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Record W2107857520 · doi:10.1517/14728222.11.2.161

Targeting acetylcholinesterase to treat neurodegeneration

2007· review· en· W2107857520 on OpenAlexaff
Ulrike Holzgrabe, Petra Kapková, Vildan Alptüzün, Josef Scheiber, Eva Kugelmann

Bibliographic record

VenueExpert Opinion on Therapeutic Targets · 2007
Typereview
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAcetylcholinesteraseAcetylcholineCholinergicNeurodegenerationPharmacologyAlzheimer's diseaseDiseaseMedicineNeuroscienceAchéCholinesteraseMuscarinic acetylcholine receptorChemistryInternal medicineBiologyBiochemistryEnzymeReceptor

Abstract

fetched live from OpenAlex

Neurodegenerative disorders, such as Alzheimer's disease, are often characterised by the degeneration of the cholinergic system. Thus, the aim of many treatment regimens is to support this system either by means of muscarinic agonists or by inhibitors of acetylcholinesterase (AChE), the latter being able to increase the concentration of acetylcholine. However, both pharmacological groups of drugs can only help in the beginning of the progressive disease. The finding that the occupation of the peripheral anionic site of AChE is able to stop the formation of the amyloid plaque led to the development of bivalent ligands that occupy both the active and the peripheral site. This dual action might be more beneficial for treatment of Alzheimer s disease than simple inhibition of the acetylcholine hydrolysis. Thus, the new bivalent ligands are the focus of this review.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.156
GPT teacher head0.445
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations213
Published2007
Admission routes1
Has abstractyes

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