QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology.

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber crosssectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the “patchy” distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigatorspecific needs and provides novel analytical approaches for quantifying muscle morphology

Exosome loaded immunomodulatory biomaterials alleviate local immune response in immunocompetent diabetic mice post islet xenotransplantation

Foreign body response (FBR) to biomaterials compromises the function of implants and leads to medical complications. Here, we report a hybrid alginate microcapsule (AlgXO) that attenuated the immune response after implantation, through releasing exosomes derived from human Umbilical Cord Mesenchymal Stem Cells (XOs). Upon release, XOs suppress the local immune microenvironment, where xenotransplantation of rat islets encapsulated in AlgXO led to >170 days euglycemia in immunocompetent mouse model of Type 1 Diabetes. In vitro analyses revealed that XOs suppressed the proliferation of CD3/CD28 activated splenocytes and CD3+ T cells. Comparing suppressive potency of XOs in purified CD3+ T cells versus splenocytes, we found XOs more profoundly suppressed T cells in the splenocytes co-culture, where a heterogenous cell population is present. XOs also suppressed CD3/CD28 activated human peripheral blood mononuclear cells (PBMCs) and reduced their cytokine secretion including IL-2, IL-6, IL-12p70, IL-22, and TNFα. We further demonstrate that XOs mechanism of action is likely mediated via myeloid cells and XOs suppress both murine and human macrophages partly by interfering with NFκB pathway. We propose that through controlled release of XOs, AlgXO provide a promising new platform that could alleviate the local immune response to implantable biomaterials

The immune system in Duchenne muscular dystrophy: Friend or foe

Duchenne muscular dystrophy (DMD) is a genetic disease caused by mutations in the X-linked dystrophin gene, resulting in reduced or absent protein production, subsequently leading to the structural instability of the dystroglycan complex (DGC), muscle degeneration, and early death in males. Thus, current treatments have been targeting the genetic defect either by bypassing the mutation through exon skipping or replacing the defective gene through gene therapy and stem cell approaches. However, what has been an underappreciated mediator of muscle pathology and, ultimately, of muscle degeneration and fibrotic replacement, is the prominent inflammatory response. Of potentially critical importance, however, is the fact that the elements mediating the inflammatory response also play an essential role in tissue repair. In this opinion piece, we highlight the detrimental and supportive immune parameters that occur as a consequence of the genetic disorder and discuss how changes to immunity can potentially ameliorate the disease intensity and be employed in conjunction with efforts to correct the genetic disorder

FOXO1 Mediates Vitamin D Deficiency–Induced Insulin Resistance in Skeletal Muscle

Prospective epidemiological studies have consistently shown a relationship between vitamin D deficiency, insulin resistance, and type 2 diabetes mellitus (DM2). This is supported by recent trials showing that vitamin D supplementation in prediabetic or insulin-resistant patients with inadequate vitamin D levels improves insulin sensitivity. However, the molecular mechanisms underlying vitamin D deficiency-induced insulin resistance and DM2 remain unknown. Skeletal muscle insulin resistance is a primary defect in the majority of patients with DM2. Although sustained activation of forkhead box O1 (FOXO1) in skeletal muscle causes insulin resistance, a relationship between vitamin D deficiency and FOXO1 activation in muscle is unknown. We generated skeletal muscle-specific vitamin D receptor (VDR)-null mice and discovered that these mice developed insulin resistance and glucose intolerance accompanied by increased expression and activity of FOXO1. We also found sustained FOXO1 activation in the skeletal muscle of global VDR-null mice. Treatment of C2C12 muscle cells with 1,25-dihydroxyvitamin D (VD3) reduced FOXO1 expression, nuclear translocation, and activity. The VD3-dependent suppression of FOXO1 activation disappeared by knockdown of VDR, indicating that it is VDR-dependent. Taken together, these results suggest that FOXO1 is a critical target mediating VDR-null signaling in skeletal muscle. The novel findings provide the conceptual support that persistent FOXO1 activation may be responsible for insulin resistance and impaired glucose metabolism in vitamin D signaling-deficient mice, as well as evidence for the utility of vitamin D supplementation for intervention in DM2

The immune system in Duchenne muscular dystrophy: Friend or foe.

Duchenne muscular dystrophy (DMD) is a genetic disease caused by mutations in the X-linked dystrophin gene, resulting in reduced or absent protein production, subsequently leading to the structural instability of the dystroglycan complex (DGC), muscle degeneration, and early death in males. Thus, current treatments have been targeting the genetic defect either by bypassing the mutation through exon skipping or replacing the defective gene through gene therapy and stem cell approaches. However, what has been an underappreciated mediator of muscle pathology and, ultimately, of muscle degeneration and fibrotic replacement, is the prominent inflammatory response. Of potentially critical importance, however, is the fact that the elements mediating the inflammatory response also play an essential role in tissue repair. In this opinion piece, we highlight the detrimental and supportive immune parameters that occur as a consequence of the genetic disorder and discuss how changes to immunity can potentially ameliorate the disease intensity and be employed in conjunction with efforts to correct the genetic disorder