Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

GEMAS: Prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra,wereusedtopredictdistributioncoefficient(Kd)valuesforselectedaddedsolublemetalcations(Agþ,Co 2þ,Cu 2þ,Mn 2þ,Ni 2þ, Pb2þ, Sn 4þ, and Zn2þ) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a singlepointsolublemetal orradioactiveisotopespike.Theoptimummodels, usingacombinationofMIR–DRIFTspectra andsoilpH,resulted ingoodpredictionsforlogKdþ1forCo,Mn,Ni,Pb,andZn(R20.83)butpoorpredictionsforAg,Cu,andSn(R2<0.50).Thesemodels wereappliedtothepredictionoflogKdþ1valuesintheremaining4313unknownsoils.ThePLSRmodelsprovidearapidandinexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validationwillbeneededtoenablethepredictionoflogKdþ1valuesinsoilsworldwidewithdifferentsoiltypesandpropertiesnotcovered in the existing mode