The proof-of-concept of ASS234: Peripherally administered ASS234 enters the central nervous system and reduces pathology in a male mouse model of Alzheimer disease
Bibliographic record
Abstract
BACKGROUND: The heterogeneity of Alzheimer disease requires the development of multitarget drugs for treating the symptoms of the disease and its progression. Both cholinergic and monoamine oxidase dysfunctions are involved in the pathological process. Thus, we hypothesized that the development of therapies focused on these targets might be effective. We have developed and assessed a new product, coded ASS234, a multipotent acetyl and butyrylcholinesterase/monoamine oxidase A-B inhibitor with a potent inhibitory effect on amyloid-β aggregation as well as antioxidant and antiapoptotic properties. But there is a need to reliably correlate in vitro and in vivo drug release data. METHODS: We examined the effect of ASS234 on cognition in healthy adult C57BL/6J mice in a model of scopolamine-induced cognitive impairment that often accompanies normal and pathological aging. Also, in a characterized transgenic APPswe/PS1ΔE9 mouse model of Alzheimer disease, we examined the effects of short-term ASS234 treatment on plaque deposition and gliosis using immunohistochemistry. Toxicology of ASS234 was assessed using a quantitative high-throughput in vitro cytotoxicity screening assay following the MTT assay method in HepG2 liver cells. RESULTS: In vivo, ASS234 significantly decreased scopolamine-induced learning deficits in C57BL/6J mice. Also, reduction of amyloid plaque burden and gliosis in the cortex and hippocampus was assessed. In vitro, ASS234 exhibited lesser toxicity than donepezil and tacrine. LIMITATIONS: The study was conducted in male mice only. Although the Alzheimer disease model does not recapitulate all features of the human disease, it exhibits progressive monoaminergic neurodegeneration. CONCLUSION: ASS234 is a promising alternative drug of choice to treat the cognitive decline and neurodegeneration underlying Alzheimer 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".