Biological volume EM with focused Ga ion beam depends on formation of radiation-resistant Ga-rich layer at block face.

Volume electron microscopy (vEM) enables biologists to visualize nanoscale 3D ultrastructure of entire eukaryotic cells and tissues prepared by heavy atom staining and plastic embedding. The highest resolution vEM technique is focused ion-beam scanning electron microscopy (FIB-SEM), which provides nearly isotropic (~5-10 nm) spatial resolution at fluences of > 10,000 e/nm. However, it is not clear how such high resolution is achievable because serial block-face (SBF) SEM, which incorporates an in-situ ultramicrotome instead of a Ga FIB beam, results in radiation-induced collapse of similar specimen blocks at fluences of only ~20 e/nm.

Densely Populated Cell and Organelles Segmentation with U-Net Ensembles.

The complex and highly intertwined morphology of activated platelets within thrombi poses significant challenges for segmentation. In this work, we present a robust dual-network pipeline for cell and organelle segmentation. This multi-network approach enables the detection of fine details near the membrane while simultaneously facilitating long-range smoothing in regions distal to the membrane, drastically improving the performance of the watershed clustering algorithm compared to single-network approaches.

Microtubule-dependent apical polarization of basement membrane matrix mRNAs in mouse epithelial cells.

The basement membrane (BM) demarcating epithelial tissues undergoes rapid expansion to accommodate tissue growth and morphogenesis during embryonic development. To facilitate the secretion of bulky BM proteins, their mRNAs are polarized basally in the follicle epithelial cells of the Drosophila egg chamber to position their sites of production close to their deposition. In contrast, we observed the apical rather than basal polarization of all major BM mRNAs in the outer epithelial cells adjacent to the BM of mouse embryonic salivary glands using single-molecule RNA fluorescence in situ hybridization (smFISH).

Deep learning, 3D ultrastructural analysis reveals quantitative differences in platelet and organelle packing in COVID-19/SARSCoV2 patient-derived platelets.

Platelets contribute to COVID-19 clinical manifestations, of which microclotting in the pulmonary vasculature has been a prominent symptom. To investigate the potential diagnostic contributions of overall platelet morphology and their α-granules and mitochondria to the understanding of platelet hyperactivation and micro-clotting, we undertook a 3D ultrastructural approach. Because differences might be small, we used the high-contrast, high-resolution technique of focused ion beam scanning EM (FIB-SEM) and employed deep learning computational methods to evaluate nearly 600 individual platelets and 30 000 included organelles within three healthy controls and three severely ill COVID-19 patients.