https://researchdata.se/en/catalogue Search results en This repository contains the processed dataset used in the study “Small-scale mixing regulates the reconfiguration of the Arabian Sea oxygen minimum zone.” The data are derived from SeaExplorer glider observations collected in the northwestern Arabian Sea and Sea of Oman between November 2024 and February 2025. The dataset includes the hydrographic, dissolved oxygen, current velocity, and microstructure turbulence variables used in the analyses and figures presented in the manuscript. It contains quality-controlled and gridded observations, derived seawater properties, processed AD2CP velocity fields, and microstructure-based estimates of turbulent kinetic energy and temperature-variance dissipation rates. Each variable within the NetCDF file has its corresponding attributes and metadata. These data were used to quantify distinct oxygen supply pathways, characterize small-scale mixing regimes, estimate diapycnal oxygen fluxes and flux convergence, and assess how mixing redistributes oxygen across different oxygen classes within the Arabian Sea oxygen minimum zone. The original observational data are archived separately on Zenodo. This repository provides the processed data products used for the manuscript analysis. The analysis and figure-generation code required to reproduce the results will be made available through the associated GitHub repository. Mon, 07 Sep 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-5281-zenodo-22650492 https://researchdata.se/en/catalogue/dataset/doi-10-5281-zenodo-22650492 University of Gothenburg Pinto-Juica, Mauro Queste, Bastien Font, Estel Mean diffusivity (MD) and fractional anisotropy (FA) obtained with diffusion tensor imaging (DTI) have been associated with cell density and tissue anisotropy across tumors, but these associations have been challenged at the microscopic level and several additional histological features have been suggested as contributing to MD and FA. To facilitate investigation of the biological underpinnings of DTI parameters, we performed ex-vivo dMRI at 200 μm isotropic resolution on 16 excised meningioma tumor samples. The samples together span a variety of microstructural features: six different meningioma types and two different grades. Diffusion tensor imaging (DTI) was used to produce maps such as MD, FA, in-plane FA (FAIP), axial diffusivity (AD) or radial diffusivity (RD). The maps were coregistered to H&E (hematoxylin & eosin) and VEGF-stained histological slides. In this repository, we provide raw and analysed DTI maps coregistered to H&E- and VEGF-stained histology slides, as well as an example analysis of the data that aims to quantify the degree to which cell density (CD), structure anisotropy (SA), as determined from histology, in comparison with convolutional neural network (CNN) account for the intra-tumor variability of MD and FAIP in meningioma tumors. The pipeline used to process the raw DTI data and the coregistration tools are hosted by GitHub and the code related to the our example analysis are available here. Please refer and cite our two journal articles mentioned in the section References below for further information on the processing and if you find this data useful. We hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by diffusion MRI. Tue, 14 Feb 2023 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23698-aida-micromen https://researchdata.se/en/catalogue/dataset/doi-10-23698-aida-micromen AIDA Data Hub Brabec, Jan Englund, Elisabet Bengzon, Johan Szczepankiewicz, Filip van Westen, Danielle Sundgren, Pia Nilsson, Markus