Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.
Cells
; 13(3)2024 Feb 01.
Article
em En
| MEDLINE
| ID: mdl-38334667
ABSTRACT
Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments in deep learning algorithms enable us to assess the behavioral phenotypes of animal models without cognitive bias during manual analysis. In this study, we established prenatal nicotine exposure (PNE) mice and evaluated their behavioral phenotypes using DeepLabCut and SimBA. We optimized the training parameters of DeepLabCut for pose estimation and succeeded in labeling a single-mouse or two-mouse model with high fidelity during free-moving behavior. We applied the trained network to analyze the behavior of the mice and found that PNE mice exhibited impulsivity and a lessened working memory, which are characteristics of ADHD. PNE mice also showed elevated anxiety and deficits in social interaction, reminiscent of autism spectrum disorder (ASD). We further examined PNE mice by evaluating adult neurogenesis in the hippocampus, which is a pathological hallmark of ASD, and demonstrated that newborn neurons were decreased, specifically in the ventral part of the hippocampus, which is reported to be related to emotional and social behaviors. These results support the hypothesis that PNE is a risk factor for comorbidity with ADHD and ASD in mice.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Transtorno do Deficit de Atenção com Hiperatividade
/
Transtorno do Espectro Autista
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Aprendizado Profundo
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Pregnancy
Idioma:
En
Revista:
Cells
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Japão