1752-Pan-Cancer Virtual Spatial Transcriptomics

The paper introduces the omnigenic neural network (OGM), a biologically structured architecture designed for human genome-scale phenotype prediction using the Gene Ontology (GO) as an inductive bias. By integrating individual-level genotypes, sex, and genetic principal components into a hierarchical gene and ontology layer, the model effectively captures non-additive interactions, such as epistasis, and accommodates multimodal data like metabolomics. Evaluated across large cohorts including the UK Biobank and the All of Us cohort, the OGM matches or outperforms traditional polygenic scores (PGS) and baseline models, especially in multilabel predictions and cross-ancestry transferability. Furthermore, the architecture provides systems-level interpretability and captures eQTL structures through methods like Integrated Gradients and Integrated Hessians, establishing a flexible framework for advanced genomic research.References:Upmeier zu Belzen J, Arnoldt L, Hollmann N, et al. An interpretable omnigenic neural network architecture for the human genome[J]. medRxiv, 2026: 2026.07. 28.26359187.前往小宇宙评论区与主播互动

Researchers created a multimodal cellular and spatial atlas comparing Broca’s area and the motor cortex across human development from infancy to adulthood to understand the biological foundations of language. By combining single-nucleus RNA sequencing, chromatin accessibility profiling, and spatial transcriptomics, the investigation mapped distinct cell types, gene expression programs, and structural architectures within these critical brain regions. The findings revealed area-specific cellular signatures, including unique glial populations, interneuron subtypes, and an early molecular code driven by cadherin genes that facilitates precise neural communication. Additionally, the study linked specific cell types, such as somatostatin-positive interneurons, to increased vulnerability for neurodevelopmental disorders like autism spectrum disorder and attention-deficit/hyperactivity disorder. Finally, evolutionary analyses of differentially accessible chromatin regions suggested that genetic adaptations supporting human linguistic abilities accumulated gradually over millions of years following the divergence of human and chimpanzee lineages.References:Moriano J, Mukhtar T, Lee J T H, et al. A multimodal interrogation of Broca’s area in the pediatric and adult human brain[J]. bioRxiv, 2026: 2026.07. 22.739934.前往小宇宙评论区与主播互动

The paper introduces RisQ, an innovative transformer-based framework designed to map human health by integrating multimodal data, including genetics, lifestyle factors, and medical histories. By treating health as a unified and interconnected system rather than isolated conditions, this model effectively predicts disease risks across a wide array of endpoints and continuous time horizons. Extensive evaluations using datasets from the UK Biobank and the All of Us cohort demonstrate that RisQ significantly outperforms traditional disease-specific and multi-disease forecasting models. Furthermore, the framework successfully generalizes to unseen medical categories and maintains high predictive performance even in low-prevalence disease regimes. Ultimately, the research illustrates that scaling input modalities, diseases, and time horizons enhances information transfer, leading to superior risk stratification and valuable biological discoveries.References:Hager P, Roth B, Buehler N, et al. Learning the shared structure of human health across diseases, modalities, and time[J]. medRxiv, 2026: 2026.07. 07.26357373.前往小宇宙评论区与主播互动

PertOmni is a novel multimodal representation-learning framework designed to analyze cellular perturbation effects across both genetic and small-molecule experiments. By employing a CLIP-style architecture with masked contrastive learning, the system aligns transcriptomic profiles and microscopic cell images with large language model-derived text embeddings of biological descriptions. This approach effectively isolates within-cell-type perturbation dynamics while minimizing confounding heterogeneity across different cell lines. The framework demonstrates robust predictive capabilities in bi-directional cross-modality retrieval, drug-gene interaction inference, and retrieval-based perturbation prediction. Ultimately, this method provides a unified computational strategy to link interventions directly to their functional targets and improve downstream drug discovery applications.References:Long W, Liu T, Szałata A, et al. Learning Perturbation Effects Through Contrastive Alignment of Multimodal Biological Embeddings[J]. bioRxiv, 2026: 2026.06. 23.734145.前往小宇宙评论区与主播互动

The paper introduce Phoenix, an advanced generative artificial intelligence framework designed to predict single-cell spatial gene expression directly from routine histology images. By scaling training across a massive, highly curated dataset named The Nest, this system successfully overcomes the high costs and slow speeds traditionally associated with spatial transcriptomics technologies. The research demonstrates that Phoenix can generalize exceptionally well zero-shot across diverse, previously unseen biological cohorts, organs, and species without requiring fine-tuning. Furthermore, the framework enables powerful in silico analyses, facilitating population-scale cancer atlases, precise biological hypothesis testing, and the discovery of actionable clinical biomarkers for predicting therapeutic responses.References:Tran M, Gindra R H, Putze P, et al. Pan-cancer virtual spatial transcriptomics from routine histology with Phoenix[J]. bioRxiv, 2026: 2026.04. 25.720812.前往小宇宙评论区与主播互动

The paper reviews the microevolutionary processes that drive the independent evolution of multicellularity across various life forms. It breaks down this transformative transition into key challenges, including group formation, the attainment of Darwinian individuality, and the development of functional integration and cellular specialization. Through comparative genomics and laboratory evolution experiments, the authors demonstrate that multicellular traits often emerge readily by repurposing ancestral unicellular machinery or through biophysical and ecological scaffolding. Finally, the sources explore how environmental shifts and genomic architecture have influenced why complex multicellularity remains a rare, highly contingent phenomenon.References:Ozan Bozdag G, Tong K, Yunker P J, et al. Overcoming key challenges in the evolutionary transition to multicellularity[J]. Nature, 2026, 658(8135): 327-336.前往小宇宙评论区与主播互动

Recent scientific findings demonstrate that human antiviral immunity and bacterial anti-phage defense mechanisms share remarkably similar evolutionary origins, structures, and functional strategies across all kingdoms of life. Both human cells and bacteria employ conserved protein pathways, such as cGAS–STING and inflammasomes, alongside nucleotide-based immune signaling molecules to detect and disrupt viral replication. Furthermore, these cellular defense systems utilize comparable mechanisms for pathogen recognition, signal amplification, and targeted effector functions like nucleic acid degradation and membrane disruption. Although human cells prioritize early innate and adaptive responses while bacteria often deploy late-stage cell death as a protective barrier, the overall architectural rules of host-virus interactions remain fundamentally unified.References:Kranzusch P J. Shared principles of human and bacterial antiviral immunity[J]. Nature, 2026, 656(8127): 307-319.前往小宇宙评论区与主播互动

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its advanced inflammatory stage, metabolic dysfunction-associated steatohepatitis (MASH), represent a major global health crisis closely linked to the obesity epidemic, poor diet, and sedentary lifestyles. The sources explain that the pathogenesis of MASH is a complex, multi-organ process driven by insulin resistance, adipose tissue dysfunction, genetic variants, endoplasmic reticulum and oxidative stress, and disruptions of the gut-liver and brain-liver axes. Furthermore, chronic inflammation involving both innate and adaptive immune responses, alongside cellular senescence and circadian rhythm misalignments, accelerates disease progression from simple steatosis to severe fibrosis, cirrhosis, and hepatocellular carcinoma. Because MASH exhibits substantial patient heterogeneity and functions as a systemic disease rather than a purely hepatic condition, researchers emphasize the necessity of personalized therapeutic strategies and multi-modal interventions to improve clinical outcomes.References:Gallage S, Govaere O, Anstee Q M, et al. Molecular mechanisms and pathogenesis of MASH[J]. Nature, 2026, 657(8130): 59-75.前往小宇宙评论区与主播互动

Recent scientific findings challenge the long-held belief that the cell-autonomous innate immune system originated exclusively through vertebrate evolution, revealing instead that many of its central components have ancient roots in prokaryotes. Through processes like endosymbiosis and evolutionary bottlenecks, early eukaryotes inherited diverse anti-phage defense mechanisms from bacteria and archaea, which eventually evolved into sophisticated immune pathways in humans, animals, and plants. These conserved molecular systems include the cGAS–STING pathway, viperin proteins, nucleotide-depleting enzymes, gasdermins, Argonaute proteins, and Toll/IL-1 receptor domains. Although rapid pathogen-driven evolution has erased direct sequence similarities between species, structural and functional analyses continue to uncover these deep evolutionary connections. Recognizing these prokaryotic origins not only illuminates the evolutionary history of immunity but also provides a powerful model for deciphering unknown mechanisms in contemporary human antiviral defense.References:Wein T, Sorek R. Bacterial origins of human cell-autonomous innate immune mechanisms[J]. Nature Reviews Immunology, 2022, 22(10): 629-638.前往小宇宙评论区与主播互动

Recent research introduces a human stem cell-based discovery platform that identified the nonselective adenosine receptor antagonist CGS15943 (CGS) as a potent therapeutic candidate for cardiac fibrosis. The study demonstrates that distinct adenosine receptor subtypes converge on Gβγ signaling to activate downstream PI3K-AKT and YAP-TEAD pathways, which drive fibroblast activation and fibrotic remodeling during heart failure. Simultaneous blockade of these receptors by CGS effectively suppresses this atypical signaling axis in both human cardiac cells and experimental disease models. Furthermore, in vivo administration of CGS successfully ameliorates fibrotic progression and improves overall cardiac function without notable toxicity. Ultimately, these findings establish the AR-Gβγ axis as a promising and actionable therapeutic target for treating fibrotic heart disease.References:Zhang H, Shivnaraine R V, Ren L, et al. Targeting an atypical G protein–coupled receptor signaling pathway for cardiac fibrosis therapy[J]. Science, 2026, 393(6818): eaej5896.前往小宇宙评论区与主播互动