Surface charge and membrane lipid composition define extracellular vesicle (EV) function: Lipid asymmetry enables new quality metrics for EV-based therapeutics
Peer-Reviewed Publication
Updates every hour. Last Updated: 14-Apr-2026 10:16 ET (14-Apr-2026 14:16 GMT/UTC)
Researchers at the University of Tokyo clarified how membrane lipid composition determines the surface charge of extracellular vesicles (EVs). They show that differences between exosomes and membrane-derived EVs arise from phospholipid asymmetry, particularly phosphatidylserine distribution. The study proposes zeta potential as a key indicator for EV classification and quality control, offering a foundation for standardization and rational design of EV-based therapeutics. This work was conducted as part of a JST COI-NEXT program, led by Innovation Center of NanoMedicine (iCONM).
Florida’s coral reefs are under siege from fast-spreading diseases like Stony Coral Tissue Loss Disease, yet their hidden structural impacts remain poorly understood. FAU researchers used advanced micro-CT imaging and deep learning to analyze coral skeletons in 3D, revealing subtle changes in porosity, density and thickness with 98% accuracy. This innovative approach offers a powerful new tool to rapidly assess reef health and better guide conservation strategies in the face of escalating environmental threats.
At present, only around 5% of patients with colon cancer are candidates for immunotherapy. This new biomarker could make it possible to determine more accurately which individuals may receive this treatment with a likelihood of success and expand the number of patients who could benefit from it. The study, led by the Hospital del Mar Research Institute and IRB Barcelona, shows that the determination of this protein, CTHRC1, can be used to assess patient prognosis. At the same time, it opens up new avenues to approach this type of tumour. The research team has demonstrated that this biomarker can be detected using routine diagnostic tests in the clinical practice of any Pathology service.
The USC research team that recently identified the hormone-encoding gene GDF15 as a key driver of pregnancy sickness has identified 9 additional genes linked to its most severe form, hyperemesis gravidarum (HG). Six of these genes had not been previously linked to the condition. Growing evidence shows HG has a strong biological and genetic basis and can lead to severe malnourishment, putting both mother and baby at risk. In the largest genetic study of HG to date, researchers from the Keck School of Medicine of USC and their international collaborators conducted a genome-wide association study (GWAS) of 10,974 women with the condition and 461,461 controls across European, Asian, African and Latino ancestries. The findings, just published in Nature Genetics, offer new clues about the condition and new hope for those affected. The researchers identified 10 genes linked to HG—four previously identified and six new. The strongest link by far was to growth differentiation factor 15 (GDF15), a gene that produces a hormone of the same name, which rises sharply during pregnancy. The other genes identified relate to key pregnancy hormones, appetite and nausea, insulin and metabolism, how the brain learns and adapts, and certain pregnancy outcomes. The findings reveal new potential treatment targets and could possibly also help match existing medications to patients based on their genetic profiles. The research team also just received approval to launch a clinical trial of metformin, a widely used diabetes medicine that increases GDF15 levels. The study will test whether taking metformin before pregnancy can desensitize women to the hormone, potentially reducing nausea and vomiting or preventing HG in women who have had it before.
The study, published in Cell Reports, describes how a connection between the hippocampal hemispheres is essential for spatial navigation and memory-based decision-making. The results show that this connection is altered in a genetic disease model associated with schizophrenia, which could help to understand the origin of cognitive deficits.