Amyloid-β-Induced Action Potential Desynchronization and Degradation of Hippocampal Gamma Oscillations Is Prevented by Interference with Peptide Conformation Change and Aggregation
Bibliographic record
Abstract
The amyloid-β hypothesis of Alzheimer's Disease (AD) focuses on accumulation of amyloid-β peptide (Aβ) as the main culprit for the myriad physiological changes seen during development and progression of AD including desynchronization of neuronal action potentials, consequent development of aberrant brain rhythms relevant for cognition, and final emergence of cognitive deficits. The aim of this study was to elucidate the cellular and synaptic mechanisms underlying the Aβ-induced degradation of gamma oscillations in AD, to identify aggregation state(s) of Aβ that mediate the peptides neurotoxicity, and to test ways to prevent the neurotoxic Aβ effect. We show that Aβ(1-42) in physiological concentrations acutely degrades mouse hippocampal gamma oscillations in a concentration- and time-dependent manner. The underlying cause is an Aβ-induced desynchronization of action potential generation in pyramidal cells and a shift of the excitatory/inhibitory equilibrium in the hippocampal network. Using purified preparations containing different aggregation states of Aβ, as well as a designed ligand and a BRICHOS chaperone domain, we provide evidence that the severity of Aβ neurotoxicity increases with increasing concentration of fibrillar over monomeric Aβ forms, and that Aβ-induced degradation of gamma oscillations and excitatory/inhibitory equilibrium is prevented by compounds that interfere with Aβ aggregation. Our study provides correlative evidence for a link between Aβ-induced effects on synaptic currents and AD-relevant neuronal network oscillations, identifies the responsible aggregation state of Aβ and proofs that strategies preventing peptide aggregation are able to prevent the deleterious action of Aβ on the excitatory/inhibitory equilibrium and on the gamma rhythm.
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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 | 0.000 |
| 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".