Angiotensin II, a neuropeptide at the frontier between endocrinology and neuroscience: is there a link between the angiotensin II type 2 receptor and Alzheimer’s disease?
Bibliographic record
Abstract
Amyloid-β peptide deposition, abnormal hyperphosphorylation of tau, as well as inflammation and vascular damage, are associated with the development of Alzheimer's disease (AD). Angiotensin II (Ang II) is a peripheral hormone, as well as a neuropeptide, which binds two major receptors, namely the Ang II type 1 receptor (AT1R) and the type 2 receptor (AT2R). Activation of the AT2R counteracts most of the AT1R-mediated actions, promoting vasodilation, decreasing the expression of pro-inflammatory cytokines, both in the brain and in the cardiovascular system. There is evidence that treatment with AT1R blockers (ARBs) attenuates learning and memory deficits. Studies suggest that the therapeutic effects of ARBs may reflect this unopposed activation of the AT2R in addition to the inhibition of the AT1R. Within the context of AD, modulation of AT2R signaling could improve cognitive performance not only through its action on blood flow/brain microcirculation but also through more specific effects on neurons. This review summarizes the current state of knowledge and potential therapeutic relevance of central actions of this enigmatic receptor. In particular, we highlight the possibility that selective AT2R activation by non-peptide and highly selective agonists, acting on neuronal plasticity, could represent new pharmacological tools that may help improve impaired cognitive performance in AD and other neurological cognitive disorders.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".