We studied the spatial conformation and activity of mitochondria in the developing syncytial male germline cysts during spermatogenesis of the medicinal leeches using light, fluorescent, transmission electron microscopy, and serial block-face scanning electron microscopy. In cysts with spermatogonia and spermatocytes, mitochondria form networks and are in a dynamic hyperfusion state, while in cysts with spermatids, a single huge mitochondrion is observed. As spermiogenesis progresses, this huge mitochondrion is finally located in the future midpiece. The highest activity, in terms of membrane potential, of the mitochondria in H. medicinalis germline cysts was observed in cysts with spermatocytes; the lowest was in cysts with late elongated spermatids.

BACKGROUND: For decoding the mechanism of how cells and organs function information on their ultrastructure is essential. High-resolution 3D imaging has revolutionized morphology. Serial block face scanning electron microscopy (SBF-SEM) offers non-laborious, automated imaging in 3D of up to ~ 1 mm3 large biological objects at nanometer-scale resolution. For many samples there are obstacles. Quality imaging is often hampered by charging effects, which originate in the nonconductive resin used for embedding. Especially, if the imaged region of interest (ROI) includes the surface of the sample and neighbours the empty resin, which insulates the object. This extra resin also obscures the sample\'s morphology, thus making navigation to the ROI difficult.
RESULTS: Using the example of small arthropods and a fish roe we describe a workflow to prepare samples for SBF-SEM using the minimal resin (MR) embedding method. We show that for imaging of surface structures this simple approach conveniently tackles and solves both of the two major problems-charging and ROI localization-that complicate imaging of SBF-SEM samples embedded in an excess of overlying resin. As the surface ROI is not masked by the resin, samples can be precisely trimmed before they are placed into the imaging chamber. The initial approaching step is fast and easy. No extra trimming inside the microscope is necessary. Importantly, charging is absent or greatly reduced meaning that imaging can be accomplished under good vacuum conditions, typically at the optimal high vacuum. This leads to better resolution, better signal to noise ratio, and faster image acquisition.
CONCLUSIONS: In MR embedded samples charging is minimized and ROI easily targeted. MR embedding does not require any special equipment or skills. It saves effort, microscope time and eventually leads to high quality data. Studies on surface-linked ROIs, or any samples normally surrounded by the excess of resin, would benefit from adopting the technique.

The flatworm planarian, Schmidtea mediterranea (Smed) is a master at regenerating and rebuilding whole animals from fragments. A full understanding of Smed\'s regenerative capabilities requires a high-resolution characterization of organs, tissues, and the adult stem cells necessary for regeneration in their native environment. Here, we describe a serial block face scanning electron microscopy (SBF-SEM) protocol, optimized for Smed specifically, for visualizing the ultrastructure of membranes and condensed chromosomes in this model organism.

UNASSIGNED: The visual signals evoked at the retinal ganglion cells are modified and modulated by various synaptic inputs that impinge on lateral geniculate nucleus cells before they are sent to the cortex. The selectivity of geniculate inputs for clustering or forming microcircuits on discrete dendritic segments of geniculate cell types may provide the structural basis for network properties of the geniculate circuitry and differential signal processing through the parallel pathways of vision. In our study, we aimed to reveal the patterns of input selectivity on morphologically discernable relay cell types and interneurons in the mouse lateral geniculate nucleus.
UNASSIGNED: We used two sets of Scanning Blockface Electron Microscopy (SBEM) image stacks and Reconstruct software to manually reconstruct of terminal boutons and dendrite segments. First, using an unbiased terminal sampling (UTS) approach and statistical modeling, we identified the criteria for volume-based sorting of geniculate boutons into their putative origins. Geniculate terminal boutons that were sorted in retinal and non-retinal categories based on previously described mitochondrial morphology, could further be sorted into multiple subpopulations based on their bouton volume distributions. Terminals deemed non-retinal based on the morphological criteria consisted of five distinct subpopulations, including small-sized putative corticothalamic and cholinergic boutons, two medium-sized putative GABAergic inputs, and a large-sized bouton type that contains dark mitochondria. Retinal terminals also consisted of four distinct subpopulations. The cutoff criteria for these subpopulations were then applied to datasets of terminals that synapse on reconstructed dendrite segments of relay cells or interneurons.
UNASSIGNED: Using a network analysis approach, we found an almost complete segregation of retinal and cortical terminals on putative X-type cell dendrite segments characterized by grape-like appendages and triads. On these cells, interneuron appendages intermingle with retinal and other medium size terminals to form triads within glomeruli. In contrast, a second, presumed Y-type cell displayed dendrodendritic puncta adherentia and received all terminal types without a selectivity for synapse location; these were not engaged in triads. Furthermore, the contribution of retinal and cortical synapses received by X-, Y- and interneuron dendrites differed such that over 60% of inputs to interneuron dendrites were from the retina, as opposed to 20% and 7% to X- and Y-type cells, respectively.
UNASSIGNED: The results underlie differences in network properties of synaptic inputs from distinct origins on geniculate cell types.

The identity and function of a given cell type relies on the differential expression of gene batteries that promote diverse phenotypes and functional specificities. Therefore, the identification of the molecular and morphological fingerprints of cell types across taxa is essential for untangling their evolution. Here we use a multidisciplinary approach to identify the molecular and morphological features of an exocrine, pancreas-like cell type harbored within the sea urchin larval gut. Using single cell transcriptomics, we identify various cell populations with a pancreatic-like molecular fingerprint that are enriched within the S. purpuratus larva digestive tract. Among these, in the region where they reside, the midgut/stomach domain, we find that populations of exocrine pancreas-like cells have a unique regulatory wiring distinct from the rest the of the cell types of the same region. Furthermore, Serial Block-face scanning Electron Microscopy (SBEM) of the exocrine cells shows that this reported molecular diversity is associated to distinct morphological features that reflect the physiological and functional properties of this cell type. Therefore, we propose that these sea urchin exocrine cells are homologous to the well-known mammalian pancreatic acinar cells and thus we trace the origin of this particular cell type to the time of deuterostome diversification. Overall, our approach allows a thorough characterization of a complex cell type and shows how both the transcriptomic and morphological information contribute to disentangling the evolution of cell types and organs such as the pancreatic cells and pancreas.

The blood system is supported by hematopoietic stem and progenitor cells (HSPCs) found in a specialized microenvironment called the niche. Many different niche cell types support HSPCs, however how they interact and their ultrastructure has been difficult to define. Here, we show that single endogenous HSPCs can be tracked by light microscopy, then identified by serial block-face scanning electron microscopy (SBEM) at multiscale levels. Using the zebrafish larval kidney marrow (KM) niche as a model, we followed single fluorescently labeled HSPCs by light sheet microscopy, then confirmed their exact location in a 3D SBEM dataset. We found a variety of different configurations of HSPCs and surrounding niche cells, suggesting there could be functional heterogeneity in sites of HSPC lodgement. Our approach also allowed us to identify dopamine beta-hydroxylase (dbh) positive ganglion cells as a previously uncharacterized functional cell type in the HSPC niche. By integrating multiple imaging modalities, we could resolve the ultrastructure of single rare cells deep in live tissue and define all contacts between an HSPC and its surrounding niche cell types.

The ability of locusts to detect looming stimuli and avoid collisions or predators depends on a neuronal circuit in the locust\'s optic lobe. Although comprehensively studied for over three decades, there are still major questions about the computational steps of this circuit. We used fourth instar larvae of Locusta migratoria to describe the connection between the lobula giant movement detector 1 (LGMD1) neuron in the lobula complex and the upstream neuropil, the medulla. Serial block-face scanning electron microscopy (SBEM) was used to characterize the morphology of the connecting neurons termed trans-medullary afferent (TmA) neurons and their synaptic connectivity. This enabled us to trace neurons over several hundred micrometers between the medulla and the lobula complex while identifying their synapses. We traced two different TmA neurons, each from a different individual, from their synapses with the LGMD in the lobula complex up into the medulla and describe their synaptic relationships. There is not a simple downstream transmission of the signal from a lamina neuron onto these TmA neurons; there is also a feedback loop in place with TmA neurons making outputs as well as receiving inputs. More than one type of neuron shapes the signal of the TmA neurons in the medulla. We found both columnar and trans-columnar neurons connected with the traced TmA neurons in the medulla. These findings indicate that there are computational steps in the medulla that have not been included in models of the neuronal pathway for looming detection.

This study investigated the relationship of the expression of transient receptor potential channel 1 (TRPC1), small breast epithelial mucin (SBEM) in breast cancer tissues with clinical pathological features and prognosis of patients. Altogether 50 patients with breast cancer who were treated in Weifang People\'s hospital from April 2017 to November 2018 were selected, and the mRNA and protein differences of TRPC1 and SBEM in breast cancer patients and normal breast cancer tissues were detected by qRT-PCR and Western blot. Spearman test was used for correlation analysis. Logistic univariate and multivariate analysis were performed on the risk factors related to breast cancer metastasis in breast cancer patients. The expression of TRPC1 and SBEM in breast cancer tissues was significantly higher than that in normal breast tissues (P<0.001). The mRNA expression of TRPC1, SBEM and protein was not related to age, tumor size and tissue grade of breast cancer patients, but related to TNM stage, clinical stage and lymph node metastasis (P<0.001). The relative expression of TRPC1 was positively correlated with clinical stage of breast cancer (r=0.992, P<0.001). The relative expression of SBEM was positively correlated with the clinical stage of breast cancer (r=0.853, P<0.001). The relative expression of TRPC1 was positively correlated with TNM staging of breast cancer (r=0.860, P<0.001). The relative expression of SBEM was positively correlated with TNM staging of breast cancer (r=0.880, P<0.001). Multivariate conditional Logistic regression analysis showed that TNM staging, TRPC1, SBEM were independent risk factors for malignant breast cancer metastasis. On the contrary, expression of TRPC1 and SBEM in breast cancer tissues was up-regulated. TRPC1 and SBEM may be involved in the process of breast cancer occurrence, development and metastasis, and can be used as potential tissue biomarkers in diagnosis of breast cancer metastasis and disease assessment.

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One recent technical innovation in neuroscience is microcircuit analysis using three-dimensional reconstructions of neural elements with a large volume Electron microscopy (EM) data set. Large-scale data sets are acquired with newly-developed electron microscope systems such as automated tape-collecting ultramicrotomy (ATUM) with scanning EM (SEM), serial block-face EM (SBEM) and focused ion beam-SEM (FIB-SEM). Currently, projects are also underway to develop computer applications for the registration and segmentation of the serially-captured electron micrographs that are suitable for analyzing large volume EM data sets thoroughly and efficiently. The analysis of large volume data sets can bring innovative research results. These recently available techniques promote our understanding of the functional architecture of the brain.