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Record W6921460485 · doi:10.64336/001c.29109

The discovery of new acetylcholinesterase inhibitors as potential therapeutics for Alzheimer’s disease

2021· article· en· W6921460485 on OpenAlexaff

Bibliographic record

VenueJournal of High School Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Methods and Technologies
Canadian institutionsSurrey Memorial Hospital
Fundersnot available
KeywordsAcetylcholinesteraseDiseaseAcetylcholineNeurotransmitterNeurotransmissionDrug discoveryHuman diseaseNeurotransmitter systems

Abstract

fetched live from OpenAlex

Alzheimer’s disease is an irreversible, progressive neurodegenerative disease that is the most common form of dementia. It has been shown that the neurotransmission controlled by acetylcholine plays a critical role in nervous system function, and the lack of this neurotransmitter contributes to Alzheimer’s disease. There are numerous ways to design therapeutics for Alzheimer’s disease, one of which includes the inhibition of the enzyme acetylcholinesterase. The aim of this work was to identify new inhibitors of acetylcholinesterase that would serve as starting points to designing more efficient inhibitors. Computational studies were employed to virtual screen potential inhibitors and analyze their interactions with acetylcholinesterase. As a result, potential inhibitors that bind more favorably to acetylcholinesterase compared to currently approved inhibitors and have appropriate drug-like properties for human use were discovered. This work pioneers future research efforts seeking to develop new therapeutics for Alzheimer’s disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.404
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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