Automated image-analysis method for the quantification of fiber morphometry and fiber type population in human skeletal muscle

Muscle fibre morphometric analysis (MusMA) correlates with muscle function and cardiovascular risk prognosis

Morphometry of striated muscle fibres is critical for monitoring muscle health and function. Here, we evaluated functional parameters of skeletal and cardiac striated muscle in two experimental models using the Morphometric Analysis of Muscle Fibre tool (MusMA). The collagen-induced arthritis model was used to evaluate the function of skeletal striated muscle and the non-alcoholic fatty liver disease model was used for cardiac striated muscle analysis. After euthanasia, we used haeamatoxylin and eosin stained sections of skeletal and cardiac muscle to perform muscle fibre segmentation and morphometric analysis. Morphometric analysis classified muscle fibres into six subpopulations: normal, regular hypertrophic, irregular hypertrophic, irregular, irregular atrophic and regular atrophic. The percentage of atrophic fibres was associated with lower walking speed (p = 0.009) and lower body weight (p = 0.026), respectively. Fibres categorized as normal were associated with maximum grip strength (p < 0.001) and higher march speed (p < 0.001). In the evaluation of cardiac striated muscle fibres, the percentage of normal cardiomyocytes negatively correlated with cardiovascular risk markers such as the presence of abdominal adipose tissue (p = .003), miR-33a expression (p = .001) and the expression of miR-126 (p = .042) Furthermore, the percentage of atrophic cardiomyocytes correlated significantly with the Castelli risk index II (p = .014). MusMA is a simple and objective tool that allows the screening of striated muscle fibre morphometry, which can complement the diagnosis of muscle diseases while providing functional and prognostic information in basic and clinical research.

Duchenne and Becker muscular dystrophy: Cellular mechanisms, image analysis, and computational models: A review

The muscle is the principal tissue that is capable to transform potential energy into kinetic energy. This process is due to the transformation of chemical energy into mechanical energy to enhance the movements and all the daily activities. However, muscular tissues can be affected by some pathologies associated with genetic alterations that affect the expression of proteins. As the muscle is a highly organized structure in which most of the signaling pathways and proteins are related to one another, pathologies may overlap. Duchenne muscular dystrophy (DMD) is one of the most severe muscle pathologies triggering degeneration and muscle necrosis. Several mathematical models have been developed to predict muscle response to different scenarios and pathologies. The aim of this review is to describe DMD and Becker muscular dystrophy in terms of cellular behavior and molecular disorders and to present an overview of the computational models implemented to understand muscle behavior with the aim of improving regenerative therapy.

Receptor interacting protein kinase-3 mediates both myopathy and cardiomyopathy in preclinical animal models of Duchenne muscular dystrophy

BACKGROUND

Duchenne muscular dystrophy (DMD) is a progressive muscle degenerative disorder, culminating in a complete loss of ambulation, hypertrophic cardiomyopathy and a fatal cardiorespiratory failure. Necroptosis is the form of necrosis that is dependent upon the receptor-interacting protein kinase (RIPK) 3; it is involved in several inflammatory and neurodegenerative conditions. We previously identified RIPK3 as a key player in the acute myonecrosis affecting the hindlimb muscles of the mdx dystrophic mouse model. Whether necroptosis also mediates respiratory and heart disorders in DMD is currently unknown.

METHODS

Evidence of activation of the necroptotic axis was examined in dystrophic tissues from Golden retriever muscular dystrophy (GRMD) dogs and R-DMDdel52 rats. A functional assessment of the involvement of necroptosis in dystrophic animals was performed on mdx mice that were genetically depleted for RIPK3. Dystrophic mice aged from 12 to 18 months were analysed by histology and molecular biology to compare the phenotype of muscles from mdxRipk3+/+ and mdxRipk3-/- mice. Heart function was also examined by echocardiography in 40-week-old mice.

RESULTS

RIPK3 expression in sartorius and biceps femoris muscles from GRMD dogs positively correlated to myonecrosis levels (r = 0.81; P = 0.0076). RIPK3 was also found elevated in the diaphragm (P ≤ 0.05). In the slow-progressing heart phenotype of GRMD dogs, the phosphorylated form of RIPK1 at the Serine 161 site was dramatically increased in cardiomyocytes. A similar p-RIPK1 upregulation characterized the cardiomyocytes of the severe DMDdel52 rat model, associated with a marked overexpression of Ripk1 (P = 0.007) and Ripk3 (P = 0.008), indicating primed activation of the necroptotic pathway in the dystrophic heart. MdxRipk3-/- mice displayed decreased compensatory hypertrophy of the heart (P = 0.014), and echocardiography showed a 19% increase in the relative wall thickness (P < 0.05) and 29% reduction in the left ventricle mass (P = 0.0144). Besides, mdxRipk3-/- mice presented no evidence of a regenerative default or sarcopenia in skeletal muscles, moreover around 50% less affected by fibrosis (P < 0.05).

CONCLUSIONS

Our data highlight molecular and histological evidence that the necroptotic pathway is activated in degenerative tissues from dystrophic animal models, including the diaphragm and the heart. We also provide the genetic proof of concept that selective inhibition of necroptosis in dystrophic condition improves both histological features of muscles and cardiac function, suggesting that prevention of necroptosis is susceptible to providing multiorgan beneficial effects for DMD.

A deep learning-based automated image analysis for histological evaluation of broiler pectoral muscle

Global market demand for chicken breast muscle with high yield and quality, together with the high incidence rate of breast muscle abnormalities in recent years highlights the need for tools that can provide a rapid and precise evaluation of breast muscle development and morphology. In this study, we used a novel deep learning-based automated image analysis workflow combining Fiji (ImageJ) with Cellpose and MorphoLibJ plugins to generate an automated diameter and cross-sectional area quantification for broiler breast muscle. We compared data of myofiber diameter from 14-day-old broiler chicks, generated either by manual analysis or by automated analysis. Comparison between manual and automated analysis methods exhibited a striking accuracy rate of up to 99.91%. Moreover, the automated analysis method was much faster. When the automated analysis method was implemented on 84 breast muscle cross-section images it characterized 59,128 myofibers within 4.2 h, while manual analysis of 27 breast muscle cross-section images enabled analysis of 17,333 myofibers in 54 h. The automated image analysis method was also more productive, producing data sets of both diameter and cross-sectional area at an 80-fold higher rate than the manual analysis (26,279 vs. 321 data sets per hour, respectively). In order to demonstrate the ability of this automated image analysis tool to detect differences in breast muscle histomorphology, we applied it on cross sections from chicks of control and in ovo feeding group, injected with a methionine source [2-hydroxy-4-(methylthio) butanoic calcium salt (HMTBa)], known to effect skeletal muscle histomorphology. Analysis was performed on 19,807 myofibers from the control group and 21,755 myofibers from the HMTBa group and was completed in less than 1 h. The clear advantages of this automated image analysis workflow characterized by high precision, high speed, and high productiveness demonstrate its potential to be implemented as a reproducible and readily adaptable research or diagnostic tool for chicken breast muscle development and morphology.

Bioengineered 3D Skeletal Muscle Model Reveals Complement 4b as a Cell-Autonomous Mechanism of Impaired Regeneration with Aging

A mechanistic understanding of cell-autonomous skeletal muscle changes after injury can lead to novel interventions to improve functional recovery in an aged population. However, major knowledge gaps persist owing to limitations of traditional biological aging models. 2D cell culture represents an artificial environment, while aging mammalian models are contaminated by influences from non-muscle cells and other organs. Here, a 3D muscle aging system is created to overcome the limitations of these traditional platforms. It is shown that old muscle constructs (OMC) manifest a sarcopenic phenotype, as evidenced by hypotrophic myotubes, reduced contractile function, and decreased regenerative capacity compared to young muscle constructs. OMC also phenocopy the regenerative responses of aged muscle to two interventions, pharmacological and biological. Interrogation of muscle cell-specific mechanisms that contribute to impaired regeneration over time further reveals that an aging-induced increase of complement component 4b (C4b) delays muscle progenitor cell amplification and impairs functional recovery. However, administration of complement factor I, a C4b inactivator, improves muscle regeneration in vitro and in vivo, indicating that C4b inhibition may be a novel approach to enhance aged muscle repair. Collectively, the model herein exhibits capabilities to study cell-autonomous changes in skeletal muscle during aging, regeneration, and intervention.

Porta J, Nascimento A, Jou C. Innovative Computerized Dystrophin Quantification Method Based on Spectral Confocal Microscopy

Several clinical trials are working on drug development for Duchenne and Becker muscular dystrophy (DMD and BMD) treatment, and, since the expected increase in dystrophin is relatively subtle, high-sensitivity quantification methods are necessary. There is also a need to quantify dystrophin to reach a definitive diagnosis in individuals with mild BMD, and in female carriers. We developed a method for the quantification of dystrophin in DMD and BMD patients using spectral confocal microscopy. It offers the possibility to capture the whole emission spectrum for any antibody, ensuring the selection of the emission peak and allowing the detection of fluorescent emissions of very low intensities. Fluorescence was evaluated first on manually selected regions of interest (ROIs), proving the usefulness of the methodology. Later, ROI selection was automated to make it operator-independent. The proposed methodology correctly classified patients according to their diagnosis, detected even minimal traces of dystrophin, and the results obtained automatically were statistically comparable to the manual ones. Thus, spectral imaging could be implemented to measure dystrophin expression and it could pave the way for detailed analysis of how its expression relates to the clinical course. Studies could be further expanded to better understand the expression of dystrophin-associated protein complexes (DAPCs).

Pathological and Comprehensive Genetic Investigation of Autopsy Cases of Idiopathic Bradyarrhythmia

BACKGROUND

Idiopathic bradyarrhythmia is considered to be due to pathological degeneration of the cardiac conduction system (CCS) during aging. There appears to have been no comprehensive genetic investigations in patients with idiopathic bradyarrhythmia.Methods and Results: Ten autopsy cases with advanced bradyarrhythmia (6 men and 4 women; age: 70-94 years, 81.5±6.9 years; 5 cases each of sinus node dysfunction [SND] and complete atrioventricular block [CAVB]) were genetically investigated by using whole-exome sequencing. Morphometric analysis of the CCS was performed with sex-, age- and comorbidity-matched control cases. As a result, severe loss of nodal cells and distal atrioventricular conduction system were found in SND and CAVB, respectively. However, the conduction tissue loss was not significant in either the atrioventricular node or the proximal bundle of His in CAVB cases. A total of 13 heterozygous potential variants were found in 3 CAVB and 2 SND cases. Of these 13 variants, 4 were missense in the known progressive cardiac conduction disease-related genes: GATA4 and RYR2. In the remaining 9 variants, 5 were loss-of-function mutation with highly possible pathogenicity.

CONCLUSIONS

In addition to degenerative changes of selectively vulnerable areas in the heart during advancing age, the vulnerability of the CCS, which may be associated with "rare variants of small effect," may also be a contributing factor to the degeneration of CCS, leading to "idiopathic" bradyarrhythmia.

Histological Methods to Assess Skeletal Muscle Degeneration and Regeneration in Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a progressive disease caused by the loss of function of the protein dystrophin. This protein contributes to the stabilisation of striated cells during contraction, as it anchors the cytoskeleton with components of the extracellular matrix through the dystrophin-associated protein complex (DAPC). Moreover, absence of the functional protein affects the expression and function of proteins within the DAPC, leading to molecular events responsible for myofibre damage, muscle weakening, disability and, eventually, premature death. Presently, there is no cure for DMD, but different treatments help manage some of the symptoms. Advances in genetic and exon-skipping therapies are the most promising intervention, the safety and efficiency of which are tested in animal models. In addition to in vivo functional tests, ex vivo molecular evaluation aids assess to what extent the therapy has contributed to the regenerative process. In this regard, the later advances in microscopy and image acquisition systems and the current expansion of antibodies for immunohistological evaluation together with the development of different spectrum fluorescent dyes have made histology a crucial tool. Nevertheless, the complexity of the molecular events that take place in dystrophic muscles, together with the rise of a multitude of markers for each of the phases of the process, makes the histological assessment a challenging task. Therefore, here, we summarise and explain the rationale behind different histological techniques used in the literature to assess degeneration and regeneration in the field of dystrophinopathies, focusing especially on those related to DMD.

Effects of eccentric, concentric and eccentric/concentric training on muscle function and mass, functional performance, cardiometabolic health, quality of life and molecular adaptations of skeletal muscle in COPD patients: a multicentre randomised trial

Background

Chronic obstructive pulmonary disease (COPD) is the third cause of death worldwide. COPD is characterised by dyspnoea, limited exercise tolerance, and muscle dysfunction. Muscle dysfunction has been linked to dysregulation between muscle protein synthesis, myogenesis and degradation mechanisms. Conventional concentric cycling has been shown to improve several clinical outcomes and reduce muscle wasting in COPD patients. Eccentric cycling is a less explored exercise modality that allows higher training workloads imposing lower cardio-metabolic demand during exercise, which has shown to induce greater muscle mass and strength gains after training. Interestingly, the combination of eccentric and concentric cycling training has scarcely been explored. The molecular adaptations of skeletal muscle after exercise interventions in COPD have shown equivocal results. The mechanisms of muscle wasting in COPD and whether it can be reversed by exercise training are unclear. Therefore, this study aims two-fold: (1) to compare the effects of 12 weeks of eccentric (ECC), concentric (CONC), and combined eccentric/concentric (ECC/CONC) cycling training on muscle mass and function, cardiometabolic health, physical activity levels and quality of life in severe COPD patients; and (2) to examine the molecular adaptations regulating muscle growth after training, and whether they occur similarly in specific muscle fibres (i.e., I, IIa and IIx).

Methods

Study 1 will compare the effects of 12 weeks of CONC, ECC, versus ECC/CONC training on muscle mass and function, cardiometabolic health, levels of physical activity and quality of life of severe COPD patients using a multicentre randomised trial. Study 2 will investigate the effects of these training modalities on the molecular adaptations regulating muscle protein synthesis, myogenesis and muscle degradation in a subgroup of patients from Study 1. Changes in muscle fibres morphology, protein content, genes, and microRNA expression involved in skeletal muscle growth will be analysed in specific fibre-type pools.

Discussion

We aim to demonstrate that a combination of eccentric and concentric exercise could maximise the improvements in clinical outcomes and may be ideal for COPD patients. We also expect to unravel the molecular mechanisms underpinning muscle mass regulation after training in severe COPD patients.

Trial Registry: Deutshches Register Klinischer Studien; Trial registration: DRKS00027331; Date of registration: 12 January 2022. https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00027331.

Automated bone healing evaluation: New approach to histomorphometric analysis

This study aimed to assess different approaches for bone healing evaluation on histological images and to introduce a new automatic evaluation method based on segmentation with distinct thresholds. We evaluated the hyperbaric oxygen therapy (HBO) effects on bone repair in type 1 diabetes mellitus rats. Twelve animals were divided into four groups (n = 3): non-diabetic, non-diabetic + HBO, diabetic, and diabetic + HBO. Diabetes was induced by intravenous administration of streptozotocin (50 mg/kg). Bone defects were created in femurs and HBO was immediately started at one session/day. After 7 days, the animals were euthanized, femurs were removed, demineralized, and embedded in paraffin. Histological sections were stained with hematoxylin and eosin (HE) and Mallory's trichrome (MT), and evaluated using three approaches: (1) conventional histomorphometric analysis (HE images) using a 144-point grid to quantify the bone matrix; (2) a semi-automatic method based on bone matrix segmentation to assess the bone matrix percentage (MT images); and (3) automatic approach, with the creation of a plug-in for ImageJ software. The time required to perform the analysis in each method was measured and subjected to Bland-Altman statistical analysis. All three methods were satisfactory for measuring bone formation and were not statistically different. The automatic approach reduced the working time compared to visual grid and semi-automated method (p < .01). Although histological evaluation of bone healing was performed successfully using all three methods, the novel automatic approach significantly shortened the time required for analysis and had high accuracy.

Alternative splicing diversifies the skeletal muscle transcriptome during prolonged spaceflight

BACKGROUND

As the interest in manned spaceflight increases, so does the requirement to understand the transcriptomic mechanisms that underlay the detrimental physiological adaptations of skeletal muscle to microgravity. While microgravity-induced differential gene expression (DGE) has been extensively investigated, the contribution of differential alternative splicing (DAS) to the plasticity and functional status of the skeletal muscle transcriptome has not been studied in an animal model. Therefore, by evaluating both DGE and DAS across spaceflight, we set out to provide the first comprehensive characterization of the transcriptomic landscape of skeletal muscle during exposure to microgravity.

METHODS

RNA-sequencing, immunohistochemistry, and morphological analyses were conducted utilizing total RNA and tissue sections isolated from the gastrocnemius and quadriceps muscles of 30-week-old female BALB/c mice exposed to microgravity or ground control conditions for 9 weeks.

RESULTS

In response to microgravity, the skeletal muscle transcriptome was remodeled via both DGE and DAS. Importantly, while DGE showed variable gene network enrichment, DAS was enriched in structural and functional gene networks of skeletal muscle, resulting in the expression of alternatively spliced transcript isoforms that have been associated with the physiological changes to skeletal muscle in microgravity, including muscle atrophy and altered fiber type function. Finally, RNA-binding proteins, which are required for regulation of pre-mRNA splicing, were themselves differentially spliced but not differentially expressed, an upstream event that is speculated to account for the downstream splicing changes identified in target skeletal muscle genes.

CONCLUSIONS

Our work serves as the first investigation of coordinate changes in DGE and DAS in large limb muscles across spaceflight. It opens up a new opportunity to understand (i) the molecular mechanisms by which splice variants of skeletal muscle genes regulate the physiological adaptations of skeletal muscle to microgravity and (ii) how small molecule splicing regulator therapies might thwart muscle atrophy and alterations to fiber type function during prolonged spaceflight.

A dog model for centronuclear myopathy carrying the most common DNM2 mutation

Mutations in DNM2 cause autosomal dominant centronuclear myopathy (ADCNM), a rare disease characterized by skeletal muscle weakness and structural anomalies of the myofibres, including nuclear centralization and mitochondrial mispositioning. Following the clinical report of a Border Collie male with exercise intolerance and histopathological hallmarks of CNM on the muscle biopsy, we identified the c.1393C>T (R465W) mutation in DNM2, corresponding to the most common ADCNM mutation in humans. In order to establish a large animal model for longitudinal and preclinical studies on the muscle disorder, we collected sperm samples from the Border Collie male and generated a dog cohort for subsequent clinical, genetic and histological investigations. Four of the five offspring carried the DNM2 mutation and showed muscle atrophy and a mildly impaired gait. Morphological examinations of transverse muscle sections revealed CNM-typical fibres with centralized nuclei and remodelling of the mitochondrial network. Overall, the DNM2-CNM dog represents a faithful animal model for the human disorder, allows the investigation of ADCNM disease progression, and constitutes a valuable complementary tool to validate innovative therapies established in mice.

Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges

Histopathology is widely used to analyze clinical biopsy specimens and tissues from pre-clinical models of a variety of musculoskeletal conditions. Histological assessment relies on scoring systems that require expertise, time, and resources, which can lead to an analysis bottleneck. Recent advancements in digital imaging and image processing provide an opportunity to automate histological analyses by implementing advanced statistical models such as machine learning and deep learning, which would greatly benefit the musculoskeletal field. This review provides a high-level overview of machine learning applications, a general pipeline of tissue collection to model selection, and highlights the development of image analysis methods, including some machine learning applications, to solve musculoskeletal problems. We discuss the optimization steps for tissue processing, sectioning, staining, and imaging that are critical for the successful generalizability of an automated image analysis model. We also commenting on the considerations that should be taken into account during model selection and the considerable advances in the field of computer vision outside of histopathology, which can be leveraged for image analysis. Finally, we provide a historic perspective of the previously used histopathological image analysis applications for musculoskeletal diseases, and we contrast it with the advantages of implementing state-of-the-art computational pathology approaches. While some deep learning approaches have been used, there is a significant opportunity to expand the use of such approaches to solve musculoskeletal problems.

Enhancing Interrogation of Skeletal Muscle Samples for Informative Quantitative Data

Careful quantitative analysis of histological preparations of muscle samples is crucial to accurate investigation of myopathies in man and of interpretation of data from animals subjected to experimental or potentially therapeutic treatments. Protocols for measuring cell numbers are subject to problems arising from biases associated with preparative and analytical techniques. Prominent among these is the effect of polarized structure of skeletal muscle on sampling bias. It is also common in this tissue to collect data as ratios to convenient reference dominators, the fundamental bases of which are ill-defined, or unrecognized or not accurately assessable. Use of such 'floating' denominators raises a barrier to estimation of the absolute values that assume practical importance in medical research, where accurate comparison between different scenarios in different species is essential to the aim of translating preclinical research findings in animal models to clinical utility in Homo sapiens.This review identifies some of the underappreciated problems with current morphometric practice, some of which are exacerbated in skeletal muscle, and evaluates the extent of their intrusiveness into the of building an objective, accurate, picture of the structure of the muscle sample. It also contains recommendations for eliminating or at least minimizing these problems. Principal among these, would be the use of stereological procedures to avoid the substantial counting biases arising from inter-procedure differences in object size and section thickness.Attention is also drawn to the distortions of interpretation arising from use of undefined or inappropriate denominators.

Automatic and unbiased segmentation and quantification of myofibers in skeletal muscle

Skeletal muscle has the remarkable ability to regenerate. However, with age and disease muscle strength and function decline. Myofiber size, which is affected by injury and disease, is a critical measurement to assess muscle health. Here, we test and apply Cellpose, a recently developed deep learning algorithm, to automatically segment myofibers within murine skeletal muscle. We first show that tissue fixation is necessary to preserve cellular structures such as primary cilia, small cellular antennae, and adipocyte lipid droplets. However, fixation generates heterogeneous myofiber labeling, which impedes intensity-based segmentation. We demonstrate that Cellpose efficiently delineates thousands of individual myofibers outlined by a variety of markers, even within fixed tissue with highly uneven myofiber staining. We created a novel ImageJ plugin (LabelsToRois) that allows processing of multiple Cellpose segmentation images in batch. The plugin also contains a semi-automatic erosion function to correct for the area bias introduced by the different stainings, thereby identifying myofibers as accurately as human experts. We successfully applied our segmentation pipeline to uncover myofiber regeneration differences between two different muscle injury models, cardiotoxin and glycerol. Thus, Cellpose combined with LabelsToRois allows for fast, unbiased, and reproducible myofiber quantification for a variety of staining and fixation conditions.

Quantifying the Effects of Aging on Morphological and Cellular Properties of Human Female Pelvic Floor Muscles

Age-related pelvic floor muscle (PFM) dysfunction is a critical defect in the progression to pelvic floor disorders (PFDs). Despite dramatic prevalence of PFDs in older women, the underlying pathophysiology of age-related PFM dysfunction remains poorly understood. Using cadaveric specimens, we quantified aging effects on functionally relevant PFM properties and compared PFMs with the appendicular muscles from the same donors. PFMs, obturator internus, and vastus lateralis were procured from younger (N = 4) and older (N = 11) donors with known obstetrical and medical history. Our findings demonstrate that PFMs undergo degenerative, rather than atrophic, alterations. Importantly, age-related fibrotic degeneration disproportionally impacts PFMs compared to the appendicular muscles. We identified intramuscular lipid accumulation as another contributing factor to the pathological alterations of PFMs with aging. We observed a fourfold decrease in muscle stem cell (MuSC) pool of aged relative to younger PFMs, but the MuSC pool of appendicular muscles from the same older donors was only twofold lower than in younger group, although these differences were not statistically significant. Age-related degeneration appears to disproportionally impact PFMs relative to the appendicular muscles from the same donors. Knowledge of tissue- and cell-level changes in aged PFMs is essential to promote our understanding of the mechanisms governing PFM dysfunction in older women.

MyoSight-semi-automated image analysis of skeletal muscle cross sections

BACKGROUND

Manual analysis of cross-sectional area, fiber-type distribution, and total and centralized nuclei in skeletal muscle cross sections is tedious and time consuming, necessitating an accurate, automated method of analysis. While several excellent programs are available, our analyses of skeletal muscle disease models suggest the need for additional features and flexibility to adequately describe disease pathology. We introduce a new semi-automated analysis program, MyoSight, which is designed to facilitate image analysis of skeletal muscle cross sections and provide additional flexibility in the analyses.

RESULTS

We describe staining and imaging methods that generate high-quality images of immunofluorescent-labelled cross sections from mouse skeletal muscle. Using these methods, we can analyze up to 5 different fluorophores in a single image, allowing simultaneous analyses of perinuclei, central nuclei, fiber size, and fiber-type distribution. MyoSight displays high reproducibility among users, and the data generated are in close agreement with data obtained from manual analyses of cross-sectional area (CSA), fiber number, fiber-type distribution, and number and localization of myonuclei. Furthermore, MyoSight clearly delineates changes in these parameters in muscle sections from a mouse model of Duchenne muscular dystrophy (mdx).

CONCLUSIONS

MyoSight is a new program based on an algorithm that can be optimized by the user to obtain highly accurate fiber size, fiber-type identification, and perinuclei and central nuclei per fiber measurements. MyoSight combines features available separately in other programs, is user friendly, and provides visual outputs that allow the user to confirm the accuracy of the analyses and correct any inaccuracies. We present MyoSight as a new program to facilitate the analyses of fiber type and CSA changes arising from injury, disease, exercise, and therapeutic interventions.

Effects of lycopene on skeletal muscle-fiber type and high-fat diet-induced oxidative stress

Increasing studies report that many natural products can participate in formation of muscle fibers. This study aimed to investigate the effect of lycopene on skeletal muscle-fiber type in vivo and in vitro. C2C12 myoblasts were used in vitro study, and the concentration of lycopene was 10 µM. In vivo, 8-week-old male C57/BL6 mice were used and divided into four groups (n=8): (1) ND: normal-fat diet; (2) ND+Lyc: normal-fat diet mixed with 0.33% w/w lycopene; (3) HFD: high-fat diet; and (4) HFD+Lyc: high-fat diet mixed with 0.33% w/w lycopene. The mice tissue samples were collected after 8 weeks feeding. We found that lycopene supplementation enhanced the protein expression of slow-twitch fiber, succinate dehydrogenase, and malic dehydrogenase enzyme activities, whereas lycopene reduced the protein expression of fast-twitch fibers, lactate dehydrogenase, pyruvate kinase enzyme activities. Moreover, lycopene can promote skeletal muscle triglyceride deposition, enhanced the mRNA expression of genes related to lipid synthesis, reduced the mRNA expression of genes related to lipolysis. And high-fat diet-induced dyslipidemia and oxidative stress were attenuated after lycopene supplementation. Additionally, lycopene supplementation reduced the glycolytic reserve but enhanced mitochondrial ATP production in C2C12 cells. These results demonstrated that lycopene affects the activities of metabolic enzymes in muscle fibers, promotes the expression of slow-twitch fibers, and enhanced mitochondrial respiratory capacity. We speculated that lycopene affects the muscle-fiber type through aerobic oxidation, suggesting that lycopene exerts potential beneficial effects on skeletal muscle metabolism.

Comprehensive histological investigation of age-related changes in dermal extracellular matrix and muscle fibers in the upper lip vermilion

OBJECTIVE

Few histological studies have directly examined age-related changes within the lips, although non-invasive investigations of such changes are increasing. Therefore, this study aimed to provide histological and molecular data on age-dependent alterations in the vermilion.

METHODS

Upper vermilion specimens from 15 female Caucasian cadavers (age range, 27-78 years) were investigated histologically or immunohistochemically.

RESULTS

Histologically, age-dependent decreases in areas occupied by hyaluronan and collagenous fibres in the dermis of upper vermilion were demonstrated. Elastic fibre content varied widely between individuals. The area occupied by muscle fibres in the orbicularis oris muscle region within the vermilion also correlated negatively with age. Immunohistochemically, signals of four proteins were attenuated in vermilion from older individuals compared with young individuals: procollagen type I, hyaluronan synthase (HAS)1, myosin heavy chain (MYH)2 (a component of fast-twitch oxidative muscle fibres) and MYH7 (a component of slow-twitch muscle fibres). In contrast, signals of cell migration inducing hyaluronidase 1 (CEMIP) were intensified in vermilion from older individuals. No marked differences between young and older individuals were seen in procollagen type III, HAS2, HAS3, hyaluronidase (HYAL)1, HYAL2, MYH1 or MYH4.

CONCLUSION

Age-dependent decreases of hyaluronan in the dermis of vermilion were prominent, possibly due to both the decrease in synthesis (HAS1) and the increase in degradation (CEMIP). Furthermore, age-dependent decreases in collagenous fibres and two types of muscle fibre in the vermilion were also identified histologically. Type I collagen, MYH2 and MYH7 appear to represent the molecules responsible for these respective decrements.

A high-throughput digital script for multiplexed immunofluorescent analysis and quantification of sarcolemmal and sarcomeric proteins in muscular dystrophies

The primary molecular endpoint for many Duchenne muscular dystrophy (DMD) clinical trials is the induction, or increase in production, of dystrophin protein in striated muscle. For accurate endpoint analysis, it is essential to have reliable, robust and objective quantification methodologies capable of detecting subtle changes in dystrophin expression. In this work, we present further development and optimisation of an automated, digital, high-throughput script for quantitative analysis of multiplexed immunofluorescent (IF) whole slide images (WSI) of dystrophin, dystrophin associated proteins (DAPs) and regenerating myofibres (fetal/developmental myosin-positive) in transverse sections of DMD, Becker muscular dystrophy (BMD) and control skeletal muscle biopsies. The script enables extensive automated assessment of myofibre morphometrics, protein quantification by fluorescence intensity and sarcolemmal circumference coverage, colocalisation data for dystrophin and DAPs and regeneration at the single myofibre and whole section level. Analysis revealed significant variation in dystrophin intensity, percentage coverage and amounts of DAPs between differing DMD and BMD samples. Accurate identification of dystrophin via a novel background subtraction method allowed differential assessment of DAP fluorescence intensity within dystrophin positive compared to dystrophin negative sarcolemma regions. This enabled surrogate quantification of molecular functionality of dystrophin in the assembly of the DAP complex. Overall, the digital script is capable of multiparametric and unbiased analysis of markers of myofibre regeneration and dystrophin in relation to key DAPs and enabled better characterisation of the heterogeneity in dystrophin expression patterns seen in BMD and DMD alongside the surrogate assessment of molecular functionality of dystrophin. Both these aspects will be of significant relevance to ongoing and future DMD and other muscular dystrophies clinical trials to help benchmark therapeutic efficacy.

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

METHODS

Muscle sections were stained for cell boundary (laminin) and myofiber type (myosin heavy chain isoforms). Myosoft, running in the open access software platform FIJI (ImageJ), was used to analyze myofiber size and type in transverse sections of entire gastrocnemius/soleus muscles.

RESULTS

Myosoft provides an accurate analysis of hundreds to thousands of muscle fibers within 25 minutes, which is >10-times faster than manual analysis. We demonstrate that Myosoft is capable of handling high-content images even when image or staining quality is suboptimal, which is a marked improvement over currently available and comparable programs.

CONCLUSIONS

Myosoft is a reliable, accurate, high-throughput, and convenient tool to analyze high-content muscle histology. Myosoft is freely available to download from Github at https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub.

[Automated image-analysis method applied to -dermatomyositis]

L’analyse histologique du tissu musculaire est un élément déterminant pour le diagnostic et la compréhension physiopathologique des myopathies. Le développement d’outils numériques et informatiques permet des analyses d’images quantifiées à grande échelle applicable aux biopsies musculaires.

L’analyse d’images automatisée permet de déterminer la taille de l’ensemble des myofibres sur un échantillon de muscle et d’évaluer l’atrophie myocytaire. Le codage couleur selon la taille permet de visualiser directement la topographie de l’atrophie myocytaire. Cette approche morphométrique appliquée à la dermatomyosite permettra une meilleure stratification des patients.

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.