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Facing the gaps that the traditional long short-term memory (LSTM) and convolution neural network (CNN) cannot differentially deal with the input data based on the corresponding trend and stage information in remaining useful life (RUL) prediction, a more accurate and robust RUL prediction model is constructed. First, a temporally multi-differential LSTM (TMLSTM) with the multi-trend division unit and multicellular unit is proposed, and a spatially multi-differential CNN (SMCNN) with the multi-stage division unit and differentiated convolutions is designed. Then, by combining TMLSTM and SMCNN, a spatiotemporally multi-differential deep neural network (SMDN) is developed for predicting the equipment RUL, which enhances the ability of feature extraction from the spatiotemporal perspective by using the multi-trend and multi-stage information. Via several evaluation indexes, the Commercial Modular Aero Propulsion System Simulation dataset and the wind turbine gearbox bearing dataset are used to validate the superiority of the proposed method over several existing prediction methods.

Objectives Although neonates and infants undergoing cardiac surgery on cardiopulmonary bypass (CPB) are at high risk of developing perioperative morbidity and mortality, including lung injury, the intraoperative profile of lung injury in this cohort is not well-described. Given that the postoperative course of patients in the pediatric cardiac surgical arena has become increasingly expedited, the objective of this study was to characterize the profiles of postoperative mechanical ventilatory support in neonates and infants undergoing cardiac surgery on CPB and to examine the characteristics of lung mechanics and lung injury in this patient population who are potentially amendable to early postoperative recovery in a single tertiary pediatric institution. Design A retrospective data analysis of neonates and infants who underwent cardiac surgery on cardiopulmonary bypass. Setting A single-center, university teaching hospital. Participants The study included 328 neonates and infants who underwent cardiac surgery on cardiopulmonary bypass. Interventions A subset of 128 patients were studied: 58 patients undergoing ventricular septal defect (VSD) repair, 36 patients undergoing complete atrioventricular canal (CAVC) repair, and 34 patients undergoing bidirectional Glenn (BDG) shunt surgery. Measurements and Main Results Of the entire cohort, 3.7% experienced in-hospital mortality. Among all surgical procedures, VSD repair (17.7%) was the most common, followed by CAVC repair (11.0%) and BDG shunt surgery (10.4%). Of patients who underwent VSD repair, CAVC repair, and BDG shunt surgery, 65.5%, 41.7%, and 67.6% were off mechanical ventilatory support within 24 hours postoperatively, respectively. In all three of the surgical repairs, lung compliance decreased after CPB compared to pre-CPB phase. Sixty point three percent of patients with VSD repair and 77.8% of patients with CAVC repair showed a PaO2/FIO2 (P/F) ratio of 24 hours) postoperative mechanical ventilatory support. A higher volume of transfused platelets also was associated with postoperative ventilatory support ≥24 hours in patients undergoing VSD repair, CAVC repair, and BDG shunt surgery. Conclusions There was a high incidence of lung injury after CPB in neonates and infants, even in surgeries amendable for early recovery. Given that CPB-related factors (CPB duration, crossclamp time) and volume of transfused platelet were significantly associated with prolonged postoperative ventilatory support, the underlying cause of cardiac surgery-related lung injury can be multi-factorial.

Graph simulation is one of the most fundamental problems in graph processing and analytics. It can help users to generate new graphs on different scales to mimic observed real-life graphs in many applications such as social networks, biology networks, and information technology. In this paper, we focus on one of the most important types of graph generators: general graph generators, which aim to reproduce the properties of the observed graphs regardless of the domains. Though a variety of graph generators have been proposed in the literature, there are still several important research gaps in this area. In this paper, we first give an overview of the existing general graph generators, including recently emerged deep learning-based approaches. We classify them into four categories: simple model-based generators, complex model-based generators, autoencoder-based generators, and GAN-based generators. Then we conduct a comprehensive experimental evaluation of 20 representative graph generators based on 17 evaluation metrics and 12 real-life graphs. We provide a general roadmap of recommendations for how to select general graph generators under different settings. Furthermore, we propose a new method that can achieve a good trade-off between simulation quality and efficiency. To help researchers and practitioners apply general graph generators in their applications or make a comprehensive evaluation of their proposed general graph generators, we also implement an end-to-end platform that is publicly available.

Background and aim Activated hepatic stellate cells (HSCs) are the most critical cells responsible for liver fibrosis, and platelet-derived growth factor (PDGF) is the most prominent mitogen for HSCs in fibrogenesis. This study aimed to explore the potential of gadolinium (Gd)-labeled cyclic peptides (pPB) targeting PDGF receptor-β (PDGFR-β) as a magnetic resonance imaging (MRI) radiotracer to identify the progression of liver fibrosis by imaging hepatic PDGFR-β expression. Methods Mice treated with carbon tetrachloride (CCl4 ) were used to mimic hepatic fibrosis in vivo. The binding activity of FITC-labeled pPB to PDGFR-β was assessed in cultured human HSCs (HSC-LX2). MRI was performed to visualize hepatic PDGFR-β expression in mice with different degrees of liver fibrosis after Gd-labeled pPB was injected. Results Hepatic PDGFR-β expression level was correlated with the severity of liver fibrosis, and the majority of cells expressing PDGFR-β were found to be activated HSCs in fibrotic livers. Culture-activated human HSCs expressed abundant PDGFR-β, and FITC-labeled pPB could bind to these cells in a concentration-dependent and time-dependent manner. With Gd-labeled pPB as a tracer, an MRI modality demonstrated that the relative hepatic T1-weighted MRI signal value progressively increased with the severity of hepatic fibrosis and reduced with remission. Conclusions Hepatic PDGFR-β expression reflects the progression of hepatic fibrosis, and MRI using Gd-labeled pPB as a tracer exhibits potential for distinguishing liver fibrosis staging in mice.

BACKGROUND Vesical Imaging-Reporting and Data System (VI-RADS) has been shown to be effective in diagnosing muscle invasion of bladder cancer (BC) in primary patients. PURPOSE To evaluate the diagnostic efficacy of VI-RADS in a BC target population which included post-treatment patients, and to determine the repeatability. STUDY TYPE Prospective. POPULATION Seventy-three patients (42 with primary BC, 31 with post-treatment BC). FIELD STRENGTH/SEQUENCE 3.0 T MRI with propeller fast spin-echo T2 WI, echo planer imaging diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI). ASSESSMENT VI-RADS scores were independently assessed by five radiologists with different levels of experience. The diagnostic efficiency in each group (primary and post-treatment) and of each radiologist was assessed. STATISTICAL TESTS Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and area under the curve (AUC) in receiver operating characteristic curve analysis were calculated to evaluate VI-RADS diagnostic performance. Interobserver agreement was assessed using weighted Kappa statistics. A P value

Trenchless detection technology for oil and gas pipeline defect is of great significance to remedy the shortcomings of in-pipeline detection and pipeline direct assessment technology. Pipeline defect detection technology can be expanded and the long-term service of the pipeline can be achieved due to the trenchless detection technology. According to the fluctuation range of ground magnetic field caused by typical pipeline defect, fluxgate sensor was selected as the sensitive element to detect the magnetic fluctuation of the pipeline in this paper. Excitation circuit, detection circuit and data processing circuit of fluxgate sensor were designed. Long-distance pipeline defect detection experiments under indoor and field conditions were carried out by using a self-made fluxgate detector. The indoor experimental results showed that the sensitivity of the magnetic detector is higher than that of the international advanced magnetic detector, and it can detect artificial pipe defects with a depth greater than 20% of the wall thickness at a distance of 1.6 ∼ 2.2 m (7 ∼ 10 times the pipe diameter). The field experimental results showed that the magnetic detector could detect corrosion thinning of pipeline with buried depth of 2.5 m (3.5 times diameter) effectively.

The barrel vault elastic gridshell is a type of spatial structure composed of long continuous solid timber or hollow GFRP members and achieves its shape from elastic deformations during the construction process of lifting or pushing. The shape forming mechanism of elastic gridshells is very complicated due to significant geometric non-linearity. This research aims to propose analytic formulations to estimate the deformed shapes of barrel vault elastic gridshells considering the mechanical properties of structure. Simplified model of a single member subjected to distributed loads and concentrated forces was established for theoretical analysis, from which the deformations and bending moments of the structure were calculated. Finite element models were further established to validate the accuracy of the proposed approach, and both simple cantilever beams and spatial barrel vault elastic gridshells were employed as investigation objects. Various cases of dimensional parameters were covered so that the wide applicability of such analytical method can be verified. Results show that the derived performance indexes of all members are very close to the results from finite element analysis, indicating that the proposed theoretical approach is effective and efficient in predicting the structural behaviors of barrel vault elastic gridshells when lifting construction method is adopted.

To compare the difference of evaluating the microcirculatory function status of primary small HCC between DCE-MRI with two-compartmental pharmacokinetic model and IVIM-DWI. 27 patients (22 men, 5 women; mean age, 49 years; range 36–65 years) with primary single sHCC who underwent IVIM-DWI and DCE–MRI before the operation were included in this retrospective study. The MR perfusion parameters are Ktrans, Ve, Kep, D, D* and f. Pathological results include pathological grade (low grade ≤ II, high grade > II) and MVD. The perfusion parameters and pathological results of sHCC were analyzed and compared in their relevance, sensitivity and specificity. Statistical methods included Spearman and ROC curve analysis. The perfusion parameters (Ktrans, Kep, D*, f) were significantly positive correlated (r = 0.892, 0.808, 0.589 and 0.543, P = 0.000, 0.000, 0.001 and 0.003 with MVD of sHCC. The parameter Ve and D values were negatively correlated (r = − 0.454 and − 0.399, P = 0.017 and 0.039, respectively) with the pathological grade. Regarding the evaluation MVD of sHCC, the evaluation of the sensitivity and specificity performance was present in descending order: Ktrans > Kep > PF > D*. In the evaluation pathological grade of sHCC, the sensitivity and specificity were better by parameters D than Ve. DCE-MRI is better than IVIM-DWI for evaluation microcirculation functional status of sHCC. But for evaluating the pathological grade, IVIM-DWI is better than DCE-MRI. Combination of the two imaging techniques may provide more comprehensive evaluation in microcirculation functional status of the sHCC.

Response evaluation criteria in solid tumors (RECIST) often fail to identify clinically meaningful response to bevacizumab-containing therapy in colorectal liver metastasis (CRLM). This study aimed to develop RECIST by combining contrast-enhanced and diffusion-weighted magnetic resonance imaging (MRI). A total of 126 patients with CRLM who underwent hepatic resection after bevacizumab-containing chemotherapy were split into initial analyses cohort (N = 42, with 76 indexed liver metastases) and validation cohort (N = 84). In lesion-based analyses, percentage decrease of arterial enhancement area and percentage increase of apparent diffusion coefficient (ADC) value from baseline to post-chemotherapy were measured. Their optimal cutoff values for distinguishing pathology-confirmed major and minor response were determined. Then, the developed RECIST (D-RECIST) was established by combining functional and size-based items. Survival relevance of D-RECIST and RECIST was examined in the validation cohort. Percentage decrease of arterial enhancement area and increase of ADC value significantly differed between lesions of pathologic major or minor response, with optimal cutoffs of approximately 33% and 19%, respectively. Patients defined as responders by D-RECIST had a significantly longer median disease-free survival (DFS) than non-responders (p = 0.021; 12.9 versus 8.6 months). No significant difference was observed with RECIST (p = 0.524). In a Cox regression model, D-RECIST- but not RECIST-defined responses independently predicted the DFS (p = 0.034 and 0.811). D-RECIST-defined responses provided significant prognostic information, and thus may serve as a better response evaluation approach than RECIST in CRLM treated with bevacizumab-containing therapy. • Changes in arterial enhancement area and apparent diffusion coefficient value are associated with pathological response in colorectal liver metastases treated with bevacizumab. • The MRI-based response criteria developed by combining size-based and functional features can provide significant prognostic information.

Objectives To develop radiomics-based nomograms for preoperative microvascular invasion (MVI) and recurrence-free survival (RFS) prediction in patients with solitary hepatocellular carcinoma (HCC) ≤ 5 cm. Methods Between March 2012 and September 2019, 356 patients with pathologically confirmed solitary HCC ≤ 5 cm who underwent preoperative gadoxetate disodium–enhanced MRI were retrospectively enrolled. MVI was graded as M0, M1, or M2 according to the number and distribution of invaded vessels. Radiomics features were extracted from DWI, arterial, portal venous, and hepatobiliary phase images in regions of the entire tumor, peritumoral area ≤ 10 mm, and randomly selected liver tissue. Multivariate analysis identified the independent predictors for MVI and RFS, with nomogram visualized the ultimately predictive models. Results Elevated alpha-fetoprotein, total bilirubin and radiomics values, peritumoral enhancement, and incomplete or absent capsule enhancement were independent risk factors for MVI. The AUCs of MVI nomogram reached 0.920 (95% CI: 0.861–0.979) using random forest and 0.879 (95% CI: 0.820–0.938) using logistic regression analysis in validation cohort (n = 106). With the 5-year RFS rate of 68.4%, the median RFS of MVI-positive (M2 and M1) and MVI-negative (M0) patients were 30.5 (11.9 and 40.9) and > 96.9 months (p < 0.001), respectively. Age, histologic MVI, alkaline phosphatase, and alanine aminotransferase independently predicted recurrence, yielding AUC of 0.654 (95% CI: 0.538–0.769, n = 99) in RFS validation cohort. Instead of histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest achieved comparable accuracy in MVI stratification and RFS prediction. Conclusions Preoperative radiomics-based nomogram using random forest is a potential biomarker of MVI and RFS prediction for solitary HCC ≤ 5 cm. Key Points • The radiomics score was the predominant independent predictor of MVI which was the primary independent risk factor for postoperative recurrence. • The radiomics-based nomogram using either random forest or logistic regression analysis has obtained the best preoperative prediction of MVI in HCC patients so far. • As an excellent substitute for the invasive histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest (MVI-RF) achieved comparable accuracy in MVI stratification and outcome, reinforcing the radiologic understanding of HCC angioinvasion and progression.

In the mechanical transmission system, the gear is one of the most widely used transmission components. The failure of the gear will cause serious accidents and huge economic loss. Therefore, the remaining life prediction of the gear is of great importance. In order to accurately predict the remaining life of the gear, a new type of long-short-term memory neural network with macroscopic–microscopic attention (MMA) is proposed in this article. First, some typical time-domain and frequency-domain characteristics of vibration signals are calculated, respectively, such as the maximum value, the absolute mean value, the standard deviation, the kurtosis, and so on. Then, the principal component of these characteristics is extracted by the isometric mapping method. The importance of fusional characteristic information is filtered via a proposed MMA mechanism so that the input weight of neural network data and recursive data can reach multilevel real-time amplification. With the new long short-term memory neural network, the health characteristics of gear vibration signals can be predicted based on the known fusion features. The experimental results show that this method can predict the remaining life of gears and bearings well, and it has higher prediction accuracy than the conventional prediction methods.

Defect detection is now an active research area for production quality assurance. Traditional visual inspection systems are developed by human beings, which is a time-consuming, labour-intensive, and highly error-prone process, and are therefore unreliable. To overcome these problems, the authors proposed a new method for detecting defects when printing on a 3D micro-textured surface. They utilise an orientation code as the basis to resist the fluctuations in illumination. Based on the consistency of the pixel pairs, they developed a model called multiple paired pixel consistency to represent the statistical relationship between each pixel pair in defect-free images. Finally, based on this model, they designed a defect detection method. Even with different defect sizes, illumination conditions, noise intensities, and other characteristics, the performance of the proposed algorithm is extremely stable and highly accurate, and the recall, precision, and F-measure in most of the results can reach 0.85,0.93, and 0.9, respectively. In addition, the defect detection rate can reach almost 100%. This demonstrates that the authors' approach can achieve state-of-the-art accuracy in real industrial applications.

BACKGROUND Oxaliplatin-induced liver injury (OILI) not only impairs hepatic regeneration but also increases postoperative morbidity and mortality. Therefore, noninvasive, accurate, and early diagnosis of OILI is mandatory. PURPOSE To evaluate the potential of T1 mapping on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI for assessing OILI in a mouse model. STUDY TYPE Case control, animal model. ANIMAL MODEL Thirty oxaliplatin-treated mice and 10 control mice were included. FIELD STRENGTH Volumetric interpolated breath-hold examination sequence: 3T scanner with a phased-array animal 8-channel coil. T1 mapping before and at hepatobiliary phase (HBP) after injection of Gd-EOB-DTPA were undertaken. ASSESSMENT T1 relaxation times of the liver parenchyma were measured and the reduction rate (ΔT1 %) was calculated. Histological findings were used as a standard reference. STATISTICAL TESTS The Kruskal-Wallis test with pairwise comparisons using the Mann-Whitney U-test were applied to compare the parameters across groups. Spearman's rank correlation test and receiver operating characteristics (ROC) analyses were performed. Areas under the curves (AUCs) were compared using the DeLong method. RESULTS Histologically, mice were classified as normal (n = 10), hepatocellular degeneration without fibrosis (n = 16), and hepatocellular degeneration with fibrosis (n = 14). HBP T1 relaxation time increased with the severity of OILI (rho = 0.60, P

PURPOSE: We aimed to evaluate which morphologic features on magnetic resonance imaging (MRI) could predict the progression of pancreatic cystic lesions (PCLs) that are suitable for follow-up. METHODS: A total of 2176 MRI findings of PCLs were retrospectively reviewed between January 2009 and December 2016. The study population was composed of 223 patients. Clinical data and morphologic features of PCLs were recorded. We divided the individuals into two sub-groups according to the final features on MRI. Univariable and multivariable regression analyses were performed to identify independent risk factors for progression of PCLs. RESULTS: A total of 84 PCLs (37.7%) progressed during follow-up, while 139 PCLs (62.3%) were stable. Age (odds ratio [OR], 1.042; P = 0.017), number of lesions (OR, 0.491; P = 0.048), communication to pancreatic duct (PD) (OR, 2.425; P = 0.007) and presence of septa (OR, 6.105; P < 0.001) were significant independent factors for progression of PCLs. Among 84 lesions that progressed, 23 lesions (27.4%) increased to ≥ 30 mm in diameter or showed worrisome imaging features at the end of follow-up that needed clinical intervention. The initial size and communication to PD were independent factors for progression of PCLs necessitating clinical intervention (P < 0.001 and P = 0.011, respectively). CONCLUSION: Age, number of the lesions, communication to PD and presence of septa were independent risk factors for the progression of PCLs, and the initial size and communication to PD could potentially predict PCLs needing clinical interventions.

Concrete simply supported beams are widely used in small- and medium-sized bridges. Hinged slabs and joints are damaged in service easily, as they are the main load-carrying members of bridge. In this paper, using the high sensitivity and strong antinoise characteristics of strain energy to damage, a strain energy information entropy index is proposed for identifying local damage in hinge joints and hinged slabs. Moreover, a new damage index of the local strain energy entropy function is constructed according to the strain energy of a hinge joint element and its surrounding elements. A simply supported beam model is established to verify the effectiveness of the proposed index. The numerical simulation results show that the proposed damage index of hinge joints can accurately locate and quantify the degree of damage of single-hinge joints and multihinge joints. The improved modal strain energy information entropy index is sensitive to single-hinge slab damage and can accurately identify damage with noise levels of 5% and 10%.

As one of important thermostatically controlled loads (TCLs), domestic electric water heaters (DEWHs) show considerable potential for utilities to shave peak load working with direct load control (DLC). The electricity consumption of DEWHs is high in regard to daily domestic electricity consumption, which shows the potential for peak shifting services through the direct control of DEWHs. In practice, off-control is commonly used to control DEWHs, and finding suitable DEWHs to turn off is the main objective of DLC. However, it is difficult to decide which DEWH can be turned off when end-user comfort is taken into consideration, especially with the absence of temperature measurement information. In this paper, a novel control method is proposed to control DEWHs without temperature information. A time-varied weight matrix is generated based on patterns of DEWHs, and the temperatures of DEWHs can be estimated by the weight matrix and their states. The weight matrix and heating durations are used to generate a customer satisfaction prediction index, which can be used as a reference during DLC. The index can be used to select suitable DEWHs to turn off or to turn back on to maintain end-user comfort. The proposed method only needs the on-off states of DEWHs, which are available in practice. Simulation results prove that the proposed method can work well to reduce peak demand without affecting end-user comfort.

Background The presence of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) is a significant adverse prognostic factor. This study sought to investigate the correlation between preoperative imaging parameters and MVI in ICC. Methods A total of 108 patients with surgically resected single ICC tumors (34 MVI-positive and 74 MVI-negative lesions) who underwent MRI examination, including T1WI, T2WI, DWI, and dynamic enhancement imaging, were enrolled in this retrospective study. The following qualitative and quantitative characteristics were evaluated: tumor morphology, signal features on T1WI and T2WI, intrahepatic duct dilatation, hepatic capsule retraction, target sign on DWI, dynamic enhancement pattern, arterial phase enhancement pattern, dot−/band-like enhancement inside the tumor, visible vessel penetration inside the tumor (hepatic artery, portal vein, or hepatic vein), integrity of the enhancement edge of the arterial phase, peripheral hepatic enhancement, tumor size, maximum enhancement edge thickness, arterial edge enhancement ratio, and delayed phase enhancement ratio. Other clinicopathological features were also used to predict and evaluate MVI in ICC. Chi-square test, Fisher’s exact test, and independent t-test were used for univariate analysis to determine the relationships among the presence of MVI and these MR parameters. Logistic regression analysis was used to identify predictors of MVI among these MR parameters. Results Among MRI characteristics, tumor morphology, intrahepatic duct dilatation, arterial phase enhancement pattern, visible hepatic artery penetration sign, maximum diameter of the tumor and the arterial phase edge enhancement ratio were correlated with MVI (P = 0.007, 0.003, 0.008, 0.000, 0.003, and 0.002, respectively). Furthermore, higher CA19–9 levels (≥37 U/ml) and pathological tumor grade III were also related to MVI (P = 0.014 and 0.004, respectively). However, multivariate logistic regression analysis demonstrated that none of the parameters were independent risk factors for the diagnosis of MVI in ICCs. Conclusion For the preoperative prediction of MVI in ICC, six qualitative and quantitative data obtained on preoperative MRI, as well as one tumorigenic marker and the pathological tumor grade, were statistically significant. More research is needed to identify MR characteristics that can be used as independent risk factors.

A number of recent studies have adopted long short-term memory (LSTM) in extensive applications, such as handwriting recognition and time series prediction, with considerable success. However, the parameters of LSTM have greatly influenced its accuracy and performance. In this study, LSTM with fruit fly optimization algorithm (FOA), called FOA-LSTM, is designed to solve time series problems. As a novel intelligent algorithm, FOA is applied to decide on the optimal hyper-parameter of LSTM. Experiments under the NN3 time series, three comparative experiments and the monthly energy consumption of the USA are conducted to verify the effectiveness of the FOA-LSTM model. The results indicate that the symmetric mean absolute percentage error (SMAPE) is reduced by up to 11.44% in the last 11 monthly series in the NN3 dataset. Four comparative experiments and the real-life series verify further that the FOA-LSTM model obtains a better result compared with other forecasting models.

We aimed to develop a radiomics-based model derived from gadoxetic acid–enhanced MR images to preoperatively identify cytokeratin (CK) 19 status of hepatocellular carcinoma (HCC). A cohort of 227 patients with single HCC was classified into a training set (n = 159) and a time-independent validated set (n = 68). A total of 647 radiomic features were extracted from multi-sequence MR images. The least absolute shrinkage and selection operator regression and decision tree methods were utilized for feature selection and radiomics signature construction. A multivariable logistic regression model incorporating clinico-radiological features and the fusion radiomics signature was built for prediction of CK19 status by evaluating area under curve (AUC). In the whole cohort, 57 patients were CK19 positive and 170 patients were CK19 negative. By combining 11 and 6 radiomic features extracted in arterial phase and hepatobiliary phase images, respectively, a fusion radiomics signature achieved AUCs of 0.951 and 0.822 in training and validation datasets. The final combined model integrated a-fetoprotein levels, arterial rim enhancement pattern, irregular tumor margin, and the fusion radiomics signature, with a sensitivity of 0.818 and specificity of 0.974 in the training cohort and that of 0.769 and 0.818 in the validated cohort. The nomogram based on the combined model showed satisfactory prediction performance in training (C-index 0.959) and validation (C-index 0.846) dataset. The combined model based on a fusion radiomics signature derived from arterial and hepatobiliary phase images of gadoxetic acid–enhanced MRI can be a reliable biomarker for CK19 status of HCC. • Arterial rim enhancement pattern and irregular tumor margin on hepatobiliary phase on gadoxetic acid–enhanced MRI can be useful for evaluating CK19 status of HCC. • A radiomics-based model performed better than the clinico-radiological model both in training and validation datasets for predicting CK19 status of HCC. • The nomogram based on the fusion radiomics signature can be easily used for CK19 stratification of HCC.

Financial time series analysis plays a central role in hedging market risks and optimizing investment decisions. This is a challenging task as the problems are always accompanied by multi-modality streams and lead-lag effects. For example, the price movements of stock are reflections of complicated market states in different diffusion speeds, including historical price series, media news, associated events, etc. Furthermore, the financial industry requires forecasting models to be interpretable and compliant. Therefore, in this paper, we propose a multi-modality graph neural network (MAGNN) to learn from these multimodal inputs for financial time series prediction. The heterogeneous graph network is constructed by the sources as nodes and relations in our financial knowledge graph as edges. To ensure the model interpretability, we leverage a two-phase attention mechanism for joint optimization, allowing end-users to investigate the importance of inner-modality and inter-modality sources. Extensive experiments on real-world datasets demonstrate the superior performance of MAGNN in financial market prediction. Our method provides investors with a profitable as well as interpretable option and enables them to make informed investment decisions.

Funding Information: This work is supported by the National Natural Science Foundation of China under grant no. 6207030573 , the National Basic Research Program of China (973 Program) under grant no. 2012CB934200 , and the Specialized Research Fund for the Doctoral Program of Higher Education under grant no. 20130071110018 . Publisher Copyright: © 2021 Elsevier B.V. Copyright: Copyright 2021 Elsevier B.V., All rights reserved. The NO2 sensing performance of a special lateral photovoltaic self-powered gas sensor based on the N-hyperdoped microstructured silicon (N-Si) is systematically studied under the different light illumination. The dependence of sensing characteristics on light intensity and wavelength is obtained, respectively. Results show that the sensing properties can be changed effectively by the different intensities and wavelengths, suggesting that a multidimensional regulation/optimization for the sensing characteristics is possible by light. More interestingly, the light with wavelength of 940 nm and intensity of ∼18 μW/cm2 could bring a comprehensive optimization for gas sensing, under which the N-Si sensor exhibits the excellent overall performance with simultaneously the low light power needed, good gas response, high sensitivity, wide detectable range and short response time at room temperature.

The 2019 novel coronavirus infection has brought a great challenge in prevention and control of the national epidemic of coronavirus disease 2019 (COVID-19) in China. During the fight against the epidemic of COVID-19, properly carrying out pre-examination and triage for patients with skin lesions and fever has been a practical problem encountered in hospitals for skin diseases as well as clinics of dermatology in general hospitals. Considering that certain skin diseases may have symptom of fever, and some of the carriers of 2019 novel coronavirus and patients with COVID-19 at their early stage may do not present any symptoms of COVID-19, to properly deal with the visitors to clinics of dermatology, the Chinese Society of Dermatology organized experts to formulate the principles and procedures for pre-examination and triage of visitors to clinics of dermatology during the epidemic of COVID-19.

Wide-dynamic-range NOx sensors are vital for the environment and health purposes, but few sensors could achieve wide-range detection with ultralow and ultrahigh concentrations at the same time. In this article, the microstructured and nitrogen-hyperdoped silicon (N-Si) for NOx gas sensing is investigated systematically. Working by the change of surface conductivity, the sensor is ultrasensitive to low concentrations of NOx down to 11 ppb and shows a rapid response/recovery time of 22/33 s for 80 ppb. When the NOx concentration increases and exceeds a threshold value (10-50 ppm), an n-p conduction-type transition is observed due to the inversion of the conduction type of major carriers, which limits the dynamic range of the sensor at high concentration. However, when the sensor works in a photovoltaic self-powered mode under the asymmetric light illumination, the limitation can be successfully overcome. Therefore, with the combination of the two working principles, a wide dynamic range stretching over 6 orders of magnitude (∼0.011-4000 ppm) can be achieved.

Background Tuberculosis (TB) patient management (TPM) is crucial to improve patient compliance to treatment. The coverage of TPM delivered by TB dispensaries or Centers for Disease Control and Prevention (CDC) was not high under the previous CDC model of TB control in China. In the integrated TB control model in China, TB patient management (TPM) was mainly delivered by lay health workers (LHWs) in primary health care (PHC) sectors. This study aims to investigate TPM delivery in resource-limited western China and to identify factors affecting TPM delivery by LHWs under the integrated TB control model. Methods A stratified random sampling was used to select study sites. Pulmonary TB (PTB) patients ≥15 years old from selected counties/districts in Guizhou Province were surveyed from August 2015 to May 2016. Structured questionnaires were used to collect data. A χ2 test and logistic regression were used to identify factors associated with self-administered treatment (non-TPM). Results In total, 638 PTB patients were included in the final analysis. Close to 30% of patients were ethnic minorities. More than 30% of patients were from counties with high TB burden, and 24.9% of patients had poor compliance to treatment. Only 37.1% of patients received TPM delivered by LHWs under the integrated TB control model throughout the treatment period. The main reasons for unwillingness to manage reported by patients included social stigma and no perceived need. Being ethnic minorities (OR = 3.35) was a main factor associated with lower likelihood of receiving TPM, while living in areas with middle or high TB burden may increase the likelihood of receiving TPM (OR = 0.17 and 0.25, respectively). Among current management approaches, more than 85% of patients chose phone reminder as their preferred TPM by LHWs. Conclusions TPM under the integrated model in West China is still low and need further improvement, and the impeding factors of TPM need to be addressed. Strengthening patient-centered and community-based TPM and developing more feasible approaches of TPM delivery should be explored in future research in this region. Electronic supplementary material The online version of this article (10.1186/s40249-019-0563-3) contains supplementary material, which is available to authorized users.

Context Brainstem tumour surgery is difficult, and accidents can easily occur. Objective To explore the effect of dexmedetomidine hydrochloride on brainstem tumour surgery. Design, setting and participants A total of 60 patients with brainstem tumours successfully operated on by our hospital from March 2016 to March 2018 were selected as subjects. Interventions These patients were randomised into two groups: the research group (n = 30) and control group (n = 30). Patients in the control group were given propofol together with a placebo (0.9% sodium chloride solution) to maintain anaesthesia after general anaesthesia, while patients in the research group were supplemented with dexmedetomidine hydrochloride. Main outcome measure Awakening time, overall stability of various indicators in the operation and adverse reactions during the awakening period were observed. Results The results revealed that patients in the research group had a longer awakening time, higher mean stability rate, higher effective rate and less incidence of adverse reactions during the awakening period than the control group; the differences were all statistically significant (P

Objectives To evaluate the diagnostic value of liver extracellular volume (ECVliver) measurement by equilibrium MR in staging liver fibrosis in chronic hepatitis B (CHB) patients, and to compare its performance with serum fibrosis indices. Materials and methods 91 CHB patients were included and underwent gadopentetate dimeglumine-enhanced MRI with T1 mapping sequence before and 15-min after contrast. ECVliver, aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis index based on the four factors (FIB-4) were calculated and compared between fibrosis subgroups, and the correlations between the three indices and fibrosis stage or inflammatory activity were measured by Spearman correlation analysis and stepwise multiple regression analysis. Diagnostic performance in evaluating liver fibrosis stage was assessed and compared using receiver operating characteristic analysis. Results Interobserver agreement showed an excellent interclass correlation coefficient of 0.895 for ECVliver. ECVliver, APRI and FIB-4 were different between fibrosis stages as a whole (F/H = 18.44–24.36, P ≤ 0.001). ECVliver had the strongest correlation with fibrosis stage (r = 0.727, P Conclusion MR ECVliver provides a promising noninvasive tool in staging liver fibrosis for CHB patients, superior to the fibrosis indices of APRI and FIB-4.

To overcome the limitations of low sensitivity and instability of metal-medium-metal tunable surface plasmon resonance (SPR) sensors excited by planar waveguides, a silver-graphene-medium-graphene-silver film symmetrical SPR sensing structure excited by planar waveguides is proposed. And optimize sensor performance through modeling. The principle of symmetry structure for sensing tunability is analysed, finding that sensing with a silver film has a higher sensitivity than a gold film. However, since the silver film is easily oxidized, it affects the stability and repeatability of the sensor. To solve this problem, the graphene layer is added to the silver film to improve the disadvantage of easy oxidation of the silver film. A plane waveguide with a refractive index distribution of the residual error function of the excitation is prepared by ion exchange. The sensor structure was modeled and analyzed, and the influence of metal material, metal thickness, graphene layer number and thickness of the detection medium on the performance of the sensor was studied, and the sensing structure was better optimized. The results show that the silver film has a better sensing performance and higher sensitivity than the gold film. By adjusting the thickness of the detection medium, the refractive index range of the detection medium has a certain tunability: the choice of graphene thickness optimises sensor stability and detection sensitivity.

Background The purpose was to investigate the difference of detection rate of incidental pancreatic cystic lesions (PCLs) with computed tomography (CT) and magnetic resonance imaging (MRI) and to compare the difference between CT and MRI and to explore the effect of this difference on surgical resection. Methods We reviewed the diagnostic reports for incidental PCLs between 2013 and 2016. Images of PCLs would be re-evaluated. Clinical and imaging data were recorded. The chi-square and independent t-test were conducted for categorical and continuous variables. Results The prevalence of PCLs was 1.91% (1038/54210) and 3.36% (1282/38099) on CT and MRI respectively, and increased with increasing age (P

To retrospectively evaluate the value of MR features based on Liver Imaging Reporting and Data System (LI-RADS ver.2017) for identifying the status of cytokeratin (CK) 19 expression of HCC before surgery.A total of 201 patients with 207 HCCs who underwent MR imaging were reviewed retrospectively. MR features based on LI-RADS ver.2017 as well as clinical data were compared between CK19-positive (n = 51) and CK19-negative (n = 156) HCCs groups. Potential predictive parameters were identified by univariate and multivariate logistic regression analysis and diagnostic odds ratios (ORs) were recorded.MR features including targetoid appearance (p = 0.001) was more frequently observed while non-peripheral "washout" (p 0.0001) and non-rim arterial phase hyper-enhancement (p 0.0001) were found less frequently in CK19-positive HCCs compared to CK19-negative HCCs. At multivariate analysis, serum alphafetoprotein (AFP)20 ng/ml (OR = 5.9) and targetoid appearance (OR = 4.2) and non-peripheral "washout" (OR = 0.2) were significant independent predictors of CK19-positive HCCs.Targetoid appearance and absence non-peripheral "washout" combined with elevated AFP were useful for differentiating CK19-positive HCCs from CK19-negative HCC.

To explore whether volumetric acquisition of histogram analysis of apparent diffusion coefficient (ADC) maps could quantify liver fibrosis stages. 84 patients underwent MRI exams including DWI before surgery or liver biopsy were included. Histogram analysis of whole liver ADC maps were performed and parameters including ADC mean, ADC median, ADC skewness, ADC kurtosis, ADC standard deviation (SD), ADC 5th, 10th, 25th, 75th, 90th and 95th percentiles were calculated. The correlations between different histopathologic grades and histogram analysis parameters were determined. For the significant parameters, receiver operating characteristics (ROC) analyses were further established to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. The ADC mean and ADC median, ADC SD, ADC5th, 10th, 25th, 75th, 90th and 95th percentile were significantly lower with the increasing grade of liver fibrosis (rho: from − 0.580 to − 0.230). ADC skewness and ADC kurtosis were significantly higher with the increasing grade of liver fibrosis (rho: 0.243, 0.347, respectively). Areas under the ROC curve (AUC) of ADC mean and ADC 75th percentile for identification liver fibrosis (F1–F4), moderate to advanced liver fibrosis (F2–F4), advanced liver fibrosis (F3–F4), cirrhosis (F4) were 0.87, 0.83, 0.82, 0.76 and 0.88, 0.82, 0.80, 0.74, respectively. Histogram analysis of volumetric acquisition of liver ADC maps has a potential value for quantifying liver fibrosis grades.

Greeks are the price sensitivities of financial derivatives and are essential for pricing, speculation, risk management, and model calibration. Although the pathwise method has been popular for cal...

The existing laser remote range-gated imaging system in China is large, expensive and impractical. To achieve long distance imaging, the high-power laser, high-power laser pulse drive, optical system and field synchronisation control are improved in this paper. The improved system is lightweight, easy to use and has a small volume. Experimental results show that the system can clearly map the target at 6 km far away and has a good adaptive adjustment function.

To evaluate the value of MR liver extracellular volume (ECVliver) in assessment of liver fibrosis with chronic hepatitis B (CHB), and to compare its performance with two-dimensional (2D) shear-wave elastography (SWE). A total of 68 CHB patients who were histologically diagnosed as fibrosis stages F0 to F4 were retrospectively analyzed. All patients underwent gadopentetate dimeglumine-enhanced T1-mapping and 2D SWE. ECVliver and liver stiffness were measured and compared between fibrosis subgroups; their correlations with histologic findings were evaluated using Spearman correlation test and multiple regression analysis. Diagnostic performance in evaluating liver fibrosis stages was assessed and compared using receiver-operating characteristic analysis. Both ECVliver and liver stiffness increased as the fibrosis score increased (F = 17.08 to 10.99, P

Purpose The goal of this study was to investigate the Liver Imaging Reporting and Data System (LI-RADS) v.2017 for the categorization of hepatocellular carcinomas (HCCs) with gadoxetic acid compared with gadopentetate dimeglumine-enhanced 1.5-T magnetic resonance imaging (MRI). Material and methods We included 141 high-risk patients with 145 pathologically-confirmed HCCs who first underwent gadopentetate dimeglumine-enhanced 1.5-T followed by gadoxetic acid-enhanced 1.5-T MRI. Two independent radiologists evaluated the presence or absence of major HCC features and assigned LI-RADS categories after considering ancillary features on both MRIs. Finally, the sensitivity of LI-RADS category 5 (LR-5) and the frequencies of major HCC features were compared between gadoxetic acid- and gadopentetate dimeglumine-enhanced 1.5-T MRI using the Wilcoxon test. Results The sensitivity of LR-5 for diagnosing HCCs was significantly different between gadoxetic acid- and gadopentetate dimeglumine-enhanced MRI (73.8% [107/145] vs 26.2% [38/145], P

Accurate tourism demand forecasting is fundamental in the tourism industry, while effective tourism demand forecasting using search query data (SQD) has become popular in the tourism management field. SQD is a type of statistical time series provided by search engines that can reflect netizens’ attention on certain events. Scholars attempt to establish a reasonable relationship between tourism demand and SQD for its timeliness and comprehensiveness. The current study proposes an effective deep learning technique called stacked autoencoder with echo-state regression (SAEN) to accurately forecast tourist flow based on search query data. In the proposed SAEN approach, stacked autoencoder is adopted to hierarchically learn high-level predictive indicators from substantial SQD and connected by an echo-state regression layer to model the nonlinear time series relationship between tourism flow and the learned indicators. Four realistic applications (i.e., one comparative case and three extended cases in the US and China with different SQD sources) are used to verify the forecasting performance of SAEN. Numerical results indicate that SAEN is better than the current literature findings, including time series approach, econometric model, common machine learning algorithms, and state-of-the-art deep learning techniques. The structure parameters of SAEN are further analyzed empirically and theoretically. Moreover, this study determined a different impact of network depth and echo-state reservoir scale on the performance of SAEN. The proposed SAEN can be an appropriate alternative for tourism demand forecasting in complex data situations.

Background Gadoxetic acid-enhanced magnetic resonance imaging (MRI) has been widely used in clinical practice. However, scientific evidence is lacking for recommending a particular sequence for measuring tumor size. Purpose To retrospectively compare the size of hepatocellular carcinoma (HCC) measured on different gadoxetic acid-enhanced MRI sequences using pathology as a reference. Material and Methods A total of 217 patients with single HCC who underwent gadoxetic acid-enhanced MRI before surgery were included. The size of the HCC was measured by two abdominal radiologists independently on the following sequences: T1-weighted; T2-weighted; b-500 diffusion-weighted imaging (DWI); and arterial, portal venous, transitional, and hepatobiliary phases. Tumor size measured on MRI was compared with pathological size by using Pearson correlation coefficient, independent-sample t test, and Bland–Altman plot. Agreement between two readers was evaluated with intraclass correlation coefficient (ICC). Results Correlation between the MR images and pathology was high for both readers (0.899–0.955). Absolute error between MRI and pathologic assessment was lowest on hepatobiliary phase images for both readers (reader 1, 2.8±4.2 mm; reader 2, 3.2±3.4 mm) and highest on arterial phase images for reader 1 (4.9±4.4 mm) and DWI phase images for reader 2 (5.1±4.9 mm). Absolute errors were significantly different for hepatobiliary phase compared with other sequences for both readers (reader 1, P≤0.012; reader 2, P≤0.037). Inter-reader agreements for all sequence measurements were strong (0.971–0.997). Conclusion The performance of gadoxetic acid-enhanced MRI sequences varied with HCC size, and the hepatobiliary phase may be optimal among these sequences.

Purpose To evaluate the value of preoperative computed tomography (CT) features including morphologic and quantitative features for predicting the Ki-67 labeling index (Ki-67LI) of gastric gastrointestinal stromal tumors (GISTs). Methods We retrospectively included 167 patients with gastric GISTs who underwent preoperative contrast-enhanced CT. We assessed the morphologic features of preoperative CT images and the quantitative features including the maximum diameter of tumor, total tumor volume, mean total tumor CT value, necrosis volume, necrosis volume ratio, enhanced tissue volume, and mean CT value of enhanced tissue. Potential predictive parameters to distinguish the high-level Ki-67LI group (>4%, n = 125) from the low-level Ki-67LI group (≤4%, n = 42) were compared and subsequently determined in multivariable logistic regression analysis. Results Growth pattern (p = 0.036), shape (p = 0.000), maximum diameter (p = 0.018), total tumor volume (p = 0.021), mean total tumor CT value (p = 0.009), necrosis volume (p = 0.006), necrosis volume ratio (p = 0.000), enhanced tissue volume (p = 0.027), and mean CT value of enhanced tissue (p = 0.004) were significantly different between the two groups. Multivariate logistic regression analysis indicated that lobulated/irregular shape (odds ratio [OR] = 3.817; p = 0.000) and high necrosis volume ratio (OR = 1.935; p = 0.024) were independent factors of high-level Ki-67LI. Conclusions Higher necrosis volume ratio in combination with lobulated/irregular shape could potentially predict high expression of Ki-67LI for gastric GISTs.

Purpose Microvascular invasion (MVI) is a critical determinant of the early recurrence and poor prognosis of patients with hepatocellular carcinoma (HCC). Prediction of MVI status is clinically significant for the decision of treatment strategies and the assessment of patient’s prognosis. A deep learning (DL) model was developed to predict the MVI status and grade in HCC patients based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical parameters.Methods HCC patients with pathologically confirmed MVI status from January to December 2016 were enrolled and preoperative DCE-MRI of these patients were collected in this study. Then they were randomly divided into the training and testing cohorts. A DL model with eight conventional neural network (CNN) branches for eight MRI sequences was built to predict the presence of MVI, and further combined with clinical parameters for better prediction.Results Among 601 HCC patients, 376 patients were pathologically MVI-absent, and 225 patients were MVI-present. To predict the presence of MVI, the DL model based only on images achieved an area under curve (AUC) of 0.915 in the testing cohort as compared to the radiomics model with an AUC of 0.731. The DL combined with clinical parameters (DLC) model yielded the best predictive performance with an AUC of 0.931. For the MVI grade stratification, the DLC models achieved an overall accuracy of 0.793. Survival analysis demonstrated that the patients with DLC-predicted MVI status were associated with the poor overall survival (OS) and recurrence-free survival (RFS). Further investigation showed that hepatectomy with the wide resection margin contributes to better OS and RFS in the DLC-predicted MVI-present patients.Conclusion The proposed DLC model can provide a non-invasive approach to evaluate MVI before surgery, which can help surgeons make decisions of surgical strategies and assess patient’s prognosis.

To identify drugs that are potentially used for the treatment of COVID-19, the potency of 1403 FDA-approved drugs were evaluated using a robust pseudovirus assay and the candidates were further confirmed by authentic SARS-CoV-2 assay. Four compounds, Clomiphene (citrate), Vortioxetine, Vortioxetine (hydrobromide) and Asenapine (hydrochloride), showed potent inhibitory effects in both pseudovirus and authentic virus assay. The combination of Clomiphene (citrate), Vortioxetine and Asenapine (hydrochloride) is much more potent than used alone, with IC50 of 0.34 μM.

Survival rates are usually used to evaluate the effect of cancer treatment and prevention. No study has focused on the characteristic of population-based cancer survival in Fujian, which is regarded as one of the high-risk areas of cancer in China. This study aims to analyze the 5-year relative survival of patients in Fujian Province using population-based cancer registry data. A total of 8 population-based registries in Fujian Province reported cancer cases diagnosed in 2012-2014. Relative survival was calculated as the ratio between observed survival and expected survival. The 5-year relative survival for all cancers combined was 36.19% and the age-standardized 5-year relative survival for all patients was 31.80%. Females had higher relative survival than males (38.90% and 27.00%). The patients in urban areas had higher relative survival than those in rural areas (32.34% and 31.29%). Lung, gastric, liver, colorectal, and esophageal cancers were the five most common cancers, with 5-year relative survival below 50%. This is the first study that evaluated the population-based cancer relative survival in Fujian, China. Our study suggests that the overall survival of cancer patients in Fujian Province is poor. Furthermore, the results of this study can be used as a baseline for further research in Fujian, and provide important evidence for cancer etiology research.

The dynamics, duration, and nature of immunity produced during SARS-CoV-2 infection are still unclear. Here, we longitudinally measured virus-neutralising antibody, specific antibodies against the spike (S) protein, receptor-binding domain (RBD), and the nucleoprotein (N) of SARS-CoV-2, as well as T cell responses, in 25 SARS-CoV-2-infected patients up to 121 days post-symptom onset (PSO). All patients seroconvert for IgG against N, S, or RBD, as well as IgM against RBD, and produce neutralising antibodies (NAb) by 14 days PSO, with the peak levels attained by 15–30 days PSO. Anti-SARS-CoV-2 IgG and NAb remain detectable and relatively stable 3–4 months PSO, whereas IgM antibody rapidly decay. Approximately 65% of patients have detectable SARS-CoV-2-specific CD4+ or CD8+ T cell responses 3–4 months PSO. Our results thus provide critical evidence that IgG, NAb, and T cell responses persist in the majority of patients for at least 3–4 months after infection., Understanding if lasting immune responses can be induced by SARS-CoV-2 infection is important for controlling the COVID-19 pandemic. Here, the authors show, in a cohort of 25 patients, that IgG and T cell responses, as well as neutralising antibody, are still detectable against various SARS-CoV-2 proteins 3 months post-symptom onset, while IgM levels largely wane at this time.

Background: The performance of liver stiffness measurement (LSM) obtained using FibroScan can be affected by several factors and cut-off values were different for fibrosis caused by various etiologies. The aim of this study was to evaluate the diagnostic performance of LSM in nonalcoholic fatty liver disease (NAFLD) patients with abnormal glucose metabolism and investigate whether LSM value would be affected by metabolic indicators. Methods: The study involved 91 NAFLD patients with abnormal glucose metabolism who underwent liver biopsy. The receiver operator characteristic (ROC) curves were used to evaluate the diagnostic accuracy, with the biopsy results taken as the gold standard. Multivariate linear regression and subgroup analysis were used to determine the correlated indicators.Results: The areas under ROC curves (AUROCs) of LSM values in diagnosing fibrosis stage≥1, 2, 3 and 4 were 0.793 (95% confidence interval [CI]: 0.695-0.871), 0.764 (95% CI: 0.663-0.846), 0.837 (95% CI: 0.744-0.906) and 0.902 (95% CI: 0.822-0.955), with cut-off values of 6.3, 7.6, 8.3 and 13.8 kPa, respectively. Multivariate linear regression demonstrated that HbA1c (β=0.200, p=0.038) and AST (β=0.200, p=0.044) were independently associated with LSM value after adjustment for fibrosis stage from liver biopsy. Subgroup analysis revealed that LSM values were slightly higher in patients with HbA1c ≥7% than those HbA1c 2 than those BMI 2.Conclusions: FibroScan was valuable for the evaluation of liver fibrosis in NAFLD patients with abnormal glucose metabolism. It was recommended for evaluating severe fibrosis, especially for excluding advanced fibrosis. Glucose metabolism state may affect LSM value.

Background: The existing risk stratification systems for gastrointestinal stromal tumors (GISTs) are mainly based on tumor size measurements without consideration of the cystic or necrotic components within tumors and mitosis index. We aimed to develop and validate a new model to predict recurrence-free survival (RFS) after surgical resection of primary gastric GISTs. Methods: In this study, 210 consecutive patients who underwent preoperative contrast-enhanced CT and surgery were retrospectively analyzed and divided into training (n = 132) and validation (n = 78) datasets. Semiautoquantitative CT parameters were evaluated. Moreover, morphological CT features and pathological mitosis index were reviewed. Univariate and multivariate Cox regression analyses were performed to develop a novel model whose performance was evaluated and compared with that of the modified National Institutes of Health (NIH) risk stratification. Findings: The model comprised direct invasion (p= 0·003; hazard ratio (HR) = 3·965), enhanced tissue volume (p= 0·012; HR = 1·432), and mitosis index (p= 0·012; HR = 1·013), which showed better predictive performance than the modified NIH risk stratification in the training (concordance index (C-index) = 0·837 vs. 0·751; p= 0·005) and validation (C-index = 0·830 vs. 0·726; p= 0·028) datasets for 3- and 5-year RFS. Decision curve analysis revealed that the model had a greater overall net benefit than the modified NIH risk stratification. Interpretation: Our prognostic model’s performance was superior to that of the modified NIH risk stratification for predicting RFS after curative resection of primary gastric GISTs. Funding: This paper is supported by China International Medical Foundation (grant number Z-2014-07- 2003-04); Shanghai Municipal Key Clinical Specialty (grant number shslczdzk03202); Clinical Research Plan of SHDC (grant number SHDC2020CR1029B). Declaration of Interest: None to declare. Ethical Approval: Ethics approval was obtained for this study in Zhongshan Hospital, Fudan university (approval number B2016-075R).

Background The performance of liver stiffness measurements (LSMs) obtained using FibroScan can be affected by several factors, and cut-off values are different for fibrosis caused by various aetiologies. The study aims to evaluate the diagnostic accuracy of LSM in nonalcoholic fatty liver disease (NAFLD) patients with abnormal glucose metabolism and investigate whether the LSM value would be affected by metabolic indicators. Methods The study involved 91 NAFLD patients with abnormal glucose metabolism who underwent liver biopsy. The diagnostic accuracy of LSM value was evaluated by the receiver operator characteristic (ROC) curves, with the biopsy results taken as the gold standard. Multivariate linear regression and subgroup analysis were performed to determine the correlated indicators. Results The areas under the ROC curves (AUROCs) of LSM values for detecting fibrosis stage ≥1, 2, 3 and 4 were 0.793 (95% confidence interval [CI]: 0.695–0.871), 0.764 (95% CI: 0.663–0.846), 0.837 (95% CI: 0.744–0.906) and 0.902 (95% CI: 0.822–0.955), with cut-off values of 6.3, 7.6, 8.3 and 13.8 kPa, respectively. Multivariate linear regression demonstrated that haemoglobin A1c (HbA1c, β = 0.205, P = 0.026) and alanine aminotransferase (ALT, β = 0.192, P = 0.047) were independently associated with the LSM value after adjustment for fibrosis stage, ballooning and inflammation grade from liver biopsy. Subgroup analysis demonstrated that LSM values were slightly higher in patients with HbA1c ≥7% than in those with HbA1c 2 than in those with BMI 2. Conclusions FibroScan was valuable for the evaluation of liver fibrosis in NAFLD patients with abnormal glucose metabolism. FibroScan is recommended to evaluate severe fibrosis, especially to exclude advanced fibrosis. Glucose metabolism state may affect LSM values.

To investigate whether an isotropic T1-weighted gradient echo (T1-GRE) sequence using a compressed sensing (CS) technique during liver magnetic resonance imaging (MRI) can improve the image quality compared to that using a standard parallel imaging (PI) technique in patients with hepatocellular carcinoma (HCC).Forty-nine patients with single pathologically confirmed HCC were included in the prospective study, who underwent a 3.0 T MRI including the two T1-GRE sequences (CS and PI). Qualitative analysis including the relative contrast (RC) of liver-to-lesion, liver-to-portal vein and liver-to-hepatic vein on pre-contrast and postcontrast (delayed phase) images were calculated. Respiratory motion artifact, gastrointestinal motion artifact and overall image quality were scored by using a 4-point scale.RC of liver-to-lesion, liver-to-portal vein and liver-to-hepatic vein measured on both pre-contrast and postcontrast phase images were significantly higher for CS than for PI. The scores of overall image quality was comparable between PI and CS (3.98 ± 0.10vs 3.96 ± 0.13, P = 0.083 for pre-contrast; 3.96 ± 0.16 vs 3.93 ± 0.17, P = 0.132 for postcontrast, respectively). The scores of gastrointestinal motion artifact was significantly higher for PI than for CS (3.92 ± 0.21 vs 3.69 ± 0.33 for pre-contrast; 3.86 ± 0.21 vs 3.59 ± 0.30 for postcontrast, P 0.001 for both). The scores of respiratory motion artifact was significantly higher for PI only in pre-contrast sequence (3.97±0.11 vs 3.89 ± 0.22, P = 0.002 for pre-contrast; 3.95 ± 0.18 vs 3.90 ± 0.22, P = 0.083 for postcontrast, respectively).Compared to the standard PI sequence, the CS technique can provide greater contrast in displaying HCCs and hepatic vessels in MRI without compromise of overall image quality.

Background. Benvitimod cream, a novel synthetic small molecule, was effective in treating mild-to-moderate plaque psoriasis. We conducted a phase III clinical trial to assess the efficacy and safety of benvitimod cream in patients with mild-to-moderate plaque psoriasis. Methods. We randomly assigned 686 patients (2:1:1) to receive 1% benvitimod cream, 0.005% calcipotriol ointment or placebo twice a day for 12 weeks. The primary efficacy end points were the percentage of patients with a 75% or greater reduction from baseline in the psoriasis area and severity index (PASI 75) score and with a score of 0 or 1 in static physician's global assessment (sPGA) at week 12. Results. The results showed that 50.4% of patients in the benvitimod group achieved PASI 75, which was significantly higher than that in the calcipotriol (38.5%, P

Objective: This study aimed to investigate if CT-detected extramural venous invasion (ctEMVI) was associated with the presence of lymph node metastasis (LNM) and survival outcomes in patients with gastric cancer. Methods: We retrospectively reviewed 105 patients with pathologically proved gastric cancer who underwent pre-operative CT examinations and received radical gastrectomy with extended lymphadenectomy. Differences in CT characteristics between the LNM-positive and -negative groups were assessed by two observers. Binary logistic regression analysis was performed to determine the risk factors of lymph node metastasis in gastric cancer. Progression-free survival analysis was performed by Kaplan–Meier method. Results: Two observers reached good inter-reader agreements in ctEMVI and ctN status with κ values of 0.711 and 0.751, respectively. The frequency of ctEMVI-positive status was 58.1% (61/105) in patients with gastric cancer. The LNM-positive group showed higher possibility of ctEMVI-positive status (81.7% vs 26.7%, p＜0.001), larger tumor volume (mean volume, 40.77 vs 22.09 mL, p＜0.001), poor tumor margin (45.0% vs 26.7% , p = 0.054) and high enhancement on arterial phase (43.3% vs 26.7%, p = 0.023) and venous phase (60.0% vs 44.4%, p = 0.048), than LNM-negative group. In multivariate analysis, ctEMVI status and tumor volume were identified as independent risk factors for lymph node metastasis with odds ratio (OR) of 9.804 (95% CI, 3.076－31.246; p＜0.001) and 1.030 (95% CI, 1.001－1.060; p = 0.044). CT-detected EMVI presented better diagnostic efficiency for lymph node metastasis than CT-defined N status, with sensitivity (81.7% vs 70.0%), specificity (73.3% vs 71.1%), accuracy (78.1% vs 70.5), PPV (80.3% vs 76.4%), and NPV (75.0% vs 64.0%), respectively. Kaplan–Meier curves showed that patients with positive ctEMVI findings has lower PFS rate than patients with negative ctEMVI findings (Log-rank test, p = 0.007). Conclusion: CT-detected EMVI was significantly associated with lymph node metastasis and progression free survival in patients with gastric cancer. Compared to CT-defined N status, ctEMVI provided superior diagnostic performance to predict pathologic Nstatus. Advances in knowledge: Our study proved that CT-detected EMVI is a promising imaging marker to predict lymph node metastasis and poor prognosis, which may contribute to the precise evaluation of gastric cancer before surgery.

Objective Accuracy of preoperative T-staging for colon cancer remains disappointing and may potentially influenced by patients’ individual characteristics including visceral adipose tissue (VAT). We sought to clarify the impact of VAT on the accuracy of T-staging by CT. Methods This study of 216 consecutive patients who underwent elective surgery was conducted in a single cancer center, to control other potentially confounding factors. Patients were divided into accurate- and mis-staging groups according to the comparison between preoperative CT-defined (cT) and postoperative pathologic T-stages (pT). Patients’ individual characteristics, including CT-based VAT at L2/L3 level, age, sex, body mass index (BMI), tumor location, present of bowel obstruction and pathologic subtype, were compared between the two groups. Association between VAT and mis-staging was assessed using multivariate logistic regression to adjust for confounders. Results Of the 216 patients, 84 (39%) were mis-staged by CT. The mean VAT in accurate-staging group was significantly higher than that in mis-staging group (146.8 ± 66.1 cm2 vs 98.1 ± 44.7 cm2, P Conclusion A lower-VAT is associated with an increased probability of inaccurate clinical T-staging in colon cancer.