Protection against β-amyloid-induced synaptic and memory impairments via altering β-amyloid assembly by bis(heptyl)-cognitin
Bibliographic record
Abstract
β-amyloid (Aβ) oligomers have been closely implicated in the pathogenesis of Alzheimer's disease (AD). We found, for the first time, that bis(heptyl)-cognitin, a novel dimeric acetylcholinesterase (AChE) inhibitor derived from tacrine, prevented Aβ oligomers-induced inhibition of long-term potentiation (LTP) at concentrations that did not interfere with normal LTP. Bis(heptyl)-cognitin also prevented Aβ oligomers-induced synaptotoxicity in primary hippocampal neurons. In contrast, tacrine and donepezil, typical AChE inhibitors, could not prevent synaptic impairments in these models, indicating that the modification of Aβ oligomers toxicity by bis(heptyl)-cognitin might be attributed to a mechanism other than AChE inhibition. Studies by using dot blotting, immunoblotting, circular dichroism spectroscopy, and transmission electron microscopy have shown that bis(heptyl)-cognitin altered Aβ assembly via directly inhibiting Aβ oligomers formation and reducing the amount of preformed Aβ oligomers. Molecular docking analysis further suggested that bis(heptyl)-cognitin presumably interacted with the hydrophobic pockets of Aβ, which confers stabilizing powers and assembly alteration effects on Aβ. Most importantly, bis(heptyl)-cognitin significantly reduced cognitive impairments induced by intra-hippocampal infusion of Aβ oligomers in mice. These results clearly demonstrated how dimeric agents prevent Aβ oligomers-induced synaptic and memory impairments, and offered a strong support for the beneficial therapeutic effects of bis(heptyl)-cognitin in the treatment of 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 | 0.000 |
| 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".