ARGENT: Multi-task learning model for predicting autism-related genes and drug targets using heterogeneous graph convolutional network DOI

Xinxin Miao,

Yu Weiwei

Future Generation Computer Systems, Journal Year: 2024, Volume and Issue: 160, P. 942 - 950

Published: June 28, 2024

Language: Английский

Diet-Gut Microbiome Nexus: A New Paradigm in Food-Based Mental Disease Therapeutics DOI
Sakshi Anand, Pradeep Kumar,

Sevaram Singh

et al.

Food Reviews International, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 27

Published: March 19, 2025

Language: Английский

Citations

0
Evidence of synbiotic potential of oat beverage enriched with inulin and fermented by L. rhamnosus LR B in a dynamic in vitro model of human colon DOI

Giovanna Alexandre Fabiano,

Ricardo Pinheiro de Souza Oliveira, Suelí Rodrigues

et al.

Food Research International, Journal Year: 2025, Volume and Issue: 211, P. 116489 - 116489

Published: April 17, 2025

Language: Английский

Citations

0
Exploring the potential causal association of gut microbiota on panic and conduct disorder: A two-sample Mendelian randomization approach DOI
Abiodun J. Fatoba, Claire L. Simpson

Journal of Affective Disorders, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Comprehensive Analysis of Gut Microbiota Composition and Functional Metabolism in Children with Autism Spectrum Disorder and Neurotypical Children: Implications for Sex-Based Differences and Metabolic Dysregulation DOI Open Access
Amapola De Sales-Millán,

Paulina Reyes-Ferreira,

José Felix Aguirre‐Garrido

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(12), P. 6701 - 6701

Published: June 18, 2024

This study aimed to investigate the gut microbiota composition in children with autism spectrum disorder (ASD) compared neurotypical (NT) children, a focus on identifying potential differences bacteria between these groups. The was analyzed through massive sequencing of region V3-V4 16S RNA gene, utilizing DNA extracted from stool samples participants. Our findings revealed no significant dominant bacterial phyla (Firmicutes, Bacteroidota, Actinobacteria, Proteobacteria, Verrucomicrobiota) ASD and NT However, at genus level, notable disparities were observed abundance Blautia, Prevotella, Clostridium XI, XVIII, all which have been previously associated ASD. Furthermore, sex-based analysis unveiled additional discrepancies composition. Specifically, three genera (Megamonas, Oscilibacter, Acidaminococcus) exhibited variations male female groups both cohorts. Particularly noteworthy exclusive presence Megamonas females Analysis predicted metabolic pathways suggested an enrichment related amine polyamine degradation, as well amino acid degradation group. Conversely, implicated carbohydrate biosynthesis, fermentation found be underrepresented. Despite limitations our study, including relatively small sample size (30 31 children) utilization derived gene rather than metagenome sequencing, contribute growing body evidence suggesting association Future research endeavors should validating larger sizes exploring functional significance microbial Additionally, there is critical need for further investigations elucidate sex their implications pathology treatment.

Language: Английский

Citations

1
ARGENT: Multi-task learning model for predicting autism-related genes and drug targets using heterogeneous graph convolutional network DOI

Xinxin Miao,

Yu Weiwei

Future Generation Computer Systems, Journal Year: 2024, Volume and Issue: 160, P. 942 - 950

Published: June 28, 2024

Language: Английский

Citations

0