A new study generated one of the most comprehensive spatially resolved transcriptomic maps of cellular communication between bone and skeletal muscle in a young mouse. Using spatial transcriptomics, computational deconvolution, and ligand-receptor network analysis, researchers identified signaling pathways that coordinate tissue maintenance, remodeling, and vascular support. Key interactions involving collagen, thrombospondin, tenascin, and VEGF pathways were validated experimentally and across independent datasets. The findings provide a foundation for studying musculoskeletal disorders and aging.

Sperm carry far more than DNA. As they develop in the testis and mature in the epididymis, they also carry a shifting set of chemical marks on RNA — a molecular layer that may help shape fertility and influence how paternal experiences are passed to the next generation.

Now, researchers have produced a detailed map of this changing “sperm RNA modification code.” In a study published in Science China Life Sciences, the team profiled 27 types of RNA modifications across mouse testis development, purified spermatogenic cells, sperm collected from different regions of the epididymis and a typeⅡdiabetes mellitus mouse model. The work reveals that sperm RNA modifications are not static labels, but a dynamic program that is written, erased and reorganized as sperm move toward maturity.

G protein-coupled receptors (GPCRs) are important therapeutic targets for numerous diseases. However, developing highly selective drugs for GPCRs remains a challenge. Researchers have now developed a new platform termed extracellular vesicle (EV)-Systematic Evolution of Ligands by Exponential Enrichment, which uses EVs to efficiently isolate potent DNA aptamers. Using this method, they identified an analgesic aptamer that targets µ-opioid receptor to mimic morphine-like activity, demonstrating the platform’s potential in accelerating drug discovery for GPCR-related conditions

Some memories remain with us for years, shaping how we learn from experience and adapt to the world around us. Others disappear quickly, even when they once seemed important. Although scientists have long studied how memories are formed in the brain, far less is known about what allows certain memories to persist over time.

A research team led by Dr. KOH Wuhyun at the Center for Memory and Glioscience within the Institute for Basic Science (IBS), together with researchers at the Korea Brain Research Institute (KBRI), has now discovered that astrocytes play a critical role in this process. Astrocytes are star-shaped cells in the brain that have traditionally been considered support cells for neurons. The study shows that these cells actively help determine whether memories can be maintained over long periods of time, revealing a previously unknown mechanism that supports long-term memory persistence.

In mammals, hair follicles emerge during embryonic development, forming geometric patterns that vary from one species to another. But how is the position of each hair determined? A team from the University of Geneva (UNIGE) has shown that a simple mechanism based on the movement of cells in response to chemical signals can reproduce the formation of hair follicles in two mammalian species. Published in PNAS, the study sheds new light on the self-organizing principles that give rise to complex biological structures.

Virtual fences could make managing grazing livestock on farms more flexible and more efficient whilst improving animal welfare. A new study by the University of Göttingen shows that virtual fences trigger similar behaviour in cattle, in terms of how they move around in the field, to conventional electric fences. This finding clearly puts the concerns, which are commonly expressed about animal welfare, into perspective. The results were published in the journal Animal.

Understanding nanoparticle morphology is essential for elucidating their physical behavior and functional performance. Such morphological characterization of nanoparticles is important for understanding structure–function relationships in colloidal and bionano systems. Here, we present a deep-learning-based framework that enables nanoparticle morphology classification from standard nanoparticle tracking analysis (NTA) data by integrating features derived from single-particle Brownian-motion trajectories and temporal fluctuations in scattered-light intensity. The combined feature representation consistently improved binary (two-category) classification performance across all particle-type combinations, reducing the low-accuracy cases observed in single-feature models and achieving accuracies exceeding 0.82 with 100-frame data. For three-class classification, the per-class correctness averaged approximately 80%. The integrated approach maintained stable performance even with limited particle counts or short data lengths (down to ∼20 frames), underscoring its robustness for practical scenarios such as biomedical diagnostics, rare-material analysis, and environmental nanoparticle monitoring. These capabilities highlight its practical relevance for applications such as extracellular vesicle characterization and nanomedicine quality control. By integrating complementary trajectory- and scattering-intensity-based descriptors, this framework offers a reliable and practical route to scalable, morphology-resolved nanoparticle analysis in liquid media using standard NTA measurements.

Colorless carotenoids have attracted growing interest as naturally derived ingredients for food and cosmetic applications, but their individual geometric isomers have remained difficult to isolate and study. Researchers have now purified high-purity phytoene and phytofluene isomers and comprehensively characterized their structures, ultraviolet absorption, antioxidant properties, isomerization behavior, and skin-related biological activities. Their findings reveal multifunctional properties that may support next-generation skincare, nutricosmetics, and healthy aging products across the food, cosmetic, healthcare, and wellness industries.