Human Amylin Actions on Rat Cholinergic Basal Forebrain Neurons: Antagonism of Beta-Amyloid Effects
Bibliographic record
Abstract
Human amylin (hAmylin), a 37-amino acid pancreatic peptide, and amyloid beta protein (A beta), a 39-43 amino acid peptide, abundantly deposited in the brains of Alzheimer's patients, induce neurotoxicity in hippocampal and cortical cultures. Although the mechanism of this neurotoxicity is unknown, both peptides are capable of modulating ion channel function that may result in a disruption of cellular homeostasis. In this study, we examined the effects of hAmylin on whole cell currents in chemically identified neurons from the rat basal forebrain and the interactions of hAmylin-induced responses with those of A beta. Whole cell patch-clamp recordings were performed on enzymatically dissociated neurons of the diagonal band of Broca (DBB), a cholinergic basal forebrain nucleus. Bath application of hAmylin (1 nM to 5 microM) resulted in a dose-dependent reduction in whole cell currents in a voltage range between -30 and +30 mV. Single-cell RT-PCR analysis reveal that all DBB neurons responding to hAmylin or A beta were cholinergic. Using specific ion channel blockers, we identified hAmylin and A beta effects on whole cell currents to be mediated, in part, by calcium-dependent conductances. Human amylin also depressed the transient outward (IA) and the delayed rectifier (IK) potassium currents. The hAmylin effects on whole cell currents could be occluded by A beta and vice versa. Human amylin and A beta responses could be blocked with AC187 (50 nM to 1 microM), a specific antagonist for the amylin receptor. The present study indicates that hAmylin, like A beta, is capable of modulating ion channel function in cholinergic basal forebrain neurons. Furthermore, the two peptides may share a common mechanism of action. The ability of an amylin antagonist to block the responses evoked by hAmylin and A beta may provide a novel therapeutic approach for Alzheimer's disease.
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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".