Search Results (12)

The pericellular matrix (PCM) is a specialized extracellular matrix that surrounds cells. Interactions with the PCM enable the cells to sense and respond to mechanical signals, triggering a proper adaptive response. Collagen VI is a component of muscle and tendon PCM. Mutations in collagen VI genes cause a distinctive group of inherited skeletal muscle diseases, and Ullrich congenital muscular dystrophy (UCMD) is the most severe form. In addition to muscle weakness, UCMD patients show structural and functional changes of the tendon PCM. In this study, we investigated whether PCM alterations due to collagen VI mutations affect the response of tendon fibroblasts to mechanical stimulation. By taking advantage of human tendon cultures obtained from unaffected donors and from UCMD patients, we analyzed the morphological and functional properties of cellular mechanosensors. We found that the length of the primary cilia of UCMD cells was longer than that of controls. Unlike controls, in UCMD cells, both cilia prevalence and length were not recovered after mechanical stimulation. Accordingly, under the same experimental conditions, the activation of the Hedgehog signaling pathway, which is related to cilia activity, was impaired in UCMD cells. Finally, UCMD tendon cells exposed to mechanical stimuli showed altered focal adhesions, as well as impaired activation of Akt, ERK1/2, p38MAPK, and mechanoresponsive genes downstream of YAP. By exploring the response to mechanical stimulation, for the first time, our findings uncover novel unreported mechanistic aspects of the physiopathology of UCMD-derived tendon fibroblasts and point at a role for collagen VI in the modulation of mechanotransduction in tendons. Full article

Collagen VI-related disorders constitute a spectrum of severities from the milder Bethlem myopathy (BM) to the Ullrich congenital muscular dystrophy (UCMD), which is more severe, and an intermediate form characterized by muscle weakness that begins in infancy. Affected children are able to walk, although walking becomes increasingly difficult starting in early adulthood. They develop contractures in the ankles, elbows, knees, and spine in childhood. In some affected cases, the respiratory muscles are weakened, requiring mechanical ventilation, particularly during sleep. Individuals with collagen VI-related myopathy are at risk of restrictive lung disease and sleep-disordered breathing due to the development of scoliosis associated with neuromuscular weakness. Typical signs of respiratory failure are not always present, and some patients are unaware that their respiratory muscles have become weaker. Here, we report a case of an intermediate form of collagen VI-related myopathy confirmed by next-generation sequencing. The girl presented morning headache, irritability, and aggressiveness, and because of these main symptoms, she was referred by the neurologist for respiratory evaluation. The result of spirometry was associated with hypoventilation shown during sleep studies, indicating the necessity to initiate home non-invasive ventilation (NIV) with immediate improvement in the symptoms. Neuromuscular disorders (NMDs) have a great impact on sleep, but only very few studies evaluating sleep quality in young patients with collagen VI-related myopathy have been described. Daytime symptoms of sleep-disordered breathing may include irritability, emotional lability, and poor attentiveness, but these can be overseen by the severity of other complex medical problems in patients with collagen VI-related myopathy. We underline the importance of the close monitoring of respiratory function, sleep evaluation, and decision making to support the NIV treatment of other collagen VI-related myopathy variant-specific patients. Early recognition of sleep disturbances and initiation of respiratory support can preserve or enhance the quality of life for patients and their caregivers. Routine screening for identification of emotional distress should be instituted in the clinical practice using validated psychological measures in a multidisciplinary approach with different intervention strategies for both patient and parent when necessary. Full article

Pathogenetic mechanism recognition and proof-of-concept clinical trials were performed in our patients affected by collagen VI-related myopathies. This study, which included 69 patients, aimed to identify innovative clinical data to better design future trials. Among the patients, 33 had Bethlem myopathy (BM), 24 had Ullrich congenital muscular dystrophy (UCMD), 7 had an intermediate phenotype (INTM), and five had myosclerosis myopathy (MM). We obtained data on muscle strength, the degree of contracture, immunofluorescence, and genetics. In our BM group, only one third had a knee extension strength greater than 50% of the predicted value, while only one in ten showed similar retention of elbow flexion. These findings should be considered when recruiting BM patients for future trials. All the MM patients had axial and limb contractures that limited both the flexion and extension ranges of motion, and a limitation in mouth opening. The immunofluorescence analysis of collagen VI in 55 biopsies from 37 patients confirmed the correlation between collagen VI defects and the severity of the clinical phenotype. However, biopsies from the same patient or from patients with the same mutation taken at different times showed a progressive increase in protein expression with age. The new finding of the time-dependent modulation of collagen VI expression should be considered in genetic correction trials. Full article

Collagen VI exerts several functions in the tissues in which it is expressed, including mechanical roles, cytoprotective functions with the inhibition of apoptosis and oxidative damage, and the promotion of tumor growth and progression by the regulation of cell differentiation and autophagic mechanisms. Mutations in the genes encoding collagen VI main chains, COL6A1, COL6A2 and COL6A3, are responsible for a spectrum of congenital muscular disorders, namely Ullrich congenital muscular dystrophy (UCMD), Bethlem myopathy (BM) and myosclerosis myopathy (MM), which show a variable combination of muscle wasting and weakness, joint contractures, distal laxity, and respiratory compromise. No effective therapeutic strategy is available so far for these diseases; moreover, the effects of collagen VI mutations on other tissues is poorly investigated. The aim of this review is to outline the role of collagen VI in the musculoskeletal system and to give an update about the tissue-specific functions revealed by studies on animal models and from patients’ derived samples in order to fill the knowledge gap between scientists and the clinicians who daily manage patients affected by collagen VI-related myopathies. Full article

Here, we described three affected boys from two unrelated families of Ossetian-Digor origin from the Republic of North Ossetia-Alania who were admitted to the Research Centre for Medical Genetics with unspecified muscular dystrophy. High-throughput sequencing was performed and revealed two novel frameshift variants in the COL6A2 gene (NM_001849.3) in a heterozygous state each in both cases: c.508_535delinsCTGTGG and c.1659_1660del (case 1) and c.1689del and c.1659_1660del (case 2). In two cases, the same nucleotide variant in the COL6A2 gene (c.1659_1660del) was observed. We have suggested that the variant c.1659_1660del may be common in the Ossetian-Digor population because two analyzed families have the same ancestry from the same subethnic group of Ossetians). The screening for an asymptomatic carriage of the nucleotide variant c.1659_1660del in 54 healthy donors from Ossetian-Digor population revealed that the estimated carrier frequency is 0.0093 (CI: 0.0002–0.0505), which is high for healthy carriers of the pathogenic variant. Molecular genetic, anamnestic data and clinical examination results allowed us to diagnose Ullrich muscular dystrophy in those affected boys. Genetic heterogeneity and phenotypic diversity of muscular dystrophies complicate diagnosis. It is important to make a differential diagnosis of such conditions and use HTS methods to determine the most accurate diagnosis. Full article

Ullrich congenital muscular dystrophy (UCMD) is a severe form of muscular dystrophy caused by the loss of function of collagen VI, a critical component of the muscle-tendon matrix. Magnetic resonance imaging of UCMD patients’ muscles shows a peculiar rim of abnormal signal at the periphery of each muscle, and a relative sparing of the internal part. The mechanism/s involved in the early fat substitution of muscle fiber at the periphery of muscles remain elusive. We studied a muscle biopsy of the rectus femoris/deep fascia (DF) of a 3-year-old UCMD patient, with a homozygous mutation in the COL6A2 gene. By immunohistochemical and ultrastructural analysis, we found a marked fatty infiltration at the interface of the muscle with the epimysium/DF and an atrophic phenotype, primarily in fast-twitch fibers, which has never been reported before. An unexpected finding was the widespread increase of interstitial cells with long cytoplasmic processes, consistent with the telocyte phenotype. Our study documents for the first time in a muscle biopsy the peculiar pattern of outside-in muscle degeneration followed by fat substitution as already shown by muscle imaging, and an increase of telocytes in the interstitium of the deep fascia, which highlights a potential involvement of this structure in the pathogenesis of UCMD. Full article

As satellite observation technology rapidly develops, the number of remote sensing (RS) images dramatically increases, and this leads RS image retrieval tasks to be more challenging in terms of speed and accuracy. Recently, an increasing number of researchers have turned their attention to this issue, as well as hashing algorithms, which map real-valued data onto a low-dimensional Hamming space and have been widely utilized to respond quickly to large-scale RS image search tasks. However, most existing hashing algorithms only emphasize preserving point-wise or pair-wise similarity, which may lead to an inferior approximate nearest neighbor (ANN) search result. To fix this problem, we propose a novel triplet ordinal cross entropy hashing (TOCEH). In TOCEH, to enhance the ability of preserving the ranking orders in different spaces, we establish a tensor graph representing the Euclidean triplet ordinal relationship among RS images and minimize the cross entropy between the probability distribution of the established Euclidean similarity graph and that of the Hamming triplet ordinal relation with the given binary code. During the training process, to avoid the non-deterministic polynomial (NP) hard problem, we utilize a continuous function instead of the discrete encoding process. Furthermore, we design a quantization objective function based on the principle of preserving triplet ordinal relation to minimize the loss caused by the continuous relaxation procedure. The comparative RS image retrieval experiments are conducted on three publicly available datasets, including UC Merced Land Use Dataset (UCMD), SAT-4 and SAT-6. The experimental results show that the proposed TOCEH algorithm outperforms many existing hashing algorithms in RS image retrieval tasks. Full article

Recently, deep metric learning (DML) has received widespread attention in the field of remote sensing image retrieval (RSIR), owing to its ability to extract discriminative features to represent images and then to measure the similarity between images via learning a distance function among feature vectors. However, the distinguishability of features extracted by the most current DML-based methods for RSIR is still not sufficient, and the retrieval efficiency needs to be further improved. To this end, we propose a novel ensemble architecture of residual attention-based deep metric learning (EARA) for RSIR. In our proposed architecture, residual attention is introduced and ameliorated to increase feature discriminability, maintain global features, and concatenate feature vectors of different weights. Then, descriptor ensemble rather than embedding ensemble is chosen to further boost the performance of RSIR with reduced time cost and memory consumption. Furthermore, our proposed architecture can be flexibly extended with different types of deep neural networks, loss functions, and feature descriptors. To evaluate the performance and efficiency of our architecture, we conduct exhaustive experiments on three benchmark remote sensing datasets, including UCMD, SIRI-WHU, and AID. The experimental results demonstrate that the proposed architecture outperforms the four state-of-the-art methods, including BIER, A-BIER, DCES, and ABE, by 15.45%, 13.04%, 10.31%, and 6.62% in the mean Average Precision (mAP), respectively. As for the retrieval execution complexity, the retrieval time and floating point of operations (FLOPs), needed by the proposed architecture on AID, reduce by 92% and 80% compared to those needed by ABE, albeit with the same Recall@1 between the two methods. Full article

With the improvement of various space-satellite shooting methods, the sources, scenes, and quantities of remote sensing data are also increasing. An effective and fast remote sensing image retrieval method is necessary, and many researchers have conducted a lot of work in this direction. Nevertheless, a fast retrieval method called hashing retrieval is proposed to improve retrieval speed, while maintaining retrieval accuracy and greatly reducing memory space consumption. At the same time, proxy-based metric learning losses can reduce convergence time. Naturally, we present a proxy-based hash retrieval method, called DHPL (Deep Hashing using Proxy Loss), which combines hash code learning with proxy-based metric learning in a convolutional neural network. Specifically, we designed a novel proxy metric learning network, and we used one hash loss function to reduce the quantified losses. For the University of California Merced (UCMD) dataset, DHPL resulted in a mean average precision (mAP) of up to 98.53% on 16 hash bits, 98.83% on 32 hash bits, 99.01% on 48 hash bits, and 99.21% on 64 hash bits. For the aerial image dataset (AID), DHPL achieved an mAP of up to 93.53% on 16 hash bits, 97.36% on 32 hash bits, 98.28% on 48 hash bits, and 98.54% on 64 bits. Our experimental results on UCMD and AID datasets illustrate that DHPL could generate great results compared with other state-of-the-art hash approaches. Full article

As satellite observation technology improves, the number of remote sensing images significantly and rapidly increases. Therefore, a growing number of studies are focusing on remote sensing image retrieval. However, having a large number of remote sensing images considerably slows the retrieval time and takes up a great deal of memory space. The hash method is being increasingly used for rapid image retrieval because of its remarkably fast performance. At the same time, selecting samples that contain more information and greater stability to train the network has gradually become the key to improving retrieval performance. Given the above considerations, we propose a deep hash remote sensing image retrieval method, called the hard probability sampling hash retrieval method (HPSH), which combines hash code learning with hard probability sampling in a deep network. Specifically, we used a probability sampling method to select training samples, and we designed one novel hash loss function to better train the network parameters and reduce the hashing accuracy loss due to quantization. Our experimental results demonstrate that HPSH could yield an excellent representation compared with other state-of-the-art hash approaches. For the university of California, merced (UCMD) dataset, HPSH+S resulted in a mean average precision (mAP) of up to 90.9% on 16 hash bits, 92.2% on 24 hash bits, and 92.8% on 32 hash bits. For the aerial image dataset (AID), HPSH+S achieved a mAP of up to 89.8% on 16 hash bits, 93.6% on 24 hash bits, and 95.5% on 32 hash bits. For the UCMD dataset, with the use of data augmentation, our proposed approach achieved a mAP of up to 99.6% on 32 hash bits and 99.7% on 64 hash bits. Full article

Mutations in collagen VI genes cause two major clinical myopathies, Bethlem myopathy (BM) and Ullrich congenital muscular dystrophy (UCMD), and the rarer myosclerosis myopathy. In addition to congenital muscle weakness, patients affected by collagen VI-related myopathies show axial and proximal joint contractures, and distal joint hypermobility, which suggest the involvement of tendon function. To gain further insight into the role of collagen VI in human tendon structure and function, we performed ultrastructural, biochemical, and RT-PCR analysis on tendon biopsies and on cell cultures derived from two patients affected with BM and UCMD. In vitro studies revealed striking alterations in the collagen VI network, associated with disruption of the collagen VI-NG2 (Collagen VI-neural/glial antigen 2) axis and defects in cell polarization and migration. The organization of extracellular matrix (ECM) components, as regards collagens I and XII, was also affected, along with an increase in the active form of metalloproteinase 2 (MMP2). In agreement with the in vitro alterations, tendon biopsies from collagen VI-related myopathy patients displayed striking changes in collagen fibril morphology and cell death. These data point to a critical role of collagen VI in tendon matrix organization and cell behavior. The remodeling of the tendon matrix may contribute to the muscle dysfunction observed in BM and UCMD patients. Full article

Ullrich congenital muscular dystrophy (UCMD) bring heavy burden to patients’ families and society. Because the incidence of this disease is very low, studies in patients are extremely limited. Animal models of this disease are indispensable. UCMD belongs to extracellular matrix-related diseases. However, the disease models constructed by knocking out some pathogenic genes of human, such as the Col6a1, Col6a2, or Col6a3 gene, of mice could not mimic UCMD. The purpose of this study is to construct a mouse model which can resemble the pathology of UCMD. miR-29 is closely related to extracellular matrix deposition of tissues and organs. To address this issue, we developed a mouse model for overexpression miR-29 using Tet-on system. In the muscle-specific miR-29ab1 cluster transgenic mice model, we found that mice exhibited dyskinesia, dyspnea, and spinal anomaly. The skeletal muscle was damaged and regenerated. At the same time, we clarify the molecular mechanism of the role of miR-29 in this process. Different from human, Col4a1 and Col4a2, target genes of miR-29, are the key pathogenic genes associating with these phenotypes. This mouse model simulates the human clinical and pathological characteristics of UCMD patients and is helpful for the subsequent research and treatment of UCMD. Full article