Cord blood lipid correlation network profiles are associated with subsequent attention-deficit/hyperactivity disorder and autism spectrum disorder symptoms at 2 years: a prospective birth cohort study

EBioMedicine, Год журнала: 2024, Номер 100, С. 104949 - 104949

Опубликована: Янв. 9, 2024

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum (ASD) are neurodevelopmental conditions with early life origins. Alterations in blood lipids have been linked to ADHD ASD; however, prospective data limited. This study examined (i) associations between the cord lipidome ADHD/ASD symptoms at 2 years of age, (ii) prenatal perinatal predictors lipidome, (iii) mediation by lipidome.

Язык: Английский

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STAIG: Spatial transcriptomics analysis via image-aided graph contrastive learning for domain exploration and alignment-free integration

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Янв. 27, 2025

Язык: Английский

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Exploring the Molecular Terrain: A Survey of Analytical Methods for Biological Network Analysis

Symmetry, Год журнала: 2024, Номер 16(4), С. 462 - 462

Опубликована: Апрель 10, 2024

Biological systems, characterized by their complex interplay of symmetry and asymmetry, operate through intricate networks interacting molecules, weaving the elaborate tapestry life. The exploration these networks, aptly termed “molecular terrain”, is pivotal for unlocking mysteries biological processes spearheading development innovative therapeutic strategies. This review embarks on a comprehensive survey analytical methods employed in network analysis, focusing elucidating roles asymmetry within networks. By highlighting strengths, limitations, potential applications, we delve into reconstruction, topological analysis with an emphasis detection, examination dynamics, which together reveal nuanced balance between stable, symmetrical configurations dynamic, asymmetrical shifts that underpin functionality. equips researchers multifaceted toolbox designed to navigate decipher networks’ intricate, balanced landscape, thereby advancing our understanding manipulation systems. Through this detailed exploration, aim foster significant advancements paving way novel interventions deeper comprehension molecular underpinnings

Язык: Английский

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Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics

Skin Research and Technology, Год журнала: 2024, Номер 30(2)

Опубликована: Фев. 1, 2024

Abstract Background Mounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses not fully understood. Our study aimed to find potential crucial genes in UC through machine learning integrated bioinformatics. Methods The overlapping differentially expressed (DEGs) of datasets GSE13355 GSE87466 were identified. Then functional enrichment analysis was performed. LASSO, SVM‐RFE key module WGCNA considered as genes. receiver operator characteristic (ROC) curve used estimate their diagnostic confidence. CIBERSORT conducted evaluate immune cell infiltration. Finally, GSE30999 GSE107499 retrieved validate. Results 112 DEGs identified revealed they closely related inflammatory response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, SLAMF7, ultimately ROC curves showed all had high confidence test validation datasets. indicated a correlation infiltrating cells Conclusion In our study, we focused on comprehensive understanding UC. identification eight may contribute only mechanism, but also identifying occult patients, even serving therapeutic targets future.

Язык: Английский

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Reconstructing the transcriptional regulatory network of probiotic L. reuteri is enabled by transcriptomics and machine learning

mSystems, Год журнала: 2024, Номер 9(3)

Опубликована: Фев. 13, 2024

ABSTRACT Limosilactobacillus reuteri , a probiotic microbe instrumental to human health and sustainable food production, adapts diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) 117 RNA-seq data sets decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific sets. Our findings indicate ICA provides qualitative advancement captures nuanced relationships within clusters other methods may miss. This study uncovers fundamental properties of L. ’s TRN deepens our understanding arginine metabolism co-regulation riboflavin fatty acid conversion. It also sheds light on conditions regulate genes biosynthetic cluster allows for speculation potential role isoprenoid biosynthesis in adaptive response changes. By integrating transcriptomics machine learning, we provide system-level mechanism fluctuations, thus setting stage modeling transcriptome applications microbial production. IMPORTANCE have studied beneficial plays significant production foods, type foods are nutritionally dense healthier low-carbon emissions compared traditional foods. Similar how humans adapt their lifestyles different environments, this adjusts behavior by modulating expression genes. learning analyze large-scale these behave across conditions. From this, identified unique patterns demonstrating based 50 (such as various sugars, salts, cocultures, milk, fruit juice). research helps us understand better functions, especially processes like breaking down certain nutrients adapting stressful More importantly, with findings, become closer using knowledge improve produce more help microbes.

Язык: Английский

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Hypergraph-based analysis of weighted gene co-expression hypernetwork

Frontiers in Genetics, Год журнала: 2025, Номер 16

Опубликована: Апрель 4, 2025

Background With the rapid advancement of gene sequencing technologies, Traditional weighted co-expression network analysis (WGCNA), which relies on pairwise relationships, struggles to capture higher-order interactions and exhibits low computational efficiency when handling large, complex datasets. Methods To overcome these challenges, we propose a novel Weighted Gene Co-expression Hypernetwork Analysis (WGCHNA) based hypergraph, where genes are modeled as nodes samples hyperedges. By calculating hypergraph Laplacian matrix, WGCHNA generates topological overlap matrix for module identification through hierarchical clustering. Results four expression datasets show that outperforms WGCNA in functional enrichment. identifies biologically relevant modules with greater complexity, particularly processes like neuronal energy metabolism linked Alzheimer’s disease. Additionally, enrichment uncovers more comprehensive pathway hierarchies, revealing potential regulatory relationships targets. Conclusion effectively addresses WGCNA’s limitations, providing superior accuracy detecting deeper insights disease research, making it powerful tool analyzing biological systems.

Язык: Английский

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Transcriptome meta-analysis reveals the hair genetic rules in six animal breeds and genes associated with wool fineness

Frontiers in Genetics, Год журнала: 2024, Номер 15

Опубликована: Июнь 14, 2024

Wool plays an irreplaceable role in the lives of livestock and textile industry. The variety hair quality shape leads to diversity its functions applications, finer wool has a higher economic value. In this study, 10 coarse fine ordos sheep skin samples were collected for RNA-seq, skin/hair follicle RNA-seq datasets other five animal breeds obtained from NCBI. Weighted gene co-expression network analysis showed that common genes clustered into eight modules. Similar expression patterns rabbits with same types, different species brown modules significantly correlated breeds. GO KEGG enrichment analyses that, most module associated development. Hence, tissues may determine morphology animal. differentially expressed revealed 32 highly candidate fineness Ordos sheep. Among them, KAZALD1 (grey module), MYOC (brown C1QTNF6 FOS (tan ITGAM, MX2, MX1, IFI6 have been reported be involved regulation cycle or loss. Additionally, 12 genes, including KAZALD1, MYOC, C1QTNF6, FOS, are across various species. above results suggest share similar molecular regulatory basis fineness. Finally, study provides theoretical reference breeding as well investigation origin evolution hair.

Язык: Английский

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Machine Learning Identification of Neutrophil Extracellular Trap-Related Genes as Potential Biomarkers and Therapeutic Targets for Bronchopulmonary Dysplasia

International Journal of Molecular Sciences, Год журнала: 2025, Номер 26(7), С. 3230 - 3230

Опубликована: Март 31, 2025

Neutrophil extracellular traps (NETs) play a key role in the development of bronchopulmonary dysplasia (BPD), yet their molecular mechanisms contributing to BPD remain unexplored. Using GSE32472 dataset, which includes 100 blood samples from postnatal day 28, we conducted comprehensive bioinformatics analyses identify differentially expressed genes (DEGs) and construct gene modules. We identified 86 DEGs, were enriched immune inflammatory pathways, including NET formation. Weighted co-expression network analysis (WGCNA) revealed module associated with BPD. By intersecting 69 NET-related (NRGs), 149 genes, 12 (DENRGs). Immune infiltration an increase neutrophils, dendritic cells, macrophages patients. Machine learning models (LASSO, SVM-RFE, RF) 5 upregulated biomarkers—MMP9, Siglec-5, DYSF, MGAM, S100A12—showing potential as diagnostic biomarkers for Validation using nomogram, ROC curves, qRT-PCR confirmed accuracy these biomarkers. Clinical data showed that Siglec-5 was most strongly correlated severity, while DYSF grade retinopathy prematurity (ROP) its laser treatment. Clustering two distinct subtypes different microenvironment profiles. Drug–gene interaction inhibitors targeting MGAM MMP9. In conclusion, study identifies five reliable tools BPD, upregulation association disease severity complications, such ROP, highlighting clinical relevance advancing diagnostics

Язык: Английский

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Harnessing neo-domestication of wild pigmented rice for enhanced nutrition and sustainable agriculture

Theoretical and Applied Genetics, Год журнала: 2025, Номер 138(5)

Опубликована: Май 1, 2025

Язык: Английский

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Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms

Applied Sciences, Год журнала: 2023, Номер 13(12), С. 7342 - 7342

Опубликована: Июнь 20, 2023

The process of aging is a complex phenomenon that involves progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, scientific community has utilized several tools. Among them, mitochondrial DNA emerged as crucial factor biological aging, given dysfunction thought to significantly contribute phenomenon. Additionally, Drosophila melanogaster proven be valuable model organism studying due its low cost, capacity generate large populations, ease genetic manipulation tissue dissection. Moreover, graph theory been employed dynamic changes gene expression patterns associated with investigate interactions between aging-related diseases. In study, we have integrated these approaches examine co-expression at various stages development. By applying graph-theory techniques, identified modules co-expressing genes, highlighting those contain high number genes. We found important genes involved age-related diseases melanogaster, including UQCR-C1, ND-B17.2, ND-20, Pdhb. Our findings shed light on role demonstrate utility research.

Язык: Английский

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