β-Amyloid Peptide Activates Non-α7 Nicotinic Acetylcholine Receptors in Rat Basal Forebrain Neurons
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative condition characterized by profound deficits in memory and cognitive function. Neuropathological hallmarks of the disease include a loss of basal forebrain cholinergic neurons and the deposition of beta-amyloid peptide (Abeta) in neuritic plaques. At a cellular level, considerable attention has focused on a study of Abeta interactions with the neuronal nicotinic acetylcholine receptor (nAChR) subtypes. In this study, using cell-attached and outside-out single channel recordings from acutely dissociated rat basal forebrain neurons, we report that Abeta and nicotine activate nAChRs with two distinct levels of single-channel conductance. Whole cell recordings from these neurons reveal Abeta and nicotine, in a concentration-dependent and reversible manner, evoke brisk depolarizing responses and an inward current. The effects of Abeta on both single channel and whole cell are blocked by the noncompetitive nAChR antagonist mecamylamine and competitive nAChR antagonist dihydro-beta-erythroidine, but not the specific alpha7-selective nAChR antagonist methyllycaconitine, indicating that Abeta activated non-alpha7 nAChRs on basal forebrain neurons. In addition, the non-alpha7 nAChR agonists UB-165, epibatidine, and cytisine, but not the selective alpha7 agonist AR-R17779, induced similar responses as Abeta and nicotine. Thus non-alpha7 nAChRs may also represent a novel target in mediating the effects of Abeta 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) | 0.001 | 0.001 |
| 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 | 0.001 |
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".