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Viruses manipulate host cellular machinery to propagate their life cycle, with one key strategy being the mimicry of short linear motifs (SLiMs) found in host proteins. While databases continue to expand with virus–host protein–protein interaction (vhPPI) data, accurately predicting viral mimicry remains challenging due to the inherent degeneracy of SLiMs. In this study, we investigate how viral genomic composition influences motif mimicry and the mechanisms through which viruses hijack host cellular functions. We assessed domain–motif interaction (DMI) enrichment differences, and also predicted new DMIs based on known viral motifs with varying stringency levels, using SLiMEnrich v.1.5.1. Our findings reveal that dsDNA viruses capture significantly more known DMIs compared to other viral groups, with dsRNA viruses also exhibiting higher DMI enrichment than ssRNA viruses. Additionally, we identified new vhPPIs mediated via SLiMs, particularly within different viral genomic contexts. Understanding these interactions is vital for elucidating viral strategies to hijack host functions, which could inform the development of targeted antiviral therapies.

Lung cancer (LC) continues to pose the highest mortality and exhibits a common prevalence among all types of cancer. The genetic interaction between human eukaryotes and microbial cells plays a vital role in orchestrating every physiological activity of the host. The dynamic crosstalk between gut and lung microbiomes and the gut–lung axis communication network has been widely accepted as promising factors influencing LC progression. The advent of the 16s rDNA sequencing technique has opened new horizons for elucidating the lung microbiome and its potential pathophysiological role in LC and other infectious lung diseases using a molecular approach. Numerous studies have reported the direct involvement of the host microbiome in lung tumorigenesis processes and their impact on current treatment strategies such as radiotherapy, chemotherapy, or immunotherapy. The genetic and metabolomic cross‐interaction, microbiome‐dependent host immune modulation, and the close association between microbiota composition and treatment outcomes strongly suggest that designing microbiome‐based treatment strategies and investigating new molecules targeting the common holobiome could offer potential alternatives to develop effective therapeutic principles for LC treatment. This review aims to highlight the interaction between the host and microbiome in LC progression and the possibility of manipulating altered microbiome ecology as therapeutic targets. Host–microbiome interaction in lung cancer. Both local (lung) and distal (gut) microbiota play critical roles in lung cancer

This article provides a comprehensive analysis of the multifaceted impacts of transnational migration in Nepal, drawing on findings from 42 systematically selected research articles. Employing a thematic analysis approach, the study constructs a schematic representation delineating four key themes: the use effect of remittance income on individuals, the offset effect on land, the substitution effect on people due to a reduced workforce, and the neglect effect on land stemming from decreased working members in households and communities. This comprehensive examination sheds light on the migration dynamics and addresses its implications for rural sustainability. The central theme underscores the connections between transnational migration and its implication for food security, livelihood enhancement, income diversification, and ecological restoration. The paper emphasizes the importance of understanding these interlinkages for informed policy decisions aligned with long-term macroeconomic goals. The synthesized framework contributes to theoretical foundations and encourages further research on the impacts of transnational migration in agrarian economies and the pathways for socio-economic transitions.