Health-related quality of life in Chinese SLE patients: evidence from 1568 SLE patients and 2610 healthy controls.

OBJECTIVE: To investigate the effects of systemic lupus erythematosus (SLE) on health-related quality of life (HRQOL), the relationship between disease activity and HRQOL, and potential factors affecting HRQOL in Chinese SLE patients. METHODS: This study recruited 1568 patients and 2610 controls to explore the effects of SLE on HRQOL. The association between disease activity and HRQOL, and the influencing factors of HRQOL were determined in 1568 patients. Then, we prospectively followed 1096 patients to explore the association between reduced disease activity and improved HRQOL, and the influencing factors of improved HRQOL. The Short-Form 36 (SF-36) and SLE disease activity index (SLEDAI) were used to evaluate HRQOL and disease activity. RESULTS: Chinese SLE patients had lower HRQOL than controls in all domains (P < 0.001), especially in role-physical (RP) and role-emotional (RE). Compared with SLE patients from outside China, the HRQOL of Chinese patients appeared to be higher in mental component summary (MCS) but lower in RP and RE. SLEDAI was negatively correlated with HRQOL, which was validated using the results of a follow-up study, where SLEDAI reduction was positively associated with HRQOL improvements (P < 0.05). Furthermore, personality, life nervous and experiences of adverse life events may influence HRQOL and HRQOL improvements. CONCLUSION: SLE significantly affected the HRQOL of Chinese patients, especially in RP and RE. Disease activity was negatively correlated with HRQOL. We also found for the first time some factors affecting HRQOL, which can be regarded as the basis for improving the HRQOL of SLE patients.

Impact of climate factors and climate-gene interaction on systemic lupus erythematosus patients' response to glucocorticoids therapy.

BACKGROUND: Glucocorticoids (GCs) were the essential drugs for systemic lupus erythematosus (SLE). However, different patients differ substantially in their response to GCs treatment. Our current study aims at investigating whether climate variability and climate-gene interaction influence SLE patients' response to the therapy of GCs. METHODS: In total, 778 SLE patients received therapy of GCs for a study of 12-week follow-up. The efficacy of GCs treatment was evaluated using the Systemic Lupus Erythematosus Disease Activity Index. The climatic data were provided by China Meteorological Data Service Center. Additive and multiplicative interactions were examined. RESULTS: Compared with patients with autumn onset, the efficacy of GCs in patients with winter onset is relatively poor (ORadj = 1.805, 95%CIadj : 1.181-3.014, padj = 0.020). High mean relative humidity during treatment decreased the efficacy of GCs (ORadj = 1.033, 95%CIadj : 1.008-1.058, padj = 0.011), especially in female (ORadj = 1.039, 95%CIadj : 1.012-1.067, padj = 0.004). There was a significant interaction between sunshine during treatment and TRAP1 gene rs12597773 on GCs efficacy (Recessive model: AP = 0.770). No evidence of significant interaction was found between climate factors and the GR gene polymorphism on the improved GCs efficacy in the additive model. Multiplicative interaction was found between humidity in the month prior to treatment and GR gene rs4912905 on GCs efficacy (Dominant model: OR = 0.470, 95%CI: 0.244-0.905, p = 0.024). CONCLUSIONS: Our findings suggest that climate variability influences SLE patients' response to the therapy of GCs. Interactions between climate and TRAP1/GR gene polymorphisms were related to GCs efficacy. The results guide the individualized treatment of SLE patients.

Mitochondrial DNA genetic variants are associated with systemic lupus erythematosus susceptibility, glucocorticoids efficacy and prognosis.

OBJECTIVE: To investigate the associations of mitochondrial DNA (mtDNA) genetic variants with SLE susceptibility, glucocorticoid (GC) efficacy and prognosis. METHODS: Our study was done in two stages. First, we performed whole mitochondrial genome sequencing in 100 patients and 100 controls to initially screen potential mtDNA variants associated with disease and GC efficacy. Then, we validated the results in an independent set of samples. In total, 605 SLE patients and 604 normal controls were included in our two-stage study. A two-stage efficacy study was conducted in 512 patients treated with GCs for 12 weeks. We also explored the association between mtDNA variants and SLE prognosis. RESULTS: In the combined sample, four mtDNA variants (A4833G, T5108C, G14569A, CA514-515-) were associated with SLE susceptibility (all PBH < 0.05). We confirmed that T16362C was related to efficacy of GCs (PBH = 0.014). Significant associations were detected between T16362C and T16519C and the efficacy of GCs in females with SLE (PBH < 0.05). In the prognosis study, variants A4833G (PBH = 0.003) and G14569A (PBH = 9.744 × 10-4) substantially increased SLE relapse risk. Female patients harbouring variants T5108C and T16362C were more prone to relapse (PBH < 0.05). Haplotype analysis showed that haplogroup G was linked with SLE susceptibility (PBH = 0.001) and prognosis (PBH = 0.013). Moreover, mtDNA variant-environment interactions were observed. CONCLUSION: We identified novel mtDNA genetic variants that were associated with SLE susceptibility, GC efficacy, and prognosis. Interactions between mtDNA variants and environmental factors were related to SLE risk and GC efficacy. Our findings provide important information for future understanding of the occurrence and development of SLE.

Associations of RPEL1 and miR-1307 gene polymorphisms with disease susceptibility, glucocorticoid efficacy, anxiety, depression, and health-related quality of life in Chinese systemic lupus erythematosus patients.

OBJECTIVE: Our present study intended to examine the associations of RPEL1 and miR-1307 gene polymorphisms (rs4917385 and rs7911488) with susceptibility, glucocorticoids (GCs) efficacy, anxiety, depression, and health-related quality of life (HRQoL) in Chinese systemic lupus erythematosus (SLE) patients. METHODS: Initially, 1000 participants (500 SLE cases and 500 controls) were recruited for the case-control study. Then, 429 cases who received GCs were followed through 12 weeks to explore GCs efficacy, depression, anxiety, and HRQoL. We selected the iMLDR technique for genotyping: RPEL1: rs4917385 (G/T) and miR-1307: rs7911488 (A/G). RESULTS: The minor G allele of rs7911488 reduced the risk of SLE (p = .024). Four haplotypes consisting of rs4917385 and rs7911488 were associated with SLE susceptibility (p < .025). Both rs4917385 and rs7911488 were associated with anxiety symptoms and physical function (PF) in SLE patients (p < .025). The rs4917385 was associated with depression and its improvement. No statistical significance was found between RPEL1 and miR-1307 gene polymorphisms with GCs efficacy. Meanwhile, additive interaction analysis showed a significant association between RPEL1 and miR-1307 gene polymorphisms with tea consumption in anxiety. CONCLUSION: RPEL1 and miR-1307 gene polymorphisms (rs4917385 and rs7911488) might be related to SLE susceptibility in Chinese population. Additionally, the two polymorphisms were possibly associated with depression, anxiety, and HRQoL in Chinese SLE population.

Association of DYNC1H1 gene SNP/CNV with disease susceptibility, GCs efficacy, HRQOL, anxiety, and depression in Chinese SLE patients.

BACKGROUND: Systemic lupus erythematosus is a heterogeneous autoimmune disease characterized by multi-system injuries and overproduction of autoantibodies. There are many genetic studies on SLE, but no report has considered the relationship between cytoplasmic dynein and SLE susceptibility. OBJECTIVES: Our study intends to investigate whether DYNC1H1 gene SNP/CNV is related to SLE susceptibility, GCs efficacy, HRQOL, anxiety, and depression in Chinese SLE patients. METHODS: A total of 502 cases and 544 healthy controls were recruited into the case-control study, and 472 subjects from the case group were followed up for 12 weeks to evaluate GCs efficacy, HRQOL, anxiety, and depression. Multiplex SNaPshot technique was applied to genotype the seven SNPs of DYNC1H1, and AccuCopyTM method was conducted to quantify the copy number of DYNC1H1. Anxiety and depression were evaluated using HAMA and HAMD-24 scales, respectively. The SF-36 scale was used to assess HRQOL. RESULTS: The significant association between SNP rs1190606 and SLE susceptibility was displayed in the dominant model (PBH = 0.004) as well as its allele model (PBH = 0.004). We also found that SNP rs2273440 was related to photosensitization symptom in SLE patients (PBH = 0.032). In the follow-up study, SNP rs11160668 was connected with the improvement of BP in male patients (PBH = 0.011). However, no association of DYNC1H1 gene with GCs efficacy, anxiety, and depression was found. No CNV in DYNC1H1 was detected. CONCLUSIONS: The study suggests that DYNC1H1 gene polymorphisms may have an effect on SLE susceptibility and BP improvement of HRQOL in Chinese SLE patients.

Copy number variations and polymorphisms in HSP90AB1 and risk of systemic lupus erythematosus and efficacy of glucocorticoids.

The aim of our study was to assess the associations of HSP90AB1 copy number variations (CNVs) with systemic lupus erythematosus (SLE) risk and glucocorticoids (GCs) efficacy, as well as the relationship between HSP90AB1 single-nucleotide polymorphisms (SNPs) and GCs efficacy. HSP90AB1 CNVs and SLE risk were analysed in 519 patients and 538 controls. Patients treated with GCs were followed up for 12 weeks and were divided into sensitive and insensitive groups to investigate the effects of CNVs (419 patients) and SNPs (457 patients) on the efficacy of GCs. Health-related quality of life (HRQoL) was also measured by SF-36 at baseline and week 12 to explore the relationship between CNVs/SNPs and HRQoL improvements in Chinese SLE patients. Our results indicated a statistically significant association between HSP90AB1 CNVs and SLE (PBH  = 0.039), and this association was more pronounced in the female subgroup (PBH  = 0.039). However, we did not detect association of HSP90AB1 CNVs/SNPs with efficacy of GCs. But we found a marginal association between SNP rs13296 and improvement in Role-emotional, while this association was not strong enough to survive in the multiple testing corrections. Collectively, our findings suggest that the copy number of HSP90AB1 is associated with SLE susceptibility. But copy number and polymorphisms of HSP90AB1 may not be associated with efficacy of GCs.

Microfluidic technologies for vasculature biomimicry.

Microfluidic technology has been extensively employed in biology and medicine since the field emerged in the 1990s. By utilizing microfluidic approaches, a variety of vascular system-related structures and functions have been mimicked on in vitro platforms. Herein, we begin by introducing microfluidic circulatory devices for the study of two-dimensional (2D) endothelial cells culture. Next, we focus on recent progress on on-chip mimicry of native vasculature, specifically generation of complex three-dimensional (3D) structures within cell-laden hydrogels using microfluidics and self-assembly-based methods. The utilization of microfluidic technology will facilitate the construction of progressively biomimetic in vitro models that have great potential in complementing existing animal models. We envision such platforms to be utilized in a wide range of applications involving vascular systems, including microphysiological studies, drug screening, and disease modeling.

Centrifugation-Assisted Single-Cell Trapping in a Truncated Cone-Shaped Microwell Array Chip for the Real-Time Observation of Cellular Apoptosis.

Microfluidic devices have been extensively used in single-cell assays. However, most of them have complicated structures (multiple layers, valves, and channels) and require the assistance of a pump or pressure-controlling system. In this paper, we present a facile centrifugation-assisted single-cell trapping (CAScT) approach based on a truncated cone-shaped microwell array (TCMA) chip for real-time observation of cellular apoptosis. Our method requires neither a pump nor a pressure-controlling system, and it greatly reduces the complexity of other cell-trapping devices. This method is so fast and efficient that single-cell occupancy could reach approximately 90% within a few seconds. Combined with modern fluorescence microscopy, CAScT makes the highly ordered and addressable TCMA a high-throughput platform (10(4)-10(5) single-cell trapping sites per cm(2)) for single-cell analysis. Cells trapped in it could be exposed to various chemicals by directly immersing it in bulk solutions without the significant loss of cells due to the truncated cone shape of the microwells. As a proof of concept, we demonstrated the ability of our chip for the real-time observation of the apoptosis of single HeLa cells induced by the common anticancer drug doxorubicin. This simple, robust, and efficient approach possesses great potential in diverse applications, such as drug screening, biosensing, and fundamental biological research.

SGReg: segmentation guided 3D/2D rigid registration for orthogonal X-ray and CT images in spine surgery navigation.

Objective.One of the essential technologies in various image-guided spine surgeries is the rigid registration of 3D pre-operative CT and 2D intra-operative X-ray images. The 3D/2D registration is patterned as two essential tasks, that is, dimensional correspondence establishment and estimation of the 3D pose. 3D data is projected to 2D for dimensional correspondence by most of the existing methods, which makes pose parameters difficult to estimate caused by the loss of spatial information. This work aims to develop a reconstruction based 3D/2D registration method for spine surgery navigation.Approach.A novel segmentation-guided 3D/2D registration (SGReg) method for orthogonal X-ray and CT images was proposed based on reconstruction. SGReg consists of a bi-path segmentation network and an inter-path multi-scale pose estimation module. The X-ray segmentation path in the bi-path segmentation network reconstructs 3D spatial information from 2D orthogonal X-ray images to segmentation masks; meanwhile, the CT segmentation path predicts segmentation masks from 3D CT images, thereby bringing the 3D/2D data into dimensional correspondence. In the inter-path multi-scale pose estimation module, the features from the two segmentation paths are integrated, and the pose parameters are directly regressed under the guidance of the coordinate information.Main result.We evaluated SGReg using a public dataset CTSpine1k and compared the registration performance with other methods. SGReg achieved considerable improvement over other methods with great robustness.SignificanceWe have proposed an end-to-end 3D/2D registration framework named SGReg. Based on the idea of reconstruction, SGReg performs a unified framework between dimensional correspondence establishment and direct pose estimation in 3D space, showing significant potential in spine surgery navigation.

Understanding the role of exosomal lncRNAs in rheumatic diseases: a review.

Rheumatic diseases, a group of diseases whose etiology is still unclear, are thought to be related to genetic and environmental factors, leading to complex pathogenesis. Based on their multi-system involvement, the diagnosis and treatment continue to face huge challenges. Whole-genome assays provide a distinct direction for understanding the underlying mechanisms of such diseases. Exosomes, nano-sized bilayer membrane vesicles secreted by cells, are mentioned as a key element in the physiological and pathological processes of the body. These exosomes mediate biologically active substances, such as nucleic acids, proteins, and lipids and deliver them to cells. Notably, long non-coding RNAs (lncRNAs), a unique class of non-coding RNAs, have been implicated in the pathogenesis of rheumatic diseases. However, the mechanism needs to be further explored. This article provided a comprehensive review of the findings on exosomal lncRNAs in rheumatic diseases, including rheumatoid arthritis, osteoarthritis, systemic lupus erythematosus, autoimmune liver diseases, primary dermatomyositis, and systemic sclerosis. Through in-depth understanding of these lncRNAs and their involved signaling pathways provide new theoretical supports for the diagnosis and treatment of rheumatic diseases.

SpineRegNet: Spine Registration Network for volumetric MR and CT image by the joint estimation of an affine-elastic deformation field.

Spine registration for volumetric magnetic resonance (MR) and computed tomography (CT) images plays a significant role in surgical planning and surgical navigation system for the radiofrequency ablation of spine intervertebral discs. The affine transformation of each vertebra and elastic deformation of the intervertebral disc exist at the same time. This situation is a major challenge in spine registration. Existing spinal image registration methods failed to solve the optimal affine-elastic deformation field (AEDF) simultaneously, only consider the overall rigid or elastic alignment with the help of a manual spine mask, and encounter difficulty in meeting the accuracy requirements of clinical registration application. In this study, we propose a novel affine-elastic registration framework named SpineRegNet. The SpineRegNet consists of a Multiple Affine Matrices Estimation (MAME) Module for multiple vertebrae alignment, an Affine-Elastic Fusion (AEF) Module for joint estimation of the overall AEDF, and a Local Rigidity Constraint (LRC) Module for preserving the rigidity of each vertebra. Experiments on T2-weighted volumetric MR and CT images show that the proposed approach achieves impressive performance with mean Dice similarity coefficients of 91.36%, 81.60%, and 83.08% for the mask of the vertebrae on Datasets A-C, respectively. The proposed technique does not require a mask or manual participation during the tests and provides a useful tool for clinical spinal disease surgical planning and surgical navigation systems.

Online identification and classification of Gannan navel oranges with Cu contamination by LIBS with IGA-optimized SVM.

Elements such as minerals and heavy metals play important roles in the nutrition and safety of agricultural products. It is necessary to develop rapid, online, real-time and in situ methods for monitoring the substances in farm products. Gannan navel oranges are a unique variety of fruit, which may be affected by Cu pollution due to abundant copper mines and other factors. An online identification and classification system based on laser-induced breakdown spectroscopy (LIBS) was developed to detect possible Cu residue in Gannan navel oranges. First, transmission and classification equipment for Gannan navel oranges was built. Second, an LIBS detection module was designed. Finally, a software system for the whole online detection platform was developed based on the C# programming language. The series of operations for the online detection system, which includes the loading, transmission, detection and classification of orange samples, can be controlled. Since the navel orange has an elliptical shape, the LIBS detection module was designed with a long focal length to reduce the influence of fruit plane size fluctuation. The long focal length was optimized to 698 mm, and the depth of field was ±6 mm. Furthermore, a parameter optimization model using a support vector machine (SVM) based on an improved genetic algorithm (IGA) is proposed to improve the classification effect of Gannan navel oranges. This model avoids the over-learning or under-learning caused by improper parameter selection in the regression prediction of SVM. The IGA is used to optimize the penalty parameter c and the kernel parameter g of SVM. LIBS spectral data from two types of navel orange samples with and without Cu contamination were selected as test datasets, and the classification results were compared with those of the standard genetic algorithm-support vector machine (GA-SVM). The investigation showed that the IGA-SVM can provide better classification of navel oranges based on analysis of the LIBS spectral data, and the classification accuracy can reach 98%, which provides significant guidance for the use of LIBS to quickly realize online screening of heavy metals in agriculture products.

In situ deposition of 0D CeO2 quantum dots on Fe2O3-containing solid waste NH3-SCR catalyst: Enhancing redox and NH3 adsorption ability.

As NOx has been turning into a crucial environmental problem, NH3-SCR technology with relatively simple device, reliable operation and low secondary pollution, has become a widely used commercial and mature de-nitration technology. However, some weaknesses restricted the further application of commercialized V2O5-WO3/TiO2 NH3-SCR catalysts, while Fe2O3-based catalysts have received much attention due to their high thermal stability, passable N2 selectivity and low cost. In this study, Fe2O3-containing solid waste derived from Zn extraction process of electric arc furnace dust was exploited as the base material for catalyst preparing. Owing to the complementary and synergistic effect of CeO2 and Fe2O3, 0D CeO2 quantum dots (CeQDs) with fully-exposed active sites, large specific surface area, and rapid charge transfer have been introduced and deposited onto Fe2O3-containing solid waste nanorods. The in-situ deposition of CeQDs led to the admirable enhancement in NH3-SCR catalytic activity, N2 selectivity and SO2 tolerance of the extremely low-cost Fe2O3 catalyst. Comprehensive characterizations and DFT calculations describing the adsorption of O2 and NH3 were applied to analyze the catalyst structure and further investigate the detailed relationship between structural properties and activity as well as reaction mechanism. This work provides new insights for the high-value utilization of iron-containing solid waste and a practical reference for boosting the performance of NH3-SCR catalysts by introducing quantum dots.

Improving sensitivity and connectivity of retinal vessel segmentation via error discrimination network.

PURPOSE: Automated retinal vessel segmentation is crucial to the early diagnosis and treatment of ophthalmological diseases. Many deep-learning-based methods have shown exceptional success in this task. However, current approaches are still inadequate in challenging vessels (e.g., thin vessels) and rarely focus on the connectivity of vessel segmentation. METHODS: We propose using an error discrimination network (D) to distinguish whether the vessel pixel predictions of the segmentation network (S) are correct, and S is trained to obtain fewer error predictions of D. Our method is similar to, but not the same as, the generative adversarial network. Three types of vessel samples and corresponding error masks are used to train D, as follows: (1) vessel ground truth; (2) vessel segmented by S; (3) artificial thin vessel error samples that further improve the sensitivity of D to wrong small vessels. As an auxiliary loss function of S, D strengthens the supervision of difficult vessels. Optionally, we can use the errors predicted by D to correct the segmentation result of S. RESULTS: Compared with state-of-the-art methods, our method achieves the highest scores in sensitivity (86.19%, 86.26%, and 86.53%) and G-Mean (91.94%, 91.30%, and 92.76%) on three public datasets, namely, STARE, DRIVE, and HRF. Our method also maintains a competitive level in other metrics. On the STARE dataset, the F1-score and area under the receiver operating characteristic curve (AUC) of our method rank second and first, respectively, reaching 84.51% and 98.97%. The top scores of the three topology-relevant metrics (Conn, Inf, and Cor) demonstrate that the vessels extracted by our method have excellent connectivity. We also validate the effectiveness of error discrimination supervision and artificial error sample training through ablation experiments. CONCLUSIONS: The proposed method provides an accurate and robust solution for difficult vessel segmentation.

DGMSNet: Spine segmentation for MR image by a detection-guided mixed-supervised segmentation network.

Spine segmentation for magnetic resonance (MR) images is important for various spinal diseases diagnosis and treatment, yet is still a challenge due to the inter-class similarity, i.e., shape and appearance similarities appear in neighboring spinal structures. To reduce inter-class similarity, existing approaches focus on enhancing the semantic information of spinal structures in the supervised segmentation network, whose generalization is limited by the size of pixel-level annotated dataset. In this paper, we propose a novel detection-guided mixed-supervised segmentation network (DGMSNet) to achieve automated spine segmentation. DGMSNet consists of a segmentation path for generating the spine segmentation prediction and a detection path (i.e., regression network) for producing heatmaps prediction of keypoints. A detection-guided learner in the detection path is introduced to generate a dynamic parameter, which is employed to produce a semantic feature map for segmentation path by adaptive convolution. A mixed-supervised loss comprised of a weighted combination of segmentation loss and detection loss is utilized to train DGMSNet with a pixel-level annotated dataset and a keypoints-detection annotated dataset. During training, a series of models are trained with various loss weights. In inference, a detection-guided label fusion approach is proposed to integrate the segmentation predictions generated by those trained models according to the consistency of predictions from the segmentation path and detection path. Experiments on T2-weighted MR images show that DGMSNet achieves the state-of-the-art performance with mean Dice similarity coefficients of 94.39% and 87.21% for segmentations of 5 vertebral bodies and 5 intervertebral discs on the in-house and public datasets respectively.

An association study on the risk, glucocorticoids effectiveness, and prognosis of systemic lupus erythematosus: insight from mitochondrial DNA copy number.

This study aimed to explore the role of mitochondrial DNA copy number (mtDNAcn) in the risk, glucocorticoid (GC) effectiveness, and prognosis of systemic lupus erythematosus (SLE) and its interactions with environmental factors and tumor necrosis factor receptor-associated protein 1 (TRAP1) genetic polymorphisms. We first conducted a case-control study of 1198 subjects (595 SLE patients and 603 healthy controls). Subsequently, we followed up with patients to assess the effectiveness of GC treatment and the prognosis of SLE. Real-time fluorescent quantitative PCR (qPCR) was used to quantify mtDNAcn. Associations were estimated using logistic regression, and prognosis analysis was performed using Kaplan-Meier analysis and Cox proportional hazards models. Interactions on multiplicative and additive scales were also evaluated. Individuals with low mtDNAcn had an increased risk of SLE (P < 0.001). Low mtDNAcn was associated with poor GC effectiveness in patients with spicy food consumption or with arthritis (P < 0.05). mtDNAcn was significantly related to the prognosis of SLE in the drinking subgroup (P = 0.018). Furthermore, we found significant interactions between mtDNAcn and environmental factors/TRAP1 genetic polymorphisms on the risk, GC effectiveness, and prognosis of SLE. Our data suggest that low mtDNAcn is associated with an increased risk of SLE. Alteration of mtDNAcn may be associated with GC effectiveness and prognosis in certain subgroups of SLE. The interactions between mtDNAcn, environmental factors, and TRAP1 gene polymorphisms may jointly affect the risk, GC effectiveness, and prognosis of SLE.

Synergistic effect of sarcopenia and poor balance on osteoporotic vertebral fracture in Chinese patients with rheumatoid arthritis.

OBJECTIVES: This study aimed to investigate the synergistic effect of sarcopenia and poor balance on osteoporotic vertebral fracture (VOPF) in Chinese patients with rheumatoid arthritis (RA). METHODS: A total of 238 RA patients and 158 normal subjects were enrolled in the case-control study. Poor balance capability (Berg balance scale (BBS) score < 40) and sarcopenia (skeletal muscle mass index (SMI) <7.0 (male)/5.7 (female)) between RA patients and normal subjects were compared. Associations of poor balance capability or sarcopenia with disease activity, structural damage, and joint function in different groups were also investigated. RESULTS: The incidence of sarcopenia in RA was 58.4%, significantly higher than that in controls (P<0.0001). Moreover, the percentages of low balance capacity (BBS<40) in RA were 43.7%, which was higher than that in controls (P<0.0001). The prevalence of VOPF in the case group was 19.3%, which was higher than that in the controls (P<0.0001). In the RA group, compared to RA patients without VOPF, RA patients with VOPF had higher percentages of poor balance and sarcopenia (P<0.05). Compared with RA patients without sarcopenia or good balance, RA patients with sarcopenia or poor balance had a higher incidence of VOPF, higher disease activity, severer structural damage, and worse joint function (P<0.05). The incidence of VOPF in patients combined with good balance and non-sarcopenia (4.8%) was significantly lower than that in patients combined with poor balance and sarcopenia (38.2%) (P<0.0001). Logistic regression indicated that higher SMI and higher BBS scores were protective factors for VOPF in RA patients, while age was a risk factor for VOPF in RA patients (P<0.0001). CONCLUSION: Sarcopenia and poor balance are popular in Chinese patients with RA, and they are associated with disease activity and structural damage. There is a synergistic effect of sarcopenia and poor balance on VOPF in RA. Key Points • Sarcopenia and balance capability were popular (about a half) in patients with RA. • Sarcopenia and poor balance had a synergistic effect on VOPF in RA.

SpineParseNet: Spine Parsing for Volumetric MR Image by a Two-Stage Segmentation Framework With Semantic Image Representation.

Spine parsing (i.e., multi-class segmentation of vertebrae and intervertebral discs (IVDs)) for volumetric magnetic resonance (MR) image plays a significant role in various spinal disease diagnoses and treatments of spine disorders, yet is still a challenge due to the inter-class similarity and intra-class variation of spine images. Existing fully convolutional network based methods failed to explicitly exploit the dependencies between different spinal structures. In this article, we propose a novel two-stage framework named SpineParseNet to achieve automated spine parsing for volumetric MR images. The SpineParseNet consists of a 3D graph convolutional segmentation network (GCSN) for 3D coarse segmentation and a 2D residual U-Net (ResUNet) for 2D segmentation refinement. In 3D GCSN, region pooling is employed to project the image representation to graph representation, in which each node representation denotes a specific spinal structure. The adjacency matrix of the graph is designed according to the connection of spinal structures. The graph representation is evolved by graph convolutions. Subsequently, the proposed region unpooling module re-projects the evolved graph representation to a semantic image representation, which facilitates the 3D GCSN to generate reliable coarse segmentation. Finally, the 2D ResUNet refines the segmentation. Experiments on T2-weighted volumetric MR images of 215 subjects show that SpineParseNet achieves impressive performance with mean Dice similarity coefficients of 87.32 ± 4.75%, 87.78 ± 4.64%, and 87.49 ± 3.81% for the segmentations of 10 vertebrae, 9 IVDs, and all 19 spinal structures respectively. The proposed method has great potential in clinical spinal disease diagnoses and treatments.

Taxus wallichiana var. chinensis (Pilg.) Florin Aqueous Extract Suppresses the Proliferation and Metastasis in Lung Carcinoma via JAK/STAT3 Signaling Pathway.

As one of the most common neoplasms globally, lung cancer (LC) is the leading cause of cancer-related mortality. Recurrence and metastasis negatively influencing therapeutic efficacy and overall survival demand new strategies in LC treatment. The advantages of TCM are increasingly highlighted. In this study, we obtained the major chemical components and their ratios in the aqueous extract of Taxus wallichiana var. chinensis (Pilg.) Florin (AETW) by UPLC-Q/TOF-MS/MS detection. The CCK-8 assay revealed that AETW could selectively inhibit the growth of A549 and HCC827 cells in a dose-dependent manner with little effect on normal human lung cells. Moreover, both in vitro and in vivo experiments showed that AETW was able to suppress the capacities of cell migration and invasion and downregulate the EMT and the JAK/STAT3 signaling pathway. To further probe into the molecular mechanism, the overexpression of STAT3 was performed into LC cells with AETW treatment, which counteracted the inhibitory effect on malignant behaviors of A549 and HCC827 cells with the decline in the expressions of p-JAK and p-STAT3. Taken together, we propose that AETW may inhibit the proliferation and metastasis by inactivating the JAK/STAT3 axis.

Associations of FKBP4 and FKBP5 gene polymorphisms with disease susceptibility, glucocorticoid efficacy, anxiety, depression, and health-related quality of life in systemic lupus erythematosus patients.

OBJECTIVES: To explore the associations of FKBP4 and FKBP5 gene polymorphisms with disease susceptibility, glucocorticoid (GC) efficacy, anxiety, depression, and health-related quality of life (HRQOL) in systemic lupus erythematosus (SLE) patients. METHODS: All subjects were collected from the First and the Second Affiliated Hospital of Anhui Medical University in Hefei, China, during 2011 to 2015. In the case-control study, 541 SLE patients and 543 controls were recruited. In the follow-up study, 466 patients completed the 12-week follow-up and then were divided into GC-sensitive and GC-insensitive groups. Genotyping was determined using Multiplex SNaPshot technique. Data were analyzed using chi-square test and univariate and multivariate logistic regression analyses. RESULTS: rs4713904, rs9368878, and rs7757037 of FKBP5 were associated with depression in SLE patients (rs4713904, PBH = 0.037; rs9368878, PBH = 0.001; rs7757037, PBH = 0.003). Moreover, rs4713904 was associated with GC efficacy in males with SLE (PBH = 0.011). The rs755658 of FKBP5 was associated with improvement in social function (PBH = 0.022) and mental component summary (PBH = 0.028). The rs4713907 of FKBP5 was related to improvement in total score of SF-36, bodily pain, and mental component summary score (all PBH = 0.018). Furthermore, the rs12582595 of FKBP4 was correlated with general health improvement (PBH = 0.033). No associations were seen between FKBP4/FKBP5 gene polymorphisms and SLE susceptibility and anxiety. CONCLUSIONS: FKBP5 gene polymorphisms may be associated with depression and GC efficacy of SLE patients. Meanwhile, the genetic polymorphisms of FKBP4 and FKBP5 genes may be associated with HRQOL improvement in SLE patients. Key Points • FKBP5 gene polymorphisms were associated with depression of SLE patients. • FKBP5 gene polymorphisms were associated with GC efficacy of SLE patients. • FKBP5 gene polymorphisms were associated with HRQOL improvement in SLE patients. • FKBP4 gene polymorphisms were associated with HRQOL improvement in SLE patients.