![]() Merkin Institute for Transformative Technologies in Healthcare The Merkin Institute is supporting early-stage ideas aimed at advancing powerful technological approaches for improving how we understand and treat disease.Klarman Cell Observatory The Klarman Cell Observatory is systematically defining mammalian cellular circuits, how they work together to create tissues and organs, and are perturbed to cause disease.Gerstner Center for Cancer Diagnostics The Gerstner Center is developing next-generation diagnostic technology for cancer detection and tracking disease progression.Carlos Slim Center for Health Research The Slim Center aims to bring the benefits of genomics-driven medicine to Latin America, gleaning new insights into diseases with relevance to the region.Collaborations and consortia We join with institutions and scientists the world over to address foundational challenges in science and health.Resources, services, and tools Key scientific datasets and computational tools developed by our scientists and their collaborators.Publications A catalog of scientific papers published by our members and staff scientists.Partnering and licensing We work closely with pharmaceutical, biotech, and technology partners to accelerate the translation of our discoveries.Patient-partnered research Patients partner with our scientists to accelerate the pace of discovery and find better treatments.COVID-19 Our community is deeply engaged in the local, national, and global effort to respond to COVID-19.Thus, the Muscle2View is a viable tool for researchers aiming to quantify immunohistochemical variables from skeletal muscle biopsies.ĬellProfiler capillary-to-fiber interface high-content immunohistochemistry image analysis skeletal muscle biopsy. In addition to fiber typing, myonuclei counting, and the quantification of fiber type-specific morphological measurements, the Muscle2View pipeline can identify the complex capillary-to-fiber network from a batch of images within minutes. NEW & NOTEWORTHY Here, we developed a freely available CellProfiler-based pipeline termed Muscle2View, which provides unbiased, high-content analysis of muscle cross-sectional immunohistochemistry images. This robust analysis is done in one single run within a user-friendly and flexible environment based on the free and widely used image software CellProfiler. In addition to the classical morphological measurements, the Muscle2View can identify the complex capillary-to-fiber network and myonuclear density in a fiber type-specific manner. Collectively, we demonstrate that the Muscle2View pipeline can provide unbiased and high-content analysis of muscle cross-sectional immunohistochemistry images. For several variables, however, there were differences (5-15%) between values computed by manual counting and Muscle2View, suggesting that the methods should not necessarily be used interchangeably. When comparing the Muscle2View pipeline to manual or semiautomatic analysis, overall the results revealed strong correlations. The novel identification of the capillary-to-fiber interface allowed for the calculation of microvascular factors such as capillary contacts (CC), individual capillary-to-fiber ratio (C/Fi), and capillary-to-fiber perimeter exchange (CFPE) index. Provided that the images are of sufficient quality and the settings are configured for the specific study, the pipeline allows for automatic and unsupervised analysis of fiber borders, myonuclei, capillaries, and morphometric parameters in a fiber type-specific manner from large batches of images in <10 min/tissue sample. Here, we developed Muscle2View, a free CellProfiler-based pipeline that integrates all key fiber-morphological variables, including the novel quantification of the capillary-to-fiber interface, in one single tool. Because manual immunohistochemical analysis of features such as skeletal muscle fiber typing, capillaries, myonuclei, and fiber size-related parameters is time consuming and prone to user subjectivity, automatic computational methods could allow for faster and more objective evaluation. ![]()
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