Myeloid-Mas Signaling Modulates Pathogenic Crosstalk among MYC+CD63+ Endothelial Cells, MMP12+ Macrophages, and Monocytes in Acetaminophen-Induced Liver Injury.

Acetaminophen overdose is a leading cause of acute liver failure (ALF). Despite the pivotal role of the inflammatory microenvironment in the progression of advanced acetaminophen-induced liver injury (AILI), a comprehensive understanding of the underlying cellular interactions and molecular mechanisms remains elusive. Mas is a G protein-coupled receptor highly expressed by myeloid cells; however, its role in the AILI microenvironment remains to be elucidated. A multidimensional approach, including single-cell RNA sequencing, spatial transcriptomics, and hour-long intravital imaging, is employed to characterize the microenvironment in Mas1 deficient mice at the systemic and cell-specific levels. The characteristic landscape of mouse AILI models involves reciprocal cellular communication among MYC+CD63+ endothelial cells, MMP12+ macrophages, and monocytes, which is maintained by enhanced glycolysis and the NF-κB/TNF-α signaling pathway due to myeloid-Mas deficiency. Importantly, the pathogenic microenvironment is delineated in samples obtained from patients with ALF, demonstrating its clinical relevance. In summary, these findings greatly enhance the understanding of the microenvironment in advanced AILI and offer potential avenues for patient stratification and identification of novel therapeutic targets.

Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging.

High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40 GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.