) for escape latency in the Morris water maze (MWM), and 13.89 (95% CI: 8.84–18.94; p < 0.001) for target quadrant time in the probe test. Additionally, ADN-R Ag was reported to mitigate AD pathology by reducing Aβ depositions through inhibition of GSK3β/BACE1/NF-κB pathway, suppressing neuronal inflammation by suppressing microglial and astrocytes activity and reducing and IL1β and TNFα levels, enhancing autophagy, and improving mitochondrial function with significant involvement of the AMPK pathway. CONCLUSION: Based on the current study, ADN-R Ag has therapeutic effects on AD. However, considering the complex underlying molecular mechanisms and limited prior studies, further research is needed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".