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Regulations limiting the sale of flavored e-cigarette products are controversial for their potential to interfere with e-cigarette use as a cessation aid in addition to curbing youth use. Limited research suggests that flavor might enhance the addictive potential of e-cigarettes; however, the acute effects of flavored aerosols on brain function among humans have not been assessed. The present study aimed to isolate and compare the neural substrates of flavored and unflavored e-cigarette aerosols on brain function among nine female daily smokers. Participants inhaled aerosolized e-liquid with 36 mg/mL of nicotine with and without a strawberry-vanilla flavor while undergoing functional magnetic resonance imaging. We used general linear modeling to compare whole-brain mean neural activation and seed-to-voxel task-based functional connectivity between the flavored and unflavored inhalation runs. Contrary to our hypothesis, the flavored aerosol was associated with weaker activation than the unflavored aerosol in the brain stem and bilateral parietal-temporal-occipital region of the cortex. Instead, the flavor engaged taste-related brain regions while suppressing activation of the neural circuits typically engaged during smoking and nicotine administration. Alternatively, functional connectivity between subcortical dopaminergic brain seeds and cortical brain regions involved in motivation and reward salience were stronger during the flavored compared to unflavored aerosol run. The findings suggest that fruity and dessert-flavored e-cigarettes may dampen the reward experience of aerosol inhalation for smokers who initiate e-cigarette use by inhibiting activation of dopaminergic brain circuits. These preliminary findings may have implications for understanding how regulations on flavored e-cigarettes might impact their use as cessation aids. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

As interconnects dominate circuit performance in modern FPGAs, placement becomes a crucial stage for timing closure. Traditional FPGA placers seldom consider the timing constraints, and thus may lead to illegal routing solutions. In this paper, we present an incremental timing-driven placement flow for advanced FPGAs. First, a timing-based global placement strategy is designed to guide heterogeneous blocks to desired locations with satisfied timing constraints. Then, a timing-aware packing algorithm is developed to mitigate the design complexity while improving the timing results. Finally, we propose a critical path-based optimization method to generate optimized layout without timing violations. We evaluate our algorithm based on industrial circuits using an advanced FPGA device. The experimental results show that our placer achieves an 5.1% improvement in worst slack, and produces placements that require 16.7% less time to route when compared with the leading commercial tool Xilinx Vivado.

In smart city, technologies such as blockchain, Internet of Things (IoT) and edge computing tend to be integrated that promotes horizontal information exchange and multi-party cooperation. Large amounts of superior services can be provided by analyzing the information. However, lots of IoT devices generating the information do not have sufficient resources to resist malicious attacks so that the devices deliberately upload the tampered data, which reduces quality of service. To solve the problem, we propose a data source trusted proof mechanism based on the node security measurement and threshold ring signature method. The mechanism firstly judges whether a node is in a trusted domain based on the proposed Distributed Sub-domain Networking (DSN) method to reduce energy consumption and avoid single point failure. Then, it quantifies security value of the nodes in the trusted domain based on the proposed three-dimension security measurement method. Finally, it confirms authenticity of the nodes using the Chinese Remainder Theorem (CRT)-based threshold ring signature scheme.Simulation results show our proposed mechanism can distinguish all malicious nodes among trusted nodes, the loss rate of trusted nodes is reduced to less than 5% and the false report rate is reduced to less than 10%.

Diabetes affects almost half a billion people, and all individuals with type 1 diabetes (T1D) and a large portion of individuals with type 2 diabetes rely on self-administration of the peptide hormone insulin to achieve glucose control. However, this treatment modality has cumbersome storage and equipment requirements and is susceptible to fatal user error. Here, reasoning that a cell-based therapy could be coupled to an external induction circuit for blood glucose control, as a proof of concept we developed far-red light (FRL)-activated human islet-like designer (FAID) cells and demonstrated how FAID cell implants achieved safe and sustained glucose control in diabetic model mice. Specifically, by introducing a FRL-triggered optogenetic device into human mesenchymal stem cells (hMSCs), which we encapsulated in poly-(l-lysine)-alginate and implanted subcutaneously under the dorsum of T1D model mice, we achieved FRL illumination-inducible secretion of insulin that yielded improvements in glucose tolerance and sustained blood glucose control over traditional insulin glargine treatment. Moreover, the FAID cell implants attenuated both oxidative stress and development of multiple diabetes-related complications in kidneys. This optogenetics-controlled "living cell factory" platform could be harnessed to develop multiple synthetic designer therapeutic cells to achieve long-term yet precisely controllable drug delivery.

Cognitive model is playing very important role in predicting students’ performance and recommending learning resources. Thus, it has received a great deal of attention from researchers. However, most of the existing work design models from the aspect of students, ignoring the internal relation between problems and skills. To address this problem, we propose a deep cognitive diagnosis framework to obtain students’ mastery of skills and problems by enhancing traditional cognitive diagnosis methods with deep learning. First, we model the skill proficiency of students according to their responses to objective and subjective problems. Second, students’ mastery on problems is modeled based on attention mechanism and neural network, considering both the importance and the interactions of skills. Finally, considering the facts that students may carelessly select or simply guess the answer, we predict students’ performance via the proposed model. Extensive experiments are carried out on two real-world data sets, and the results have proved the effectiveness and interpretability of this work.

Underwater imaging is a crucial and challenging problem. The backscattering caused by particles in turbid water can severely degrade the image. In this paper, A novel image dehazing method is devised, which combines optics with image processing technology. This method can directly remove part of the backscattering through polarization technology, and then quickly solve the dehazing image through our algorithm. Experimental results show that our method is valid and robust for targets of diverse materials, grayscale images and color images in diverse scattering environments. Furthermore, our method takes only 2 percent of the time of the fast dark channel prior (DCP) method when processing 1 K resolution images, which meets the requirements of real-time.

In recent years, Industrial Internet of Things (IIoT) has gradually attracted the attention of the industry owing to its accurate time synchronization, communication accuracy, and high adaptability. As an important data structure, graphs are widely used in IIoT applications, where entities and their relationships can be expressed in the form of graphs. With the widespread adoption of IIoT and cloud computing, an increasing number of individuals or organizations are outsourcing their IIoT graph data to cloud servers to enjoy the unlimited storage space and fast computing service. To protect the privacy of graph data, graphs are usually encrypted before being outsourced. In this article, we propose a search pattern privacy system for approximate shortest distance query of encrypted graphs in IIoT. To realize search pattern privacy, we adopt two noncolluded cloud servers to accomplish different tasks. We leverage the first server to store the encrypted data and perform query operations, and use the second one to rerandomize the contents and shuffle the locations of the queried records. Before queries, we generate the trapdoors by using different random numbers. After queries, we ask the second server to rerandomize the contents of the records that the first server touched. In addition, we shuffle the physical locations of original records by inserting some fake records. In this way, all contents and physical locations of the touched records change, so that the first server cannot distinguish whether two queries are the same or not. To enhance the efficiency on the user side, we further improve this system by moving some heavy workloads from the user to the cloud. The security analysis and the performance evaluation show that our work is secure and efficient.

Mining protective coal seams is an effective approach for coal and gas outburst control, but a large amount of gangue is usually produced when mining a thin protective seam and dealing with the gangue can be a challenging task. In the paper, a novel integrated mining system by extracting two panels simultaneously was demonstrated in the 12th coal mine of the Pingdingshan coalfield: one panel was mined in the thin protective coal seam, and the other one was mined in the protected coal seam. The thickness of the protective seam was only 0.8 m, but the mining height reached 1.8 m, indicating that there was about 1 m thick roof stone being mined. An underground coal preparation plant was built, and the mixture of coal and gangue from the protective panel was sorted underground. The sorted coal was delivered to the surface stockpile, while the waste rock was directly backfilled into the gob of the panel in the protected coal seam. Thus, waste rock did not need to be lifted up to the surface, which can reduce material handing cost and minimise mining footprint on the surface. In order to prevent the migration of pressure relief gas into the working areas of the protective coal seam, the main reasons causing gas exceedance in the upper corner of U-shaped ventilation system were investigated, and then the Y-shaped ventilation system and various gas extraction boreholes were implemented to effectively control the pressure relief gas. Numerical models were developed to assess the effect of applying gob backfilling during the extraction of two panels in parallel. The results show that the gob backfilling can reduce the surface subsidence and horizontal movement, which is very helpful for the protection of ground water and surface infrastructures.

Edge computing is emerging to empower the future of Internet of Things (IoT) applications. However, due to heterogeneity of applications, it is a significant challenge for the edge cloud to effectively allocate multidimensional limited resources (CPU, memory, storage, bandwidth, etc.) with constraints of applications’ Quality of Service (QoS) requirements. In this paper, we address the resource allocation problem in Edge-IoT systems through developing a novel framework named DeepEdge that allocates resources to the heterogeneous IoT applications with the goal of maximizing users’ Quality of Experience (QoE). To achieve this goal, we develop a novel QoE model that considers aligning the heterogeneous requirements of IoT applications to the available edge resources. The alignment is achieved through selection of QoS requirement range that can be satisfied by the available resources. In addition, we propose a novel two-stage deep reinforcement learning (DRL) scheme that effectively allocates edge resources to serve the IoT applications and maximize the users’ QoE. Unlike the typical DRL, our scheme exploits deep neural networks (DNN) to improve actions’ exploration by using DNN to map the Edge-IoT state to joint resource allocation action that consists of resource allocation and QoS class. The joint action not only maximize users’ QoE and satisfies heterogeneous applications’ requirements but also align the QoS requirements to the available resources. In addition, we develop a Q-value approximation approach to tackle the large space problem of Edge-IoT. Further evaluation shows that DeepEdge brings considerable improvements in terms of QoE, latency and application tasks’ success ratio in comparison to the existing resource allocation schemes.

The most widely-used data for civilian Space Situational Awareness are the Two-Line Element sets (TLEs) provided by the USSTRATCOM. TLEs play critical roles in space monitoring and analysis activities, and are also used in many applications requiring position information of space objects. However, TLEs suffer from uneven data quality, and it is usually necessary to perform outlier or anomaly detections before utilizing these ephemerides. There are many such procedures available in the published literature, and thresholds are usually obtained through simulations or from experiences, which lacks theoretical soundness and thus is inflexible to use. A new filter based on the Expectation Maximization (EM) algorithm is proposed to ease some restrictions, in which outlier thresholds are determined based on the variances estimated in the polynomial regression and prediction, which makes the new filter theoretically sound and more flexible to use. The new filter can be applied to detect outliers in TLEs of objects in any orbital regions, under various space environments, and enduring different operations such as orbit maneuvers. Multiple experiments are presented to demonstrate the effectiveness of the proposed filter to detect outliers of different magnitudes in TLEs. Simulated outliers in the mean motion and eccentricity with the relative magnitude ≥ 5 × 10 - 3 are almost 100% detected, 74% – 98% of outliers in the inclination with the relative magnitude = 0.01 are detected, and 37% – 68% of those with the relative magnitude 5 × 10 - 3 detected. In addition, sequences can be more accurately identified, which help detect outliers in different sequences, making the proposed filter more applicable to complex situations.

With the explosive development of the Internet of Things (IoT), massive equipments are involved in the indoor environment with the demand of precise localization to provide intelligent interconnection. The visible light positioning (VLP) system, with the light emitting diode (LED) and the photo-diode (PD) or image sensor as the transceiver, has attracted a lot of attention due to low cost, high accuracy, energy efficiency, electromagnetic interference free, safety, and so on. In this article, we address the architecture and multiplexing methods of the VLP systems, together with their influence in positioning. From the engineering's point of view, we introduce a novel signature code with reduced complexity and computation. Performing the coding and decoding scheme, the received signal strengths (RSSs) from different LEDs can be decomposed. Based on these RSSs, an adaptive positioning mechanism is first considered following the analysis of merits of the common positioning algorithms, which is verified with optimal positioning performance. It can be concluded that the proposed VLP system has great potential to fit well for a large scene with massive IoT devices.

With the development of deep neural networks, the smart edge-cloud scenario is expected to meet the diverse and personalized requirements of users. However, the exiting edge-cloud architecture requires the deployment of manually designed neural networks. Providing adaptive network architecture in this environment, especially for heterogeneous edge devices, becomes the major challenge. To this end, we design the customized network architecture with neural architecture search for adaptively neural network search. Specifically, our architecture can be identified in three parts: cloud layer, equipped with huge amounts of computing resources, conducts multi-objective architecture search on a proxy dataset; the edge layer aims to train the optimal architecture based on the target dataset from scratch, which makes full use of the computing resource of the edge server; and the user layer deploys the multi-objective model in diverse devices for inference in real time. Furthermore, we deploy an industrial sensor monitoring scenario as a case study to search for the temporal convolutional network, demonstrating the effectiveness of the proposed architecture. Experimental results show the feasibility of the proposed architecture.

Soils in coal coking plants can contain both polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs). In this study, we analyzed PAH-HM pollution of soil in a coking plant in Beijing, China ...

Background Subglottic paragangliomas (PGs) are exceptionally rare and unpredictable, occasionally presenting at an atypical location. There are three different clinical forms of subglottic PGs: intraluminal (tracheal PGs), extraluminal (thyroid PGs) and the mixed type (both intraluminal and extraluminal, mixed-subglottic PGs). These tumors are usually misdiagnosed as other relatively common primary thyroid or laryngotracheal tumors, and the treatment is troublesome. Case presentation A 22-year-old male patient with subglottic PGs has been successively misdiagnosed as thyroid tumors and subglottic hemangiomas, and lastly underwent local extended lumpectomy and laryngotracheal reconstruction with a pedicled thoracoacromial artery perforator flap (PTAPF). The patient was decannulated successfully after the second-stage tracheal reconstruction with a local flap, and no evidence of local recurrence and distant metastasis of the tumor until now. Conclusion Subglottic PGs can be easily misdiagnosed as laryngotracheal or thyroid tumors when presented at an atypical location. It is essential for otolaryngologists and head and neck surgeons to remain vigilant against these tumors. If the tumor is not diagnosed or removed completely, patients may encounter a risk of lethal paroxysm, which is incredibly troublesome.

Background. A lack of knowledge and inadequate practices of health care providers (HCPs) are the main obstacles to effective cancer pain management (CPM). The main objective of the study was to evaluate the CPM knowledge, CPM practice, and attitudes towards pharmacists’ participation and advanced methods in CPM of physicians, nurses, and pharmacists in China. Methods. An open online survey was adopted using social media software (WeChat) as the platform to conduct a nationwide survey of HCPs involved in CPM in public medical institutions at all levels in China from March to June 2019. Results. A total of 1279 physicians, 2267 nurses, and 1466 pharmacists participated in the survey. Among the three types of professionals, nurses had the highest level of practical ability (61.63 ± 28.99) and best attitudes towards pharmacists’ participation and advanced methods in CPM (72.05 ± 33.71) and physicians had the best mastery of CPM-related knowledge (69.60 ± 28.45), while pharmacists performed the worst in these three aspects (50.04 ± 26.69, 61.49 ± 28.95, and 62.07 ± 36.46, respectively). Only 19.69% of the hospitals had a pharmacist to tumor patient ratio ≥1 : 50. Hierarchical analysis showed that passing a good pain management (GPM) ward program and participating in advanced training had positive impacts on the scores of all three parts in the three professions (ptrend

The current security method of Internet-of-Vehicles (IoV) systems is rare, which makes it vulnerable to various attacks. The malicious and unauthorized nodes can easily invade the IoV systems to destroy the integrity, availability, and confidentiality of information resources shared among vehicles. Indeed, access control mechanism can remedy this. However, as a static method, it cannot timely response to these attacks. To solve this problem, we propose an intelligent edge-chain-enabled access control framework with vehicle nodes and roadside units (RSUs) in this study. In our scenario, vehicle nodes act as lightweight nodes, whereas RUSs serve as full and edge nodes to provide access control services. Considering the low accuracy of risk prediction due to limited training sets, we leverage a generative adversarial networks (GANs) to convert the risk prediction to a sequence generation. Moreover, aiming at the problems of gradient disappearance and mode collapse existed in the original GANs, we devise a Wasserstein combined GANs (WCGANs). Simulation results demonstrate that WCGAN has higher prediction accuracy than the original GANs. Additionally, it can also improve the accuracy of access control of risk prediction-based access control (RPBAC) model.

Objective To explore the effect of age at diagnosis as a continuous variable on survival and treatment choice of patients with early-stage endometrial carcinoma (EC). Materials and methods We retrospectively analyzed data from patients with early-stage EC from January 1999 to December 2015 in multiple institutions in China. All patients received primary hysterectomy/bilateral salpingo-oophorectomy and adjuvant radiotherapy for EC confirmed pathology of stage I and II disease (FIGO 2009 staging). All patients were divided into low-risk, intermediate-risk, high-intermediate-risk and high-risk groups according to ESMO-ESGO-ESTRO risk classification. Results The median follow-up time was 57months, and the 5-year cancer-specific survival (CSS) was 95.7%. Age as a continuous variable was an independent prognostic factor for CSS. With an increase in age, the hazard ratio (HR) for CSS increases gradually. Other independent prognostic factors included myometrial invasion (MI), grade, and chemotherapy. In the stratified analysis of age, the HRs of age on CSS in patients >70y were 5.516, 5.015, 4.469, 4.618, 5.334, and 5.821 after adjusting for cancer characteristics, local treatment, chemotherapy and treatment-related late toxicity. In patients 66-70-year-old, the HRs were 2.509, 2.074, 2.101, 2.091, 2.157 and 1.621 after adjusting for the above covariates. In patients ≤65y, there was no significant difference in the HR of age on CSS after adjustment. Conclusion Age as a continuous variable is an independent prognostic factor and 65 year-old may be the best cut-off point for CSS in patients with early-stage EC in the Asian population. Quality of life should be given greater weight in the choice of therapeutic schedule for those patients >70 y.

Custodiol-HTK cardioplegia (Custodiol-HTK Koheler Chemie, GmbH, Bensheim, Germany) causes fluctuations in serum sodium levels, hyponatremia, and is associated with postoperative seizures. We investigated the influence of scavenging right atrial effluent during delivery on intraoperative serum sodium levels and postoperative seizure incidence in pediatric cardiac surgery patients.A total of 204 patients younger than age 18 years undergoing congenital heart surgery between January 2016 and March 2018 were analyzed retrospectively. Serum sodium levels after administration of Custodiol-HTK cardioplegia were compared between the scavenge and nonscavenge groups and then in the propensity score-matched cohort (n = 96). Postoperative seizures were documented clinically and with electroencephalogram findings. Logistic regression models were used to identify the independent predictors of serum sodium level after aortic crossclamp.Of 204 patients, 156 (76.5%) were in the nonscavenge, and 48 (23.5%) in the scavenge groups. A serum sodium level130 mEq/L after crossclamp and administration of Custodiol-HTK cardioplegia in the nonscavenge group were 70% versus 21% in the scavenge group (odds ratio, 8.8; 95% confidence interval, 4.1-18.3; P .0001) in the entire cohort, and 77% versus 21% (odds ratio, 12.8; 95% confidence interval, 4.8-33.1; P .0001) in the propensity score-matched cohort. Of 16 patients experiencing a postoperative seizure, 14 (87.5%) had a sodium level130 mEq/L and 2 (12.5%) had a sodium level ≥130 mEq/L (odds ratio, 5.1; 95% confidence interval, 1.3-22.8; P = .021) after crossclamp. Postoperative seizures occurred in the nonscavenge group but not the scavenge group in the entire cohort (P = .02) and in the propensity score-matched patients (P = .041). Multivariable analysis of the entire cohort showed that scavenge intervention was an independent factor associated with significantly decreased risk of sodium level130 mEq/L (odds ratio, 0.17; 95% confidence interval, 0.08-0.36; P = .000).Right atrial effluent scavenging was protective against fluctuations in serum sodium levels after crossclamp and Custodiol-HTK cardioplegia administration independently in both entire and matched cohort, and was also associated with decreased incidence of postoperative seizures.

OBJECTIVES To evaluate the impact of providing personalized depression risk information on self-help and help-seeking behaviors among individuals who are at high risk of having a major depressive episode (MDE). MATERIALS AND METHODS In a mixed methods randomized controlled trial, participants who were at high risk of having a MDE, were recruited from across Canada, and were randomized into intervention (n = 358) and control (n = 354) groups. Participants in the intervention group received their personalized depression risk estimated by sex-specific risk prediction models for MDE. All participants were assessed at baseline, 6 and 12 months. RESULTS Repeated measure mixed effects modeling showed significant between group differences in self-help scores. In the complete case analysis, the between group difference in mean self-help change score was 1.13 at 12 months (effect size = 0.16). Among participants who reported "fair" or "poor health," the between group difference in mean self-help change score was 2.78 at 12 months (effect size = 0.35). The qualitative data revealed three themes and the findings are consistent with the quantitative results. CONCLUSIONS Providing personalized depression risk information has a positive impact on self-help in high-risk individuals, particularly in those with poor health.

Although it is known that peripheral arterial disease (PAD) is associated with chronic myopathies, the acute muscular responses to exercise in this population are less clear. This study used diffusion tensor imaging (DTI) to compare acute exercise-related muscle damage between PAD patients and healthy controls. Eight PAD patients and seven healthy controls performed graded plantar flexion in the bore of a 3T MRI scanner. Exercise began at 2 kg and increased by 2 kg every 2 min until failure, or completion of 10 min of exercise. DTI images were acquired from the lower leg pre- and post-exercise, and were analyzed for mean diffusivity, fractional anisotropy (FA), and eigenvalues 1–3 (λ1–3) of the medial gastrocnemius (MG) and tibialis anterior (TA). Results indicated a significant leg by time interaction for mean diffusivity, explained by a significantly greater increase in diffusivity of the MG in the most affected legs of PAD patients (11.1 × 10–4 ± 0.5 × 10–4 mm2/s vs. 12.7 × 10–4 ± 1.2 × 10–4 mm2/s at pre and post, respectively, P = 0.02) compared to healthy control subjects (10.8 × 10–4 ± 0.3 × 10–4 mm2/s vs. 11.2 × 10–4 ± 0.5 × 10–4 mm2/s at pre and post, respectively, P = 1.0). No significant differences were observed for the TA, or λ1–3 (all P ≥ 0.06). Moreover, no reciprocal changes were observed for FA in either group (all P ≥ 0.29). These data suggest that calf muscle diffusivity increases more in PAD patients compared to controls after exercise. These findings are consistent with the notion that acute exercise results in increased muscle damage in PAD.

Rationale: Corticosteroid resistance (CR) is a serious drawback to steroid therapy in patients with ulcerative colitis (UC); the underlying mechanism is incompletely understood. Twist1 protein (TW1) is an apoptosis inhibitor and has immune regulatory functions. This study aims to elucidate the roles of TW1 in inducing and sustaining the CR status in UC. Methods: Surgically removed colon tissues of patients with ulcerative colitis (UC) were collected, from which neutrophils were isolated by flow cytometry. The inflammation-related gene activities in neutrophils were analyzed by RNA sequencing. A CR colitis mouse model was developed with the dextran sulfate sodium approach in a hypoxia environment. Results: Higher TW1 gene expression was detected in neutrophils isolated from the colon tissues of UC patients with CR and the CR mouse colon tissues. TW1 physically interacted with glucocorticoid receptor (GR)α in CR neutrophils that prevented GRα from interacting with steroids; which consequently abrogated the effects of steroids on regulating the cellular activities of neutrophils. STAT3 (Signal Transducer and Activator of Transcription-3) interacted with Ras protein activator like 1 to sustain the high TW1 expression in colon mucosal neutrophils of CR patients and CR mice. Inhibition of TW1 restored the sensitivity to corticosteroid of neutrophils in the colon tissues of a CR murine model. Conclusions: UC patients at CR status showed high TW1 expression in neutrophils. TW1 prevented steroids from regulating neutrophil activities. Inhibition of TW1 restored the sensitivity to corticosteroids in the colon tissues at the CR status.

Aim: To evaluate the cost–effectiveness of ribociclib plus fulvestrant versus fulvestrant in hormone receptor-positive/human EGF receptor 2-negative advanced breast cancer. Materials & methods: A three-state Markov model was developed to evaluate the costs and effectiveness over 10 years. Direct costs and utility values were obtained from previously published studies. We calculated incremental cost–effectiveness ratio to evaluate the cost–effectiveness at a willingness-to-pay threshold of $150,000 per additional quality-adjusted life year. Results: The incremental cost–effectiveness ratio was $1,073,526 per quality-adjusted life year of ribociclib plus fulvestrant versus fulvestrant. Conclusions: Ribociclib plus fulvestrant is not cost-effective versus fulvestrant in the treatment of advanced hormone receptor-positive/human EGF receptor 2-negative breast cancer. When ribociclib is at 10% of the full price, ribociclib plus fulvestrant could be cost-effective.

The advent of smart and wearable electronics endows flexible pressure sensors with promising potentiality. Ti3C2Tx-based MXene is considered as one of attractive sensing materials for its metallic conductivity and adjustable interlayer. However, existing flexible MXene pressure sensor still requires a technical breakthrough that simultaneously possessing high sensitivity, fast response, and durability in low-pressure regime and excellent mechanical strength. Herein, a Ti3C2Tx-based pressure sensor with distinctly enhanced sensing functionality and mechanical strength is demonstrated though inserting high-strength of bacterial cellulose nanofibers to control the interlayer of MXene. By optimizing the bacterial cellulose content and MXene interlayer space, the resultant sensor device exhibits high mechanical strength (225 MPa), wide-sensing range with low detective limit (0.4 Pa), high sensitivity (up to 95.2 kPa−1, in < 50 Pa region), fast response (95 ms) and outperformed repeatability (25,000 cycles), as well as low operation voltage of 0.1 V. For practical application demos, the sensor can monitor multiple human biologic activities, including subtle pressures (e.g., swallow, heartbeat and pulse), acoustic vibrations and gesture motions, and serve as electronic skin for mapping pressure distribution, elucidating the potential application in medical diagnosis, smart robotics and human-machine interfacing.

Surface water quality is an important factor affecting the ecological environment and human living environment. The monitoring of surface water quality by remote sensing monitoring technology can provide important research significance for water resources protection and water quality evaluation. Finding the optimal spectral index sensitive to water quality for remote sensing monitoring of water quality is extremely important for surface water quality analysis and treatment in the Ebinur Lake Basin in arid areas. This study used Sentinel-2MSI data at 10 m resolution to quickly monitor the water quality of the watershed. Through laboratory experiments and measurement data from the Ebinur Lake Basin, 22 water quality parameters (WQPs) were obtained. Through Z-score and redundancy analysis, 9 WQPs with significant contributions were extracted. Based on the remote sensing spectral band, four water indexes (NDWI, NWI, EWI, AWEI-nsh) and 2D modeling spectral index (DI, RI, NDI), the correlation analysis between WQPs and two kinds of spectral band indexes is carried out, and it is concluded that the overall correlation between WQP and 2D spectral modeling is more relevant. This paper calculates the evaluation and models the 2D spectrum of the Water Quality Index (WQI). The WQI is predicted and modeled through four machine learning algorithms (RF, SVM, PLSR, PLSR-SVM).The results show that the inversion effect of the two-dimensional spectral modeling index on water quality parameters (WQPs) is superior to that of the water index, and the correlation coefficient of the DI (R12-R1) SWIR-2 and BLUE band interpolation index reaches 0.787. On this basis, three kinds of two-dimensional spectral modeling indexes are used to inversely synthesize the WQI, and the correlation coefficient of the ratio index of the RI (R11/R8) SWIR-1 and near-infrared (NIR) bands is preferably 0.69. In the WQI prediction, the partial least squares regression support vector machine (PLSR-SVM) model in machine learning algorithms has good modeling and prediction effects (R2c = 0.873, R2v = 0.87), which can provide a good basis. The research results provide references for remote monitoring of surface water in arid areas, and provide a basis for water quality prediction and safety evaluation. HIGHLIGHTS Inversion of water quality in the Ebinur Lake Basin by Sentinel-2 MSI data.; Analysis of the contribution rate of different water quality parameters in water by Z-score and PCA.; Comparison of classical water quality index, correlation between spectral modeling and water quality parameters.; Modeling and predicting water quality index (WQI) using machine learning and linear correlation methods.

Fiber Optics Reflectance Spectroscopy (FORS) has been widely used in the field of cultural heritage for material identification. Nevertheless, it had been rarely applied in the study of bronze corrosion products. This paper aims at exploring the potential of FORS on corrosion products analysis, proposing it as an innovative non-destructive technique for the condition assessment of bronze artefacts in museum collections. A gilded bronze statue “Vajrasattva Bodhisattva” dated to the Ming dynasty (A. D. 1368-1644) from National Museum of China was investigated. The in-situ FORS analysis was conducted on 36 points, revealing copper trihydroxychloride (atacamite/clinoatacamite) and chalconatronite as two major types of corrosion products. This result was double-confirmed by Raman and XRD analyses of 10 samples taken from these points. It proves that FORS is a very promising technique for non-destructive in-situ detection of chloride-bearing bronze corrosions. It may revolutionize the way of screening artefacts with bronze disease, helping conservators get the distribution “map” of different bronze corrosion quickly and comprehensively, and making appropriate treatment proposals accordingly.

Diabetic nephropathy (DN) is one of the most serious complications of diabetes that leads to decline of renal function. Although numerous studies have revealed that microRNAs (miRNAs) play essential roles in the progression of DN, whether miR-365 is involved remains elusive. The successful construction of DN model was confirmed by ELSIA, hematoxylin–eosin (HE) and Masson staining assay. The expression of miR-365 was detected through RT-qPCR. The levels of BDNF, p-TrkB, α-smooth muscle actin (SMA), collagen IV (Col.IV), transforming growth factor-β1 (TGF-β1), tumor necrosis factor α (TNF-α), and interleukin-6 (IL-6) were evaluated by western blot, IF or ELISA assays. Luciferase reporter assay was used to detect the interaction between miR-365 and BDNF. The DN mice model was induced by streptozotocin (STZ). Then miR-365 expression was found to upregulate in tissues of DN rat. Furthermore, elevated expression of miR-365 was found in high glucose (HG)-treated HK-2 cells. Silencing of miR-365 suppressed the accumulation of ECM components and secretion of inflammatory cytokines in HK-2 cells. In addition, it was demonstrated that miR-365 could target BDNF. The protein levels of BDNF and p-TrkB were negatively regulated by miR-365 in HK-2 cells. Moreover, inhibition of miR-365 suppressed the levels of SMA, Col.IV, TGF-β1, TNF-α, and IL-6, indicating the renal fibrosis was inhibited by miR-365 knockdown. MiR-365 could regulate BDNF-TrkB signal axis in STZ induced DN fibrosis and renal function. The results of the current study might provide a promising biomarker for the treatment of DN in the future.

Position and Orientation system (POS), a loosely integrated inertial navigation system (INS) and global positioning system (GPS), can provide high-accuracy motion information for the airborne remote sensing loads, which plays a crucial role in airborne remote sensing imaging. However, the airborne POS often suffers from the harsh environment, such as aircraft maneuver mode and other external disturbance, which will lead to measurement noise unknown and further affects the accuracy of motion parameters. In this paper, an adaptive central difference Kalman filter method based on expectation maximization algorithm is proposed, which can estimate measurement noise adaptively and further improve the performance of POS. A flight experiment is conducted and the results show that the proposed method achieves higher-accuracy motion information by compared with the traditional CDKF method and covariance matching.

Stroke is a kind of cerebrovascular disease that heavily damages people’s life and health. The quantitative analysis of brain MRI images plays an important role in the diagnosis and treatment of stroke. Deep neural networks with massive data learning ability supply a powerful tool for lesion detection. In order to study the property of the stroke lesions and complete intelligent automatic detection, we collaborated with two authoritative hospitals and collected 5,668 brain MRI images of 300 ischemic stroke patients. All the lesion regions in the images were accurately labeled by professional doctors to ensure the authority and effectiveness of the data. Three categories of deep learning object detection networks including Faster R-CNN, YOLOV3, and SSD are applied to implement automatic lesion detection with the best precision of 89.77%. Meanwhile, statistical analysis of the locations, shapes of the lesions, and possible related diseases is conducted with valid conclusions. The research contributes to the intelligent assisted diagnosis and prevention and treatment of ischemic stroke.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) epidemic, tumor patients and their families might suffer from greater psychological stress as a result of anxiety or other psychological disorders. We conducted an online study during the epidemic to explore the mental state of tumor patients and their families during this extraordinary time. METHODS: A cross-sectional survey was carried out. Questionnaires were distributed through the WeChat "Questionnaire Star" network. The snowball sampling technique was adopted and further promoted by subjects who had completed the questionnaire. RESULTS: A total of 1,030 valid questionnaires were collected. There were 609 (59.13%) tumor patients and 421 (40.87%) family members. One hundred and fifty-six (15.15%) subjects had anxiety, among which 65 (6.31%) had moderate to severe anxiety. Single-factor analysis indicated that age (>60 years old), the farmer occupation, and a high sleep disorder assessment score were risk factors for anxiety, while the latter two might also be independent risk factors, as suggested by multi-factor analysis. Infrequent contact with doctors was an independent risk factor for cancer patients, while uninterrupted anti-tumor therapy was an independent protective factor. 40.19% of the subjects expressed a need for psychosocial support during the COVID-19 period. CONCLUSIONS: The COVID-19 outbreak resulted in tumor patients and their relatives experiencing greater psychological pressure than usual, and patients were more worried about anti-tumor treatment and disease progression impacted by the epidemic. Both groups had a significant need for psychosocial help.

Objective:. The impact of dairy fat on inflammatory bowel disease remained inconclusive. We aimed to compare the effects of whole-milk and skimmed-milk consumption on the risk of inflammatory bowel disease using a Mendelian randomization analysis. Methods:. We conducted a genome-wide association study of the preference for whole versus skimmed milk using data for 20,200 whole-milk consumers and 67,847 skimmed-milk consumers from the UK Biobank. The lead single nucleotide polymorphisms in the associated loci were identified at the genome-wide significance level, and were further employed as instrumental variables for whole-milk preference. We conducted a two-sample Mendelian randomization analysis with whole-milk preference as the exposure and inflammatory bowel disease as the outcome. The pleiotropic effects and heterogeneity of the instrumental variables were estimated using Mendelian randomization-Egger regression and Cochran Q test, respectively. This study was conducted using the UKB resources under the application “53536”. The UK Biobank was approved by the North West Multi-center Research Ethics Committee, the National Information Governance Board for Health and Social Care in England and Wales, and the Community Health Index Advisory Group in Scotland. Results:. The genome-wide association study identified five lead nucleotide polymorphisms associated with whole-milk preference. Mendelian randomization indicated that whole-milk preference significantly decreased the risk of inflammatory bowel disease (β=−1.735, P = 0.048). Of the two subtypes, whole-milk preference was associated with a lower risk of Crohn disease (β=−2.549, P = 0.032), but had no significant effect on the risk of ulcerative colitis (β=−1.002, P = 0.44). Conclusion:. Consumption of whole-milk fat may protect against Crohn disease, compared with skimmed milk. This conclusion was based on causal inference in a cohort study, and further validation in randomized controlled trials is warranted.

The COVID-19 pandemic is the third outbreak this century of a zoonotic disease caused by a coronavirus, following the emergence of severe acute respiratory syndrome (SARS) in 20031 and Middle East respiratory syndrome (MERS) in 20122. Treatment options for coronaviruses are limited. Here we show that clofazimine-an anti-leprosy drug with a favourable safety profile3-possesses inhibitory activity against several coronaviruses, and can antagonize the replication of SARS-CoV-2 and MERS-CoV in a range of in vitro systems. We found that this molecule, which has been approved by the US Food and Drug Administration, inhibits cell fusion mediated by the viral spike glycoprotein, as well as activity of the viral helicase. Prophylactic or therapeutic administration of clofazimine in a hamster model of SARS-CoV-2 pathogenesis led to reduced viral loads in the lung and viral shedding in faeces, and also alleviated the inflammation associated with viral infection. Combinations of clofazimine and remdesivir exhibited antiviral synergy in vitro and in vivo, and restricted viral shedding from the upper respiratory tract. Clofazimine, which is orally bioavailable and comparatively cheap to manufacture, is an attractive clinical candidate for the treatment of outpatients and-when combined with remdesivir-in therapy for hospitalized patients with COVID-19, particularly in contexts in which costs are an important factor or specialized medical facilities are limited. Our data provide evidence that clofazimine may have a role in the control of the current pandemic of COVID-19 and-possibly more importantly-in dealing with coronavirus diseases that may emerge in the future.

Objective: The current study used the Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey (CAFVMHS) to (1) examine the incidence and prevalence of mental disorders and (2) estimate the comorbidity of mental disorders over the follow-up period. Method: The CAFVMHS (2018) is a longitudinal study with two time points of assessment. The sample is comprised of 2,941 Canadian Forces members and veterans who participated in the 2002 Canadian Community Health Survey: Canadian Forces Supplement. The World Health Organization Composite International Diagnostic Interview (WHO-CIDI) was utilized to diagnose Diagnostic and Statistical Manual-IV post-traumatic stress disorder (PTSD), major depressive episode (MDE), generalized anxiety disorder, social anxiety disorder (SAD), and alcohol abuse and dependence. Self-report health professional diagnoses were assessed for attention deficit hyperactivity disorder (ADHD), mania, obsessive compulsive disorder (OCD), and personality disorder. We established weighted prevalence of mental disorders and examined the association between mental disorders using logistic regression. Results: In 2018, lifetime prevalence of any WHO-CIDI-based or self-reported mental disorder was 58.1%. Lifetime prevalence of any mood or anxiety disorder or PTSD was 54.0% in 2018. MDE (39.9%), SAD (25.7%), and PTSD (21.4%) were the most common mental disorders. There was a substantial increase in new onset or recurrence/persistence of mental disorders between the two measurement points (16-year assessment gap); 2002–2018 period prevalences were 43.5% for mood and anxiety disorder and 16.8% for alcohol abuse or dependence. The prevalence of self-reported ADHD, OCD, any personality disorder, and mania were 3.3%, 3.0%, 0.8%, and 0.8%, respectively. Comorbidity between mental disorders increased over the follow-up. Conclusions: This study demonstrates a high burden of mental disorders among a large Canadian military and veteran cohort. These findings underscore the importance of prevention and intervention strategies to reduce the burden of mental disorders and alcohol use disorders in these populations.

The Genomic Landscape of Chinese Breast CancerBackground : The comprehensive genomic profiling (CGP) through next-generation sequencing (NGS) brought a new understanding of breast cancer and provided more information about further clinical treatment. However, the genomic features in Chinese breast cancer group are limited to date, which might offer both prognostic and predictive values. Patients and Methods: Hybrid capture-based CGP was performed on 126 primary and 38 relapsed/metastatic breast cancer patients using a 324-gene panel assay (FoundationOne CDx) to identify all classes of genomic alterations, including base substitutions, insertions and deletions, rearrangement and copy number changes. Tissue samples were obtained by surgery or biopsy. Results:There was no sample with unstable microsatellite status both in primary and relapsed/metastatic breast cancer patients. The tumor mutational burden was higher in Relapsed/metastatic breast cancer than in primary breast cancer (2.91±0.29 for primary, 5.10±0.50 for relapsed/metastatic breast cancer, respectively, p Conclusions:There was significant molecular heterogeneity between primary and relapsed/metastatic breast cancer in Chinese patients and between Chinese and other ethic group. Fig The mutational landscape of top 21 most frequently mutated genes (mutational incidence >5%) in Chinese breast cancers (n=184). The upper histogram showed the total number of mutations in every patient. The bottom bars indicated the clinical characteristics, samples were grouped by primary breast cancers (n=141) and relapsed/metastatic breast cancers (n=43). Sidebar on the left summarized the mutational incidence of each gene and listed the separate frequencies of primary and R/M patients. Sidebar on the right classified different mutation types. Citation Format: Qiuting You, Jianli Zhao, Kai Chen, Yi Chen, Minhua Zeng, Biaolin Wen, Linxiaoxiao Ding, Fengxi Su. The genomic landscape of Chinese breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-40.

Whether primary tumor surgery is better than no surgery in patients with de novo stage IV breast cancer remains controversial. This study combined prospective clinical trials and a multicenter cohort to evaluate the impact of locoregional surgery in de novo stage IV breast cancer. The GRADE approach was used to assess the quality of evidence in meta-analysis, and propensity score matching analysis was used in the cohort study. This study was registered with PROSPERO CRD42016043766 and ClinicalTrials.gov NCT04456855. A total of 1110 patients from six trials and 353 patients from the cohort study were included. The meta-analysis showed that compared with no surgery, locoregional surgery did not prolong overall survival (hazard ratio [HR] = 0.90, P = 0.40; moderate-quality) but had a significantly longer locoregional progression-free survival (HR = 0.23, P

The programed bimodal photoelectrochemical (PEC)-sensing platform based on DNA structural switching induced by targets binding to aptamers was innovatively designed for the simultaneous detection of mucin 1 (MUC1) and microRNA 21 (miRNA-21). To promote excellent current intensity as well as enhance the sensitivity of aptasensors, the evenly distributed WO3/Fe2O3 heterojunction was prepared as a transducer material, notably reducing the background signal response and extending the absorption of light. The multifunctional paper-based biocathode was assembled to provide a visual colorimetric assay. When introducing the integrated signal probe (ISP) composed of signal probe 1 (sP1) and signal probe 2 (sP2) on paper-based working units modified with gold nanoparticles (AuNPs), recognition sites of two targets were formed. In the presence of MUC1 protein, both sP1 and the target on the working unit were released into the corresponding colorimetric unit because of the DNA specific recognition. The horseradish peroxidase-streptavidin (HRP-SA) carried by free sP1 could oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to turn a blue-colored oxidized TMB (oxTMB) in the presence of hydrogen peroxide (H2O2), which ultimately gained a higher photocurrent signal. Furthermore, miRNA-21 was modified on another working unit by binding with sP2, leading to changes in the current signal and thus enabling real-time detection of analytes with the assistance of a digital multimeter. The PEC aptasensor offered a wide dynamic range of 10 fg·mL-1-100 ng mL-1 for MUC1 and 0.1 pM-10 nM for miRNA-21, with a low detection limit of 3.4 fg·mL-1 and 36 fM, respectively. It laid the foundation for synchronous detection of multiple analytes and initiated a new way for the enhancement in modern next-generation disease diagnosis.

The two-dimensional (2D)/three-dimensional (3D) heterojunction perovskite solar cell (PSC) has recently been recognized as a promising photovoltaic structure for achieving high efficiency and long-...

The novel coronavirus disease 2019 (COVID-19) continues to be a major public health concern. The aim of this study was to describe the presenting characteristics, epidemiology and predictors of outcomes among confirmed COVID-19 cases seen at a large community healthcare system which serves the epicenter and diverse region of Florida. We conducted a retrospective analysis of individuals with lab-confirmed SARS-CoV-2 infection who were seen, from March 2, 2020 to May 31, 2020, at Memorial Healthcare System in South Florida. Data was extracted from a COVID-19 registry of patients with lab-confirmed SARS-CoV-2 infection. Univariate and backward stepwise multivariate logistic regression models were used to determine predictors of key study outcomes. There were a total of 1692 confirmed COVID-19 patients included in this study. Increasing age was found to be a significant predictor of hospitalization, 30-day readmission and death. Having a temperature of 38 °C or more and increasing comorbidity score were also associated with an increased risk of hospitalization. Significant predictors of ICU admission included having a saturated oxygen level less than 90%, hypertension, dementia, rheumatologic disease, having a respiratory rate greater than 24 breaths per minute. Being of Hispanic ethnicity and immunosuppressant utilization greatly increased the risk of 30-day readmission. Having an oxygen saturation less than 90% and an underlying neurological disorder were associated with an increased likelihood of death. Results show that a patient’s demographic, underlying condition and vitals at triage may increase or reduce their risk of hospitalization, ICU admission, 30-day readmission or death. Supplementary Information The online version contains supplementary material available at 10.1007/s10900-020-00957-y.

To present our initial experience and evaluate the feasibility of the novel technique of completely intracorporeal laparoscopic “reverse 7” ileal ureteral replacement (IUR). Between December 2018 and September 2019, two patients underwent completely intracorporeal laparoscopic “reverse 7” IUR, which were female patients with bilateral extensive ureteral strictures (BEUS) secondary to radical hysterectomy and pelvic lymph node dissection for cervical cancer and postoperative radiotherapy. Antegrade pyelography and retrograde pyelography showed BEUS preoperatively. The novel technique was performed successfully by the same surgeon without conversion to open surgery. The operating time of each patient was 420 min and 410 min, respectively. Meanwhile, the estimated blood loss of each patient was 120 ml and 100 ml, respectively. There were no major complications during the perioperative period. After ureteral stent was removed, antegrade pyelography postoperatively revealed excellent drainage with the resolution of hydronephrosis in both patients. After removing of ureteral stent and nephrostomy tube, no patients have a complaint about the donor site or the onset of flank pain. To our knowledge, we present the initial experience with completely intracorporeal laparoscopic “reverse 7” IUR. With initial follow-up outcomes, this novel minimally invasive technique appears to be feasible and efficacious in treating BEUS in carefully selected patients.

Background: Cyclin-dependent kinase (CDK) 4/6 inhibitors are frequently used anti-cancer agents in hormone receptor-positive breast cancers. This study assessed the course of research and development (R&D) for CDK4/6 inhibitors in terms of publications over the past two decades. Methods: The Web of Science (WOS) and PubMed databases were searched to identify publications related to research on CDK4/6 inhibitors since 2001. The VOS Viewer software was used to analyze co-occurring keywords to stratify the publication data and collaborations in research. Results: There were 1395 publications related to research on CDK4/6 inhibitors since 2001. Eight of the top 10 institutions originated from the USA and the other two were a Swiss Pharmaceutical Company and French Research Institute. Bardia A, the first author for some of the articles published in the USA, was the most prolific with 25 publications. The journal with the most publications was Cancer Res with 162 publications. Basic research comprised six of the 10 most frequently cited publications and the rest consisted of three reviews and a clinical trial. The most common keywords for publications since 2011 were "palbociclib", "abemaciclib", "ribociclib" and "double blind", indicating the successful development of CDK4/6 inhibitors as anticancer drugs. Conclusions: This study provides a comprehensive review of the CDK4/6 inhibitors R&D history. The data imply that drug development in this field is a decade-long process and clinical trials have been performed before clinical applications. Thereafter, research was conducted on the adverse effects and drug resistance associated with the inhibitors.

The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort (n= 431) and an internal validation cohort (n = 300) collected from one clinical center, and in an external validation cohort (n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.

Aging frailty is a complex geriatric syndrome that becomes more prevalent with advancing age. It constitutes a major health problem due to frequent adverse outcomes. Frailty is characterized by disruption of physiological homeostasis and progressive decline of health status. Multiple factors contribute to development of frailty with advancing age, including genome instability, DNA damage, epigenetic alternations, stem cell exhaustion, among others. These interrelated factors comprehensively result in loss of tissue homeostasis and diminished reserve capacity in frailty. Therefore, the aged organism gradually represents symptoms of frailty with decline in physiological functions of organs. Notably, the brain, cardiovascular system, skeletal muscle, and endocrine system are intrinsically interrelated to frailty. The patients with frailty may display the diminished reserves capacity of organ systems. Due to the complex pathophysiology, no specific treatments have been approved for prevention of this syndrome. At such, effective strategies for intervening in pathogenic process to improve health status of frail patients are highly needed. Recent progress in cell-based therapy has greatly contributed to the amelioration of degenerative diseases related to age. Mesenchymal stem cells (MSCs) can exert regenerative effects and possess anti-inflammatory properties. Transplantation of MSCs represents as a promising therapeutic strategy to address the pathophysiologic problems of frail syndrome. Currently, MSC therapy have undergone the phase I and II trials in human subjects that have endorsed the safety and efficacy of MSCs for aging frailty. However, despite these positive results, caution is still needed with regard to potential to form tumors, and further large-scale studies are warranted to confirm the therapeutic efficacy of MSC therapy.

As one of the disruptive technologies in the fourth industrial revolution, Blockchain has irrevocably changed how people live and work. Many scholars have studied the Blockchain, and the number of related publications has increased over time. Bibliometrics is an excellent method to study the development trend of a specific field. However, few scholars have used bibliometrics to research Blockchain; the inheritance and evolution among its different research themes have not yet been fully understood. This study emphasizes the scientific evolution and research focus of Blockchain through bibliometric analysis. We analyzed 2993 publications from 2014 to 2020 using co-word analysis and cluster analysis with bibliometric tools such as the SciMAT. The most productive author, country, institutions and leading research areas were identified, outlining the Blockchain field’s fundamental developments. The results show the changes in keywords regarding Blockchain summarize the research hotspots in different periods. The study discusses the evolution process of various themes in each period, providing a meaningful reference for scholars to identify research hotspots and future research directions in the Blockchain field.

Context Owing to the complexity of chemical ingredients in traditional Chinese medicine (TCM), it is difficult to maintain quality and efficacy by relying only on chemical markers. Objective Lianhua Qingwen capsule (LHQW) was selected as an example to discuss the feasibility of a bioassay for quality control. Materials and methods Network pharmacology was used to screen potential targets in LHQW with respect to its anti-inflammatory effects. An in vitro cell model was used to validate the prediction. An anti-inflammatory bioassay was established for the quality evaluation of LHQW in 40 batches of marketed products and three batches of destructed samples. Results The tumor necrosis factor/interleukin-6 (TNF/IL-6) pathway via macrophage was selected as the potential target of LHQW. The IC50 value of LHQW on RAW 264.7 was 799.8 μg/mL. LHQW had significant inhibitory effects on the expression of IL-6 in a dose-dependent manner (p

Objectives: In this study, we aimed to compare the levels of maternal blood lipids, placental and venous blood lipid transporters, and inflammatory factor receptors in pregnant women with and without gestational diabetes mellitus (GDM). We also aimed to figure out the relationship between these values and neonatal weight. Methods: Fifty pregnant women with GDM under blood glucose control belong to the case group, and 50 pregnant women with normal glucose tolerance in concurrent delivery belong to the control group. Fasting venous blood of these pregnant women was taken 2 weeks before delivery, and umbilical cord blood was collected after delivery. The levels of triglyceride (TG), serum total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol (HDL-C) in maternal blood and umbilical cord blood were tested in the laboratory department of our hospital. The level of toll-like receptor 4 (TLR4) in serum of umbilical veins was detected by the double-antibody sandwich ELISA. Western blot and RT-PCR were used to detect the protein and mRNA expressions of TLR4, LPL, and FAT/CD36 in the placenta. Results: The level of TG in maternal blood in the case group was remarkably higher than that in the control group, which was opposite to the level of HDL-C. In the umbilical cord blood of women with GDM, the expression of TLR4 increased and was closely correlated with neonatal weight. In the placenta of women with GDM, the expressions of FAT/CD36 and TLR4 increased, and both of them were closely correlated with neonatal weight. Besides, TLR4 in umbilical cord blood increased and was closely correlated with neonatal weight. Although the expression of LPL in the placenta decreased, it had no obvious correlation with neonatal weight. Conclusions: TG in maternal blood, TLR4 in the placenta and umbilical cord blood, and FAT/CD36 in the placenta were positively correlated with neonatal weight. However, HDL-C in maternal blood was negatively correlated with neonatal weight. Although the expression of LPL in the placenta reduced due to GDM, it had no correlation with neonatal weight.

Trial Information ClinicalTrials.gov Identifier: NCT02525237 Sponsor: Xiaochun Zhang Principal Investigator: Xiaochun Zhang IRB Approved: Yes Lessons Learned Apatinib combined with S-1 was not superior to other chemotherapy regimens as first-line therapy for advanced gastric cancer. There was a tendency for patients with lymph node metastasis to have prolonged median progression-free survival and median overall survival, compared with patients with liver metastasis. Background The best choice of first-line chemotherapy regimen for patients with metastatic gastric cancer is still debated. We combined apatinib and S-1 as a new first-line therapy to treat advanced gastric cancer. The efficacy and safety of the combination were assessed, with the goal of determining the most appropriate subgroup of patients who could benefit from this new regimen. Methods This study was an open, exploratory single-arm, phase II trial. Enrolled patients received apatinib plus S-1 treatment (apatinib, 500 mg, once a day [qd], days 1–21; S-1, 40 mg/m2, bid, days 1–14). The primary endpoints were progression-free survival (PFS) and safety of this new regimen. Next-generation sequencing was used to explore potential biomarkers. Results A total of 30 patients were enrolled. The median progression-free survival (mPFS) was 4.21 months (95% confidence interval [CI], 2.29–6.13 months). The median overall survival (mOS) was 7.49 months (95% CI, 4.81–10.17 months). Patients with lymph node metastasis had prolonged mPFS and mOS when compared with those with liver metastasis (mPFS, 4.21 vs. 1.84 months; mOS, 8.21 vs. 6.31 months, p = .08). The most common grade 3 to 4 adverse events were abdominal pain, dizziness, and diarrhea. Gene mutation profiles between the two subgroups were significantly different. Conclusion Apatinib combined with S-1 was not superior to other chemotherapy regimens as first-line therapy for advanced gastric cancer. Toxicity was consistent with known profiles when given as monotherapy. There was a tendency toward prolonged mPFS and mOS in patients with lymph node metastasis compared with patients with liver metastasis, which could support the need to design a future clinical trial with a better defined patient population.