Curcumin regulates insulin pathways and glucose metabolism in the brains of APPswe/PS1dE9 mice
Bibliographic record
Abstract
Recent studies have shown the therapeutic potential of curcumin in Alzheimer's disease (AD). In 2014, our lab found that curcumin reduced Aβ40, Aβ42 and Aβ-derived diffusible ligands in the mouse hippocampus, and improved learning and memory. However, the mechanisms underlying this biological effect are only partially known. There is considerable evidence in brain metabolism studies indicating that AD might be a brain-specific type of diabetes with progressive impairment of glucose utilisation and insulin signalling. We hypothesised that curcumin might target both the glucose metabolism and insulin signalling pathways. In this study, we monitored brain glucose metabolism in living APPswe/PS1dE9 double transgenic mice using a micro-positron emission tomography (PET) technique. The study showed an improvement in cerebral glucose uptake in AD mice. For a more in-depth study, we used immunohistochemical (IHC) staining and western blot techniques to examine key factors in both glucose metabolism and brain insulin signalling pathways. The results showed that curcumin ameliorated the defective insulin signalling pathway by upregulating insulin-like growth factor (IGF)-1R, IRS-2, PI3K, p-PI3K, Akt and p-Akt protein expression while downregulating IR and IRS-1. Our study found that curcumin improved spatial learning and memory, at least in part, by increasing glucose metabolism and ameliorating the impaired insulin signalling pathways in the brain.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".