Search

Abstract A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube ( https://github.com/ZJUFanLab/scCube ), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications.

Abstract Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative method to identify spatially variable cell subpopulations by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We benchmark scSpace with both simulated and biological datasets, and demonstrate that scSpace can accurately and robustly identify spatially variated cell subpopulations. When employed to reconstruct the spatial architectures of complex tissue such as the brain cortex, the small intestinal villus, the liver lobule, the kidney, the embryonic heart, and others, scSpace shows promising performance on revealing the pairwise cellular spatial association within single-cell data. The application of scSpace in melanoma and COVID-19 exhibits a broad prospect in the discovery of spatial therapeutic markers.

Current methods to reanalyze bulk RNA-seq at spatially resolved single-cell resolution have limitations. Here, the authors develop Bulk2Space, a spatial deconvolution algorithm using single-cell and spatial transcriptomics as references, providing new insights into spatial heterogeneity within bulk tissue.

Spin density waves are a spatial modulation of the spin, and can be either commensurate or incommensurate with the crystal lattice. Here, Hu et al. use spin-polarised scanning tunnelling microscopy to observe the incommensurate spin density wave on cleaned Chromium surface.

Abstract Solid electrolyte is vital to ensure all-solid-state batteries with improved safety, long cyclability, and feasibility at different temperatures. Herein, we report a new family of amorphous solid electrolytes, xLi2O-MCly (M = Ta or Hf, 0.8 ≤ x ≤ 2, y = 5 or 4). xLi2O-MCly amorphous solid electrolytes can achieve desirable ionic conductivities up to 6.6 × 10−3 S cm−1 at 25 °C, which is one of the highest values among all the reported amorphous solid electrolytes and comparable to those of the popular crystalline ones. The mixed-anion structural models of xLi2O-MCly amorphous SEs are well established and correlated to the ionic conductivities. It is found that the oxygen-jointed anion networks with abundant terminal chlorines in xLi2O-MCly amorphous solid electrolytes play an important role for the fast Li-ion conduction. More importantly, all-solid-state batteries using the amorphous solid electrolytes show excellent electrochemical performance at both 25 °C and −10 °C. Long cycle life (more than 2400 times of charging and discharging) can be achieved for all-solid-state batteries using the xLi2O-TaCl5 amorphous solid electrolyte at 400 mA g−1, demonstrating vast application prospects of the oxychloride amorphous solid electrolytes.

Myeloid-derived growth factor (MYDGF) is an angiogenic growth factor with therapeutic potential for ischemic tissue repair and the receptor is still unknown. Here the authors present the crystal structure of human MYDGF and identify its functional epitope through mutagenesis studies.