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Record W4411834004 · doi:10.3390/life15071032

Neuronal and Glial α7 Nicotinic Acetylcholine Receptors: Role in Alzheimer’s Disease Pathophysiology

2025· review· en· W4411834004 on OpenAlexaff
Kerry Rennie

Bibliographic record

VenueLife · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsNeuroscienceBasal forebrainCholinergicCholinergic neuronNeuroinflammationBiologyHippocampusAcetylcholineNicotinic agonistForebrainMicrogliaReceptorCentral nervous systemEndocrinologyImmunologyInflammation

Abstract

fetched live from OpenAlex

Cholinergic projections from the basal forebrain to the cortex and hippocampus play a critical role in cognitive functions, many of which rely on signaling through the alpha7 nicotinic acetylcholine receptor (α7nAChR). The Alzheimer's disease (AD) brain is characterized by the profound impairment of the basal forebrain cholinergic system, including alterations in the levels of α7nAChR in various brain areas. In addition, α7nAChR binds with high affinity to beta amyloid (Aβ), suggesting α7nAChR might mediate some of Aβ's effects in the brain. Under normal physiological conditions, the interaction between Aβ and α7nAChR appears to be beneficial, supporting normal neurotransmission, synaptic plasticity, and memory functions. However, when levels of Aβ are pathologically elevated, their interaction leads to deleterious effects, implicating α7nAChR in the pathophysiology of AD. In addition to expression in neurons, α7nAChR is expressed in astrocytes and microglia, where it serves as a key component of a cholinergic pathway that regulates neuroinflammation. This review article will cover the role of α7nAChR in neurons, astrocytes and microglia under normal conditions, summarize changes in the expression or function of α7nAChR in neurons and glia in the AD brain, and discuss cell-type specific contributions of α7nAChR to AD pathology with an emphasis on interactions of α7nAChR with Aβ.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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.

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

Citations6
Published2025
Admission routes1
Has abstractyes

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