The nuclear receptor PPARγ as a therapeutic target for cerebrovascular and brain dysfunction in Alzheimer's disease
Bibliographic record
Abstract
Peroxisome proliferator-activated receptors (PPARs) are ligand-activated nuclear transcription factors that regulate peripheral lipid and glucose metabolism. Three subtypes make up the PPAR family (alpha, gamma, beta/delta), and synthetic ligands for PPARalpha (fibrates) and PPARgamma (Thiazolidinediones, TZDs) are currently prescribed for the respective management of dyslipidemia and type 2 diabetes. In contrast to the well characterized action of PPARs in the periphery, little was known about the presence or function of these receptors in the brain and cerebral vasculature until fairly recently. Indeed, research in the last decade has uncovered these receptors in most brain cell types, and has shown that their activation, particularly that of PPARgamma, is implicated in normal brain and cerebrovascular physiology, and confers protection under pathological conditions. Notably, accumulating evidence has highlighted the therapeutic potential of PPARgamma ligands in the treatment of brain disorders such as Alzheimer's disease (AD), leading to the testing of the TZDs pioglitazone and rosiglitazone in AD clinical trials. This review will focus on the benefits of PPARgamma agonists for vascular, neuronal and glial networks, and assess the value of these compounds as future AD therapeutics in light of evidence from transgenic mouse models and recent clinical trials.
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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 | 0.000 | 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 | 0.000 |
| 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".