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This brief proposes a low voltage ultra-low power 10-bit 100-MS/s successive approximation register (SAR) analog-to-digital converter (ADC). To overcome the performance degradation due to the signal-related current fluctuation under lower supply voltage, an adaptive-biasing comparator with current self-compensation (CSC) technique is proposed to obtain a constant working current, reducing the minimum supply voltage from 0.7V in conventional ADCs to 0.55V. Since full-scale range shrinks with the supply voltage, voltage undershoot in power rail caused by capacitor digital-to-analog converter (C-DAC) deteriorates effective-number-of-bits (ENOB). Conventional solutions involve enhanced regulators and large decoupling capacitors, which cost remarkable power dissipation and large chip area. This brief presents a pulse-injection undershoot compensation technique which reduces the DAC-related supply fluctuation from a typical 15mV to 1.8mV, and improves the ENOB by 0.4 bit. The prototype was fabricated in TSMC 28nm HPC CMOS technology. The proposed SAR ADC achieves an SNDR of 54.7dB and an SFDR of 68dB with the power consumption of 0.16mW under 0.55V supply voltage, a figure of merit (FoM) of 3.6-fJ/conversion-step is achieved. The chip area of the ADC core is 130μm×225μm.

With the explosion of GPS-enabled smartphones and social media platforms, geo-social networks are increasing as tools for businesses to promote their products or services. Influence maximization, which aims to maximize the expected spread of influence in the networks, has drawn increasing attention. However, most recent work tries to study influence maximization by only considering geographic distance, while ignoring the influence of users' spatio-temporal behavior on information propagation or location promotion, which can often lead to poor results. To relieve this problem, we propose a Similarity-aware Influence Maximization (SIM) model to efficiently maximize the influence spread by taking the effect of users' spatio-temporal behavior into account, which is more reasonable to describe the real information propagation. We first calculate the similarity between users according to their historical check-ins, and then we propose a Propagation to Consumption (PTC) model to capture both online and offline behaviors of users. Finally, we propose two greedy algorithms to efficiently maximize the influence spread. The extensive experiments over real datasets demonstrate the efficiency and effectiveness of the proposed algorithms. With the explosion of GPS-enabled smartphones and social media platforms, geo-social networks are increasing as tools for businesses to promote their products or services. Influence maximization, which aims to maximize the expected spread of influence in the networks, has drawn increasing attention. However, most recent work tries to study influence maximization by only considering geographic distance, while ignoring the influence of users' spatio-temporal behavior on information propagation or location promotion, which can often lead to poor results. To relieve this problem, we propose a Similarity-aware Influence Maximization (SIM) model to efficiently maximize the influence spread by taking the effect of users' spatio-temporal behavior into account, which is more reasonable to describe the real information propagation. We first calculate the similarity between users according to their historical check-ins, and then we propose a Propagation to Consumption (PTC) model to capture both online and offline behaviors of users. Finally, we propose two greedy algorithms to efficiently maximize the influence spread. The extensive experiments over real datasets demonstrate the efficiency and effectiveness of the proposed algorithms.

Edge-preserving image filtering is an essential task in computational photography and imaging. In this paper, we propose a simple yet effective global edge-preserving filter based on soft clustering, and we propose a novel soft clustering algorithm based on a restricted Gaussian mixture model. Given specified parameters, the soft clustering process is firstly performed on the image to derive the partition matrix, from which the affinity matrix is then constructed for filtering. The filtering output is calculated as the weighted average of the pixels in the local window, so the proposed filter could suppress the intensity shift artifacts that impede most global filters. Besides, the weights in the proposed filter are derived by clustering, which properly separates dissimilar pixels, so the proposed filter could handle the halo artifacts that haunt many local filters. Moreover, our filter provides flexible control over the amount of smoothing that is deficient in the deep learning-based filters. Besides the efficacy in smoothing, the proposed filter naturally has low computational complexity. Qualitative and quantitative results suggest that the proposed filter benefits various applications, including edge-preserving smoothing, image enhancing, flash/non-flash fusion, HDR tone mapping, and dehazing.

The study of Frequency Selective Surface (FSS) by Direct ink writing (DIW) has attracted much attention due to the convenience and effectiveness of 3D printing technology. However, the limited printing precision of DIW has heavily restricted its applications as the electromagnetic performance is highly sensitive to it, especially the precision at the microscale. Herein, the ultra-high printing precision of FSS was achieved through DIW by the uniformly dispersed graphene sheets to deeply modify the rheological behavior and the steric hindrance effect. Thus, the highly precision of the printed filament width as thin as 67 μm with a space of only 42 μm were achieved, which is difficult for conventional DIW, and no structural distortion is found after 3D printing, no matter it was 2D printed on a flat surface or the sharply skewed hook face, or even 3D printed to architectural structures. According to the highly improved precision, the electromagnetic performance matching between the designed model and the printed physical FSS device was perfectly achieved, reducing the center frequency error less than 0.3 GHz, and the transmission coefficient error less than 0.046. Our work promises an effective and easy preparation of high-quality FSS from the aid of graphene.

The widespread use of positioning devices has given rise to many trajectories, with each having three explicit attributes: user ID, location ID, and time-stamp and an implicit attribute: activity type (akin to “topic” in text mining). To model these trajectories, existing works learn different attribute representations by either introducing latent activity types based on topic models or transforming the location and time context into a low-dimensional space via embedding techniques. In this paper, we propose a holistic approach named Human Mobility Representation Model (HMRM) to simultaneously produce the vector representations of all four (explicit and implicit) attributes. The merits of HMRM lie in that: (1) it models the latent activity types and learns trajectory attribute embeddings in an integrated manner, and (2) it connects the activity-related distributions and these attributes embeddings by adding a newly designed collaborative learning component, and makes them mutually exchanged to take the best of both worlds. We apply HMRM to both unsupervised and supervised tasks including two activity evaluation tasks and two embedding evaluation tasks, on two real check-in datasets collected from Foursquare. Experimental results show that HMRM could not only improve the performance of capturing latent activity types, but also learn better trajectory embeddings.

Aims The ESC/EACTS myocardial revascularization guidelines recently standardized the definition of patients at high ischemic risk (HIR). However, the ability of ESC/EACTS-HIR criteria to stratify ischemic and bleeding risk in a contemporary real-world East Asian cohort remains unexplored. Methods A total of 10,167 consecutive patients undergoing PCI from prospective Fuwai PCI Registry (January 2013 to December 2013) were reviewed. ESC/EACTS-HIR features was defined as having at least one of the eight clinical and angiographic characteristics. The primary ischemic endpoint was target vessel failure (cardiac death, target vessel myocardial infarction [MI], or target vessel revascularization [TVR]); bleeding outcome was assessed using the BARC type 2, 3, or 5 bleeding. Median follow-up was 29 months. Results Compared with non-HIR patients, HIR patients (n=5,149, 50.6%) were associated with increased risk for target vessel failure (adjusted hazard ratio [HRadjust]: 1.48 [1.25-1.74]) and patient-oriented composite outcome (HRadjust: 1.44 [1.28-1.63]), as well as cardiac death, MI, and TVR. By contrast, the risk of clinically relevant bleeding was not significantly different between the two groups. (HRadjust: 0.84 [0.66-1.06]). Greater than or equal to three implanted stents and diabetic patients with diffuse multivessel coronary disease emerged as independent predictors for long-term adverse outcomes. There was no significant interaction between high bleeding risk (HBR) status and clinical outcomes associated with ESC/EACTS-HIR criteria (all Pinteraction ＞0.05). Conclusion The ESC/EACTS-HIR features identified patients at increased risk of thrombotic events, including cardiac death, but not for clinically relevant bleeding. Importantly, HBR did not modify cardiovascular risk subsequent to patients with ESC/EACTS-HIR features, suggesting its potential clinical applicability in tailoring antithrombotic therapy.

Objectives: To investigate the mechanism of astragaloside IV (AS-IV) inhibiting the invasion and metastasis of vulvar squamous cell carcinoma (VSCC). Material and methods: MTT and plate colony-formation assays were used to examine the cell proliferation of VSCC (SW962 cell line). Transwell and scratch wound-healing assays were used to analyse cell migration and invasion. Western blot was used to detect the expression of relevant proteins in terms of cell proliferation, invasion and metastasis, as well as the TGF-β1/FAK/AKT signaling pathway. Results: The results showed that AS-IV inhibited the proliferation of SW962 cells in a concentration-dependent manner, as demonstrated by the upregulation of P53 and P21 expression and the downregulation of cyclin D1 expression. AS-IV decreased the ability of cell invasion and metastasis by the downregulation of MMP-2 and MMP-9 expression. When TGF-β1 was added to SW962 cells, the expression of the N-cadherin and Vimentin were upregulated and that of the E-cadherin was downregulated. Subsequently, fibroblast-like elongated spindle-shaped cells appeared, which suggests that TGF-β1 could induce EMT in SW962 cells. Furthermore, the expression of p-FAK, p-AKT, MMP-2 and MMP-9 were upregulated. The expression of these proteins exhibited the opposite effect after AS-IV intervention. Cell invasion and metastasis were suppressed. Conclusions: AS-IV inhibits cell invasion and metastasis in VSCC through the TGF-β1/FAK/AKT signalling pathway.

End to end learning-based image dehazing methods tend to over-dehaze or under-dehaze in real scenes due to the inefficient feature extraction and feature fusion. In this letter, we propose a multiscale supervision guided context aggregation network (MSGCAN) based on two principles: improving feature extraction and enhancing feature mapping. To improve feature extraction, an attention guided context aggregation (AGCA) module is adopted to merge context features extracted by several residual dense blocks (RDB). Moreover, we output these aggregated context features on each scale and form multiscale supervision to enhance feature mapping and ensure the extracted features on each scale contain more realistic details. The experimental results show that the proposed MSGCAN performs better than other state-of-the-art dehazing methods in both synthetic and real-world scenes.

Aim. To explore the expression levels of miR-210, miR-137, and miR-153 in patients with acute cerebral infarction. Material and Methods. 76 patients with acute cerebral infarction treated in our hospital from April 2016 to October 2017 were enrolled as the observation group. Another 64 normal patients were selected as the control group. The patients were divided into the death and survival groups based on 1-year mortality of patients. qRT-PCR was used to detect the expression of miR-210, miR-137, and miR-153 in the serum of each group. Receiver operating characteristic (ROC) curve was employed to analyze the diagnostic value and predictive value of miR-210, miR-137 and miR-153 death in patients. The correlation between miR-210, miR-137, and miR-153 in the serum of the observation group was analyzed by Pearson’s test. Results. Levels of miR-210 and miR-137 in the observation group were significantly lower than those in the control group, while levels of miR-153 in the observation group were significantly higher than those in the control group (all P < 0.05 ). The ROC curve of diagnosis of acute cerebral infarction showed that the area under curve of miR-210 was 0.836, that of miR-137 was 0.843, and that of miR-153 was 0.842. The 1-year survival rate was 71.05%. The 1-year survival of the low-expression group of miR-210 and miR-137 was significantly lower than that of the high-expression group, while the 1-year survival of the low-expression group of miR-153 was significantly higher than that of the high-expression group (all P < 0.05 ). The ROC curve for predicting death showed that the area under curve of miR-210 was 0.786, that of miR-137 was 0.824, and that of miR-153 was 0.858. Pearson’s correlation analysis showed that the expression of miR-210 was positively correlated with that of miR-137, while miR-137 was negatively correlated with that of miR-153 and miR-210 was negatively correlated with that of miR-153. Conclusion. miR-210, miR-137, and miR-153 have a certain value in the diagnosis and prediction of 1-year death of acute cerebral infarction and may be potential diagnostic and predictive indicators.

Recently, a new IoT structure known as the Artificial Intelligence of Things (AIoT) comes into play. Crowd counting is a promising field in data analysis of AIoT, however, due to poor transparency and high data security risks, developing a novel network architecture that can precisely elevate the counting of heavy crowd is extremely difficult. In addition, the fusion of IoT and AI also poses several challenges. The focus of this work is on the effective design of IoT framework and deep learning algorithm towards security of smart city. The system can be used to estimate the crowd traffic in public places, and can prevent the occurrence of congestion, stampede and other accidents, such as stations, airports, large-scale exhibitions, tourist attractions and other places. The constructed system contains video collection, upload and display as well as data analysis and early warning operation at the embedded device end, and automatically tracks densely crowd areas by controlling the video monitoring device. Moreover, the cloud platform can be controlled through the network. Our proposed algorithms are composed of two main aspects, i.e., division and focus. Firstly, we propose a novel density-adaptive Gaussian kernel to elevate the quality of density maps. Then, we propose a module based on conditional random fields for feature fusion. Finally, we propose a block segmentation module to predict our segmentation results and extract the context-aware information in segmentation stage. Experiments on our captured data, the Shanghai Tech, UCF_CC_50 and UCF_QNRF datasets demonstrate that our solution has obtained better performance and lower count errors over the state of the art.

In augmented reality, it is important to achieve visual consistency between inserted virtual objects and the real scene. As specular and transparent objects can produce caustics, which affect the appearance of inserted virtual objects, we herein propose a framework for differential rendering beyond the Lambertian-world assumption. Our key idea is to jointly optimize illumination and parameters of specular and transparent objects. To estimate the parameters of transparent objects efficiently, the psychophysical scaling method is introduced while considering visual characteristics of the human eye to obtain the step size for estimating the refractive index. We verify our technique on multiple real scenes, and the experimental results show that the fusion effects are visually consistent.

Currently, advancements in separator technology for lithium-ion batteries (LIBs) have been developed due to their widespread use and key role in ion transportation. Nevertheless, there is still a need for ensuring the operation safety, service life, and user's experience of the batteries. In order to avoid the safety issues caused by the elevating temperature during working process, it is essential to endow separators with thermal shutdown function, which can timely cut off the current and prevent the electrodes from contacting. At the same time, the demand for recycling and sustainability of separators are also growing. Therefore, functional separators with irreversible or reversible thermal shutdown ability came out for future utility and manufacture. In this review, we aim to provide a comprehensive analysis of the technologies employed to enhance the safety of LIBs via highlighting the recent achievements in separators with irreversible thermal protection fabricated by different methods and mechanisms. Moreover, we summarize the intelligent materials that are able to take actions and self-adapt in reversibly thermal protection separators. Current research directions and challenges associated with the use of these LIBs separators and future perspectives in battery thermal protection are also provided. We hope such a review could provide inspiration for the separator researches dedicated on the cyclic utilization, high safety and high performance for future battery developments.

Aiming to deal with underwater localization for small-size robots in GPS-denied and structured environment, this paper proposed a novel multi-sensor fusion-based self-localization system using low-cost sensors. Based on multi-sensor information fusion, an Extended Kalman Filter (EKF) is utilized to synthesize the multi-source information from an Inertial Measurement Unit (IMU), optical flow, pressure sensor and ArUco markers, which enables the robot obtain a highly precise positioning. This method also can reduce the location drift over time owing to the loss of markers in pure markers-based localization. Specially, a velocity correction model is proposed using the angle information obtained by IMU, which can compensate optical flow-based velocity estimation errors caused by robot posture changes. Finally, to validate the performance of the proposed self-localization system, simulations are conducted using Gazebo simulator on the robot operating system (ROS). Moreover, a series of experiments in an indoor swimming pool are presented. Results of the proposed method and dead reckoning are compared in simulation and experiment to demonstrate the robustness and feasibility of the proposed localization system.

Diabetes is one of the most disturbing chronic diseases in the world. The improvement of treatment efficiency brought by self-monitoring of blood glucose can relieve symptoms and reduce complications, which is considered as the gold standard of diabetes diagnosis and nursing. Compared to the traditional finger pricking measurement with painful and discontinuous processes, continuous blood glucose monitoring (CGM) presents superior advantages in wearable and continuous assessment of blood glucose levels. However, widely used implantable CGM systems at present require implantation operation and are highly invasive, so it is hard to be accepted by users. Except for the blood, available fluids in humans, such as interstitial fluid (ISF), sweat, tears and saliva, also contain glucose associated with blood sugar and can be extracted more easily. Therefore, these more accessible fluids are expected to realize minimized traumatic blood glucose monitoring. This review introduces the latest development of wearable minimally-/non-invasive CGM device, focusing on the types of blood substitute biological fluid and suitable monitoring approaches. We also analysis the merits and drawbacks of each method, and discuss the properties such as sensitivity, stability and convenience of each meter. Beyond highlighting recent key work in this field, we discuss the future development trend of wearable minimally-/non-invasive glucose meters.

BACKGROUND Recent studies have revealed that the nasal microbiota in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is profoundly altered and is correlated with systemic inflammation. However, little is known regarding whether the microbiota can be utilized to predict nasal polyp recurrence. This study is aimed to determine whether altered nasal microbiota constituents could be used as biomarkers to predict CRSwNP recurrence. METHODS Nasal microbiota constituents were quantified and characterized using bacterial 16S ribosomal RNA gene sequencing. Selected features for least absolute shrinkage and selection operator regression-based predictors were the nasal microbiota community composition and CRSwNP patient clinical characteristics. The primary outcome was recurrence, which was determined post-admission. RESULTS By distinguishing recurrence-associated nasal microbiota taxa and exploiting the distinct nasal microbiota abundance between patients with recurrent and non-recurrent CRSwNP, we developed a predictive classifier for the diagnosis of nasal polyps' recurrence with 91.4% accuracy. CONCLUSIONS Key taxonomical features of the nasal microbiome could predict recurrence in CRSwNP patients. The nasal microbiome is an understudied source of clinical variation in CRSwNP and represents a novel therapeutic target for future prevention and treatment.

AI-driven edge computing is a development trend of the Industrial Internet of Things (IIoT). However, most existing solutions ignore the limitations of flexibility, security, and real-time performance caused by the rigid architecture of industrial control systems and the “end-to-end” computing paradigm of IIoT. This paper proposes an edge computing scheme for AI-driven IIoT. Specifically, we design a novel software-defined industry control architecture to enhance the flexibility and security of IIoT edge systems. The architecture decouples the software and hardware of Industrial devices by virtualization and industrial modeling technologies, which improves the flexibility and programmability of IIoT edge systems and alleviates the privacy issue of industrial data. Moreover, we adopt a new edge computing method, dispersed computing, to AI-driven IIoT to achieves better real-time performance and resource utilization. The proposed computing method optimizes the computing and networking of AI-driven industrial applications jointly by a multiobjective optimization scheduling algorithm. We also evaluated the performance of our scheme through experiments.

Carotid artery stenosis (CAS) is one of the leading causes of ischemic stroke. However, knowledge of the changes in the plaque itself is lacking. Information about the ultrasound and clinical features of CAS will help elucidate the changes in prognostic and risk factors.We evaluated 736 patients with carotid stenosis for an average 18-month follow-up. According to their degree of CAS stenosis, patients were allocated to one of three groups: regression (n=125), stable (n=443), or progression (n=168). An ordinal regression analysis was used to determine the risk factors for atherosclerosis progression. A logistic regression was subsequently applied to investigate the effects of CAS stenosis on cerebrovascular events after adjusting for various factors.The progression group had more male patients (P=0.02), hypoechoic plaque (P0.01), high-risk high sensitivity C-reactive protein (hs-CRP) (P=0.02), ulcerative plaque (P=0.05), and hyperlipidemia (P=0.05) than the other two groups. There were no significant differences in residual ultrasound and clinical features among the three groups, including age, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), intima-media thickness (IMT), body mass index (BMI), diabetes mellitus (DM), hypertension (HTN), coronary heart disease (CHD), statin use, ulcerative plaque. The ordinal regression analysis identified hypoechoic plaque (OR, 1.53; 95% CI: 1.14-2.05; P0.01) and high-risk hs-CRP (OR, 1.75; 95% CI: 1.17-2.61; P0.01) as independent risk factors for CAS progression. Logistic regression analysis revealed that the stroke/transient ischemic attack adjusted odds ratio was 1.80 (95% CI: 1.03-3.13) in the progression group.High-risk hs-CRP and hypoechoic plaque are independently associated with CAS progression. The progression of carotid stenosis is associated with a high risk of cerebrovascular events.

Hydrostatic thrust bearings have been applied in high speed and heavy load machine tools because they provide superior characteristics such as higher positional accuracy, greater stability, and lower friction. The energy consumption of the fluid system exceeds 40% of the total energy consumption of the machine tools To reduce the energy consumption, it is usually necessary to optimize comprehensive tribological properties of multi-pad hydrostatic thrust bearing in CNC vertical processing equipment from the perspective of the oil recess structure. Effects of oil recess structural parameters on comprehensive tribological properties in multi-pad hydrostatic thrust bearing are investigated using CFD (Computational Fluid Dynamics) and lubrication theory. Focusing on this problem, this study comprehensively investigates the effects of oil recess shape, oil recess depth, land width on the tribological properties of hydrostatic thrust bearing using numerical simulation method. The relationships between the optimal comprehensive tribological properties and structural parameters are determined. An experimental rig is set up to verify the correctness of the numerical simulation method. The results indicate that to get an optimal comprehensive performance from hydrostatic bearing based on low power consumption, it is necessary to choose a proper of oil recess structural parameters.

Summary Background The use of magnetically controlled capsules for gastroscopy is in the early stages of clinical adoption. We aimed to evaluate the safety and efficacy of a fully automated magnetically controlled capsule endoscopy (FAMCE) system in clinical practice for gastroscopy and small bowel examination. Methods We did a prospective, comparative study to evaluate the safety and efficacy of FAMCE. Patients from two hospitals in Chongqing, China were consecutively enrolled. Eligible participants were aged 18–80 years with suspected gastric pathology and no previous surgery. Participants underwent FAMCE for screening of gastric lesions, then conventional transoral gastroscopy 2 h later, and stomach examination results were compared. The primary outcome was the rate of complete detection of gastric anatomy landmarks (cardia, fundus, body, angulus, antrum, and pylorus) by FAMCE. Secondary outcomes were the time required for gastric completion by FAMCE, the rate of detection of gastric lesions by FAMCE compared with conventional transoral gastroscopy, and the rate of complete small bowel examination. Adverse events were also evaluated. The study was registered in the Chinese Clinical Trial Registry, ChiCTR2000040507. Findings Between May 12 and Aug 17, 2020, 114 patients (mean age 44·0 years [IQR 34·0–55·0]; 63 [55%] female) were enrolled. The rate of complete detection of gastric anatomical structures by FAMCE was 100% (95% CI 99·3–100·0). The concordance between FAMCE and conventional transoral gastroscopy was 99·61% (99·45–99·78). The mean completion time of a gastroscopy with FAMCE was 19·17 min (SD 1·43; median 19·00, IQR 19·00–20·00), compared with 5·21 min (2·00; 5·18, 3·68–6·45) for conventional transoral gastroscopy. In 114 enrolled patients, 214 lesions were detected by FAMCE and conventional transoral gastroscopy. Of those, 193 were detected by both modalities. FAMCE missed five pathologies (four cases of gastritis and one polyp), whereas conventional transoral gastroscopy missed 16 pathologies (12 cases of gastritis, one polyp, one fundal xanthoma, and two antral erosions). FAMCE was able to provide a complete small bowel examination for all 114 patients and detected intestinal lesions in 50 (44%) patients. During the study, two (2%) patients experienced adverse events. No serious adverse events were recorded, and there was no evidence of capsule retention. Interpretation The performance of FAMCE is similar to conventional transoral gastroscopy in completion of gastric examination and lesion detection. Furthermore, it can provide a complete small bowel examination. Therefore, FAMCE could be effective method for examination of the gastrointestinal tract. Funding Chinese National Key Research and Development Program.

Purpose To determine the safety and efficacy of microsphere embolization plus transarterial infusion chemotherapy for the treatment of gastroesophageal junction cancer with hepatic metastasis. Methods Sixty patients with gastroesophageal junction cancer and hepatic metastasis were randomly divided into two groups: group A (treatment group), which was treated with transarterial infusion chemotherapy plus microsphere embolization for gastroesophageal cancer, and with transarterial chemoembolization for hepatic metastasis; and group B (control group), which was treated with transarterial infusion chemotherapy for gastroesophageal cancer, and with transarterial chemoembolization for hepatic metastasis. The chemotherapy regimen used consisted of oxaliplatin plus FUDR. The embolization agent used for gastroesophageal cancer and the hepatic metastasis were Embosphere and ultra-liquefied lipiodol, respectively. Results The median survival time of patients in group A was 19 months, with survival rates at 12, 18, and 24 months of 93.3%, 60.0%, and 23.3%, respectively. The median survival time of patients in group B was 13 months, with survival rates at 12, 18, and 24 months of 60.0%, 30.0%, and 3.3%, respectively. There was a significant difference in survival between the two groups (P = 0.00). One month after treatment, the severity of dysphagia was significantly less in group A, as compared to that in group B (p Conclusion Treatment of gastroesophageal junction cancer with hepatic metastasis by transarterial infusion chemotherapy plus microsphere embolization can rapidly reduce tumor size near the gastroesophageal junction. This treatment is an effective therapeutic option for these patients as it can relieve dysphagia and improve long-term survival rate.

This study investigated the role and molecular mechanisms of the long intergenic non-protein coding RNA 472 (LINC00472) in neuropathic pain using a chronic constrictive injury (CCI) rat model.CCI rat model was established and PC12 cells were induced by LPS to simulate neuropathological injury in vivo and in vitro. The levels of LINC00472, miR-300, and high mobility group box protein 1 (HMGB1) in the spinal cord tissue of CCI rats and PC12 pheochromocytoma cells were assessed by qRT-PCR and western blot. The effects of LINC00472 on neuropathic pain in the CCI rats were observed by their pain behavior. ELISA was used to detect the levels of inflammatory cytokines in rat tissues and cells. The molecular mechanisms of LINC00472 were verified by luciferase experiments, RNA immunoprecipitation, and RNA pull down assays.The expression of LINC00472 and HMGB1 were upregulated, and the expression of miR-300 was downregulated in the spinal cord tissues of CCI rats and in PC12 cells. The upregulation of LINC00472 in CCI rats significantly induced the occurrence of neuropathic pain. In addition, downregulation of LINC00472 inhibited the inflammatory response of CCI rats and PC12 cells. This study identified miR-300 as a target gene of LINC00472, and HMGB1 as the target gene of miR-300. Further experiments confirmed that the expression of anti-miR-300 could partially reverse the anti-inflammatory effects and the reduction of neuropathic pain induced by low expression of LINC00472.LINC00472 promotes the progression of neuropathic pain by reducing miR-300 expression and increasing HMGB1 expression. The LINC00472/miR-300/HMGB1 axis may be a novel therapeutic target for neuropathic pain.

Depression endangers people's health conditions and affects the social order as a mental disorder. As an efficient diagnosis of depression, automatic depression detection has attracted lots of researcher's interest. This study presents an attention-based Long Short-Term Memory (LSTM) model for depression detection to make full use of the difference between depression and non-depression between timeframes. The proposed model uses frame-level features, which capture the temporal information of depressive speech, to replace traditional statistical features as an input of the LSTM layers. To achieve more multi-dimensional deep feature representations, the LSTM output is then passed on attention layers on both time and feature dimensions. Then, we concat the output of the attention layers and put the fused feature representation into the fully connected layer. At last, the fully connected layer's output is passed on to softmax layer. Experiments conducted on the DAIC-WOZ database demonstrate that the proposed attentive LSTM model achieves an average accuracy rate of 90.2% and outperforms the traditional LSTM network and LSTM with local attention by 0.7% and 2.3%, respectively, which indicates its feasibility.

With the development of modern economy, traditional sports industry enterprises have also been further developed in the financial business. How to ensure information security and financial risk management is the problem faced by sports companies. Risk assessment is the use of mathematical models to calculate the risk factors established in the previous step to predict possible risks. In response to the above problems, we developed a sports enterprise marketing and financial risk management model based on decision trees and data mining. First, we have established a relevant evaluation index system and data samples through in-depth understanding of the actual marketing and financial problems of sports companies. Second, we use the decision tree algorithm to mine and explore related data samples and conduct risk assessment through related indicators. By using the model to calculate the probability of occurrence of the risk, analyze the degree of damage. Finally, the algorithm of this paper is analyzed and discussed through simulation experiments.

Background The preoperative prognostic nutritional index (PNI) is associated with postoperative complications and long-term survival of various cancers. However, its role in esophageal squamous cell carcinoma (ESCC) is inconclusive. The aim of this study was to identify the prognostic value of PNI in predicting survival in ESCC patients undergoing radical radiotherapy. Methods We retrospectively reviewed 354 ESCC patients undergoing radical radiotherapy. The time-dependent receiver operating characteristics was used to determine the optimal cutoff value. The association between PNI and survival was determined by Kaplan-Meier method and Cox regression model. Propensity score matching was applied to balance the baseline characteristics. Results PNI was positively correlated with hemoglobin (P Conclusions The PNI is a significant and independent predictor for OS of ESCC patients undergoing radical radiotherapy.

ConspectusPolymer-based organic field-effect transistors (OFETs) have attracted great attention owing to their significantly improved performance and the recently emerged prospects for broad applic...

Objective: To explore the value of 18F-fluorodeoxyglucose positron emission tomography–computed tomography (18F-FDG PET/CT) metabolic parameters before and after neoadjuvant chemotherapy in predict...

Background Biliary stones are the most common etiology of acute pancreatitis Cholecystectomy has been accepted as a popular treatment for acute biliary pancreatitis (ABP) to reduce the risk of recurrent complications. However, the precise time of intervention still remains controversial. Objective The aim of this meta-analysis was to compare early and delayed cholecystectomy and determine the most precise timing of cholecystectomy following gallstone pancreatitis. Method Search the publications on comparison the efficacy of early cholecystectomy comparison with delayed cholecystectomy in treatment outcomes of ABP to October, 2018. After rigorous reviewing on quality, the data was extracted from eligible trials. All trials analyzed the summary hazard ratios (HRs) of the endpoints of interest, including survival data and individual postoperative complications. Results A total of 9 trials were met our inclusion criteria. The pooled results indicate that postoperative complications、readmission rate、conversion to an open procedure and cholecystectomy-related morbidity/mortality did not have statistical significance (P > 0.05) between the early and delayed cholecystectomy. While, the length of hospital stay was shorter for the early cholecystectomy group than the delayed group in all included studies. Conclusions Although the efficacy of delayed intervention in terms of inflammation reduction is definite, their adverse events are often major limitations. In the present study, an early cholecystectomy may result in a significantly shortened hospital stays without increased complications or mortality.

Intrahepatic cholangiocarcinoma (ICC) is the second most common liver cancer. Chemotherapy remains the main therapeutic strategy for advanced ICC patients, but chemosensitivity varies individually. Here, we applied cytometry by time-of-flight (CyTOF) to establish the immune profile of peripheral blood mononuclear cells (PBMCs) on the single-cell level at indicated time points before, during, and after chemotherapy. Multiplex immunofluorescence staining was applied to examine the spatial distribution of certain immune clusters. Tissue microarrays (TMAs) were used for prognostic evaluation. A total of 20 ICC patients treated with gemcitabine (GEM) were enrolled in our study, including eight cases with good response (R) and 12 cases with non-response (NR). Tremendous changes in PBMC composition, including an increased level of CD4/CD8 double-positive T cells (DPT), were observed after chemotherapy. Patients with higher level of CD4+CD45RO+CXCR3+ T cells before treatment had a favorable response to chemotherapy. Our study identified a positive correlation between the percentage of T cell subpopulations and clinical response after chemotherapy, which suggests that it is practical to predict the potential response before treatment by evaluating the proportions of the cell population in PBMCs.

OBJECTIVE Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men which is associated with profound metabolic changes. Systematic analysis of the metabolic alterations and identification of new biomarkers may benefit PCa diagnosis and a deep understanding of the pathological mechanism. The purpose of this study was to determine the metabolic features of PCa. METHODS Plasma and urine metabolites from 89 prostate cancer (PCa) patients, 84 benign prostatic hyperplasia (BPH) patients, and 70 healthy males were analyzed using LC-MS/MS and GC-MS. The Orthogonalised Partial Least Squares Discriminant Analysis (OPLS-DA) was used to find the significantly changed metabolites. The clinical value of the candidate markers was examined by receiver operating characteristic curve analysis and compared with prostate-specific antigen (PSA). RESULTS Multivariate statistical analyses found a series of altered metabolites, which related to the urea cycle, tricarboxylic acid cycle (TCA), fatty acid metabolism, and the glycine cleavage system. Plasma Glu/Gln showed the highest predictive value (AUC = 0.984) when differentiating PCa patients from healthy controls, with a higher sensitivity than PSA (96.6% vs. 94.4%). Both Glu/Gln and PSA displayed a low specificity when differentiating PCa patients from BPH patients (

AIMS Renal anaemia is a common complication of chronic kidney disease (CKD). Roxadustat is the first-in-class oral hypoxia-inducible factor prolyl hydroxylase inhibitor for the treatment of anaemia. In this systematic review, we aimed to investigate the efficacy and safety of roxadustat in the treatment of anaemia in CKD patients. METHODS PubMed, Cochrane Library, Embase, and ClinicalTrials.gov databases were searched from their inception to February 2021 for randomised controlled trials (RCTs) that compared the efficacy and safety of roxadustat to those of an erythropoiesis-stimulating agent (ESA) or a placebo in treating anaemia in CKD patients. RESULTS Nine RCTs involving 2743 patients were found. The meta-analysis showed that roxadustat increased haemoglobin (Hb) level by 0.91 g/dL (95% confidence interval [CI]: 0.47-1.34, P

Multisystem inflammatory syndrome in children (MIS-C) associated with coronavirus disease 2019 (COVID-19) has been described to partially overlap with Kawasaki disease (KD) with regard to clinical symptoms, but they are unlikely to share the same disease entity. We conducted a systematic review and meta-analysis to characterize the laboratory parameters of MIS-C compared with those of KD and Kawasaki disease shock syndrome (KDSS). Databases were searched for studies on laboratory parameters of MIS-C (hematology, inflammatory markers, cardiac markers, and biochemistry) through May 31, 2021. Twelve studies with 3073 participants yielded 969 MIS-C patients. In terms of hematology, MIS-C patients had lower levels of leukocytes, absolute lymphocyte count and platelet count (PLT) than KD patients and had similar absolute neutrophil count (ANC) and hemoglobin (Hb) levels. In terms of inflammatory markers, MIS-C patients had higher levels of C-reactive protein, D-dimer and ferritin than KD patients and had similar levels of procalcitonin and erythrocyte sedimentation rate (ESR). In terms of cardiac markers, MIS-C patients had higher CPK levels than KD patients. The levels of N-terminal pro-brain natriuretic peptide, troponin and aspartate aminotransferase were not significantly different between MIS-C and KD patients. In terms of biochemistry, MIS-C patients had lower levels of albumin, sodium and alanine aminotransferase and higher levels of creatinine than KD patients. In addition, MIS-C patients had lower levels of PLT, Hb and ESR and higher levels of ANC than KDSS patients. Measurement of laboratory parameters might assist clinicians with accurate evaluation of MIS-C and further mechanistic research.

Objectives The innate immune system participates in immunoglobulin G4–related disease (IgG4-RD). While the role of innate lymphoid cells (ILCs) in IgG4-RD remains to be elucidated, we aimed to evaluate the phenotype, function and clinical significance of ILCs in IgG4-RD patients. Methods Sixty-seven untreated IgG4-RD patients and 44 age- and sex-matched healthy controls (HCs) were enrolled. Circulating and tissue infiltration of ILCs were detected by flow cytometry. Serum suppression of tumorigenicity 2 (sST2) was detected by ELISA and membrane-bound ST2 (ST2L) was detected by flow cytometry. Tissue infiltration of IL-33 was measured by immunohistochemistry staining. Real-time quantitative PCR was performed to analyse the expression pattern of ILC2-associated genes between HCs and IgG4-RD patients. In addition, correlation analysis was performed in order to evaluate the clinical significance of ILCs in IgG4-RD. Results The frequency of circulating pan ILCs in IgG4-RD patients was lower than in HCs. ILC2s were higher in IgG4-RD compared with HCs, whereas ILC1s were lower in IgG4-RD. sST2 and ST2L were higher in IgG4-RD than in HCs. Infiltration of ILC1s in the submandibular glands of IgG4-RD patients was more prominent than ILC2s. Intracellular secretion of IL-9 was increased in ILC2s of IgG4-RD patients than in HCs. Circulating ILC2s correlated positively with Treg cells and the surface expression of CD154, PD-1 and CXCR5 in ILC2s correlated positively with CD19+ B cells, serum IgG4 levels and serum IgE, respectively. Conclusion ILCs and their subsets were significantly altered in IgG4-RD. We demonstrated the dysfunction of ILC2s in IgG4-RD by phenotype, correlation analysis and function investigation, revealing ILC2s participated in the pathogenesis of IgG4-RD.

Background & aims Preoperative obstructive jaundice is usually associated with higher post-operative mortality. Although external biliary drainage (EBD) has been widely used to relieve obstructive jaundice, the role of bile reinfusion after EBD is still controversial. The aim of our study was to study the effects of biliary obstruction, biliary drainage and bile reinfusion on bile acid metabolism and gut microbiota. Methods Firstly, we created a mice bile drainage collection (BDC) model to simulate the process of biliary obstruction, drainage and bile reinfusion. Then, we analysed the faecal, serum, liver and bile samples to investigate the effects of the process on bile acid profiles and gut microbiota. Finally, we evaluated the clinical effects of bile reinfusion. Results We evaluated the bile acid profiles of faeces, serum, liver and bile of normal mice. During biliary obstruction, secondary bile acids can still be produced, and increased in the liver and serum of mice. Compared with no bile reinfusion, bile reinfusion was beneficial to the recovery of T-ωMCA in the liver and bile, and can restore the colon crypt length shortened by biliary obstruction. Only Ruminococcus_1 proliferated when the biliary obstruction lasted for 12 days. In the clinic, bile reinfusion cannot accelerate the patient's perioperative recovery or prolong long-term survival. Conclusion We have successfully created a mice bile drainage collection model. Short-term bile reinfusion can partially benefit the recovery of the secondary bile acids in the liver and bile, but hardly benefit the patient's perioperative recovery or long-term survival. (247 words).

Objectives To explore the value of detecting the peri-device leak (PDL) and device endothelialization after left atrial appendage closure (LAAC) by cardiac computed tomography (CT) in patients with atrial fibrillation (AF), who underwent Watchman LAAC combined with radiofrequency ablation of atrial fibrillation (AFCA). Methods Patients with symptomatic drug-refractory atrial fibrillation at high risk of stroke (CHA2 DS2 -VASc Score ≥ 2), who underwent Watchman LAAC combined with AFCA in our center from March 2017 to December 2018 were enrolled. Maximum diameter of LAA orifice was determined by preoperative CCTA. A standardized view of Watchman device was obtained by postoperative CCTA multiplannar reconstruction to evaluate the PDL and device endothelialization. Results Approximately 84 patients post successful LAAC and AFCA were enrolled in this study. The satisfactory LAA occlusion rate was 100%. There was no death, bleeding, stroke, and device-related thrombus (DRT) events. At 6-month postprocedure, CCTA images evidenced complete endothelialization in 44 patients (no contrast enhancement in LAA); contrast enhancement in LAA and visible PDL in 33 patients; contrast enhancement in LAA but without PDL in seven patients (incomplete device endothelialization). Maximum diameter of LAA orifice could independently predict the occurrence of PDL (odds ratio, 1.31; 95% confidence interval, 1.11-1.55; p = .002), sensitivity was 69.7% and specificity was 80.4% with the cutoff value of maximum diameter of LAA orifice more than 28.2 mm on predicting PDL. Conclusions CCTA is feasible to evaluate PDL and device endothelialization after LAAC. The maximum diameter of LAA orifice derived from CT can independently predict the occurrence of post-LAAC PDL.

Background: This study aimed to investigate the clinical characteristics of 21 deaths and evaluate potential factors affecting disease severity and mortality risk in patients with coronavirus disease (COVID-19). Methods: This retrospective analysis assessed clinical data of 21 patients who died owing to COVID-19. Disease severity and mortality risk were assessed using Acute Physiology and Chronic Health Evaluation II (APACHE II); Sepsis-related Organ Failure Assessment (SOFA); multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension and age (MuLBSTA); and pneumonia severity index (PSI) scores. Results: The mean age of the patients was 66 ± 14 years and 15 (71.4%) patients were men. Sixteen (76.2%) patients had chronic medical illnesses. Twelve (57.1%) patients were overweight. Decreased lymphocyte proportions were observed in 17 (81.0%) patients on admission. Elevated D-dimer levels were observed in 11 (52.4%) patients, and the levels significantly increased when pneumonia deteriorated. The initial APACHE II and SOFA scores demonstrated that 18 (85.7%) and 13 (61.9%) patients, respectively, were in the middle-risk level. MuLBSTA and PSI scores after admission were associated with higher risks of mortality in 13 (61.9%) patients. Most patients developed organ failure and subsequently died. Conclusions: Older, overweight, male patients with a history of chronic illnesses and continuously decreased lymphocyte proportions and increased D-dimer levels might have higher risks of death owing to COVID-19. The combination of general scoring (SOFA) and pneumonia-specific scoring (MuLBSTA and PSI) systems after admission might be sensitive in assessing the mortality risk of patients with COVID-19 who are in critical condition.

Background. Renal replacement therapy (RRT), as a cornerstone of supportive treatment, has long been performed in critically ill patients with acute kidney injury (AKI). However, the majority of studies may have neglected the effect of the duration of RRT on the outcome of AKI patients. This paper is aiming to explore the effect of the long duration of RRT on the outcome of critically ill patients with AKI. Methods. This retrospective study was conducted by using the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. The primary outcome measure of this study was the mortality at 28 days, 60 days, and 90 days in the long-duration RRT group and the non-long-duration RRT group. The secondary outcomes assessed the difference in clinical outcome in these two groups. Lastly, the effect of the duration of RRT on mortality in AKI patients was determined as the third outcome. Results. We selected 1,020 patients in total who received RRT according to the MIMIC-II database. According to the inclusion and exclusion criteria, we finally selected 506 patients with AKI: 286 AKI patients in the non-long-duration RRT group and 220 in the long-duration RRT group. After 28 days, there was a significant difference in all-cause mortality between the long-duration RRT group and the non-long-duration RRT group ( P = 0.001 ). However, the difference disappeared after 60 days and 90 days ( P = 0.803 and P = 0.925 , respectively). The length of ICU stay, length of hospital stay, and duration of mechanical ventilation were significantly longer in the long-duration RRT group than those in the non-long-duration RRT group. Considering 28-day mortality, the longer duration of RRT was shown to be a protective factor (HR = 0.995, 95% CI 0.993–0.997, P < 0.0001 ), while 60-day and 90-day mortality were not correlated with improved protection. Conclusions. The long duration of RRT can improve the short-term prognosis of AKI patients, but it does not affect the long-term prognosis of these patients. Prognosis is determined by the severity of the illness itself. This suggests that RRT can protect AKI patients through the most critical time; however, the final outcome cannot be altered.

After the reform and opening up, my country’s economic level and total national strength have achieved unprecedented growth. The building of a well-off society in an all-round way is moving towards a harmonious society. The development of social security is also an important part of the development and improvement of a socialist harmonious society. This article is aimed at designing a rural social security system based on deep learning algorithms, using sample collection and statistical analysis methods, collecting samples, simplifying the algorithm, and establishing a new rural social security system. The data collected by the system shows that the proportion of farmers who choose very satisfied, satisfied, average, dissatisfied, and very dissatisfied with the satisfaction of the new rural insurance is 8.94%, 45.53%, 34.96%, 8.13%, and 2.44%. It can be seen that the proportion of farmers who choose to be satisfied is the largest, and more than 10.0% of farmers choose to be dissatisfied or very dissatisfied. Investigate the factors that farmers worry about participating in the new rural insurance, and the questionnaire options can also be set to multiple choices. The survey results show that 29.27% of the farmers think that the individual payment for participating in the new rural insurance is higher; 26.02% of the farmers believe that they do not understand the new rural insurance system; 9.76% of the farmers believe that it is unnecessary to pay for the new rural insurance; 22.76% of farmers choose to rely on themselves or their children in the future; 27.64% of farmers think that the system is unstable. It has basically realized the design of a brand new rural social security system starting from the deep learning of semantic computing.

Classification is the most basic and representative problem in data mining and machine learning. In recent years, more and more evolutionary algorithms (EAs) have been used to handle classification problems due to their good global search capabilities. EA-based methods construct an optimization classification model by introducing a linear equations set. Thus, EAs can be used to directly solve classification problems. However, the structure of the existing optimization classification model is closely related to the dimension of datasets, and there are often a lot of redundant, irrelevant, or noise features in the datasets. These features may lead to complex calculation and low learning efficiency, thus affecting the classification performance. Feature selection has superior performance on solving this kind of problems. Therefore, for the optimization classification model, this paper introduces the concept of feature selection and proposes an improved optimization classification model based on both structure search and weight search. Brain storm optimization (BSO) algorithm is used to solve the optimization classification model. On one hand, BSO algorithm is used to search for the optimal classification model structure which is determined by the optimal feature subset. On the other hand, BSO is used to search for the optimal weight vectors under different structures. Thus, BSO is used to search for optimal structure and weights alternately. Experimental results show that feature selection can effectively simplify the structure of the classification model and improve the classification performance. In addition, the experimental results also verify the effectiveness of BSO on searching the corresponding weights under different structures, which can further improve the classification performance.

Background Post-vaccination myopericarditis is reported after immunization with coronavirus disease 2019 (COVID-19) messenger RNA (mRNA) vaccines. The effect of inadvertent intravenous injection of this vaccine on the heart is unknown. Methods We compared the clinical manifestations, histopathological changes, tissue mRNA expression, and serum levels of cytokine/chemokine and troponin in Balb/c mice at different time points after intravenous (IV) or intramuscular (IM) vaccine injection with normal saline (NS) control. Results Although significant weight loss and higher serum cytokine/chemokine levels were found in IM group at 1–2 days post-injection (dpi), only IV group developed histopathological changes of myopericarditis as evidenced by cardiomyocyte degeneration, apoptosis, and necrosis with adjacent inflammatory cell infiltration and calcific deposits on visceral pericardium, although evidence of coronary artery or other cardiac pathologies was absent. Serum troponin level was significantly higher in IV group. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike antigen expression by immunostaining was occasionally found in infiltrating immune cells of the heart or injection site, in cardiomyocytes and intracardiac vascular endothelial cells, but not skeletal myocytes. The histological changes of myopericarditis after the first IV-priming dose persisted for 2 weeks and were markedly aggravated by a second IM- or IV-booster dose. Cardiac tissue mRNA expression of interleukin (IL)-1β, interferon (IFN)-β, IL-6, and tumor necrosis factor (TNF)-α increased significantly from 1 dpi to 2 dpi in the IV group but not the IM group, compatible with presence of myopericarditis in the IV group. Ballooning degeneration of hepatocytes was consistently found in the IV group. All other organs appeared normal. Conclusions This study provided in vivo evidence that inadvertent intravenous injection of COVID-19 mRNA vaccines may induce myopericarditis. Brief withdrawal of syringe plunger to exclude blood aspiration may be one possible way to reduce such risk.

The hysteretic working capacity of reinforced masonry shear (RMS) walls has been estimated empirically and statistically referring to the structural ultimate state with considerable uncertainty. Th...

Background: Few data are available concerning the prevalence and risk factors for allergic rhinitis (AR) in school children in Hubei Province which is located in the central part of China. This study investigated the epidemiological features of AR among school children in Hubei Province. Methods: A cross-sectional questionnaire survey on AR in school children was carried out in 5 cities in Hubei Province by cluster sampling from June to September 2018. Questionnaires were filled out by children and their parents jointly. The diagnostic criteria of AR were according to the SFAR. Questions from the questionnaire were used to examine the pattern of AR. Logistic regression analysis was used to assess the risk factors for childhood allergies. Results: The total prevalence rate of AR was 16.16%, with 24.31% (Wuhan), 4.34% (Xiangyang), 4.31% (Tianmen), 10.92% (Jingmen), and 11.42% (Huangshi), respectively. The prevalence of AR was positively correlated with gross domestic product per capita (p < 0.05). Multivariate analysis revealed that male, city of Wuhan, family history of allergy, food allergy, drug allergy, air purifier, exposure to dust, living in towns or urban area before 2 years old, maternal age for 26–35 years old, and frequent application of antibiotics increased the risk of AR, while daily outdoor time for 1–2 h, daily sleeping time >8 h, siblings, and breastfeeding for >6 months reduced the risk significantly. Conclusion: We found the apparent geographic variation of children allergies in Hubei Province. Both genetic and environment factors had impacts on the prevalence of AR in school children. Public policies should specifically target at the local risk factors for different areas.

Background Atopic dermatitis is a chronic, inflammatory condition causing a substantial burden to patients and caregivers. SHR0302 is an oral, highly selective, Janus kinase 1 inhibitor under investigation for inflammatory skin diseases. Objective The aim of this study was to investigate the efficacy and safety of SHR0302 in Chinese patients with moderate to severe atopic dermatitis. Design and Setting A randomized, double-blind, placebo-controlled, multicenter, phase II trial was conducted in China between October 2019 and August 2020. Participants Patients (n = 105) aged 18–75 years with moderate to severe dermatitis and nonresponsive or intolerant to topical or conventional systemic treatments were included. Interventions Patients were randomly assigned in a ratio of 1:1:1 to receive SHR0302 4 mg once daily, SHR0302 8 mg once daily, or placebo for 12 weeks. Main Outcome Measures The primary efficacy endpoint was the proportion of patients achieving Investigator’s Global Assessment (IGA) response (IGA of 0 [clear] or 1 [almost clear] with improvement of ≥2 grades) at week 12. Secondary efficacy assessments included Eczema Area and Severity Index (EASI) and pruritus Numerical Rating Scale (NRS) scores. Results At week 12, IGA response was achieved in nine patients (25.7%; 90% confidence interval [CI] 13.6–37.9%; p = 0.022) in the SHR0302 4 mg group, 19 patients (54.3%; 90% CI 40.4–68.1%; p

Colon cancer is the third most common malignancy and the fourth most prevalent cause of death worldwide. Unfortunately, current cancer treatment approaches suffer from low specificity toward colon ...

BACKGROUND AND OBJECTIVES This study aimed to characterize the efficacy of neoadjuvant imatinib in rectal gastrointestinal stromal tumors (GISTs) and the prognostic characteristics of patients after surgery. METHODS Patients with rectal GISTs who received neoadjuvant imatinib between 2000 and 2019 were selected from 11 large-scale tertiary hospitals in China. The best response to neoadjuvant imatinib was assessed. Propensity score matching (PSM) was conducted to reduce confounders. Recurrence free survival (RFS) and overall survival (OS) were estimated using Kaplan-Meier method. RESULTS Of the 100 patients, 75, 18, and 7 had a partial response (PR), stable disease (SD), and progressive disease (PD), respectively. The median tumor size decreased from 5 cm before treatment to 4 cm after treatment (p

Supplemental digital content is available in the text., Objective This study aimed to examine the association of a mother’s loss of a close relative before or during pregnancy with intellectual disability (ID) in the offspring. Methods We performed a nationwide population-based cohort study based on Danish national registries. All live-born singletons born in Denmark during the 1978–2016 period (n = 2,216,601) were followed up starting from birth to 38 years of age. Log-linear Poisson regression was used to estimate the association between maternal bereavement (the death of an older child, a partner, or a parent 1 year before or during pregnancy) and the risk of ID in the offspring. Results Maternal bereavement during or before pregnancy was associated with an increased risk of ID (incidence rate ratio [IRR] = 1.15; 95% confidence interval [CI] = 1.04–1.28). The risk of ID was increased by 27% when maternal bereavement occurred during pregnancy (IRR = 1.27; 95% CI = 1.08–1.49). When stratifying on the child’s sex, we also observed an increased risk of ID associated with maternal bereavement during pregnancy both for male (IRR = 1.25; 95% CI = 1.02–1.53) and for female (IRR = 1.31; 95% CI = 1.02–1.69), respectively. The IRRs for unnatural death of a relative were also elevated (IRR = 1.22; 95% CI = 0.91–1.64) in general, although the difference was not statistically significant. Conclusions Our findings suggest that prenatal stress due to maternal loss of a close relative may increase the risk of offspring’s ID of both sexes, in particular when the loss happened during pregnancy.