Beta Amyloid-Induced Depression of Hippocampal Long-Term Potentiation Is Mediated through the Amylin Receptor
Bibliographic record
Abstract
Alzheimer's disease (AD) is characterized by accumulation of amyloid-β peptide (Aβ) in the brain regions that subserve memory and cognition. The amylin receptor is a potential target receptor for expression of the deleterious actions of soluble oligomeric Aβ species. We investigated whether the amylin receptor antagonist, AC253, neutralizes the depressant effects of Aβ(1-42) and human amylin on hippocampal long-term potentiation (LTP). Furthermore, we examined whether depressed levels of LTP observed in transgenic mice, which overexpress amyloid precursor protein (TgCRND8), could be restored with AC253. In mouse hippocampal brain slices, field EPSPs were recorded from the stratum radiatum layer of the CA1 area (cornu ammonis 1 region of the hippocampus) in response to electrical stimulation of Schaeffer collateral afferents. LTP was induced by 3-theta burst stimulation protocols. Aβ(1-42) (50 nM) and human amylin (50 nM), but not Aβ(42-1) (50 nM), depressed LTP evoked using both stimulation protocols. Preapplication of AC253 (250 nM) blocked Aβ- and human amylin-induced reduction of LTP without affecting baseline transmission or LTP on its own. In contrast to wild-type controls, where robust LTP is observed, 6- to 12-month-old TgCRND8 mice show blunted LTP that is significantly enhanced by application of AC253. Our data demonstrate that the effects of Aβ(1-42) and human amylin on LTP are expressed via the amylin receptor, and moreover, blockade of this receptor increases LTP in transgenic mice that show increased brain amyloid burden. Amylin receptor antagonists could serve as potentially useful therapeutic agents in AD.
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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) | 0.000 | 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 | 0.001 |
| 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 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".