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Entity

Name
behavioral fear response
Namespace
go
Namespace Version
20180921
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/b46b65c3da259b6e86026514dfececab7c22a11b/external/go-names.belns

Appears in Networks 1

Activation of M1 and M4 muscarinic receptors as potential treatments for Alzheimer's disease and schizophrenia. v1.0.0

This file encodes the article Activation of M1 and M4 muscarinic receptors as potential treatments for Alzheimer’s disease and schizophrenia by Choi et al, 2014

In-Edges 3

act(a(CHEBI:scopolamine)) decreases bp(GO:"behavioral fear response") View Subject | View Object

Moreover, additional pre-clinical studies with TBPB demonstrated efficacy in reducing antipsychotic-like behaviors and in reversing scopolamine-impaired acquisition of contextual fear.59 Studies in cell lines also demonstrated that TBPB promoted a non-amyloidogenic pathway and decreased Abeta production, indicating that M1 modulation may have efficacy in the treatment of both symptomatic and pathologic features of AD PubMed:24511233

a(MESH:"1-(4-methoxybenzyl)-4-oxo-1,4-dihydroquinoline-3-carboxylic acid") increases bp(GO:"behavioral fear response") View Subject | View Object

In brain slice electrophysiology studies, BQCA enhanced excitatory postsynaptic currents in medial prefrontal cortical neurons,69 an area critical for higher cognitive, learning, and memory functions.70 In pre-clinical animal studies, BQCA reversed scopolamine-impaired contextual fear conditioning and rescued medial prefrontal cortex-dependent discrimination reversal learning deficits in a transgenic mouse model of AD. PubMed:24511233

a(MESH:VU0357017) increases bp(GO:"behavioral fear response") View Subject | View Object

More recently, the M1-selective allosteric agonist VU0357017 was discovered, which displayed improved potency via binding to a novel allosteric site on the M1 mAChR. VU0357017 significantly blocked scopolamine-impaired contextual fear conditioning and enhanced spatial and contextual fear learning PubMed:24511233

Out-Edges 0

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If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.