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Related Articles from SNS
Gene ancestries reveal diverse microbial associations during eukaryogenesis
Abstract The origin of eukaryotes remains a central enigma in biology1. Continuing debates agree on the pivotal role of a symbiosis between an alphaproteobacterium and an Asgard archaeon2,3. However, the nature, timing and contributions of other potential bacterial partners4,5,6 and the role of interactions with viruses7,8,9 remain contentious.
Molecular glue degraders of HuR suppress BRAF-mutant colorectal cancer
Abstract BRAF gain-of-function mutations, particularly BRAF(V600E), affect roughly 10% of all patients with colorectal cancer (CRC), and portend poor prognosis with limited therapeutic interventions. BRAF inhibitors such as encorafenib are ineffective due to MAPK pathway reactivation driven by BRAF dimerization. Combined inhibition of BRAF and EGFR, although approved therapies, results in short survival benefits and frequent treatment resistance and relapse1,2,3.
Coordinated neural, metabolic and muscular transcriptomic signatures associated with mite-biting behavior in honeybees (Apis mellifera L.)
Biting behavior is an important natural defense mechanism in honeybees (Apis mellifera) against Varroa destructor. Significant variation in this behavior exists across genetic lines of honeybees, with certain colonies exhibiting higher mite-biting activity than others. Selective breeding for enhanced biting behavior provides a promising strategy for sustainable mite control and colony resilience.
Longitudinal RNA Seq analyses reveal the prominent role of Vagococcus in broiler meat spoilage microbiome
Background Raw broiler meat products are highly perishable, and microbial activity is the main factor limiting their shelf lives. The spoilage microbiomes of broiler meat products have been studied mainly using traditional culturing methods and 16S rRNA gene amplicon sequencing, neither of which can show the activity of whole microbiome. Previous metatranscriptomic research of broiler spoilage has also remained limited to specific spoilage organisms rather than entire microbiomes.
Interpretable Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification using Multi-Omics Data
arXiv:2503.22939v4 Announce Type: replace Abstract: The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network (MOGKAN), a deep learning framework that utilizes messenger-RNA, micro-RNA sequences, and DNA methylation samples together with Protein-Protein Interaction (PPI) networks for cancer...