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PurposeUnderpinned by paradox theory, this study aims to investigate how and when intragroup cooperation and competition combine to drive individual creativity. It further examines how group goal orientation influences individuals’ creative processes by underscoring its effect on individuals' tendency to adopt a paradox lens.Design/methodology/approachA time-lagged survey was conducted with 85 leaders and 420 employees in Chinese high-tech companies that were actively engaged in innovative activities.FindingsThe results reveal that pure cooperation or pure competition exerts no significant influence on creativity, yet simultaneous high levels of cooperation and competition give rise to strong levels of creativity. This combined effect of cooperation and competition on employees' creativity could be explained by their changes in cognitive flexibility. Moreover, employees' flexible responses to high levels of cooperation and competition could be promoted when groups enact learning goals rather than performance goals.Originality/valueThis study provides a theoretical perspective on how cooperation and competition can be contingent upon each other. It also highlights the role of group learning goals when members strive to be creative in groups with high levels of competition and cooperation.

Aim: Older adult patients with nonmetastatic nasopharyngeal carcinoma (NPC) have poor outcomes relative to younger patients. The authors’ group established a nomogram to predict the overall survival of older adults with NPC and inform patient management. Methods: Cases with NPC (n = 782) were enrolled in this study; clinical data in the Surveillance, Epidemiology, and End Results database from 2010 to 2015 served as the training cohort (n = 657), and patients from Jiangxi Cancer Hospital (n = 125) served as the external validation cohort. Results: Training and external validation cohort C-index, receiver operator characteristics curves and calibration curves showed that our nomogram has great predictive ability. Conclusions: Compared with tumor-node-metastasis staging, this nomogram can help clinicians better predict the prognosis of older adults with nonmetastatic NPC.

It is well accepted that ultrasound-induced microbubble (USMB) cavitation is a promising method for drug delivery. Ultrasound-targeted destruction of cytotoxic drug-loaded lipid microbubbles (LMs) is used to promote the treatment of cancer. This study aimed to investigate the antitumor effects from combination of docetaxel-loaded cationic lipid microbubbles (DLLM+) and ultrasound (US)-triggered microbubble destruction (UTMD) on gastric cancer (GC). Here, the functional dose of DOC was identified as 1×10− 9 mol/L. We found that DLLM combined with UTMD group showed greater growth inhibition of the cultured human gastric cancer cells (HGCCs) when compared with other five groups by arresting the G2 / M phase in cell cycle. However, DLLM+ combined with UTMD showed a higher inhibition rate of tumor growth than DLLM combined with UTMD and that of the RC / CMV-p16 combined with UTMD in vitro and in vivo experiments. DLLM+ combined with UTMD significantly suppressed proliferation and promoted the apoptosis of HGCCs with more cells arrested in the G2 / M phase. In addition, DLLM+ combined with UTMD suppressed the proliferation and induced the apoptosis by arresting cells in the G2 / M phase, which leading to a great inhibition of GC progression. Thus, our results indicated that the combination of DLLM+ and UTMD might represent a novel and promising approach to chemotherapy for GC.

We consider the problem of abnormality localization for clinical applications. While deep learning has driven much recent progress in medical imaging, many clinical challenges are not fully addressed, limiting its broader usage. While recent methods report high diagnostic accuracies, physicians have concerns trusting these algorithm results for diagnostic decision-making purposes because of a general lack of algorithm decision reasoning and interpretability. One potential way to address this problem is to further train these models to localize abnormalities in addition to just classifying them. However, doing this accurately will require a large amount of disease localization annotations by clinical experts, a task that is prohibitively expensive to accomplish for most applications. In this work, we take a step towards addressing these issues by means of a new attention-driven weakly supervised algorithm comprising a hierarchical attention mining framework that unifies activation- and gradient-based visual attention in a holistic manner. Our key algorithmic innovations include the design of explicit ordinal attention constraints, enabling principled model training in a weakly-supervised fashion, while also facilitating the generation of visual-attention-driven model explanations by means of localization cues. On two large-scale chest X-ray datasets (NIH ChestX-ray14 and CheXpert), we demonstrate significant localization performance improvements over the current state of the art while also achieving competitive classification performance. Our code is available on https://github.com/oyxhust/HAM.

Background. Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients. Methods. The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics. Results. According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage. Conclusion. We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

PurposeThis study examined the dynamical and positive effects of leader consultation on employee proactivity from a motivational perspective.Design/methodology/approachSurvey data were collected twice a day from 107 employees in a week by using an experience sampling method.FindingsOn a daily basis, leader consultation had a positive effect on employees’ state work engagement, which in turn promoted employees’ proactivity. Moreover, authoritarian leadership weakened the positive relationship between leader consultation and employees’ state work engagement.Originality/valueThe findings provided a new perspective regarding the potential dynamic motivational effect of leader consultation on employees and generated interesting implications for paradoxical leadership theory.

This study investigates the firm size-innovation puzzle through distinguishing radical from incremental innovation, and examining the country-level context (i.e., university–industry collaboration in R&D and competition intensity) that the firm size-innovation relationship is contingent on. The meta-analysis including 162 studies with 112,639 firms reveals that firm size can simultaneously benefit for radical and incremental innovations, while the measurement of firm size using the non-personnel indices can result in significant difference between the firm size-radical innovation and firm size-incremental innovation. Additionally, it is found that the positive relationship between firm size and radical innovation increases when university–industry collaboration in R&D and competition intensity is stronger. This study quantitatively summarises the relationship between firm size and radical/incremental innovation and updates the correlations reported in established literatures. Drawing on awareness-motivation-capability perspective, it takes an essential and frontier step in testing the country-level context that can influence the effect of firm size on innovation.

Neolamarckia cadamba (Roxb.) Bosser is a fast-growing deciduous tree species and belongs to the Neolamarckia genus of the Rubiaceae family. This species has great economic and medical values in addition to being an important timber species for multiple industrial purposes. However, few studies have examined the genetic diversity and population structure in the natural distribution of this species in China. Here, we applied both the haploid nrDNA ITS (619 bp for aligned sequences) and mtDNA (2 polymorphic loci) markers to investigate 10 natural populations (239 individuals in total) that covered most of the distribution of the species in China. The results showed that the nucleotide diversity was π = 0.1185 ± 0.0242 for the nrDNA ITS markers and π = 0.00038 ± 0.00052 for the mtDNA markers. The haplotype diversity for the mtDNA markers was h = 0.1952 ± 0.2532. The population genetic differentiation was small (Fstn = 0.0294) for the nrDNA ITS markers but large (Fstm = 0.6765) for the mtDNA markers. There were no significant effects of isolation by distance (IBD), by elevation, and by two climatic factors (annual average precipitation and tem perature). A geographic structure among populations (Nst

When deep neural network (DNN) was first introduced to the medical image analysis community, researchers were impressed by its performance. However, it is evident now that a large number of manually labeled data is often a must to train a properly functioning DNN. This demand for supervision data and labels is a major bottleneck in current medical image analysis, since collecting a large number of annotations from experienced experts can be time-consuming and expensive. In this paper, we demonstrate that the eye movement of radiologists reading medical images can be a new form of supervision to train the DNN-based computer-aided diagnosis (CAD) system. Particularly, we record the tracks of the radiologists' gaze when they are reading images. The gaze information is processed and then used to supervise the DNN's attention via an Attention Consistency module. To the best of our knowledge, the above pipeline is among the earliest efforts to leverage expert eye movement for deep-learning-based CAD. We have conducted extensive experiments on knee X-ray images for osteoarthritis assessment. The results show that our method can achieve considerable improvement in diagnosis performance, with the help of gaze supervision.

The spontaneous pro-environmental behavior (PEB) of rural residents is essential for rural environmental governance. Existing studies have primarily focused on the impact of objective factors on individual PEB, while less attention has been paid to the role of subjective factors, such as rural residents’ subjective well-being, in shaping such behaviors. Based on the Chinese General Social Survey (CGSS) data, this study evaluates the impact of subjective well-being on the PEB of rural residents. The results show that subjective well-being significantly promoted the PEB in both the private sphere with reciprocity and the public sphere with altruistic attributes. Subjective well-being affected PEB mainly by enhancing rural residents’ social interaction and reciprocity with others and raising their fraternity and altruism. Moreover, the positive effect was mainly driven by women and individuals with more environmental knowledge. Therefore, enhancing rural residents’ subjective well-being is not only an important development goal, but also the starting point and foothold of solving the contradiction between economic development and environmental protection and promoting social harmony.

Background and purpose Non-alcoholic fatty liver disease (NAFLD) is a worldwide public health problem with no established pharmacological therapy. Here, we explored the potential benefit of P7C3-A20, a novel aminopropyl carbazole compound with neuroprotective activity, in a NAFLD model, induced in mice by a high-fat diet (HFD). Experimental approach C57BL/6J mice were given a HFD (42% fat content) for 16 weeks to induce NAFLD. P7C3-A20 (20 mg·kg-1 ·day-1 ) was given by gavage for 2 weeks. Indirect calorimetry, histological analysis, immunoblotting, immunohistochemistry, and biomedical examinations were performed. Gut microbiota were determined using a 16S ribosomal RNA sequencing analysis. Key results P7C3-A20 treatment reduced body weight gain/adiposity, improved insulin resistance, promoted energy expenditure (O2 consumption/CO2 production), inhibited lipid oxidation, suppressed hepatic inflammation (Kupffer cell number and pro-inflammatory factors), decreased necroptosis/apoptosis (receptor-interacting protein kinase 3, cleaved caspase-3, and TUNEL), and alleviated liver fibrosis and injury. Mechanistically, P7C3-A20 stimulated FGF21 and FGF1 via activating liver kinase B1 (LKB1) and AMP-activated protein kinase (AMPK), which further resulted in a reduced nuclear translocation of CREB-regulated transcription coactivator 2 (CRTC2). In AMPKα2 knockout mice, the protection of P7C3-A20 against HFD-induced metabolism abnormalities and fat accumulation, as well as the elevation of blood FGF21 and FGF1, was abolished. P7C3-A20 increased the gut microbiota species richness. Moreover, it enhanced the proportions of Akkermansia, Lactobacillus, and Prevotellaceae, while reducing the proportions of Enterobacteriaceae, Escherichia, and Parasutterella. Conclusions and implications P7C3-A20 increased levels of NAD+ and alleviated NAFLD through stimulating FGF21 and FGF1 in an LKB1/AMPK/CRTC2-dependent manner and shaping gut microbiota. Linked articles This article is part of a themed issue on Cellular metabolism and diseases. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.10/issuetoc.

Knee osteoarthritis (OA) is the most common osteoarthritis and a leading cause of disability. Cartilage defects are regarded as major manifestations of knee OA, which are visible by magnetic resonance imaging (MRI). Thus early detection and assessment for knee cartilage defects are important for protecting patients from knee OA. In this way, many attempts have been made on knee cartilage defect assessment by applying convolutional neural networks (CNNs) to knee MRI. However, the physiologic characteristics of the cartilage may hinder such efforts: the cartilage is a thin curved layer, implying that only a small portion of voxels in knee MRI can contribute to the cartilage defect assessment; heterogeneous scanning protocols further challenge the feasibility of the CNNs in clinical practice; the CNN-based knee cartilage evaluation results lack interpretability. To address these challenges, we model the cartilages structure and appearance from knee MRI into a graph representation, which is capable of handling highly diverse clinical data. Then, guided by the cartilage graph representation, we design a non-Euclidean deep learning network with the self-attention mechanism, to extract cartilage features in the local and global, and to derive the final assessment with a visualized result. Our comprehensive experiments show that the proposed method yields superior performance in knee cartilage defect assessment, plus its convenient 3D visualization for interpretability., Comment: 10 pages, 4 figures

Objective. To determine the long-term effects of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) over the contralesional M1 preceding motor task practice on the interhemispheric asymmetry of the cortical excitability and the functional recovery in subacute stroke patients with mild to moderate arm paresis. Methods. Twenty-four subacute stroke patients were randomly allocated to either the experimental or control group. The experimental group underwent rTMS over the contralesional M1 (1 Hz), immediately followed by 30 minutes of motor task practice (10 sessions within 2 weeks). The controls received sham rTMS and the same task practice. Following the 2-week intervention period, the task practice was continued twice weekly for another 10 weeks in both groups. Outcomes were evaluated at baseline (T0), at the end of the 2-week stimulation period (T1), and at 12-week follow-up (T2). Results. The MEP (paretic hand) and interhemispheric asymmetry, Fugl-Meyer motor assessment, Action Research Arm Test, and box and block test scores improved more in the experimental group than controls at T1 ( p < 0.05 ). The beneficial effects were largely maintained at T2. Conclusion. LF-rTMS over the contralesional M1 preceding motor task practice was effective in enhancing the ipsilesional cortical excitability and upper limb function with reducing interhemispheric asymmetry in subacute stroke patients with mild to moderate arm paresis. Significance. Adding LF-rTMS prior to motor task practice may reduce interhemispheric asymmetry of cortical excitabilities and promote upper limb function recovery in subacute stroke with mild to moderate arm paresis.

Lung nodule detection in chest X-ray (CXR) images is common to early screening of lung cancers. Deep-learning-based Computer-Assisted Diagnosis (CAD) systems can support radiologists for nodule screening in CXR images. However, it requires large-scale and diverse medical data with high-quality annotations to train such robust and accurate CADs. To alleviate the limited availability of such datasets, lung nodule synthesis methods are proposed for the sake of data augmentation. Nevertheless, previous methods lack the ability to generate nodules that are realistic with the shape/size attributes desired by the detector. To address this issue, we introduce a novel lung nodule synthesis framework in this paper, which decomposes nodule attributes into three main aspects including the shape, the size, and the texture, respectively. A GAN-based Shape Generator firstly models nodule shapes by generating diverse shape masks. The following Size Modulation then enables quantitative control on the diameters of the generated nodule shapes in pixel-level granularity. A coarse-to-fine gated convolutional Texture Generator finally synthesizes visually plausible nodule textures conditioned on the modulated shape masks. Moreover, we propose to synthesize nodule CXR images by controlling the disentangled nodule attributes for data augmentation, in order to better compensate for the nodules that are easily missed in the detection task. Our experiments demonstrate the enhanced image quality, diversity, and controllability of the proposed lung nodule synthesis framework. We also validate the effectiveness of our data augmentation strategy on greatly improving nodule detection performance.

Cavernous nerve injury (CNI) is the main cause of erectile dysfunction (ED) following pelvic surgery. Our previous studies have demonstrated that transplantation of different sources of mesenchymal stem cells (MSCs) was able to alleviate ED induced by CNI in rat models. However, little is known about the therapeutic effects of human gingiva-derived MSCs (hGMSCs) in CNI ED rats. Herein, we injected the hGMSCs around the bilateral major pelvic ganglia (MPG) in a rat model of CNI and evaluated their efficacy. The results showed that treatment of hGMSCs could significantly promote the recovery of erectile function, enhance smooth muscle and endothelial content, restore neuronal nitric oxide synthase (nNOS) expression, and attenuate cell apoptosis in penile tissue. Moreover, penile fibrosis was significantly alleviated after hGMSC administration. In addition, potential mechanism exploration indicated that hGMSCs might exert its functions via skewed macrophage polarity from M1 toward M2 anti-inflammatory phenotype. In conclusion, this study found that transplantation of hGMSCs significantly improved CNI-related ED, which might provide new clues to evaluate their pre-clinical application.

BACKGROUND Peritoneal dialysis is the most common treatment for end-stage renal disease. However, peritoneal fibrosis resulting from long-term peritoneal dialysis restricts peritoneal ultrafiltration. Previous studies have shown a role for 1,25-dihydroxyvitamin D3 (1,25[OH]₂D3) in preventing fibrosis, but the potential mechanisms remain unknown. This study aimed to investigate the role of 1,25(OH)₂D3 in epithelial-mesenchymal transition (EMT) and the downstream signaling pathway in HMrSV5 human peritoneal mesothelial cells in vitro. MATERIAL AND METHODS An in vitro cell model of peritoneal fibrosis was established using the HMrSV5 human peritoneal mesothelial cell line. High glucose and lipopolysaccharide (LPS) culture conditions, with or without 1,25(OH)₂D3, were used. Wnt agonist 1, a Wnt signaling pathway activator, was applied. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot were used to measure the vitamin D receptor (VDR) and histone deacetylase 3 (HDAC3) gene and protein expression levels, ß-catenin, and EMT-associated biomarkers. RESULTS High glucose plus LPS culture medium inhibited cell proliferation, induced cell apoptosis and promoted EMT in HMrSV5 cells, which was reversed by 1,25(OH)₂D3 by down-regulation of HDAC3 and upregulation of VDR. HDAC3 inhibited VDR gene expression. The expression of EMT-associated biomarkers was increased by Wnt agonist 1 and inhibited by 1,25(OH)₂D3. CONCLUSIONS In HMrSV5 human peritoneal mesothelial cells, 1,25(OH)₂D3 reversed EMT by inhibiting the expression of HDAC3 and upregulating VDR gene expression via the Wnt/ß-catenin signaling pathway.

Background Chronic kidney disease (CKD) has been considered as a major health problem in the world. Increasing uric acid (UA) could induce vascular endothelial injury, which is closely related to microinflammation, oxidative stress, and disorders of lipids metabolism. However, the specific mechanism that UA induces vascular endothelial cells injury in early CKD remains unknown. Methods Human umbilical vein endothelial cells (HUVECs) were cultured and subjected to different concentrations of UA for different periods. Early CKD rat model with elevated serum UA was established. Western blotting and quantitative real-time PCR (qPCR) were applied for measuring protein and mRNA expression of different cytokines. The animals were sacrificed and blood samples were collected for measurement of creatinine, UA, IL-1β, TNF-α, and ICAM-1. Renal tissues were pathologically examined by periodic acid-Schiff (PAS) or hematoxylin-eosin (HE) staining. Results The expression of IL-1β, ICAM-1, NLRP3 complexes, and activation of NLRP3 inflammasome could be induced by UA, but the changes induced by UA were partially reversed by siRNA NLRP3 or caspase 1 inhibitor. Furthermore, we identified that UA regulated the activation of NLRP3 inflammasome by activating ROS and K+ efflux. In vivo results showed that UA caused the vascular endothelial injury by activating NLRP3/IL-1β pathway. While allopurinol could reduce UA level and may have protective effects on cardiovascular system. Conclusions UA could regulate NLRP3/IL-1β signaling pathway through ROS activation and K+ efflux and further induce vascular endothelial cells injury in early stages of CKD.

Erectile dysfunction (ED) is an important kind of postoperative complication of pelvic surgery that affects patients' quality of life. Transplantation of mesenchymal stem cells (MSC) has been found to alleviate ED caused by cavernous nerve injury (CNI) in rats. However, little is known about whether induced pluripotent stem cell-derived mesenchymal stem cells (iMSC) have a therapeutic effect on CNI ED. We established an ED model on rats and evaluated the effect of iMSC on it. Methods: Eight-week-old male Sprague-Dawley rats were assigned to four groups and received following operation: sham operation (sham group); bilateral CNI and phosphate-buffered saline (PBS) injections (PBS group); bilateral CNI and adipose-derived mesenchymal stem cells transplantation (adMSC group); or bilateral CNI and iMSC injection (iMSC group). After therapy, the cavernous nerve was stimulated by electricity and the intracavernous pressure (IAP)/mean arterial blood pressure (MAP) was measured. The endothelial and smooth muscle tissue in the penis was assessed histologically with Masson's trichrome stain. Immunofluorescence/immunohistochemical stains were applied for the detection of nNOS, vWF, eNOS, SMA, Desmin, S100β, and caspase-3. Nude rats CNI ED model was established for the evaluation of iMSC longevity and differentiation capacity. The paracrine factors were assessed by real-time PCR. Results: Transplantation of iMSC significantly restored the IAP/MAP in this CNI ED model and showed long-term effects. It could rescue the expression of vWF, eNOS, SMA, and Desmin, which indicated the alleviation of endothelial and smooth muscle tissues of the penis. iMSC therapy also could increase the expression of nNOS in the cavernosum and S100β in the major pelvic ganglia (MPG) which contributed to the erectile function. Moreover, the level of BAX and caspase-3 were reduced and Bcl-2 was increased, which indicated the anti-apoptosis effects of iMSC. The iMSC showed little transdifferentiation and exerted their function by activating the secretome of the host. Conclusion: Transplantation of iMSC significantly improved ED induced by CNI. The iMSC may exert their effects via paracrine factors and may be a promising therapeutic candidate for treating CNI ED in the future.

The expression and biological function of long intergenic noncoding RNA00265 (LINC00265) in gastric cancer (GC) have not yet been explored. This study aimed to detect LINC00265 expression in GC tissues and cell lines, investigate its roles in the proliferation of GC cells in vitro, and elucidate the regulatory mechanisms of LINC00265 action. It was found that LINC00265 expression was significantly upregulated in GC tissue samples and cell lines compared with their normal counterparts. Additionally, LINC00265 knockdown could inhibit GC cell proliferation in vitro. Further investigation revealed that LINC00265 acted as a competing endogenous RNA for microRNA-144-3p (miR-144-3p) and inhibition of miR-144-3p markedly counteracted LINC00265 knockdown-meditated suppression on GC cell proliferation. Additionally, Chromobox 4 (CBX4) was upregulated in GC and silencing CBX4 could reduce GC cell proliferation. Then, CBX4 mRNA was demonstrated to be a direct target of miR-144-3p in GC cells and LINC00265/miR-144-3p axis could regulate CBX4 expression. Taken together, LINC00265 may promote GC cell proliferation via the miR-144-3p/CBX4 axis., Graphical Abstract

Lesion detection is a fundamental problem in the computer-aided diagnosis scheme for mammography. The advance of deep learning techniques have made a remarkable progress for this task, provided that the training data are large and sufficiently diverse in terms of image style and quality. In particular, the diversity of image style may be majorly attributed to the vendor factor. However, the collection of mammograms from vendors as many as possible is very expensive and sometimes impractical for laboratory-scale studies. Accordingly, to further augment the generalization capability of deep learning model to various vendors with limited resources, a new contrastive learning scheme is developed. Specifically, the backbone network is firstly trained with a multi-style and multi-view unsupervised self-learning scheme for the embedding of invariant features to various vendor-styles. Afterward, the backbone network is then recalibrated to the downstream task of lesion detection with the specific supervised learning. The proposed method is evaluated with mammograms from four vendors and one unseen public dataset. The experimental results suggest that our approach can effectively improve detection performance on both seen and unseen domains, and outperforms many state-of-the-art (SOTA) generalization methods.

Background:The expression levels and detailed functions of LINC00265 in gastric cancer (GC) have not yet been explored. This study aimed to measure LINC00265 expression in GC tissues and cell lines, investigate its specific roles in the aggressive characteristics of GC cells in vitro and in vivo, and elucidate the regulatory mechanisms of LINC00265 action.Materials and methods: The qRT-PCR was performed to test the RNA expression levels in GC tissues and cell lines. Cell proliferation was detected by CCK-8 and colony formation assays. Western blot assay was used to measure relevant protein expression. Luciferase reporter assays were performed to investigate the association between LINC00265 and microRNA-144-3p and CBX4.Results: LINC00265 expression was high in GC tissue samples and cell lines; LINC00265 overexpression correlated with shorter overall survival of the patients. A LINC00265 knockdown inhibited GC cell proliferation in vitro and slowed tumor growth in vivo. Mechanism investigation revealed that LINC00265 acts as a competing endogenous RNA on microRNA-144-3p (miR- 144) in GC cells. Chromobox 4 (CBX4) mRNA was identified as a direct target of miR-144-3p in GC cells. The knockdown of miR-144-3p counteracted the reduction in the malignant characteristics of GC cells by the downregulation of LINC00265.Conclusion: In conclusion, LINC00265 functions as a competing endogenous RNA targeting miR-144-3p and increases the malignancy of GC cells in vitro and in vivo by upregulating CBX4.

Cervical smear screening is an imaging-based cancer detection tool, which is of pivotal importance for the early-stage diagnosis. A computer-aided screening system can automatically find out if the scanned whole-slide images (WSI) with cervical cells are classified as “abnormal” or “normal”, and then alert pathologists. It can significantly reduce the workload for human experts, and is therefore highly demanded in clinical practice. Most of the screening methods are based on automatic cervical cell detection and classification, but the accuracy is generally limited due to the high variation of cell appearance and lacking context information from the surroundings. Here we propose a novel and hierarchical framework for automatic cervical smear screening aiming at the robust performance of case-level diagnosis and finding suspected “abnormal” cells. Our framework consists of three stages. We commence by extracting a large number of pathology images from the scanned WSIs, and implementing abnormal cell detection to each pathology image. Then, we feed the detected “abnormal” cells with corresponding confidence into our novel classification model for a comprehensive analysis of the extracted pathology images. Finally, we summarize the classification outputs of all extracted images, and determine the overall screening result for the target case. Experiments show that our three-stage hierarchical method can effectively suppress the errors from cell-level detection, and provide an effective and robust way for cervical abnormality screening.

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a dual-sampling attention network to automatically diagnose COVID- 19 from the community acquired pneumonia (CAP) in chest computed tomography (CT). In particular, we propose a novel online attention module with a 3D convolutional network (CNN) to focus on the infection regions in lungs when making decisions of diagnoses. Note that there exists imbalanced distribution of the sizes of the infection regions between COVID-19 and CAP, partially due to fast progress of COVID-19 after symptom onset. Therefore, we develop a dual-sampling strategy to mitigate the imbalanced learning. Our method is evaluated (to our best knowledge) upon the largest multi-center CT data for COVID-19 from 8 hospitals. In the training-validation stage, we collect 2186 CT scans from 1588 patients for a 5-fold cross-validation. In the testing stage, we employ another independent large-scale testing dataset including 2796 CT scans from 2057 patients. Results show that our algorithm can identify the COVID-19 images with the area under the receiver operating characteristic curve (AUC) value of 0.944, accuracy of 87.5%, sensitivity of 86.9%, specificity of 90.1%, and F1-score of 82.0%. With this performance, the proposed algorithm could potentially aid radiologists with COVID-19 diagnosis from CAP, especially in the early stage of the COVID-19 outbreak., Comment: accepted by IEEE Transactions on Medical Imaging, 2020

Background Hearing loss is a common disease globally, and more than 50% of the cases are genetic. Autosomal recessive nonsyndromic hearing loss (ARNSHL) is one of the most common types of hereditary hearing loss. Here, a novel MYO15A missense mutation was identified in a Chinese family with ARNSHL, using targeted genetic sequencing and Sanger sequencing. Case presentation: A 6-year-old girl with congenital nonsyndromic sensorineural deafness was presented from the First Affiliated hospital of Chongqing Medical University, China. We used targeted region sequencing, Sanger sequencing, functional prediction, and three-dimensional protein structure modeling to identify and verify the genes responsible for deafness in the family. Conclusions We found pathogenic compound heterozygous mutations in MYO15A, including a novel missense mutation, c.6353T > C (p.Leu2118Pro). It could provide help not only for genetic counseling but also for further understanding of the functional role of MYO15A mutations.

Objectives To evaluate the rapid repair potential of adipose‐derived stem cells (ADSCs) co‐overexpressing VEGF and GDNF on bilateral cavernous nerve injury (BCNI) in rat models. Progressive fibrosis of the penis that occurs shortly after BCNI is a key cause of clinical treatment difficulty of erectile dysfunction (ED). Traditional medications are ineffective for ED caused by BCNI. ADSCs have shown therapeutic effects in animal models, but disappointing in clinical treatment suggests that we should explore optimal treatment of it. Materials and methods We extracted ADSCs from rat epididymis. Lentiviral transfection was verified by western blot and immunofluorescence. Thirty‐six SD rats (10 weeks old) were randomly divided into six groups (n = 6 per group): sham surgery, and remaining five BCNI groups transplanted PBS or ADSCs which were genetically modified by vehicle, VEGF (ADSC‐V), GDNF (ADSC‐G), or VEGF&GDNF (ADSC‐G&V) around major pelvic ganglion (MPG). We investigated the therapeutic effects of BCNI rat model which is characterized by ED, penile tissue fibrosis and hypoxia, and lack of nitrogen nerves or vascular atrophy. Results Erectile function was almost recovered after 2 weeks of transplantation of ADSC‐G&V, promoted cavernous nerve repair, prevented penile fibrosis and preserving the vascular endothelium, which was significant differences amongst ADSC‐V or ADSC‐G. Moreover, GM‐ADSCs were detected in MPG and penis, indicating that their participation in repair of target organs and transverse nerves. Conclusions These promising data indicate that ADSCs co‐overexpressed VEGF and GDNF‐induced synergistic effects, make it a potential tool for recovering of erectile function speedily after BCNI.

Computer-aided diagnosis with deep learning techniques has been shown to be helpful for the diagnosis of the mammography in many clinical studies. However, the image styles of different vendors are very distinctive, and there may exist domain gap among different vendors that could potentially compromise the universal applicability of one deep learning model. In this study, we explicitly address style variety issue with the proposed multi-resolution and multi-reference neural style transfer (mr\(^2\)NST) network. The mr\(^2\)NST can normalize the styles from different vendors to the same style baseline with very high resolution. We illustrate that the image quality of the transferred images is comparable to the quality of original images of the target domain (vendor) in terms of NIMA scores. Meanwhile, the mr\(^2\)NST results are also shown to be helpful for the lesion detection in mammograms.

Knee osteoarthritis (OA) is one of the most common musculoskeletal disorders and requires early-stage diagnosis. Nowadays, the deep convolutional neural networks have achieved greatly in the computer-aided diagnosis field. However, the construction of the deep learning models usually requires great amounts of annotated data, which is generally high-cost. In this paper, we propose a novel approach for knee cartilage defects assessment, including severity classification and lesion localization. This can be treated as a subtask of knee OA diagnosis. Particularly, we design a self-ensembling framework, which is composed of a student network and a teacher network with the same structure. The student network learns from both labeled data and unlabeled data and the teacher network averages the student model weights through the training course. A novel attention loss function is developed to obtain accurate attention masks. With dual-consistency checking of the attention in the lesion classification and localization, the two networks can gradually optimize the attention distribution and improve the performance of each other, whereas the training relies on partially labeled data only and follows the semi-supervised manner. Experiments show that the proposed method can significantly improve the self-ensembling performance in both knee cartilage defects classification and localization, and also greatly reduce the needs of annotated data.

Ring finger protein 2 (RNF2), as a well-known E3 ligase, has an oncogenic role in various cancers. The role of RNF2 in colon cancer is still unknown. The aim of this work is to determine the biological role of RNF2 in colon cancer. We first examined the expression of RNF2 and interferon regulatory factor 4 (IRF4) in colon cancer patients and colon cancer cell lines (SW480 and HCT116). Compared with normal tumor-adjacent tissues, RNF2 was up-regulated whereas IRF4 was down-regulated in the colon cancer tissues. RNF2 was also up-regulated in colon cancer cells with respect to human fetal colon epithelial cells. RNF2 overexpression enhanced the ability of proliferation, migration and invasion of SW480 cells, whereas RNF2 knockdown caused an opposite result in HCT116 cells. Furthermore, a tumor xenograft model was constructed to verify the impact of RNF2 overexpressed-SW480 cells on tumor growth. RNF2 up-regulation elevated Ki-67 proliferation index, accelerated the growth of tumor tissues, and led to severe colon tissue damage in the tumor xenograft mice. In addition, RNF2 interacted with IRF4, and repressed IRF4 protein expression. IRF4 was a substrate of RNF2, and RNF2 promoted the ubiquitination and degradation of IRF4. RNF2 overexpression increased the ability of proliferation, migration and invasion in SW480 cells by promoting the ubiquitination and degradation of IRF4. In conclusion, this work demonstrated that RNF2 promoted tumor growth in colon cancer by regulating ubiquitination and degradation of IRF4. Thus, RNF2 may be served as a potential therapeutic target for colon cancer.

Computer vision approaches have been widely used to automatically recognize the activities of workers from videos. While considerable advancements have been made to capture complementary information from still frames, it remains a challenge to obtain motion between them. As a result, this has hindered the ability to conduct real-time monitoring. Considering this challenge, an improved convolutional neural network (CNN) that integrates Red-Green-Blue (RGB), optical flow, and gray stream CNNs, is proposed to accurately monitor and automatically assess workers' activities associated with installing reinforcement during construction. A database containing photographs of workers installing reinforcement is created from activities undertaken on several construction projects in Wuhan, China. The database is then used to train and test the developed CNN network. Results demonstrate that the developed method can accurately detect the activities of workers. The developed computer vision-based approach can be used by construction managers as a mechanism to assist them to ensure that projects meet pre-determined deliverables.

BACKGROUND Long-term exposure to hypertonic and high glucose in peritoneal dialysis fluid can result in peritoneal fibrosis. Spleen tyrosine kinase (SYK) has a role in inflammation and fibrosis. This study aimed to investigate the role of SYK in an in vivo rat model of peritoneal fibrosis and in rat peritoneal mesothelial cells (PMCs) in vitro and to investigate the underlying mechanisms. MATERIAL AND METHODS Sprague-Dawley rats (N=24) were randomized into the sham control group (N=6); the peritoneal fibrosis group (N=6) treated with intraperitoneal chlorhexidine digluconate; the SYK inhibitor group (N=6), treated with chlorhexidine digluconate and fostamatinib; and the TGF-s inhibitor group (N=6), treated with chlorhexidine digluconate and LY2109761. The rat model underwent daily intraperitoneal injection with 0.5 ml of 0.1% chlorhexidine digluconate. Rat peritoneal mesothelial cells (PMCs) were cultured in vitro in high glucose. SYK expression was measured by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot. Enzyme-linked immunosorbent assay (ELISA) and qRT-PCR measured inflammatory mediators. Transforming growth factor-s1 (TGF-s1) and Smad3 were detected by Western blot. Short hairpin RNA (shRNA) was used to target the SYK gene. RESULTS SYK was upregulated in the rat model of peritoneal fibrosis and was induced rat PMCs cultured in high glucose. Knockdown of SYK and inhibition of TGF-s1 significantly reduced fibrosis and inflammation. Findings in the in vivo rat model confirmed that SYK mediated peritoneal fibrosis by regulating TGF-s1/Smad3 signaling. CONCLUSIONS In a rat model and in rat PMCs, expression of SYK increased peritoneal fibrosis through activation of the TGF-s1/Smad3 signaling pathway.

Background Whether combined transplantation of mesenchymal stem cells (MSCs) and endothelial progenitor cells (EPCs) is more effective than transplantation of a single cell type in the restoration of erectile function is unknown. Aim To investigate the effect of combined transplantation of MSCs and EPCs on restoration of erectile function in rats with cavernous nerve injury (CNI). Methods MSCs were isolated from human bone marrow and EPCs were isolated from human umbilical cord blood. MSCs and EPCs were identified by flow cytometry and in vitro differentiation or immunofluorescence staining. 25 8-week-old male Sprague-Dawley rats were allocated to 1 of 5 groups: sham operation group, bilateral CNI group receiving periprostatic implantation of MSCs plus EPCs, MSCs, EPCs, or phosphate buffered saline (control group). 2 weeks after CNI and treatment, erectile function of rats was measured by electrically stimulating the CN. The penis and major pelvic ganglia were harvested for histologic examinations. RNA and protein levels of neurotrophin factors (vascular endothelial growth factor, nerve growth factor, and brain-derived neurotrophic factor) in mono- or coculture MSCs and EPCs were assessed by real-time polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. Outcomes Intracavernous pressure and mean arterial pressure were measured to evaluate erectile function. Histologic examinations of the penis and major pelvic ganglia and RNA and protein levels of neurotrophin factors in MSCs and EPCs were performed. Results MSCs and EPCs expressed the specified cell markers and exhibited the typical appearance and characteristics. Treatments using MSCs and/or EPCs could increase endothelial and smooth muscle contents of the corpus cavernosum, decrease caspase-3 expression and increase penile neuronal nitric oxide synthase expression, and restore the neural component of the major pelvic ganglia in rats with CNI. Combined transplantation of MSCs and EPCs had a better effect on improving erectile function than single transplantation of MSCs or EPCs. Expression levels of vascular endothelial growth factor and nerve growth factor in coculture MSCs and EPCs were significantly higher than those of primary MSCs or EPCs. Clinical Translation Combined transplantation of MSCs and EPCs was more effective in restoring erectile function in CNI-related erectile dysfunction models. Strengths and Limitations The study, for the 1st time, proved that combined transplantation of MSCs and EPCs was more effective in restoring erectile function in rats with CNI. The rat model might not represent the human condition. Conclusion Combined periprostatic transplantation of MSCs and EPCs could restore erectile function in rats with CNI more effectively. MSCs might restore CN fibers by secreting neurotrophin factors such as vascular endothelial growth factor and nerve growth factor, and EPCs could enhance the paracrine activity of MSCs.

Computer vision and pattern recognition approaches have been applied to determine unsafe behaviors on construction sites. Such approaches have been reliant on the computation of artificially complex image features that utilize a cumbersome parameter re-adjustment process. The creation of image features that can recognize unsafe actions, however, poses a significant research challenge on construction sites. This due to the prevailing complexity of spatio-temporal features, lighting, and the array of viewpoints that are required to identify an unsafe action. Considering these challenges, a new hybrid deep learning model that integrates a convolution neural network (CNN) and long short-term memory (LSTM) that automatically recognizes workers' unsafe actions is developed. The proposed hybrid deep learning model is used to: (1) identify unsafe actions; (2) collect motion data and site videos; (3) extract the visual features from videos using a CNN model; and (4) sequence the learning features that are enabled by the use of LSTM models. An experiment is used to test the model's ability to detect unsafe actions. The results reveal that the developed hybrid model (CNN + LSTM) is able to accurately detect safe/unsafe actions conducted by workers on-site. The model's accuracy exceeds the current state-of-the-art descriptor-based methods for detecting points of interest on images.

Pancreatic cancer (PC) is one of the top deaths causing cancers with low 5-year survival rate. Long non-coding RNAs (lncRNAs) are recognized as a crucial type of nonprotein-coding transcripts implicated in tumorigenesis. Emerging evidence has implied that LINC00152 exerts the potential oncogenic functions in various cancers. Nevertheless, the role of LINC00152 in PC remains elusive. In the present study, we found that LINC00152 was significantly up-regulated while miR-150 was down-regulated both in tissues and cell lines of PC, indicating their negative correlation in PC progression. Functionally, overexpression of LINC00152 promoted cell proliferation, migration and invasion, while LINC00152 knockdown reversed these effects. Mechanistic experiments reveal that miR-150 acted as a target of LINC00152 confirmed by luciferase reporter assay. Moreover, inhibition of miR-150 could markedly attenuate the suppression of cell proliferation, migration and invasion by knocking down LINC00152. Altogether, our findings concluded that LINC00152 facilitated PC progression through inhibiting miR-150 expression, indicating an innovative therapeutic target for PC.

Denervation-induced erectile dysfunction (ED) is a prevailing health problem. Our previous study revealed that endothelial progenitor cells (EPCs) promoted the effect of mesenchymal stem cells (MSCs) on restoration of denervation-induced ED in rats. However, underling mechanisms are still largely elusive. In this study, EPCs and MSCs were co-cultured and resorted to co-EPCs and co-MSCs. EPCs-derived paracrine factors containing PDGF-BB (platelet-derived growth factor) were detected, and MSCs were pre-treated with PDGF-BB, while co-MSCs were pre-treated with PDGFR inhibitor AG1296. Either viability or nerve regenerative ability of MSCs was evaluated. In addition, inhibition of either PI3K/Akt or MEK/Erk pathway was performed to evaluate the role of PI3K/Akt and MEK/Erk pathway in PDGF-BB-induced viability of MSCs. The results revealed that PDGF-BB significantly increased the proportion of PDGFR-β+ MSCs, and promoted both in-vitro and in-vivo viability, as well as nerve regenerative capacity and erectile function restoration of MSCs in rats. Inhibition of PI3K/Akt, MEK/Erk pathway or mTOR led to decrease of PDGF-BB/PDGFR-β induced viability of MSCs. To our knowledge, our study first demonstrates that EPCs promote viability and potential nerve regenerative ability of MSCs through PDGF-BB/PDGFR-β signaling and its downstream PI3K/Akt and MEK/Erk pathways. mTOR acts as a co-mediator in PI3K/Akt and MEK/Erk pathways.

BACKGROUND We aimed to explore the correlation between patients' sigmoid sinusoidal tinnitus (SST) and low-frequency sensorineural hearing loss (LFSHL) and illustrate the underlying mechanism. MATERIAL AND METHODS Seven healthy volunteers with normal hearing were subjected to 125-, 250-, and 500-Hz pure sound and different white noise-masking intensities. A retrospective analysis was made on the clinical data and postoperative follow-up data of 59 patients with SST in the First Affiliated Hospital of Chongqing Medical University. The patients' sex, age, chief complaints, affected site, concomitant symptoms, course of disease, pure-tone audiometry (PTA) results, tinnitus discomfort loudness scale results, imaging examination, and complications were collected. RESULTS The results of the simulation experiment showed that the threshold of each frequency segment was higher after noise masking than before masking; the intensity of noise masking was positively correlated with hearing loss, and the changes of the hearing threshold of the 3 frequencies before and after masking were statistically significant (P