81 research outputs found

    Image informatics strategies for deciphering neuronal network connectivity

    Get PDF
    Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

    Xanthogranulomatous salpingo-oophoritis: a case report and review of literature

    Get PDF
    Xanthogranulomatous inflammation of ovary is a rare disease that is characterized by presence of large number of lipid laden macrophages with an admixture of neutrophils, lymphocytes, plasma cells and multinucleated giant cells. It is misdiagnosed as ovarian tumour that leads to extensive surgery including hysterectomy. In this report we describe a case of Xanthogranulomatous salpingo-oophoritis along with review of literature

    Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping

    Get PDF
    To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks

    Differences in 5'untranslated regions highlight the importance of translational regulation of dosage sensitive genes

    Get PDF
    Background: Untranslated regions (UTRs) are important mediators of post-transcriptional regulation. The length of UTRs and the composition of regulatory elements within them are known to vary substantially across genes, but little is known about the reasons for this variation in humans. Here, we set out to determine whether this variation, specifically in 5’UTRs, correlates with gene dosage sensitivity. Results: We investigate 5’UTR length, the number of alternative transcription start sites, the potential for alternative splicing, the number and type of upstream open reading frames (uORFs) and the propensity of 5’UTRs to form secondary structures. We explore how these elements vary by gene tolerance to loss-of-function (LoF; using the LOEUF metric), and in genes where changes in dosage are known to cause disease. We show that LOEUF correlates with 5’UTR length and complexity. Genes that are most intolerant to LoF have longer 5’UTRs, greater TSS diversity, and more upstream regulatory elements than their LoF tolerant counterparts. We show that these differences are evident in disease gene-sets, but not in recessive developmental disorder genes where LoF of a single allele is tolerated. Conclusions: Our results confirm the importance of post-transcriptional regulation through 5'UTRs in tight regulation of mRNA and protein levels, particularly for genes where changes in dosage are deleterious and lead to disease. Finally, to support gene-based investigation we release a web-based browser tool, VuTR, that supports exploration of the composition of individual 5'UTRs and the impact of genetic variation within them

    NetMets: software for quantifying and visualizing errors in biological network segmentation

    Get PDF
    One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization

    Hepatocyte-specific IL11 cis-signaling drives lipotoxicity and underlies the transition from NAFLD to NASH

    Get PDF
    IL11 is important for fibrosis in non-alcoholic steatohepatitis (NASH) but its role beyond the stroma in liver disease is unclear. Here, we investigate the role of IL11 in hepatocyte lipotoxicity. Hepatocytes highly express IL11RA and secrete IL11 in response to lipid loading. Autocrine IL11 activity causes hepatocyte death through NOX4-derived ROS, activation of ERK, JNK and caspase-3, impaired mitochondrial function and reduced fatty acid oxidation. Paracrine IL11 activity stimulates hepatic stellate cells and causes fibrosis. In mouse models of NASH, hepatocyte-specific deletion of Il11ra1 protects against liver steatosis, fibrosis and inflammation while reducing serum glucose, cholesterol and triglyceride levels and limiting obesity. In mice deleted for Il11ra1, restoration of IL11 cis-signaling in hepatocytes reconstitutes steatosis and inflammation but not fibrosis. We found no evidence for the existence of IL6 or IL11 trans-signaling in hepatocytes or NASH. These data show that IL11 modulates hepatocyte metabolism and suggests a mechanism for NAFLD to NASH transition
    corecore