Equivalencies: 0 | Classes: 0 | Children: 0 | Explore

Entity

Name
Behavior, Addictive
Namespace
MeSH
Namespace Version
20181007
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/01c9daa61012b37dd0a1bc962521ba51a15b38f1/external/mesh-names.belns

Appears in Networks 3

In-Edges 3

a(CHEBI:nicotine) increases path(MESH:"Behavior, Addictive") View Subject | View Object

Nicotine is perhaps the most addictive drug that is widely used; 95% or more of its users with a strong desire to stop using it relapse within 1 yr (47, 203). Chronic nicotine use and the phenotypes of addiction are closely associated in humans and other animals with concurrent physiological changes in nAChR function and expression PubMed:19126755

Appears in Networks:
Annotations
Text Location
Review

p(FPLX:CHRN) association path(MESH:"Behavior, Addictive") View Subject | View Object

Decline, disruption, or alterations of nicotinic cholinergic mechanisms have been implicated in various dysfunctions, such as schizophrenia, epilepsy, autism, Alzheimer’s disease (AD), and addiction (17–23). PubMed:17009926

act(p(FPLX:CHRN)) increases path(MESH:"Behavior, Addictive") View Subject | View Object

Although many areas of the brain participate, nicotinic receptors of the midbrain dopa- mine (DA) area are particularly important during the initiation of the addic- tion process (Dani et al., 2014; De Biasi & Dani, 2011). PubMed:26472524

Out-Edges 1

path(MESH:"Behavior, Addictive") association p(FPLX:CHRN) View Subject | View Object

Decline, disruption, or alterations of nicotinic cholinergic mechanisms have been implicated in various dysfunctions, such as schizophrenia, epilepsy, autism, Alzheimer’s disease (AD), and addiction (17–23). PubMed:17009926

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

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.