A fractal characterization of the type II fiber distribution in the extensor digitorum longus and soleus muscles of the adult rat

Chronic Undernutrition Differentially Changes Muscle Fiber Types Organization and Distribution in the EDL Muscle Fascicles

Fiber type composition, organization, and distribution are key elements in muscle functioning. These properties can be modified by intrinsic and/or extrinsic factors, such as undernutrition and injuries. Currently, there is no methodology to quantitatively analyze such modifications. On one hand, we propose a fractal approach to determine fiber type organization, using the fractal correlation method in software Fractalyse. On the other hand, we applied the kernel methodology from machine learning to build radial-basis functions for the spatial distribution of fibers (distribution functions), by dividing into square cells a two-dimensional binary image for the spatial distribution of fibers from a muscle fascicle and mounting on each cell a radial-basis function in such a way that the sum of all cell functions creates a smooth version of the fiber histogram on the cell grid. The distribution functions thus created belong in a reproducing kernel Hilbert space which permits us to regard them as vectors and measure distances and angles between them. In the present study, we analyze fiber type organization and distribution in fascicles (F2, F3, F4, and F5) of the extensor digitorum longus muscle (EDLm) from control and undernourished male rats. Fibers were classified according to the ATPase activity in slow, intermediate, and fast. Then, (x, y) coordinates of fibers were used to build binary images and distribution functions for each fiber type and both conditions. The fractal organization analysis showed that fast and intermediate fibers, from both groups, had a fractal organization within the four fascicles, i.e., the fiber assembly is distributed in clusters. We also show that chronic undernutrition altered the organization of fast fibers in the F3, although it still is considered a fractal organization. Distribution function analysis showed that each fiber type (slow, intermediate, and fast) has a unique distribution within the fascicles, in both conditions. However, chronic undernutrition modified the intra-fascicular fiber type distributions, except in the F2. Altogether, these results showed that the methodology herein proposed allows for analyzing fiber type organization and distribution modifications. On the other side, we show that chronic undernutrition alters not only the fiber type composition but also the organization and distribution, which could affect the muscle functioning, and ultimately, its behavior (e.g., locomotion).

Evaluation by fractal dimension of muscle regeneration after photobiomodulation

Abstract Introduction: Many treatment modalities are used for muscle tissue recovery. Photobiomodulation is a modality that can be employed to improve the quality of tissue repair. The use of fractal dimension (FD) is an innovative methodology in the quantitative evaluation of treatment efficacy. Objective: Use FD as a quantitative analysis method to evaluate the effect of photobiomodulation of 904 nanometers (nm) in the initial phase of the muscle regeneration process. Method: Thirty male Wistar rats were divided into three groups: Control Group (CG), Injured and Untreated Group (IUT), and Injured and Treated Group (IT). Muscle injury was induced by cryoinjury in the central region of the anterior tibial (AT) belly of the left posterior limb. This was performed by an iron rod that was previously immersed in liquid nitrogen. Applications started 24 hours after the injury and occurred daily for five days. They were performed at two points in the lesion area. The rats were euthanized on the seventh day. The AT muscles were removed and frozen in liquid nitrogen. Then, the histological sections were stained using the Hematoxylin-Eosin (HE) technique and submitted to FD analysis performed by the box-counting method using ImageJ software. The Kolmogorov-Smirnov test was used for data normality, and the Kruskall-Wallis test and Dunn's post-test were used for group comparison (p<0.05%). Results: Differences between IT and IUT groups were statistically significant, and it was possible to observe the reduction of fractability with p=0.0034. Conclusion: FD is a useful tool for the analysis of skeletal muscle disorganization in the initial phase of regeneration and confirms the potentially beneficial effects of photobiomodulation to this process.

Fractal dimension analysis reveals skeletal muscle disorganization in mdx mice

Duchenne Muscular Dystrophy (DMD) is characterized by muscle extracellular matrix disorganization due to the increased collagen deposition leading to fibrosis that significantly exacerbates disease progression. Fractal dimension analysis is a method that quantifies tissue/cellular disorganization and characterizes complex structures. The first objective of the present study was use fractal analysis to evaluate extracellular matrix disorganization in mdx mice soleus muscle. Next, we mimic a hyper-proliferation of fibrogenic cells by co-culturing NIH3T3 fibroblasts and C2C12 myoblasts to test whether fibroblasts induce disorganization in myoblast arrangement. Here, we show mdx presented high skeletal muscle disorganization as revealed by fractal analysis. Similarly, this method revealed that myoblasts co-cultured with fibroblast also presented cellular arrangement disorganization. We also reanalyzed skeletal muscle microarrays transcriptomic data from mdx and DMD patients that revealed transcripts related to extracellular matrix organization. This analysis also identified Osteoglycin, which was validated as a potential regulator of ECM organization in mdx dystrophic muscles. Our results demonstrate that fractal dimension is useful tool for the analysis of skeletal muscle disorganization in DMD and also reveal a fibroblast-myoblast cross-talk that contributes to "in vitro" myoblast disarrangement.

Pathogenic accumulation of APP in fast twitch muscle of IBM patients and a transgenic model

Inclusion body myositis (IBM) is the most common age-related degenerative skeletal muscle disorder. The aberrant intracellular accumulation of the beta-amyloid (Abeta) peptide within skeletal muscle is a pathological hallmark of IBM. Skeletal muscle is comprised of both slow and fast twitch fibers, which are present in different proportions in various muscles. It remains unclear if fast and/or slow twitch fibers are differentially involved in IBM pathogenesis. To better understand the molecular pathogenesis of IBM, we analyzed human IBM muscle biopsies and muscle from a transgenic mouse model of IBM (MCK-betaAPP). Here we report that the majority of histopathologically-affected fibers in human IBM biopsies were type II fast fibers. Skeletal muscle from MCK-betaAPP mice exhibited higher transgene expression and steady-state levels of human betaAPP in fast type IIB fibers compared to slow type I fibers. These findings indicate that fast twitch fibers may selectively accumulate and be more vulnerable to betaAPP- and Abeta-mediated damage in IBM. These findings also highlight parallels between the MCK-betaAPP mice and the human IBM condition.

Histochemical and ultrastructural characteristics of leg muscle fibres in patients with repairative abdominal aortic aneurysm (AAA)

Tibialis anterior (ta) muscle biopsies before and after elective abdominal aortic aneurysm (AAA) repair operation were obtained, in order to observe possible changes after the aortic declamping reperfusion. Open muscle biopsies were taken from each of eight patients (60-75 years old) which were processed for enzyme histochemistry, and for transmission electron microscopy (EM). Morphometric analysis was applied to estimate the number and the area of muscle fibres of each fibre type. Rectus abdominis muscle biopsies were served as controls. Before the operation the predominant elements found were the presence of atrophic muscle fibres, fibre size diversity, localised cellular reactions, increased extent of connective tissue, disappearance, in many cases, of the mosaic pattern, predominance of type I and oxidative fibres, and existence of fibres with core-like structures in the sarcoplasm. Type I fibres consisted of 66.95 +/- 9% of all muscle fibres, the mean cross sectional area of which was 3,372.8 +/- 1,016 microm(2) and of type II fibres was 3,786.5 +/- 6,046 microm(2). After the aortic clamping was performed mitochondrial swelling was found, as well as disorganisation of sarcomeres. After declamping of the aorta, there were also severe edema, local fibre necrosis, and adhesion of leucocytes, whereas muscle fibre areas became 3,935.18 micro 531 microm(2) for type I and 5,804 +/- 1,075 microm(2) for type II. The short ischemic period during aortic clamping and the subsequent reperfusion resulted mainly in ultrastructural changes.

Fractals in pathology

Many natural objects, including most objects studied in pathology, have complex structural characteristics and the complexity of their structures, for example the degree of branching of vessels or the irregularity of a tumour boundary, remains at a constant level over a wide range of magnifications. These structures also have patterns that repeat themselves at different magnifications, a property known as scaling self-similarity. This has important implications for measurement of parameters such as length and area, since Euclidean measurements of these may be invalid. The fractal system of geometry overcomes the limitations of the Euclidean geometry for such objects and measurement of the fractal dimension gives an index of their space-filling properties. The fractal dimension may be measured using image analysis systems and the box-counting, divider (perimeter-stepping) and pixel dilation methods have all been described in the published literature. Fractal analysis has found applications in the detection of coding of coding regions in DNA and measurement of the space-filling properties of tumours, blood vessels and neurones. Fractal concepts have also been usefully incorporated into models of biological processes, including epithelial cell growth, blood vessel growth, periodontal disease and viral infections.