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Abstract The pathogenesis of breast cancer is still unclear. Small RNAs associated with extracellular vesicles (EVs) have been found to be involved in tumor development. It is important to explore the role of EVs small RNAs in breast cancer. In this study, we established a plasma EVS-associated small RNA dataset that included 120 women who were positive for breast cancer screening and 60 women who were negative. These small RNA included 2656 miRNAs, 728 piRNAs, and 154 tsRNAs. These data provide a reference for researchers to explore molecular diagnostic biomarkers for early breast lesions.

Abstract Elevated triglycerides (TG) are a risk factor for cardiometabolic disorders. There are limited data on lipidomics profiles associated with serum triglycerides concentrations, although these could advance our understanding of the mechanisms underlying these associations. We conducted a lipidomics study of 308 Nigerians with replication in 199 Kenyans. Regression models were used to assess the association of TG with 480 lipid metabolites. Association and mediation analyses were conducted to determine the relationship among TG, metabolites, and several cardiometabolic traits. Ninety-nine metabolites were significantly associated with TG, and 91% of these associations replicated. Overrepresentation analysis identified enrichment of diacylglycerols, monoacylglycerols, diacylglycerophosphoethanolamines, monoacylglycerophosphocholines, ceramide phosphocholines, and diacylglycerophosphocholines. TG-cardiometabolic trait associations were largely mediated by TG-associated metabolites. Associations with type 2 diabetes, waist circumference, body mass index, total cholesterol, and low-density lipoprotein cholesterol concentration were independently mediated by metabolites in multiple subpathways. This lipidomics study in sub-Saharan Africans demonstrated that TG is associated with several non-TG lipids classes, including phosphatidylethanolamines, phosphatidylcholines, lysophospholipids, and plasmalogens, some of which may mediate the effect of TG as a risk factor for cardiometabolic disorders. The study identifies metabolites that are more proximal to cardiometabolic traits, which may be useful for understanding the underlying biology as well as differences in TG-trait associations across ancestries.

Abstract Electrospray deposition (ESD) is a promising technique for depositing micro-/nano-scale droplets and particles with high quality and repeatability. It is particularly attractive for surface coating of costly and delicate biomaterials and bioactive compounds. While high efficiency of ESD has only been successfully demonstrated for spraying surfaces larger than the spray plume, this work extends its utility to smaller surfaces. It is shown that by architecting the local “charge landscape”, ESD coatings of surfaces smaller than plume size can be achieved. Efficiency approaching 100% is demonstrated with multiple model materials, including biocompatible polymers, proteins, and bioactive small molecules, on both flat and microneedle array targets. UV-visible spectroscopy and high-performance liquid chromatography measurements validate the high efficiency and quality of the sprayed material. Here, we show how this process is an efficient and more competitive alternative to other conformal coating mechanisms, such as dip coating or inkjet printing, for micro-engineered applications.

Simulated data play an important role in SAR target recognition, particularly under zero-shot learning (ZSL) conditions caused by the lack of training samples. The traditional SAR simulation method is based on manually constructing target 3D models for electromagnetic simulation, which is costly and limited by the target’s prior knowledge base. Also, the unavoidable discrepancy between simulated SAR and measured SAR makes the traditional simulation method more limited for target recognition. This paper proposes an innovative SAR simulation method based on a visual language model and generative diffusion model by extracting target semantic information from optical remote sensing images and transforming it into a 3D model for SAR simulation to address the challenge of SAR target recognition under ZSL conditions. Additionally, to reduce the domain shift between the simulated domain and the measured domain, we propose a domain adaptation method based on dynamic weight domain loss and classification loss. The effectiveness of semantic information-based 3D models has been validated on the MSTAR dataset and the feasibility of the proposed framework has been validated on the self-built civilian vehicle dataset. The experimental results demonstrate that the first proposed SAR simulation method based on a visual language model and generative diffusion model can effectively improve target recognition performance under ZSL conditions.

Summary: While insulin resistance (IR) is associated with inflammation in white adipose tissue, we report a non-inflammatory adipose mechanism of high fat-induced IR mediated by loss of Pref-1. Pref-1, released from adipose Pref-1+ cells with characteristics of M2 macrophages, endothelial cells or progenitors, inhibits MIF release from both Pref-1+ cells and adipocytes by binding with integrin β1 and inhibiting the mobilization of p115. High palmitic acid induces PAR2 expression in Pref-1+ cells, downregulating Pref-1 expression and release in an AMPK-dependent manner. The loss of Pref-1 increases adipose MIF secretion contributing to non-inflammatory IR in obesity. Treatment with Pref-1 blunts the increase in circulating plasma MIF levels and subsequent IR induced by a high palmitic acid diet. Thus, high levels of fatty acids suppress Pref-1 expression and secretion, through increased activation of PAR2, resulting in an increase in MIF secretion and a non-inflammatory adipose mechanism of IR.

Optical and SAR image registration is the primary procedure to exploit the complementary information from the two different image modal types. Although extensive research has been conducted to narrow down the vast radiometric and geometric gaps so as to extract homogeneous characters for feature point matching, few works have considered the registration issue for non-flat terrains, which will bring in more difficulties for not only sparse feature point matching but also outlier removal and geometric relationship estimation. This article addresses these issues with a novel and effective optical-SAR image registration framework. Firstly, sparse feature points are detected based on the phase congruency moment map of the textureless SAR image (SAR-PC-Moment), which helps to identify salient local regions. Then a template matching process using very large local image patches is conducted, which increases the matching accuracy by a significant margin. Secondly, a mutual verification-based initial outlier removal method is proposed, which takes advantage of the different mechanisms of sparse and dense matching and requires no geometric consistency assumption within the inliers. These two procedures will produce a putative correspondence feature point (CP) set with a low outlier ratio and high reliability. In the third step, the putative CPs are used to segment the large input image of non-flat terrain into dozens of locally flat areas using a recursive random sample consensus (RANSAC) method, with each locally flat area co-registered using an affine transformation. As for the mountainous areas with sharp elevation variations, anchor CPs are first identified, and then optical flow-based pixelwise dense matching is conducted. In the experimental section, ablation studies using four precisely co-registered optical-SAR image pairs of flat terrain quantitatively verify the effectiveness of the proposed SAR-PC-Moment-based feature point detector, big template matching strategy, and mutual verification-based outlier removal method. Registration results on four 1 m-resolution non-flat image pairs prove that the proposed framework is able to produce robust and quite accurate registration results.

The development of specific anti-cytokine/chemokine therapeutic strategies for atherosclerotic disease is challenging. Here, the authors have designed a peptide-based ectodomain mimic of the chemokine receptor CXCR4 that selectively targets MIF but not CXCL12 and blocks experimental atherosclerosis in vivo.

Change detection (CD) with heterogeneous images is currently attracting extensive attention in remote sensing. In order to make heterogeneous images comparable, the image transformation methods transform one image into the domain of another image, which can simultaneously obtain a forward difference map (FDM) and backward difference map (BDM). However, previous methods only fuse the FDM and BDM in the post-processing stage, which cannot fundamentally improve the performance of CD. In this paper, a change alignment-based change detection (CACD) framework for unsupervised heterogeneous CD is proposed to deeply utilize the complementary information of the FDM and BDM in the image transformation process, which enhances the effect of domain transformation, thus improving CD performance. To reduce the dependence of the transformation network on labeled samples, we propose a graph structure-based strategy of generating prior masks to guide the network, which can reduce the influence of changing regions on the transformation network in an unsupervised way. More importantly, based on the fact that the FDM and BDM are representing the same change event, we perform change alignment during the image transformation, which can enhance the image transformation effect and enable FDM and BDM to effectively indicate the real change region. Comparative experiments are conducted with six state-of-the-art methods on five heterogeneous CD datasets, showing that the proposed CACD achieves the best performance with an average overall accuracy (OA) of 95.9% on different datasets and at least 6.8% improvement in the kappa coefficient.

Change detection using heterogeneous remote sensing images is an increasingly interesting and very challenging topic. To make the heterogeneous images comparable, some graph-based methods have been proposed, which first construct a graph for the image to capture the structure information and then use the graph to obtain the structural changes between images. Nonetheless, previous graph-based change detection approaches are insufficient in representing and exploiting the image structure. To address these issues, in this paper, we propose an auto-weighted structured graph (AWSG)-based regression method for heterogeneous change detection, which mainly consists of two processes: learning the AWSG to capture the image structure and using the AWSG to perform structure regression to detect changes. In the graph learning process, a self-conducted weighting strategy is employed to make the graph more robust, and the local and global structure information are combined to make the graph more informative. In the structure regression process, we transform one image to the domain of the other image by using the learned AWSG, where the high-order neighbor information hidden in the graph is exploited to obtain a better regression image and change image. Experimental results and comparisons on four real datasets with seven state-of-the-art methods demonstrate the effectiveness of the proposed approach.

BackgroundActivation of intravesical protease activated receptor 4 (PAR4) leads to release of urothelial macrophage migration inhibitory factor (MIF). MIF then binds to urothelial MIF receptors to release urothelial high mobility group box-1 (HMGB1) and elicit bladder hyperalgesia. Since MIF binds to multiple receptors, we investigated the contribution of individual urothelial MIF receptors to PAR4-induced HMGB1 release in vivo and in vitro and bladder pain in vivo.Methodology/principal findingsWe tested the effect of intravesical pre-treatment with individual MIF or MIF receptor (CD74, CXCR4, CXCR2) antagonists on PAR4-induced HMGB1 release in vivo (female C57/BL6 mice) and in vitro (primary human urothelial cells) and on PAR4-induced bladder hyperalgesia in vivo (mice). In mice, PAR4 induced HMGB1 release and bladder hyperalgesia through activation of intravesical MIF receptors, CD74 and CXCR4. CXCR2 was not involved in these effects. In primary urothelial cells, PAR4-induced HMGB1 release through activation of CD74 receptors. Micturition parameters in mice were not changed by any of the treatments.Conclusions/significanceUrothelial MIF receptors CD74 and CXCR4 mediate bladder pain through release of urothelial HMGB1. This mechanism may set up persistent pain loops in the bladder and warrants further investigation. Urothelial CD74 and CXCR4 may provide novel targets for interrupting bladder pain.

PurposeThe aim of this study was to assess the impact of cataract progression using the Haigis formula-calculated intraocular lens (IOL) power and investigate the accuracy of IOL power measured at different time points.MethodsThis prospective study was performed on 75 eyes of 75 patients who underwent uneventful cataract surgery. Preoperative ocular parameters including axial length (AL), keratometry (K), anterior chamber depth (ACD), corneal astigmatism, corrected distance visual acuity (CDVA) and uncorrected distance visual acuity (UDVA) examined at the two time points, more than 3 months preoperatively and preoperative 1 day were compared. The ocular parameters measured in the two time points were used to calculate the predicted implanted IOL power and the actual IOL power was chosen on the basis of parameters measured earlier before surgery using the Haigis formula. The mean numerical error (MNE) and mean absolute error (MAE) predicted by the two time points were also compared.ResultsThere were significant differences in the ACD, IOL power, UDVA and CDVA (P0.05) during the average of 5.6 months before surgery. No statistically significant difference was detected in MNE (P>0.05), while the MAE had a significant difference in the two time points (PConclusionThe IOL power measured earlier before surgery might result in a higher accuracy and the postoperative refractive outcome tended towards emmetropia.

Broadly neutralizing antibodies targeting HIV Env could potentially be utilized as therapeutics. Here, Steinhardt et al. engineer a trispecific antibody with specificity for the receptor-binding site, a conserved Env glycan patch and the Env membrane proximal region with nearly pan-isolate neutralization breadth and high potency.

Synthetic aperture radar (SAR) can perform observations at all times and has been widely used in the military field. Deep neural network (DNN)-based SAR target recognition models have achieved great success in recent years. Yet, the adversarial robustness of these models has received far less academic attention in the remote sensing community. In this article, we first present a comprehensive adversarial robustness evaluation framework for DNN-based SAR target recognition. Both data-oriented metrics and model-oriented metrics have been used to fully assess the recognition performance under adversarial scenarios. Adversarial training is currently one of the most successful methods to improve the adversarial robustness of DNN models. However, it requires class labels to generate adversarial attacks and suffers significant accuracy dropping on testing data. To address these problems, we introduced adversarial self-supervised learning into SAR target recognition for the first time and proposed a novel unsupervised adversarial contrastive learning-based defense method. Specifically, we utilize a contrastive learning framework to train a robust DNN with unlabeled data, which aims to maximize the similarity of representations between a random augmentation of a SAR image and its unsupervised adversarial example. Extensive experiments on two SAR image datasets demonstrate that defenses based on adversarial self-supervised learning can obtain comparable robust accuracy over state-of-the-art supervised adversarial learning methods.

Remote sensing image scene classification (RSISC) has broad application prospects, but related challenges still exist and urgently need to be addressed. One of the most important challenges is how to learn a strong discriminative scene representation. Recently, convolutional neural networks (CNNs) have shown great potential in RSISC due to their powerful feature learning ability; however, their performance may be restricted by the complexity of remote sensing images, such as spatial layout, varying scales, complex backgrounds, category diversity, etc. In this paper, we propose an attention-guided multilayer feature aggregation network (AGMFA-Net) that attempts to improve the scene classification performance by effectively aggregating features from different layers. Specifically, to reduce the discrepancies between different layers, we employed the channel–spatial attention on multiple high-level convolutional feature maps to capture more accurately semantic regions that correspond to the content of the given scene. Then, we utilized the learned semantic regions as guidance to aggregate the valuable information from multilayer convolutional features, so as to achieve stronger scene features for classification. Experimental results on three remote sensing scene datasets indicated that our approach achieved competitive classification performance in comparison to the baselines and other state-of-the-art methods.

CD74 is a multifunctional protein and a receptor for Macrophage Migration Inhibitory Factor (MIF) and MIF-2 / D-dopachrome tautomerase (DDT) cytokines, upregulated in diabetic kidney disease. However, the drivers of CD74 expression and DDT function in kidney cells are poorly characterized. TWEAK is a proinflammatory cytokine that promotes kidney injury. We have now identified CD74 gene expression as upregulated in the kidneys in response to systemic TWEAK administration in mice, and have characterized the in vivo CD74 expression and the functional consequences in cultured cells. TWEAK administration to mice resulted in a progressive time-dependent (up to 24h) upregulation of kidney CD74 mRNA (RT-PCR) and protein (Western blot). Furthermore, the CD74 ligands MIF and DDT were also upregulated at the protein level 24h after TWEAK administration. Immunohistochemistry localized the increased CD74, MIF and DDT expression to tubular cells. In cultured tubular cells, TWEAK increased CD74 mRNA and protein expression dose-dependently, with a temporal pattern similar to in vivo. TWEAK-induced CD74 localized to the cell membrane, where it can function as a cytokine receptor. For the first time, we explored the actions of DDT in tubular cells and found that DDT amplified the increase in MCP-1 and RANTES expression in response to TWEAK. By contrast, DDT did not significantly modify TWEAK-induced Klotho downregulation. In conclusion, TWEAK upregulates CD74 and its ligands MIF and DDT in renal tubular cells. This may have functional consequences for kidney injury since DDT amplified the inflammatory response to TWEAK.

Nutrients related to one-carbon metabolism were previously shown to be significantly associated with the risk of cancer. The aim of this meta-analysis was to evaluate potential relationships between one-carbon metabolic factors and renal cell cancer (RCC) risk.PubMed, EMBASE, and Cochrane Library databases were searched through March 2015 for observational studies of quantitative RCC risk estimates in relation to one-carbon metabolic factors. The relative risks (RRs) with 95% confidence intervals (CIs) measured the relationship between one-carbon metabolic factors and RCC risk using a random-effects model.Of the 463 citations and abstracts identified by database search, seven cohorts from five observational studies reported data on 133,995 individuals, and included 2,441 RCC cases. Comparing the highest with the lowest category, the pooled RRs of RCC were 0.72 (95%CI: 0.52-1.00; P = 0.048) for vitamin B12. In addition, an increase in folic acid supplementation of 100 μg/day was associated with a 3% lower risk of RCC (RR, 0.97; 95%CI: 0.93-1.00; P = 0.048). Similarly, an increase of 5 nmol/L of vitamin B2 was associated with a reduced risk of RCC 0.94 (95%CI: 0.89-1.00; P = 0.045). Sensitivity analyses suggested that a higher serum vitamin B6 might contribute to a reduced risk of RCC (RR, 0.83; 95%CI: 0.77-0.89; P < 0.001).Higher levels of serum vitamin B2, B6, B12, and folic acid supplementation lowered the risk of RCC among the study participants.

Vehicle detection with orientation estimation in aerial images has received widespread interest as it is important for intelligent traffic management. This is a challenging task, not only because of the complex background and relatively small size of the target, but also the various orientations of vehicles in aerial images captured from the top view. The existing methods for oriented vehicle detection need several post-processing steps to generate final detection results with orientation, which are not efficient enough. Moreover, they can only get discrete orientation information for each target. In this paper, we present an end-to-end single convolutional neural network to generate arbitrarily-oriented detection results directly. Our approach, named Oriented_SSD (Single Shot MultiBox Detector, SSD), uses a set of default boxes with various scales on each feature map location to produce detection bounding boxes. Meanwhile, offsets are predicted for each default box to better match the object shape, which contain the angle parameter for oriented bounding boxes’ generation. Evaluation results on the public DLR Vehicle Aerial dataset and Vehicle Detection in Aerial Imagery (VEDAI) dataset demonstrate that our method can detect both the location and orientation of the vehicle with high accuracy and fast speed. For test images in the DLR Vehicle Aerial dataset with a size of 5616 × 3744 , our method achieves 76.1% average precision (AP) and 78.7% correct direction classification at 5.17 s on an NVIDIA GTX-1060.

OBJECTIVE: To investigate the construct and criterion validity of the Euro Qol-5D (EQ-5D), which allows quality-adjusted life-years to be calculated, in patients with systemic lupus erythematosus (SLE). METHODS: Consecutive SLE patients who had been followed at the Renji Hospital, School of Medicine, Shanghai Jiao Tong University were recruited. Cross-sectional correlations of the EQ-5D with equivalent domains in disease-specific health-related quality of life (HRQoL), LupusQol, Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) measures, the Systemic Lupus International Collaborating Clinics Damage Index (SDI), and patient characteristics were tested. Discriminant validity to assess the ability to distinguish between patients of different disease severity was assessed. There also were evaluations of ceiling and floor effects. RESULTS: 240 patients were recruited in total. The EQ-5D correlated moderately to strongly with all domains of the LupusQoL (r: 0.44-0.7) apart from intimate relationships (r = 0.25) and body image (r = 0.18). There was moderate negative correlation between EQ-5D and clinical assessment of disease, SLEDAI (r = -0.589) and SDI (r = -0.509). When compared with equivalent domains on LupusQoL, there was good construct validity in EQ-5D (r: 0.631-0.812). EQ-5D could also discriminate patients with varied disease severity (according SLEDAI and SDI). There was no floor effect in EQ-5D but the ceiling effect remains strong (34%). CONCLUSION: Our results provide sufficient evidence that the EQ-5D displays construct and criterion validity for use in SLE patients. Disease-specific measures of HRQoL used alongside may be a better choice.

PURPOSE: To evaluate the repeatability, reproducibility, and agreement of thickness profile measurements of eight intra-retinal layers determined by an automated algorithm applied to optical coherence tomography (OCT) images from two different instruments. METHODS: Twenty normal subjects (12 males, 8 females; 24 to 32 years old) were enrolled. Imaging was performed with a custom built ultra-high resolution OCT instrument (UHR-OCT, ∼3 µm resolution) and a commercial RTVue100 OCT (∼5 µm resolution) instrument. An automated algorithm was developed to segment the macular retina into eight layers and quantitate the thickness of each layer. The right eye of each subject was imaged two times by the first examiner using each instrument to assess intra-observer repeatability and once by the second examiner to assess inter-observer reproducibility. The intraclass correlation coefficient (ICC) and coefficients of repeatability and reproducibility (COR) were analyzed to evaluate the reliability. RESULTS: The ICCs for the intra-observer repeatability and inter-observer reproducibility of both SD-OCT instruments were greater than 0.945 for the total retina and all intra-retinal layers, except the photoreceptor inner segments, which ranged from 0.051 to 0.643, and the outer segments, which ranged from 0.709 to 0.959. The CORs were less than 6.73% for the total retina and all intra-retinal layers. The total retinal thickness measured by the UHR-OCT was significantly thinner than that measured by the RTVue100. However, the ICC for agreement of the thickness profiles between UHR-OCT and RTVue OCT were greater than 0.80 except for the inner segment and outer segment layers. CONCLUSIONS: Thickness measurements of the intra-retinal layers determined by the automated algorithm are reliable when applied to images acquired by the UHR-OCT and RTVue100 instruments.

To determine the biometry of anterior segment dimensions of the human eye on both horizontal and vertical meridians with extended scan depth optical coherence tomography (OCT) during accommodation.Twenty pre-presbyopic volunteers, aged between 24 and 30, were recruited. The ocular anterior segment of each subject was imaged using an extended scan depth OCT under non- and 3.0 diopters (D) of accommodative demands on both horizontal and vertical meridians. All the images were analyzed to yield the following parameters: pupil diameter (PD), anterior chamber depth (ACD), anterior and posterior surface curvatures of the crystalline lens (ASC and PSC) and the lens thickness (LT). Two consecutive measurements were performed to assess the repeatability and reproducibility of this OCT. They were evaluated by calculating the within-subject standard deviation (SD), a paired t-test, intra-class correlation coefficients (ICC) and the coefficient of repeatability/reproducibility (CoR).There were no significant differences between two consecutive measurements on either horizontal or vertical meridians under both two different accommodative statuses (P>0.05). The ICC for all parameters ranged from 0.775 to 0.998, except for the PSC (0.550) on the horizontal meridian under the non-accommodative status. In addition, the CoR for most of the parameters were excellent (0.004% to 4.89%). In all the parameters, only PD and PSC were found different between the horizontal and vertical meridians under both accommodative statuses (P

OBJECTIVE: To evaluate the psychometric properties and clinical utility of Chinese Multidimensional Health Assessment Questionnaire (MDHAQ-C) in patients with rheumatoid arthritis (RA) in China. METHODS: 162 RA patients were recruited in the evaluation process. The reliability of the questionnaire was tested by internal consistency and item analysis. Convergent validity was assessed by correlations of MDHAQ-C with Health Assessment Questionnaire (HAQ), the 36-item Short-Form Health Survey (SF-36) and the Hospital anxiety and depression scales (HAD). Discriminant validity was tested in groups of patients with varied disease activities and functional classes. To evaluate the clinical values, correlations were calculated between MDHAQ-C and indices of clinical relevance and disease activity. Agreement with the Disease Activity Score (DAS28) and Clinical Disease Activity Index (CDAI) was estimated. RESULTS: The Cronbach's alpha was 0.944 in the Function scale (FN) and 0.768 in the scale of psychological status (PS). The item analysis indicated all the items of FN and PS are correlated at an acceptable level. MDHAQ-C correlated with the questionnaires significantly in most scales and scores of scales differed significantly in groups of different disease activity and functional status. MDHAQ-C has moderate to high correlation with most clinical indices and high correlation with a spearman coefficient of 0.701 for DAS 28 and 0.843 for CDAI. The overall agreement of categories was satisfying. CONCLUSION: MDHAQ-C is a reliable, valid instrument for functional measurement and a feasible, informative quantitative index for busy clinical settings in Chinese RA patients.

If equipped with several radar emitters, a target will produce more than one measurement per time step and is denoted as an extended target. However, due to the requirement of all possible measurement set partitions, the exact probability hypothesis density filter for extended target tracking is computationally intractable. To reduce the computational burden, a fast partitioning algorithm based on hierarchy clustering is proposed in this paper. It combines the two most similar cells to obtain new partitions step by step. The pseudo-likelihoods in the Gaussian-mixture probability hypothesis density filter can then be computed iteratively. Furthermore, considering the additional measurement information from the emitter target, the signal feature is also used in partitioning the measurement set to improve the tracking performance. The simulation results show that the proposed method can perform better with lower computational complexity in scenarios with different clutter densities.

OBJECTIVES: To adapt and assess the validity and reliability of LupusQoL for use in Chinese patients with systemic lupus erythematosus (SLE). METHODS: Debriefing interviews of subjects with SLE guided the language modifications of the tool. The process of adaptation proceeded according to the guideline and pre-testing results of LupusQoL-China. 220 SLE patients completed LupusQoL-China and a generic preference-based measurement of health EuroQoL scale (EQ-5D), and 20 patients repeated them after 2 weeks. Internal consistency (ICR) and test-retest (TRT) reliability, convergent and discriminant validity were examined. Factor analysis and Rasch analysis were performed. RESULTS: The mean (SD) age of the 208 subjects with SLE was 33.93 (± 9.19) years. ICR and TRT of the eight domains ranged from 0.811 to 0.965 and 0.836 to 0.974, respectively. The LupusQoL-China domains demonstrated substantial evidence of construct validity when compared with equivalent domains on the EQ-5D (physical health and usual activities r = -0.63, pain and pain/discomfort r = -0.778, emotional health and anxiety/depression r = -0.761, planning and usual activities r = -0.560). Most LupusQoL-China domains could discriminate patients with varied disease activities and end-organ damage (according to SELENA-SLEDAI and SLICC-DI). The principal component analysis revealed six factors, and confirmatory factor analysis result of which is similar to eight factors model. CONCLUSIONS: These results provide evidence that the LupusQoL-China is valid as a disease-specific HRQoL assessment tool for Chinese patients with SLE.

The role and mechanism of action of MIF in hyperoxia-induced acute lung injury (HALI) in the newborn lung are not known. We hypothesized that MIF is a critical regulatory molecule in HALI in the developing lung.We studied newborn wild type (WT), MIF knockout (MIFKO), and MIF lung transgenic (MIFTG) mice in room air and hyperoxia exposure for 7 postnatal (PN) days. Lung morphometry was performed and mRNA and protein expression of vascular mediators were analyzed.MIF mRNA and protein expression were significantly increased in WT lungs at PN7 of hyperoxia exposure. The pattern of expression of Angiopoietin 2 protein (in MIFKO>WT>MIFTG) was similar to the mortality pattern (MIFKO>WT>MIFTG) in hyperoxia at PN7. In room air, MIFKO and MIFTG had modest but significant increases in chord length, compared to WT. This was associated with decreased expression of Angiopoietin 1 and Tie 2 proteins in the MIFKO and MIFTG, as compared to the WT control lungs in room air. However, on hyperoxia exposure, while the chord length was increased from their respective room air controls, there were no differences between the 3 genotypes.These data point to the potential roles of Angiopoietins 1, 2 and their receptor Tie2 in the MIF-regulated response in room air and upon hyperoxia exposure in the neonatal lung.

Coronaviruses are a family of large positive-sense RNA viruses that are responsible for a wide range of important veterinary and human diseases. Nsp1 has been shown to have an important role in the pathogenetic mechanisms of coronaviruses in vivo. To assess the function of a relatively conserved domain (LLRKxGxKG) of MHV nsp1, a mutant virus, MHV-nsp1-27D, with a 27 nts (LLRKxGxKG) deletion in nsp1, was constructed using a reverse genetic system with a vaccinia virus vector. The mutant virus had similar growth kinetics to MHV-A59 wild-type virus in 17CI-1 cells, but was highly attenuated in vivo. Moreover, the mutant virus completely protected C57BL/6 mice from a lethal MHV-A59 challenge. To further analyze the mechanism of the attenuation of the mutant virus, changes in reporter gene expression were measured in nsp1- or nsp1-27D-expressing cells; the results showed that nsp1 inhibited reporter gene expression controlled by different promoters, but that this inhibition was reduced for nsp1-27D. The research in vivo and in vitro suggests that the LLRKxGxKG region of nsp1 may play an important role in this process.

Studies have revealed that catechol-O-methyltransferase (COMT) and dopaminegic receptor2 (DRD2) modulate human attention bias for palatable food or tobacco. However, the existing evidence about the modulations of COMT and DRD2 on attentional bias for facial expressions was still limited. In the study, 650 college students were genotyped with regard to COMT Val158Met and DRD2 TaqI A polymorphisms, and the attentional bias for facial expressions was assessed using the spatial cueing task. The results indicated that COMT Val158Met underpinned the individual difference in attentional bias for negative emotional expressions (P = 0.03) and the Met carriers showed more engagement bias for negative expressions than the Val/Val homozygote. On the contrary, DRD2 TaqIA underpinned the individual difference in attentional bias for positive expressions (P = 0.003) and individuals with TT genotype showed much more engagement bias for positive expressions than the individuals with CC genotype. Moreover, the two genes exerted significant interactions on the engagements for negative and positive expressions (P = 0.046, P = 0.005). These findings suggest that the individual differences in the attentional bias for emotional expressions are partially underpinned by the genetic polymorphisms in COMT and DRD2.

An increasing number of patients have medical conditions with altered host immunity or that require immunosuppressive medications. While immunosuppression is associated with increased risk of infection, the precise effect of immunosuppression on innate immunity is not well understood. We studied monocyte Toll-like receptor (TLR) expression and cytokine production in 137 patients with autoimmune diseases who were maintained on immunosuppressive medications and 419 non-immunosuppressed individuals.Human peripheral blood monocytes were assessed for surface expression of TLRs 1, 2, and 4. After incubation with TLR agonists, in vitro production of the cytokines IL-8, TNFalpha, and MIF were measured by ELISA as a measure of TLR signaling efficiency and downstream effector responsiveness. Immunosuppressed patients had significantly higher TLR4 surface expression when compared to non-immunosuppressed adults (TLR4 %-positive 70.12+/-2.28 vs. 61.72+/-2.05, p = 0.0008). IL-8 and TNF-alpha baseline levels did not differ, but were significantly higher in the autoimmune disease group following TLR stimulation. By contrast, baseline MIF levels were elevated in monocytes from immunosuppressed individuals. By multivariable analyses, IL-8 and TNFalpha, but not MIF levels, were associated with the diagnosis of an underlying autoimmune disease. However, only MIF levels were significantly associated with the use of immunosuppressive medications.Our results reveal that an enhanced innate immune response is a feature of patients with autoimmune diseases treated with immunosuppressive agents. The increased risk for infection evident in this patient group may reflect a dysregulation rather than a simple suppression of innate immunity.

Gprc5b, a retinoic acid-inducible orphan G protein-coupled receptor (GPCR), is a member of the group C metabotropic glutamate receptor family proteins possibly involved in non-canonical Wnt signaling. Many GPCR transcripts are alternatively spliced, which diversifies this class of proteins in their cell- and tissue-specific signaling, regulatory and/or pharmacological properties. We previously generated p97FE65 isoform-specific knockout mice that showed learning/memory deficits. In this study, we further characterized the 97FE65 null mice using cDNA microarray and RT-PCR analyses.We discovered a novel brain-specific C-terminal splice variant of Gprc5b, Gprc5b_v2, which was differentially expressed in p97FE65 wild type and null mouse brains. The null mice were generated in 129/Sv ES cells, and backcrossed to C57Bl/6J for ten generations. We found that expression of Gprc5b_v2 mRNA in the brains of p97FE65 null mice was dramatically down-regulated (more than 20 fold) compared to their wild type littermates. However, expression profiles of Gprc5b variants and SNP analysis surrounding the FE65 locus suggest that the down-regulation is unlikely due to the altered FE65 function, but rather is caused by gene retention from the 129/Sv ES cells. Consistently, in contrast to ubiquitously expressed Gprc5b_v1, Gprc5b_v2 was predominantly expressed in the brain tissues of C57Bl/6J mice. The alternative splicing of the 3' terminal exon also altered the protein coding sequences, giving rise to the characteristic C-termini. Levels of Gprc5b_v2 mRNA were increased during neuronal maturation, paralleling the expression of synaptic proteins. Overexpression of both Gprc5b variants stimulated neurite-like outgrowth in a neuroblastoma cell line.Our results suggest that Gprc5b-v2 may play a role during brain maturation and in matured brain, possibly through the regulation of neuronal morphology and protein-protein interaction. This study also highlights the fact that unexpected gene retention following repeated backcrosses can lead to important biological consequences.

Inflammation promotes granulopoiesis over B lymphopoiesis in the bone marrow (BM). We studied B cell homeostasis in two murine models of T cell mediated chronic inflammation, namely calreticulin-deficient fetal liver chimeras (FLC), which develop severe blepharitis and alopecia due to T cell hyper responsiveness, and inflammatory bowel disease (IBD) caused by injection of CD4(+) naïve T cells into lymphopenic mice. We show herein that despite the severe depletion of B cell progenitors during chronic, peripheral T cell-mediated inflammation, the population of BM mature recirculating B cells is unaffected. These B cells are poised to differentiate to plasma cells in response to blood borne pathogens, in an analogous fashion to non-recirculating marginal zone (MZ) B cells in the spleen. MZ B cells nevertheless differentiate more efficiently to plasma cells upon polyclonal stimulation by Toll-like receptor (TLR) ligands, and are depleted during chronic T cell mediated inflammation in vivo. The preservation of mature B cells in the BM is associated with increased concentration of macrophage migration inhibitory factor (MIF) in serum and BM plasma. MIF produced by perivascular dendritic cells (DC) in the BM provides a crucial survival signal for recirculating B cells, and mice treated with a MIF inhibitor during inflammation showed significantly reduced mature B cells in the BM. These data indicate that MIF secretion by perivascular DC may promote the survival of the recirculating B cell pool to ensure responsiveness to blood borne microbes despite loss of the MZ B cell pool that accompanies depressed lymphopoiesis during inflammation.