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High-resolution genomic history of early medieval Europe

Nature, Published online: 01 January 2025; doi:10.1038/s41586-024-08275-2

Twigstats, a method for ancestry reconstruction, provides high-resolution genetic histories and movement patterns of people living in Europe during the first millennium ce.
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New resource available to help scientists better classify cancer subtypes

A multi-institutional team of scientists has developed a free, publicly accessible resource to aid in classification of patient tumor samples based on distinct molecular features identified by The Cancer Genome Atlas (TCGA) Network. The resource comprises classifier models that can accelerate the design of cancer subtype-specific test kits for use in clinical trials and cancer diagnosis. This is an important advance because tumors belonging to different subtypes may vary in their response to cancer therapies.
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High-quality nanodiamonds for bioimaging and quantum sensing applications

Researchers have developed nanodiamond sensors with nitrogen-vacancy (NV) centers, offering exceptional brightness and spin properties for quantum sensing and bioimaging. These nanodiamonds outperform commercial options, requiring 20 times less energy and maintaining quantum states 11 times longer. Enhanced sensitivity to magnetic fields and temperature enables precise applications, including disease detection, battery analysis, and thermal management of electronics, marking a significant advancement in nanotechnology-driven quantum sensing for biological and industrial innovations.
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Long-term in vitro expansion of a human fetal pancreas stem cell that generates all three pancreatic cell lineages

Identification of an LGR5 as a marker for a tripotent stem/progenitor cell of the human fetal pancreas. Organoids derived from single LGR5+ cells are capable of long-term expansion in vitro and generation of the three main epithelial cell lineages that make up the mammalian pancreas.
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Multi-omic markers of intraductal papillary mucinous neoplasms progression into pancreatic cancer

Semin Cancer Biol. 2024 Dec 27;109:25-43. doi: 10.1016/j.semcancer.2024.12.005. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal and common form of pancreatic cancer, it has no specific symptoms, and most of the patients are diagnosed when the disease is already at an advanced stage. Chemotherapy typically has only a modest effect, making surgery the most effective treatment option. However, only a small percentage of patients are amenable to surgery. One viable strategy to reduce PDAC death burden associated with the disease is to focus on precursor lesions and identify markers able to predict who will evolve into PDAC. While most PDACs are believed to be preceded by pancreatic intraepithelial neoplasms (PanINs), 5-10 % arise from Intraductal papillary mucinous neoplasms (IPMNs), which are mass-forming cystic lesions that are very common in the general population. IPMNs offer an invaluable model of pancreatic carcinogenesis for researchers to analyse, as well as a target population for PDAC early detection by clinicians. The evolution of IPMN into cancer is a complex and multistep process, therefore the identification of individual markers will not be the solution. In recent years, multiple omics technologies have been instrumental to identify possible biomarkers of IPMN progression and carcinogenesis. The only foreseeable strategy will be to integrate multi-omics data, alongside clinical and morphological features, into a progression score or signature using either standard epidemiologic tools or artificial intelligence. The aim of this manuscript is to review the current knowledge on genetic biomarkers and to briefly mention also additional omics, such as metabolomics, the exposome, the miRNome and epigenomics of IPMNs.

PMID:39733817 | DOI:10.1016/j.semcancer.2024.12.005

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How to build the virtual cell with artificial intelligence: Priorities and opportunities

Advances in AI and omics enable the creation of AI virtual cells (AIVCs)—multi-scale, multimodal neural network models that simulate molecules, cells, and tissues across diverse states. This vision outlines their design and collaborative development, promising to transform biological research through high-fidelity simulations, accelerating discoveries, and fostering interdisciplinary open science collaborations.
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Multiscale drug screening for cardiac fibrosis identifies MD2 as a therapeutic target

A multiscale drug discovery platform integrating human induced pluripotent stem cells, 3D-engineered heart tissues, and animal models identifies artesunate as a safe and potent antifibrotic compound.
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Identifying specific functional roles for senescence across cell types

A dual recombinase-mediated genetic system for cell-type-specific lineage tracing, ablation, and gene manipulation of senescent cells reveals distinct roles of senescence across cell types.
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