A novel ZRS variant causes preaxial polydactyly type I by increased sonic hedgehog expression in the developing limb bud.

PurposePreaxial polydactyly (PPD) is a common congenital hand malformation classified into four subtypes (PPD I-IV). Variants in the zone of polarizing activity regulatory sequence (ZRS) within intron 5 of the LMBR1 gene are linked to most PPD types. However, the genes responsible for PPD I and the underlying mechanisms are unknown.MethodsA rare large four-generation family with isolated PPD I was subjected to genome-wide genotyping and sequence analysis. In vitro and in vivo functional studies were performed in Caco-2 cells, 293T cells, and a knockin transgenic mouse model.ResultsA novel g.101779T>A (reference sequence: NG_009240.2; position 446 of the ZRS) variant segregates with all PPD I-affected individuals. The knockin mouse with this ZRS variant exhibited PPD I phenotype accompanying ectopic and excess expression of Shh. We confirmed that HnRNP K can bind the ZRS and SHH promoters. The ZRS mutant enhanced the binding affinity for HnRNP K and upregulated SHH expression.ConclusionOur results identify the first PPD I disease-causing variant. The variant leading to PPD I may be associated with enhancing SHH expression mediated by HnRNP K. This study adds to the ZRS-associated syndromes classification system for PPD and clarifies the underlying molecular mechanisms

Normal Leptin Expression, Lower Adipogenic Ability, Decreased Leptin Receptor and Hyposensitivity to Leptin in Adolescent Idiopathic Scoliosis

Leptin has been suggested to play a role in the etiology of Adolescent Idiopathic Scoliosis (AIS), however, the leptin levels in AIS girls are still a discrepancy, and no in vitro study of leptin in AIS is reported. We took a series of case-control studies, trying to understand whether Leptin gene polymorphisms are involved in the etiology of the AIS or the change in leptin level is a secondary event, to assess the level of leptin receptor, and to evaluate the differences of response to leptin between AIS cases and controls. We screened all exons of Leptin gene in 45 cases and 45 controls and selected six tag SNPs to cover all the observed variations. Association analysis in 446 AIS patients and 550 healthy controls showed no association between the polymorphisms of Leptin gene and susceptibility/severity to AIS. Moreover, adipogenesis assay of bone mesenchymal stem cells (MSCs) suggested that the adipogenic ability of MSCs from AIS girls was lower than controls. After adjusting the differentiation rate, expressions of leptin and leptin receptor were similar between two groups. Meanwhile, osteogenesis assay of MSC showed the leptin level was similar after adjusting the differentiation rate, but the leptin receptor level was decreased in induced AIS osteoblasts. Immunocytochemistry and western blot analysis showed less leptin receptors expressed in AIS group. Furthermore, factorial designed studies with adipogenesis and osteogenesis revealed that the MSCs from patients have no response to leptin treatment. Our results suggested that Leptin gene variations are not associated with AIS and low serum leptin probably is a secondary outcome which may be related to the low capability of adipogenesis in AIS. The decreased leptin receptor levels may lead to the hyposensitivity to leptin. These findings implied that abnormal peripheral leptin signaling plays an important role in the pathological mechanism of AIS

Improved Butler–Reeds–Dawson Algorithm for the Inversion of Two-Dimensional NMR Relaxometry Data

Two-dimensional (2D) NMR relaxometry has been widely used as a powerful new tool for identifying and characterizing molecular dynamics. Various inversion algorithms have been introduced to obtain the versatile relaxation information conveyed by spectra. The inversion procedure is especially challenging because the relevant data are huge in 2D cases and the inversion problem is ill-posed. Here, we propose a new method to process the 2D NMR relaxometry data. Our approach varies from Tikhonov regularization, known previously in CONTIN and Maximum Entropy (MaxEnt) methods, which need additional efforts to compute an appropriate regularization factor. This variety improves Butler–Reeds–Dawson algorithm to optimize the Tikhonov regularization problem and the regularization factor is calculated alongside. The calculation is considerably faster than the mentioned algorithms. The proposed method is compared with some widely used methods on simulated datasets, regarding algorithm efficiency and noise vulnerability. Also, the result of the experimental data is presented to test the practical utility of the proposed algorithm. The results suggest that our approach is efficient and robust. It can meet different application requirements

Disclosing the hidden structure and underlying mutational mechanism of a novel type of duplication CNV responsible for hereditary multiple osteochondromas

The additional mutational complexity associated with copy number variation (CNV) can provide important clues as to the underlying mechanisms of CNV formation. Correct annotation of the additional mutational complexity is, however, a prerequisite for establishing the mutational mechanism. We illustrate this point through the characterization of a novel ∼230 kb EXT1 duplication CNV causing autosomal dominant hereditary multiple osteochondromas. Whole-genome sequencing initially identified the CNV as having a 22-bp insertion at the breakpoint junction and, unprecedentedly, multiple breakpoint-flanking micromutations on both sides of the duplication. Further investigation revealed that this genomic rearrangement had a duplication-inverted triplication–duplication structure, the inverted triplication being a 41-bp sequence synthesized from a nearby template. This permitted the identification of the sequence determinants of both the initiation (an inverted Alu repeat) and termination (a triplex-forming sequence) of break-induced replication and suggested a possible model for the repair of replication-associated double-strand breaks

Type III Transforming Growth Factor-β Receptor RNA Interference Enhances Transforming Growth Factor β3-Induced Chondrogenesis Signaling in Human Mesenchymal Stem Cells

The type III transforming growth factor-β (TGF-β) receptor (TβRIII), a coreceptor of the TGF-β superfamily, is known to bind TGF-βs and regulate TGF-β signaling. However, the regulatory roles of TβRIII in TGF-β-induced mesenchymal stem cell (MSC) chondrogenesis have not been explored. The present study examined the effect of TβRIII RNA interference (RNAi) on TGF-β3-induced human MSC (hMSC) chondrogenesis and possible signal mechanisms. A lentiviral expression vector containing TβRIII small interfering RNA (siRNA) (SiTβRIII) or a control siRNA (SiNC) gene was constructed and infected into hMSCs. The cells were cultured in chondrogenic medium containing TGF-β3 or control medium. TβRIII RNAi significantly enhanced TGF-β3-induced chondrogenic differentiation of hMSCs, the ratio of type II (TβRII) to type I (TβRI) TGF-β receptors, and phosphorylation levels of Smad2/3 as compared with cells infected with SiNC. An inhibitor of the TGF-β signal, SB431542, not only inhibited TβRIII RNAi-stimulated TGF-β3-mediated Smad2/3 phosphorylation but also inhibited the effects of TβRIII RNAi on TGF-β3-induced chondrogenic differentiation. These results demonstrate that TβRIII RNAi enhances TGF-β3-induced chondrogenic differentiation in hMSCs by activating TGF-β/Smad2/3 signaling. The finding points to the possibility of modifying MSCs by TβRIII knockdown as a potent future strategy for cell-based cartilage tissue engineering

Automatic Lenke classification of adolescent idiopathic scoliosis with deep learning

Abstract Purpose The Lenke classification system is widely utilized as the preoperative evaluation protocol for adolescent idiopathic scoliosis (AIS). However, manual measurement is susceptible to observer‐induced variability, which consequently impacts the evaluation of progression. The goal of this investigation was to develop an automated Lenke classification system utilizing innovative deep learning algorithms. Methods Using the database from the First Affiliated Hospital of Sun Yat‐sen University, the whole spinal x‐rays images were retrospectively collected. Specifically, images collection was divided into AIS and control group. The control group consisted of individuals who underwent routine health checks and did not have scoliosis. Afterwards, relative features of all images were annotated. Deep learning was implemented through the utilization of the key‐point based detection method to realize the vertebral detection, and Cobb angle measurement and scoliosis classification were performed based on relevant standards. Besides, the segmentation method was employed to achieve the recognition of lumbar vertebral pedicle to determine the type of lumbar spine modifier. Finally, the model performance was further quantitatively analyzed. Results In the study, a total of 2082 spinal x‐ray images were collected from 407 AIS patients and 227 individuals in the control group. The model for vertebral detection achieved an F1‐score of 0.809 for curve type evaluation and an F1‐score of 0.901 for thoracic sagittal profile. The intraclass correlation efficient (ICC) of the Cobb angle measurement was 0.925. In the analysis of performance for vertebra pedicle segmentation model, the F1‐score of lumbar modification profile was 0.942, the intersection over union (IOU) of the target pixels was 0.827, and the Hausdorff distance (HD) was 6.565 ± 2.583 mm. Specifically, the F1‐score for ultimate Lenke type classifier was 0.885. Conclusions This study has constructed an automated Lenke classification system by employing the deep learning networks to achieve the recognition pattern and feature extraction. Our models require further validation in additional cases in the future

Mapk7 deletion in chondrocytes causes vertebral defects by reducing MEF2C/PTEN/AKT signaling

Mutation of the MAPK7 gene was related to human scoliosis. Mapk7 regulated the development of limb bones and skulls in mice. However, the role of MAPK7 in vertebral development is still unclear. In this study, we constructed Col2a1-cre; Mapk7f/f transgenic mouse model to delete Mapk7 in cartilage, which displayed kyphosis and osteopenia. Mechanistically, Mapk7 loss decreased MEF2C expression and thus activated PTEN to oppose PI3K/AKT signaling in vertebral growth plate chondrocytes, which impaired chondrocyte hypertrophy and attenuated vertebral ossification. In vivo, systemic pharmacological activation of AKT rescued impaired chondrocyte hypertrophy and alleviated mouse vertebral defects caused by Mapk7 deficiency. Our study firstly clarified the mechanism by which MAPK7 was involved in vertebral development, which might contribute to understanding the pathology of spinal deformity and provide a basis for the treatment of developmental disorders of the spine