Search Results (7)

Spondyloepimetaphyseal dysplasia type Isidor-Toutain (RPL13-SEMD) is an autosomal dominant skeletal dysplasia caused by heterozygous pathogenic variants in the RPL13 gene, encoding the ribosomal protein eL13. To date, 13 pathogenic variants in RPL13 have been reported, all clustering within intron 5 and exon 6, suggesting this hotspot region is critical for the function of ribosomes in skeletal tissues. Here, we present clinical and radiological characteristics of seven individuals, five children and two adults, from four unrelated families with RPL13-SEMD caused by two novel variants (c.477+5G>C and c.539_541del) and two previously reported variants (c.477+1G>C and c.548G>A) in RPL13. RNA analysis demonstrated that c.477+5G>C leads to a 54-nucleotide extension of exon 5, resulting in an 18-amino acid insertion. The phenotypic spectrum ranged from mild manifestations, such as Blount-like tibial deformity without significant short stature or Perthes-like femoral epiphyseal changes, to severe skeletal deformities with disproportionate short stature, accompanied by extraskeletal features (e.g., penoscrotal hypospadias, coccygeal abnormalities). For the first time, we describe Blount-like tibial deformity as a feature of this dysplasia, which resolves with age. Our study provides additional insights into the clinical, radiological, and genotypic features of RPL13-SEMD through detailed analysis of patients and their affected relatives. Full article

Skeletal dysplasias, characterized by bone, cartilage, and connective tissue abnormalities, often arise due to disruptions in extracellular matrix (ECM) dynamics and growth factor-dependent signaling pathways. RSPRY1, a secreted protein with RING and SPRY domains, has been implicated in bone development, yet its exact role remains to be determined. RSPRY1 gene mutations are associated with spondyloepimetaphyseal dysplasia (SEMD), a rare skeletal disorder characterized by severe epiphyseal and metaphyseal deformities. This study aimed to determine the molecular and cellular mechanisms by which RSPRY1 deficiency affects skeletal homeostasis. Transcriptome analysis of fibroblasts from patients with homozygous RSPRY1 mutations showed there was significant enrichment of transforming growth factor beta (TGF-β) signaling and ECM-related pathways. Functional wound healing assays showed that RSPRY1 knockout fibroblasts exhibited enhanced motility, a phenotype that was abrogated in RSPRY1 + SMAD3 double knockout fibroblasts, highlighting the SMAD3-dependence of RSPRY1′s effects. The observed limited response to exogenous TGF-β in RSPRY1-deficient cells indicated that there was constitutive pathway activation. These findings show that RSPRY1 is a critical regulator of TGF-β signaling in ECM dynamics and cell motility, contributing to the pathophysiology of SEMD. An improvement in our understanding of the molecular roles of RSPRY1 might yield novel therapeutic strategies that target TGF-β signaling in patients with SEMD and other skeletal dysplasias. Full article

Identifying multi-scale anomalies that have simple forms and geological significance is critical for enhancing the interpretability of gravity and magnetic survey data. In recent years, empirical mode decomposition (EMD), which was developed as a significant data-driven approach for analyzing complex signals, has been widely used in identifying gravity and magnetic anomalies due to its advantages of adaptability to nonlinear and nonstationary data. Nevertheless, the traditional EMD method is usually sensitive to outliers and irregularly spaced data because of the interpolation process in the construction of envelopes. In this regard, an extended algorithm called statistical EMD (SEMD) has been proposed based on the smoothing technique. In this study, for validation purposes, the novel SEMD method has been employed to identify multi-scale gravity and magnetic anomalies. The sensitivities of local polynomial and cubic spline smoothing methods in SEMD to combination and arrangement patterns of field sources including the size, depth, and distance in gravity and magnetic anomaly identification were investigated and compared by forward modeling under the same conditions. The results demonstrated that the local polynomial smoothing method performed better than the cubic spline smoothing method. Thus, in the case study, the SEMD method using the local polynomial smoothing technique was employed for identifying multi-scale gravity and magnetic anomalies in the eastern Tianshan orogenic belt, northwestern China. It has illustrated that the SEMD method provides a novel and useful data-driven method for extracting gravity and magnetic anomalies. Full article

Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have shortcomings such as low segmentation accuracy and manual intervention. To achieve accurate segmentation of standing tree images effectively, SEMD, a lightweight network segmentation model based on deep learning, is proposed in this article. DeepLabV3+ is chosen as the base framework to perform multi-scale fusion of the convolutional features of the standing trees in images, so as to reduce the loss of image edge details during the standing tree segmentation and reduce the loss of feature information. MobileNet, a lightweight network, is integrated into the backbone network to reduce the computational complexity. Furthermore, SENet, an attention mechanism, is added to obtain the feature information efficiently and suppress the generation of useless feature information. The extensive experimental results show that using the SEMD model the MIoU of the semantic segmentation of standing tree images of different varieties and categories under simple and complex backgrounds reaches 91.78% and 86.90%, respectively. The lightweight network segmentation model SEMD based on deep learning proposed in this paper can solve the problem of multiple standing trees segmentation with high accuracy. Full article

Theoretical accounts on social decision-making under uncertainty postulate that individual risk preferences are context dependent. Generalization of models of decision-making to dyadic interactions in the personal health context remain to be experimentally addressed. In economic utility-based models, interactive behavioral games provide a framework to investigate probabilistic learning of sequential reinforcement. Here, we model an economic trust game in the context of a chronic disease (Diabetes Type 1) which involves iterated daily decisions in complex social contexts. Ninety-one patients performed experimental trust games in both economic and health settings and were characterized by a multiple self-report set of questionnaires. We found that although our groups can correctly infer pay-off contingencies, they behave differently because patients with a biological profile of preserved glycemic control show adaptive choice behavior both in economic and health domains. On the other hand, patients with a biological profile of loss of glycemic control presented a contrasting behavior, showing non-adaptive choices on both contexts. These results provide a direct translation from neuroeconomics to decision-making in the health domain and biological risk profiles, in a behavioral setting that requires difficult and self-consequential decisions with health impact. Our findings also provide a contextual generalization of mechanisms underlying individual decision-making under uncertainty. Full article

Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves’ signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals’ analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed. Full article

Studies have shown that mutations in the matrilin-3 gene (MATN3) are associated with multiple epiphyseal dysplasia (MED) and spondyloepimetaphyseal dysplasia (SEMD). We tested whether MATN3 mutations affect the differentiation of chondroprogenitor and/or mesenchymal stem cells, which are precursors to chondrocytes. ATDC5 chondroprogenitors stably expressing wild-type (WT) MATN3 underwent spontaneous chondrogenesis. Expression of chondrogenic markers collagen II and aggrecan was inhibited in chondroprogenitors carrying the MED or SEMD MATN3 mutations. Hypertrophic marker collagen X remained attenuated in WT MATN3 chondroprogenitors, whereas its expression was elevated in chondroprogenitors expressing the MED or SEMD mutant MATN3 gene suggesting that these mutations inhibit chondrogenesis but promote hypertrophy. TGF-β treatment failed to rescue chondrogenesis markers but dramatically increased collagen X mRNA expression in mutant MATN3 expressing chondroprogenitors. Synovium derived mesenchymal stem cells harboring the SEMD mutation exhibited lower glycosaminoglycan content than those of WT MATN3 in response to TGF-β. Our results suggest that the properties of progenitor cells harboring MATN3 chondrodysplasia mutations were altered, as evidenced by attenuated chondrogenesis and premature hypertrophy. TGF-β treatment failed to completely rescue chondrogenesis but instead induced hypertrophy in mutant MATN3 chondroprogenitors. Our data suggest that chondroprogenitor cells should be considered as a potential target of chondrodysplasia therapy. Full article