Search

The optical Bloch oscillation (OBO) is an optical-quantum analogy effect that is significant for light field manipulations, such as light beam localization, oscillation and tunneling. As an intra-band oscillation, OBO was important for optical investigations in photonic lattices and atomic vapors over an extended period of time. However, OBO in reconfigurable platforms is still an open topic, even though tunability is highly desired in developing modern photonic techniques. Here we theoretically establish and experimentally demonstrate OBO in an electromagnetically induced photonic lattice with a ramping refractive index, established in a coherently-prepared three-level 85Rb atomic vapor under the electromagnetically induced transparency condition. This is achieved by interfering two coupling beams with Gaussian profiles and launching a probe beam that exhibits OBO within the resulting lattice. The induced reconfigurable photonic lattice possesses a transverse gradient, due to the innate edges of Gaussian beams, and sets a new stage for guiding the flow of light in periodic photonic environments. Our results should motivate better understanding of peculiar physical properties of an intriguing quantum-optical analogy in an atomic setting.

3D convolutional neural networks have achieved great success for action recognition. However, large variations of temporal dynamics have not been properly processed and low-level features have not been fully exploited in most existing works. To solve these two problems, we present a general and flexible framework, namely multi-level temporal dilated dense prediction network, which can incorporate with most of existing methods as backbone to improve the temporal modeling capacity. In the proposed method, a novel temporal dilated dense prediction block is designed to fully utilize temporal features with various temporal dilated rates for dense prediction while maintaining relatively low computational cost. To fuse information from low to high levels, our method combines the predictions from multiple such blocks inserted at different stages of the backbone network. In-depth analysis is given to show that short- to long-term temporal dependencies can be captured and multi-level spatio-temporal features are effectively fused for video action recognition by the proposed method. Experimental results demonstrate that our method achieves impressive performance improvement on four publicly available action recognition benchmarks including Charades, Kinetics, Something-Something-V1 and HMDB51.

Rationale and Objectives Intra-peritumoural textural transition (Ipris) is a new radiomics method, which includes a series of quantitative measurements of the image features that represent the differences between the inside and outside of the tumour. This study aimed to explore the feasibility of Ipris analysis for the preoperative prediction of axillary lymph node (ALN) status in patients with breast cancer based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and Methods This study was approved by the Institutional Review Board (IRB) of our hospital. One hundred sixty-six patients with clinicopathologically confirmed invasive breast cancer and ALN status were enrolled. All patients underwent preoperative breast DCE-MRI examinations. The primary breast lesion was manually segmented using the ITK-SNAP software for each patient. Two sets of image features were extracted, including Ipris features and conventional intratumoural features. Feature selection was conducted using Spearman correlation analysis and support vector machine with recursive feature elimination (SVM-RFE). Next, three models were established in training dataset: Model 1 was established by Ipris features; Model 2 was established by intratumoural features; Model 3 was established by combining Ipris features and intratumoural features. The performances of the three models were evaluated for the prediction of ALN status in testing datasets. Results Model 1 with four Ipris features achieved an AUC of 0.816 (95% CI, 0.733–0.883) and 0.829 (95% CI, 0.695–0.922) in the training and testing datasets, respectively. Model 2 with six intratumoural features achieved an AUC of 0.801 (95% CI, 0.716–0.870) and 0.824 (95% CI, 0.689–0.918) in the training and testing datasets, respectively. By incorporating the Ipris and intratumoural features, the AUC of Model 3 increased to 0.968 (95% CI, 0.916–0.992) and 0.855 (95% CI, 0.724–0.939) in the training and testing datasets, respectively. Conclusion Ipris features based on DCE-MRI can be used to predict ALN status in patients with breast cancer. The model combining intratumoural and Ipris features achieved higher prediction performance.

Background & aims Nonalcoholic fatty liver disease (NAFLD) is a key component of metabolic syndrome ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) and is now becoming the leading cause of cirrhosis and hepatocellular carcinoma worldwide. However, due to the complex and unclear pathophysiological mechanism, there are no specific approved agents for treating NASH. Breviscapine, a natural flavonoid prescription drug isolated from the traditional Chinese herb Erigeron breviscapus, exhibits a wide range of pharmacological properties, including effects on metabolism. However, the anti-NASH efficacy and mechanisms of breviscapine have not yet been characterized. Approach & results We evaluated the effects of breviscapine on the development of hepatic steatosis, inflammation and fibrosis in vivo and in vitro under metabolic stress. Breviscapine treatment significantly reduced lipid accumulation, inflammatory cell infiltration, liver injury and fibrosis in mice fed a high-fat diet (HFD), a high-fat/high-cholesterol (HFHC) diet, or a methionine- and choline-deficient (MCD) diet. In addition, breviscapine attenuated lipid accumulation, inflammation and lipotoxicity in hepatocytes undergoing metabolic stress. RNA sequencing and multiomics analyses further indicated that the key mechanism linking the anti-NASH effects of breviscapine was inhibition of TAK1 phosphorylation and the subsequent MAPK signaling cascade. Treatment with the TAK1 inhibitor 5Z-7-oxozeaenol abrogated breviscapine-mediated hepatoprotection under metabolic stress. Molecular docking illustrated that breviscapine directly bound to TAK1. Conclusion Breviscapine prevents metabolic stress-induced NASH progression through direct inhibition of TAK1 signaling. Breviscapine might be a novel therapeutic candidate for the treatment of NASH.

BACKGROUND AND AIMS: Unhealthy alcohol use (UAU) is one of the leading causes of global morbidity. A machine learning approach to alcohol screening could accelerate best practices when integrated into electronic health record (EHR) systems. This study aimed to validate externally a natural language processing (NLP) classifier developed at an independent medical center. DESIGN: Retrospective cohort study. SETTING: The site for validation was a midwestern United States tertiary-care, urban medical center that has an inpatient structured universal screening model for unhealthy substance use and an active addiction consult service. PARTICIPANTS/CASES: Unplanned admissions of adult patients between October 23, 2017 and December 31, 2019, with EHR documentation of manual alcohol screening were included in the cohort (n = 57 605). MEASUREMENTS: The Alcohol Use Disorders Identification Test (AUDIT) served as the reference standard. AUDIT scores ≥5 for females and ≥8 for males served as cases for UAU. To examine error in manual screening or under-reporting, a post hoc error analysis was conducted, reviewing discordance between the NLP classifier and AUDIT-derived reference. All clinical notes excluding the manual screening and AUDIT documentation from the EHR were included in the NLP analysis. FINDINGS: Using clinical notes from the first 24 hours of each encounter, the NLP classifier demonstrated an area under the receiver operating characteristic curve (AUCROC) and precision-recall area under the curve (PRAUC) of 0.91 (95% CI = 0.89-0.92) and 0.56 (95% CI = 0.53-0.60), respectively. At the optimal cut point of 0.5, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.66 (95% CI = 0.62-0.69), 0.98 (95% CI = 0.98-0.98), 0.35 (95% CI = 0.33-0.38), and 1.0 (95% CI = 1.0-1.0), respectively. CONCLUSIONS: External validation of a publicly available alcohol misuse classifier demonstrates adequate sensitivity and specificity for routine clinical use as an automated screening tool for identifying at-risk patients.

In this paper, an improved simultaneous fault diagnostic algorithm with cohesion-based feature selection and improved backpropagation multilabel learning (BP-MLL) classification is proposed to localize and diagnose different simultaneous faults on gearbox and bearings in rotating machinery. Cohesion evaluation algorithm selects high sensitivity feature parameters from time and frequency domain in high-dimensional vectors to construct low-dimensional feature vectors. The BP-MLL neural network is utilized for fault diagnosis by classifying the feature vectors. An effective global error function is proposed in BP-MLL neural network by modifying distance function to improve both generalization ability and fault diagnostic ability of full-labeled and nonlabeled situations. To demonstrate the effectiveness of the proposed method, simultaneous fault diagnosis experiments are conducted via wind turbine drivetrain diagnostics simulator (WTDDS). The experiment results show that the proposed method has better overall performance compared with conventional BP-MLL algorithm and some other learning algorithms.

Background Valproic acid (VPA) has been widely used to prevent epileptic seizures after neurosurgery in China. We have found that the incidence of liver injury (LI) in patients using VPA after neurosurgery is higher than that in other patients. Objective The objective of this study was to investigate the risk factors of LI in patients using VPA after neurosurgery. Methods A nested case-control study was conducted in patients using VPA after neurosurgery between September 2019 and March 2021. Cases of LI were matched to controls by age and body mass index (BMI). Conditional logistic regression was used to estimate matched odds ratios representing the odds of LI. A receiver operating characteristic curve was used to analyze the optimal cutoff condition. Results A total of 248 people (62 LI and 186 control) were enrolled. Among patients with vs without LI, the matched odds ratio for trough concentration of VPA was significant (matched odds ratio [OR], 1.09; 95% confidence interval [CI]: 1.01-1.19). The course of treatment (OR: 1.17, 95% CI: 1.02-1.33), Glasgow score (OR: 0.26, 95% CI: 0.10-0.67), gene polymorphisms of CYP2C19 (OR: 2.09, 95% CI: 1.03-146.93), and UGT1A6 (OR: 34.61, 95% CI: 1.19-1003.23) were all related to the outcome. The optimal cutoff of the course of treatment was 10 days, while the trough concentration of VPA was determined to be 66.16 mg/L. Conclusion Length of treatment, VPA trough concentration, and Glasgow score were associated with LI in patients after neurosurgery. A gene test may be necessary for people who are prescribed VPA for a long time.

Introduction To automatically recognize polyps of enteroscopy images and avoid pathological change, a novel Joint-Net has been proposed. Material and methods The left half of the Joint-Net is constructed by transfer learning VGG16 and its right half is deepened based on the U-Net. In the previous two skip connections, a 3 × 3 convolution layer is added and the original two convolutions are replaced by the identity blocks. To connect the left and the right half part, the asymmetric convolution layer is used. In the output, the loophole-like structure is used. Results The enteroscopy images were obtained in Changhai Hospital of Shanghai. The mean values of Dice and intersection over union were 90.05% and 82.71%. The classification accuracy of normal images and polyp images was 93.50%. Conclusions The experiments show that the Joint-Net can segment and recognize the polyps successfully.

Background Type 1 diabetes mellitus (T1DM) is one of the most common chronic illnesses among the youth. Emerging evidence has suggested poor sleep as a risk factor for glycemic control. This review aimed to examine the associations between sleep characteristics and diabetes management in children, adolescents, and emerging young adults with T1DM. Methods Following PRISMA guidelines, the authors searched articles in PubMed, Web of Science, and Scopus from 2000 through August 2020. Using inclusion and exclusion criteria, observational studies and clinical trials that examined sleep and diabetes management among individuals with T1DM (up to 25 years old) were selected for review. Results Twenty-four articles met the review criteria. Most studies did not report differences in self-report sleep between individuals with and without T1DM. However, several studies using objective sleep measures (actigraph and PSG) suggested shorter sleep duration and worse sleep quality in individuals with T1DM. Higher A1C levels and undesirable T1DM self-care behaviors were associated with short and long sleep duration, poor sleep quality, sleep disturbances, and irregular sleep, particularly among adolescent boys, young men and those from immigrant families. Self-care behaviors mediated the associations between sleep and subsequent A1C levels. Conclusions Too much or too little sleep, poor sleep quality, sleep disturbances and sleep variability are associated with undesirable T1DM management. Although more research is needed, our findings indicate the importance of including sleep education in the plan of care for children, adolescents and emerging young adults with T1DM.

Background With life span extending, breast cancer (BC) survivors may face the possibility of developing second primary cancer (SPC) and considerably shorten survivorship. However, little is known about multiple primary cancer (MPC) patients with nonmetastatic breast cancer as a first primary malignancy (BCFPM). Methods Here, we retrospectively analyzed data on cancer survivors with BCFPM diagnosed between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic factors for breast cancer‐specific survival (BCSS) were ascertained by the stepwise regression analysis and a competing risk model, and were integrated to the establishment of prognostic nomogram, of which the accuracy was measured by the calibration curve and the concordance index (C‐index). Results In total, 8616 patients were identified with 4.6% of 3‐year breast cancer‐ specific death (BCSD) and 8.6% of 5‐year BCSD. The most common SPC among BCFPM patients were female BC and lung cancer. Besides, the median latency time between BC and SPC was 22 months. At a ratio of 7:3, all patients were randomly categorized into a training cohort (n = 6032) and a validation cohort (n = 2584). By a proportional subdistribution hazards regression analysis, the following factors were considered to own independent prognostic abilities of BCSS: subtypes, grade, T classification, N classification, radiation, and sites of SPC. The nomogram could accurately predict 3‐year and 5‐year breast cancer‐associated survival of BCFPM patients with high internal and external validated C‐index, 0.715 (95% CI, 0.691–0.739), and 0.683 (95% CI, 0.642–0.724), respectively. Conclusions BC survivors remained a high risk of developing SPC and considerably shortened survival time. In this study, a favorable nomogram was constructed to as a prediction model for 3‐year and 5‐year BCSS of BCFPM patients, largely intending to prolong the life of these patients by assisting clinicians to make individualized follow‐up plans., A remarkable number of second primary cancers (SPC) occur in breast cancer survivors and constitute an emerging subgroup of tumors, with a shortage of overall understanding and normative management. Here, we gathered a mass of retrospective data with precise definition of SPC and further explored the clinical characteristics and prognostic predictors of these patients, thus effectively avoiding the deviation caused by small sample and SPC misclassification.

Aim: To explore the predictive value of plasma YAP1 for esophageal varices (EV) and high-risk EV (HRV) in patients with liver cirrhosis. Materials & methods: A total of 208 patients with liver cirrhosis were enrolled and categorized into four groups. Correlation analysis, logistic regression analysis and receiver operating characteristic curve analysis were performed to evaluate the diagnostic performance of plasma YAP1 for EV and HRV. Results: Plasma YAP1 levels were significantly elevated with the occurrence and progression of EV in cirrhotic patients. The multivariate logistic regression analysis revealed that plasma YAP1 is an independent predictor for EV and HRV. For predicting EV and HRV, the YAP1 cut-off values of 5.43 and 6.98 ng/ml yielded the area under the receiver operating characteristic curves of 0.944 and 0.955, respectively. Conclusion: Plasma YAP1 is a potential novel noninvasive biomarker for predicting EV and HRV in patients with liver cirrhosis.

As the influence of online reviews on customers is drastically increasing, their financial impact and factors on review attributes have been examined in hospitality literature. Online reviews have been highlighted as an important cue that drives firm performance, but little attention has been made to the dynamic interconnections of online reviews with other cues that are likely to be used simultaneously. This study therefore investigated the multifaced relationship between online reviews and brand in the restaurant context. Two-stage least squares analysis was applied to analyze the effect of these two cues on financial performance of 1,210 Iowa restaurants from 2010 to 2017. Our analysis showed that the financial impact of positive reviews decreased in the presence of brand and that customer engagement in online reviews was different depending on brand strength. Based on the findings, restaurant managers are advised to shift the focus of marketing strategies as brand strength grows.

Noise and distortion in real signals have posed challenges in signal detection in ultrahigh-frequency (UHF) radio frequency identification (RFID) systems, with the exception of large frequency deviation. In this article, signal detection in a UHF RFID system was treated as a time-series classification problem. A support vector machine-based detector was proposed for real-time signal detection to optimize the system performance. The improved system was able to achieve frame synchronization detection and time-series data detection with a frequency deviation of ± 22%. With the analysis of the frame format, the frame synchronization was based on the sequence detection with the most likely selection, and the data detection was performed using a symbol-by-symbol method with two-step adjustments in order to reduce time and hardware costs. The algorithm was mainly trained offline using the experimental data, and then efficiently implemented in a UHF RFID system based on a software-defined radio platform. The system was validated on real-time signals of commercial tags. The experimental results showed that the learned detector had displayed improvements in detection accuracy and stability when compared to the existing method based on a correlation algorithm.

Exaggerated immune response and cytokine storm are accounted for the severity of COVID-19, including organ dysfunction, especially progressive respiratory failure and generalized coagulopathy. Uncontrolled activation of complement contributes to acute and chronic inflammation, the generation of cytokine storm, intravascular coagulation and cell/tissue damage, which may be a favorable target for the treatment of multiple organ failure and reduction of mortality in critically ill patients with COVID-19. Cytokine storm suppression therapy can alleviate the symptoms of critically ill patients to some extent, but as a remedial etiological measure, its long-term efficacy is still questionable. Anti-complement therapy has undoubtedly become an important hotspot in the upstream regulation of cytokine storm. However, chemosynthetic complement inhibitors are expensive, and their drug resistance and long-term side effects require further investigation. New complement inhibitors with high efficiency and low toxicity can be obtained from natural products at low development cost. This paper puts forward some insights of the development of natural anti-complement products in traditional Chinese medicine, that may provide a bright perspective for suppressing cytokine storm in critically ill patients with COVID-19. Supplementary Information The online version contains supplementary material available at 10.1186/s13020-021-00478-3.

Background Adverse events of chemotherapy may be caused by pharmacodynamics or psychological factors such as negative expectations, which constitute nocebo effects. In a randomized controlled trial, we examined whether educating patients about the nocebo effect is efficacious in reducing the intensity of self-reported adverse events. Methods In this proof-of-concept study, N = 100 outpatients (mean age: 60.2 years, 65% male, 54% UICC tumour stage IV) starting first-line, de novo chemotherapy for gastrointestinal cancers were randomized 1:1 to a nocebo education (n = 49) or an attention control group (n = 51). Our primary outcome was patient-rated intensity of four chemotherapy-specific and three non-specific adverse events (rated on 11-point Likert scales) at 10-days and 12-weeks after the first course of chemotherapy. Secondary outcomes included perceived control of adverse events and tendency to misattribute symptoms. Results General linear models indicated that intensity of adverse events differed at 12-weeks after the first course of chemotherapy (mean difference: 4.04, 95% CI [0.72, 7.36], p = .02, d = 0.48), with lower levels in the nocebo education group. This was attributable to less non-specific adverse events (mean difference: 0.39, 95% CI [0.04, 0.73], p = .03, d = 0.44) and a trend towards less specific adverse events in the nocebo education group (mean difference: 0.36, 95% CI [− 0.02, 0.74], p = .07, d = 0.37). We found no difference in adverse events at 10-days follow-up, perceived control of adverse events, or tendency to misattribute non-specific symptoms to the chemotherapy. Conclusions This study provides first proof-of-concept evidence for the efficacy of a brief information session in preventing adverse events of chemotherapy. However, results regarding patient-reported outcomes cannot rule out response biases. Informing patients about the nocebo effect may be an innovative and clinically feasible intervention for reducing the burden of adverse events. Trial registration Retrospectively registered on March 27, 2018 to the German Clinical Trial Register (ID: DRKS00009501).

The study investigates the effect of signaling multiple identities on interpersonal trust.

Purpose This paper aims to address the spacecraft attitude control problem using hybrid actuators in the presence of actuator saturation, uncertainties and faults, inertia uncertainties and external disturbances. Design/methodology/approach A hybrid actuator configuration is used where thrusters are engaged for rapid attitude maneuvers, while reaction wheels (RWs) are used for fine pointing. Findings The key advantages are two-fold: a finite-time high-level controller is designed to produce the three-axis virtual control torques; an online robust control allocation (RobCA) scheme is proposed to redistribute virtual control signals to the actuators with taking into account the actuator saturation, uncertainties and faults; and the RobCA scheme allows a smooth switch between thrusters and RWs, which handles the inaccuracy problem of thrusters and saturation problem of RWs. Practical implications An online RobCA algorithm is designed that maps the total control demands onto individual actuator settings and allows a smooth switch between thrusters and RWs. Simulation results show the effectiveness of the proposed control strategy. Originality/value This work may be used on modern space missions, which impose higher requirements on smooth switching of spacecraft thrusters and RWs.

This study presents a novel cylindrical vane pump based on the traditional working principle. The efficiency of the cylindrical vane pump was verified by experimental validation and numerical analysis. Numerical analysis, such as kinematics analysis, was performed in Pro/Mechanism and unsteady flow-field analysis was performed using ANSYS FLUENT. The stator surface equations were derived using the geometric theory of the applied spatial triangulation function. A three-dimensional model of the cylindrical vane pump was established with the help of MATLAB and Pro/E. The kinematic analysis helped in developing kinematic equations for cylindrical vane pumps and proved the effectiveness of the structural design. The maximum inaccuracy error of the computational fluid dynamics (CFD) model was 5.7% compared with the experimental results, and the CFD results show that the structure of the pump was reasonable. An experimental test bench was developed, and the results were in excellent agreement with the numerical results of CFD. The experimental results show that the cylindrical vane pump satisfied the three-element design of a positive-displacement pump and the trend of changes in efficiency was the same for all types of efficiency under different operating conditions. Furthermore, the volumetric efficiency presented a nonlinear positive correlation with increased rotational velocity, the mechanical efficiency showed a nonlinear negative correlation, and the total efficiency first increased and then decreased. When the rotational velocity was 1.33[Formula: see text] and the discharge pressure was 0.68[Formula: see text], the total efficiency reached its maximum value.

The purpose of this study was to evaluate the association between starchy vegetable consumption and subgroup consumption in the first trimester and the risk of gestational diabetes mellitus (GDM).A prospective study (Among the 1444 participants in our study, 520 were diagnosed with GDM. The adjusted RRs (95% CIs) for GDM from the lowest to the highest quartiles of total starchy vegetable consumption were 1.00 (reference), 1.29 (1.06, 1.57), 1.13 (0.93, 1.40), and 1.26 (1.02, 1.56), respectively;A higher consumption of total starchy vegetables and potatoes in the first trimester is associated with a greater risk of GDM.

A reliable system simulation combining socio-economic development with water environment and comprehensively reflect a watershed's dynamic features is crucial. In this study, a complex system dynamics model is constructed to evaluate dynamic changes of socio-economic development and ecological environment of Weihe River Basin (WHR). Development trends of the population, economy, land resources, water demand and supply, water environment and water pollution and management are obtained from 2005 to 2030 through scenarios analysis representing different regional development orientations, namely, population growth (S1), economic leading (S2), resources saving (S3), environment leading (S4), collaborative development (S5). Compared with other scenarios, the total population and GDP will, respectively, reach 3,716.55 × 104 person and 40,077.30 × 108 yuan, and the gap between demand and supply and the amount of water pollution will, respectively, narrow to 0.56 × 108 and 12.26 × 108 cubic meters in collaborative development scenario (S5). The results reveal the collaborative development scenario (S5) can achieve not only steady population and economy growth, as well as narrow down the gap between water supply and demand, but also optimize watershed environment management of the WHR. Thus, the system dynamics model used in our research provides a powerful tool for assisting decision-making on issues of coordinative socio-economic development, environmental health protection, water resources conservation, etc., in a river basin area. Highlights Discussing interrelations among socio-economy, resources and environment in watershed.; Evaluating the joint effects of socio-economic development and watershed environment management.; Water resource demand causes the water resource imbalance in the Weihe River Basin.; Strengthening environmental protection requires coordinative development.; Identifying optimal and practical strategy for coordinative development mode.

A 5-bit 360° active phase shifter of digital control with a novel two-step vector-sum technique in $0.18\mu \text{m}$ SiGe process is presented in this brief for X-band phased arrays. The two-step vector-sum technique is based on a sub-phase shifter array controlled by high quality logic circuit to avoid the issue of control circuit with low accuracy in the conventional scheme. The implemented phase shifter features good performance of 11.25° phase resolution and full 360° phase synthesizing between 8–12 GHz. Measurements display that the RMS gain error is below 0.6 dB while the RMS phase error is lower than 4.6°. The measured insertion loss is less than – 11.9 dB at 12 GHz while the return loss is better than – 13 dB over 8 to 12 GHz. With a 3.3V voltage supply, the DC power consumption is 73.92 mW. The designed phase shifter has a compact size of 0.6 $mm^{2}$ .

AIM: To observe whether silicone oil (SO) tamponade could decrease macular perfusion after retinal detachment repair. METHODS: A prospective observational case-control study. Patients diagnosed with primary macular off rhegmatogenous retinal detachment undergoing successful retinal repair surgery with vitrectomy were strictly selected. Optical coherence tomography angiography findings were compared between SO and air tamponade groups. Two postoperative visiting points were set (1 and 3mo). RESULTS: Totally 29 patients (29 eyes) were enrolled. Twenty cases had SO tamponade while 9 cases were with air tamponade. At the first visiting point, superficial parafoveal vessel density (PFSVD) significantly decreased in the SO group (P=0.0403), especially in the superior quadrant or superior-hemi area (P=0.0089, 0.0426, respectively). Parafoveal deep vessel density (PFDVD) had no difference between the two groups. At the second visiting point, all quadrants of PFSVD reduced significantly in the SO group (P=0.0256, 0.0001, 0.0031

Study Design: Modified Delphi study. Objective: The objective of this study was to establish expert consensus on the application of lateral lumbar interbody fusion (LLIF) by using the modified Delphi study. Methods: From June 2019 to March 2020, Members of the Chinese Study Group for Lateral Lumbar Spine Surgery were selected to collect expert feedback using the modified Delphi method where 65 spine surgeons from all over China agreed to participate. Four rounds were performed: 1 face-to-face meeting and 3 subsequent survey rounds. The consensus was achieved with ≥a 70.0% agreement for each question. The recommendation of grade A was defined as ≥90.0% of the agreement for each question. The recommendation of grade B was defined as 80.0-89.9% of the agreement for each question. The recommendation of grade C was defined as 70.0-79.9% of the agreement for each question. Results: A total of 65 experts formed a panelist group, and the number of questionnaires collected was 63, 59, and 62 in the 3 rounds. In total, 5 sections, 71 questions, and 382 items achieved consensus after the Delphi rounds including summary; preoperative evaluation; application at the lumbar spinal stenosis, lumbar disc herniation, lumbar spondylolisthesis, adult degenerative scoliosis, postoperative adjacent segmental degeneration, and revision surgery; complications; and postoperative follow-up evaluation of LLIF. Conclusion: The modified Delphi method was utilized to ascertain an expert consensus from the Chinese Study Group for Lateral Lumbar Spine Surgery to inform clinical decision-making in the application of LLIF. The salient grade A recommendations of the survey are enumerated.

Objectives:Fruit intake may influence gestational diabetes mellitus (GDM) risk. However, prospective evidence remains controversial and limited. The current study aimed to investigate whether total fruit and specific fruit intake influence GDM risk.Design:A prospective cohort study was conducted. Dietary information was collected by a 3-d 24-h dietary recall. All participants underwent a standard 75-g oral glucose tolerance test at 24–28 gestational weeks. Log-binomial models were used to estimate the association between fruit intake and GDM risk, and the results are presented as relative risks (RR) and 95 % CI.Setting:Southwest China.Participants:Totally, 1453 healthy pregnant women in 2017.Results:Total fruit intake was not associated with lower GDM risk (RR of 1·03 (95 % CI 0·83, 1·27) (Ptrend = 0·789)). The RR of GDM risk was 0·73 for the highest anthocyanin-rich fruit intake quartile compared with the lowest quartile (95 % CI 0·56, 0·93; Ptrend = 0·015). A higher grape intake had a linear inverse association with GDM risk (Q4 v. Q1: RR = 0·65; 95 % CI 0·43, 0·98; Ptrend = 0·044), and after further adjustment for anthocyanin intake, the inverse association tended to be non-linear (Q4 v. Q1: RR = 0·65; 95 % CI 0·44, 0·98; Ptrend = 0·079). However, we did not find an association between glycaemic index-grouped fruit, glycaemic load-grouped fruit or other fruit subtype intake and GDM risk.Conclusions:In conclusion, specific fruit intake (particularly anthocyanin-rich fruit and grapes) but not total fruit intake was inversely associated with GDM risk.

Cytokines are key components of the immune system and play pivotal roles in anticancer immune response. Cytokines as either therapeutic agents or targets hold clinical promise for cancer precise treatment. Here, we provide an overview of the various roles of cytokines in the cancer immunity cycle, with a particular focus on the clinical researches of cytokine-based drugs in cancer therapy. We review 27 cytokines in 2630 cancer clinical trials registered with ClinicalTrials.gov that had completed recruitment up to January 2021 while summarizing important cases for each cytokine. We also discuss recent progress in methods for improving the delivery efficiency, stability, biocompatibility, and availability of cytokines in therapeutic applications.

Malnutrition in gastric cancer patients with normal body mass index (BMI) is often ignored. This study aimed to explore the role of sarcopenia in predicting postoperative complication and long-term survival in gastric cancer patients with normal BMI. We included patients with normal BMI (18.5 kg/m2 ≤ BMI ＜ 23 kg/m2 ) who underwent radical gastrectomy between July 2014 and December 2016. Sarcopenia was assessed by muscle mass, handgrip strength, and gait speed. Kaplan-Meier survival analysis was used to analyze the association between sarcopenia and the prognosis of gastric cancer patients. Univariate and multivariate analyses were used to identify risk factors contributing to postoperative complications and long-term survival. Overall, 267 gastric cancer patients with normal BMI were included in this study; of which, 49 (18.35%) patients were diagnosed with sarcopenia. Sarcopenia patients had higher incidence of a major postoperative complication, longer postoperative hospital stays, and greater hospital costs. The Kaplan-Meier survival analysis showed that sarcopenia patients had poorer overall survival than non-sarcopenia patients. Univariate and multivariate analyses showed that sarcopenia was an independent predictor for postoperative complication and long-term survival in such patients. Sarcopenia is an independent predictor for postoperative complication and long-term survival in patients with normal BMI after radical gastrectomy for gastric cancer. We recommend that patients with normal BMI should perform nutritional risk screening by sarcopenia.

With the development of e-commerce, an increasing number of online reviews can serve as a promising data source for enterprises to improve online products. This paper proposes a method for modelling consumer satisfaction based on online reviews using the improved Kano model from the perspective of risk attitude and aspiration. Firstly, the attributes concerned by consumers are extracted from online reviews, and sentiment analysis of the extracted attributes is carried out using Standford CoreNLP. Secondly, to identify the types of product attributes, an improved Kano model is proposed based on the effects of product attributes on consumer total utility. On this basis, different attribute types are illustrated from the perspective of risk attitude. Then, the consumer aspirations are mined based on the risk attitudes of different attributes and the attribute impact on consumer satisfaction. According to the risk attitudes and aspirations of different attributes, the quantified satisfaction functions are constructed to provide more objective and accurate improvement suggestions. Finally, the proposed method is applied to the hotel service improvement to illustrate the effectiveness. First published online 13 April 2021

Based on information asymmetry, agency theory and resource-based view (RBV), this study investigates the impact of venture capital (VC) on venture firm innovation performance, ascertains the extent to which VC affects venture firm innovation performance and finds the mediating effect of management incentives. Constructing a sample of a novel panel dataset of firms listed on the SME Board of China, we examined a sample of 927 start-ups between 2008 and 2017, showing a notable negative relationship between VC and Patent, and a positive relationship between VC and total factor productivity (TFP), providing stable evidence that VC could not spur firm patent directly, but facilitate the commercialization of innovation. Moreover, it shows that management equity incentives (MEI) and management cash incentives (MCI) playing significant positive mediating role between VC and TFP, while there is no mediating effect between VC and Patent. Findings of this study strengthen the experience of VC and suggest how practitioners of SMEs to enhance the commercialization of innovation, considerably extends our understanding of the impact of VC on venture firm innovation performance.

Background Programmed death protein (ligand) 1 [PD-(L)1] inhibitors have provided new therapeutic options for advanced lung cancer. However, patients with hepatitis B virus (HBV) infection have been traditionally excluded from most registered trials of this form of treatment. Methods We performed a retrospective analysis of patients with HBV and advanced lung cancer who received anti-PD-1 immunotherapy from September 2018 to May 2020 in our department. Treatment-related hepatotoxicity was evaluated and recorded. Overall response rate and progression free survival were also assessed in the patients using iRECIST. Results Seventeen patients were evaluated in this analysis. Of these, six (35.3%) experienced hepatic transaminase elevation during immunotherapy. Three of these patients developed Grade 3 hepatic immune-related adverse events and received systemic corticosteroids, following which aminotransferase levels recovered to normal in all patients and no adverse events were observed in subsequent treatment. No patient experienced HBV reactivation or flare. One patient developed active pulmonary tuberculosis (TB). Other adverse events were mild, well tolerated and short term. The objective response rate (ORR) of the cohort was 62.5%, and the median progression-free survival (PFS) was 3 months. Conclusions Lung cancer patients can be treated safely with anti-PD-1 inhibitors in the context of HBV infection. Close monitoring for hepatotoxicity and prophylactic antiviral therapy is advised. Further studies on the use of anti-PD-1 inhibitors in HBV-infected patients are needed.

Background In 2015, a Chinese expert consensus on photopatch testing (PPT) was established, based on European consensus methodology. Objectives To update current information on the prevalence of photoallergic contact dermatitis (PACD) to 20 photoallergens and their clinical relevance in the Chinese context. Methods A retrospective analysis of 2372 patients who performed PPT in a tertiary referral center in China between 2015 and 2019 was completed. A total of 1208 PACD reactions were observed in 897 (37.8%) patients, and 413 reactions were of current or past relevance. Results The proportion of reactions of current or past relevance was 34.2%. The most frequent photoallergens were chlorpromazine, thimerosal, potassium dichromate, and formaldehyde. The ultraviolet absorbers, benzophenone and Para-aminobenzoic acid, showed opposite gender distribution to PACD. Twenty-five patients (1.9%) developed PACD reactions to a newly added photoallergen preparation - fragrance mix I. Patients with chronic actinic dermatitis, widespread exposed-site or generalized dermatitis, and older age were more likely to have PACD. Conclusions This study is the first to profile PACD reactions with clinical relevance in China. The prevalence of PACD to culprit photoallergens was affected by regional peculiarities. Attention needs to be paid to the age, body-site distribution, and known diagnoses of patients for the identification of PACD.

Objective To explore the associations of duration and quality of sleep during pregnancy with preterm birth and small for gestational age (SGA). Methods A prospective study was carried out on 1082 healthy women with singleton pregnancies from Chengdu, China. Self-report questionnaires, including duration and quality of sleep and other information, were administered at 8-12, 24-28, and 32-36 weeks of pregnancy. Data on gestational age and weight and length of the neonates were recorded after delivery. After controlling the potential confounders, a multivariable logistic regression model was performed to evaluate whether duration and quality of sleep were associated with preterm birth and SGA. Results Participants with short duration of sleep during the third trimester were more likely to report preterm birth (odds ratio [OR] 2.16, 95% confidence interval [CI 1.26-4.81) and SGA (OR 2.67, 95% CI 1.18-6.54). Participants with poor quality of sleep during the third trimester were at high risk for preterm birth (OR 2.26, 95% CI 1.29-5.84) and SGA (OR 2.08, 95% CI 1.19-5.38). Conclusion Short duration and poor quality of sleep during pregnancy are associated with an increased risk of preterm birth and SGA. Sleep characteristics should be assessed during prenatal evaluations to decrease adverse maternal and fetal outcomes.

We compared the performance of five assays for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) detection on nasopharyngeal swab samples: Roche “cobas,” Luminex “ARIES,” MiRXES “Fortitude,” Altona “RealStar,” and Thermo Fisher Scientific “TaqPath.” A total of 94 nasopharyngeal swab samples were obtained from 80 confirmed coronavirus disease 2019 cases in the first 2 weeks of illness (median, 7 days; range, 2–14 days) and 14 healthy controls. After collection, all samples were transported to the hospital clinical laboratory within 24 h. These samples were tested on all five assays within 3 days of sample receipt. Of the 94 samples, 69 yielded the same result on all platforms, resulting in an agreement of 73.4% (69 of 94). Of these, 14 were the healthy control swabs which all tested negative, demonstrating good specificity across all platforms. The ARIES assay had the lowest detection rate (68.8%), followed by Fortitude (85.0%), RealStar (86.3%), cobas (95.0%), and TaqPath (100%). Statistically significant differences were observed for ARIES, Fortitude, and RealStar when compared against the best performing TaqPath using McNemar's χ 2 test. A consensus result was established based on the results obtained by the cobas, Fortitude, RealStar, and TaqPath. Six discrepancies had failed to reach a consensus and were adjudicated using the Cepheid Xpert Xpress SARS‐CoV‐2. Overall, the TaqPath and cobas assays were the most sensitive at detecting their designated SARS‐CoV‐2 gene targets. On the other hand, the ARIES assay was the least sensitive, thus warranting the need for assay re‐optimization before go‐live at the testing laboratory.

Bacillus cereus spores are concerns for food spoilage and foodborne disease in food industry due to their high resistance to heat and various disinfectants. The aim of this study was to investigate...

We aimed to examine the association between low-carbohydrate diet (LCD) scores during the first trimester and gestational diabetes mellitus (GDM) risk in a Chinese population. A total of 1455 women were included in 2017. Dietary information during the first trimester was collected by 24-h dietary recalls for 3 d. The overall, animal and plant LCD scores, which indicated adherence to different low-carbohydrate dietary patterns, were calculated. GDM was diagnosed based on the results of a 75-g, 2-h oral glucose tolerance test at 24–28 weeks gestation. Log-binomial models were used to estimate relative risks (RR) and 95 % CI. The results showed that the multivariable-adjusted RR of GDM from the lowest to the highest quartiles of the overall LCD score were 1·00 (reference), 1·15 (95 % CI 0·92, 1·42), 1·30 (95 % CI 1·06, 1·60) and 1·24 (95 % CI 1·01, 1·52) (P = 0·026 for trend). Multivariable-adjusted RR (95 % CI) of GDM from the lowest to the highest quartiles of the animal LCD score were 1·00 (reference), 1·20 (95 % CI 0·96, 1·50), 1·41 (95 % CI 1·14, 1·73) and 1·29 (95 % CI 1·04, 1·59) (P = 0·002 for trend). After additional adjustment for gestational weight gain before GDM diagnosis, the association of the overall LCD score with GDM risk was non-significant, while the association of animal LCD score with GDM risk remained significant. In conclusion, a low-carbohydrate dietary pattern characterised by high animal fat and protein during the first trimester is associated with an increased risk of GDM in Chinese women.

In times of public health emergencies, health agencies need to engage and communicate with the public in real-time to share updates and accurate information. This is especially the case for the COVID-19 pandemic where public engagement can potentially save lives and flatten the curve. This paper considers how the use of interactive features and strategic network positions of health agencies on social media influenced their public engagement outcomes. Specifically, we analyzed 203 U.S. public health agencies' Twitter activity and the public engagement they received by extracting data from a large-scale Twitter dataset collected from January 21st to May 31st, 2020. Results show that health agencies' network position in addition to their two-way communication strategy greatly influenced the level of public engagement with their COVID-19 related content on Twitter. Findings highlight the benefits of strategic social media communication of public health agencies resides not only in how agencies use social media but also in their formation of network position to amplify their visibility. As official sources of health and risk information, public health agencies should coordinate their social media communication efforts to strategically position themselves in advantageous network positions to augment public engagement outcomes.

Green infrastructure can effectively coordinate environmental, social and economic development, and has become one of the important strategies to achieve sustainable development. This study used CiteSpace and VOSviewer to analyze 2194 papers in the field of green infrastructure published from 1995 to 2019 in the Web of Science database using the bibliometrics and visualization methods. Results demonstrate a substantial increase in the number of studies on green infrastructure in recent years, with European and American countries leading the study of green infrastructure. Landscape and Urban Planning, Urban Forestry & Urban Greening, and Journal of Environmental Management are the first three cited journals in green infrastructure study. By studying co-cited literature, the study of green infrastructure has been found to involve the relationship between green infrastructure and ecosystem and human health, construction, evaluation and management of green infrastructure, and analysis of a special aspect of green infrastructure, among others. Clustering analysis results of green infrastructure keywords indicate that the existing studies have concentrated on green infrastructure in stormwater management, ecosystem services, biodiversity protection, and climate change. This study provides references for green infrastructure for sustainable environment development.

Named data networking (NDN) aims to change the traditional content delivery method and caching by router nodes caching and participating in forwarding. NDN-caching can reduce the expected flood of global data traffic by providing cache storage at intermediate nodes for transmitted content objects, making data broadcasting in an efficient way. In this paper, a novel caching strategy based on entropy weighting method and TOPSIS is proposed for efficient content dissemination to improve NDN’s in-network caching performance. Firstly, the consumer’s request process is modeled by the entropy weighting method and TOPSIS to obtain the best cache node for the cache object according to the real-time status of the node. Secondly, two cache replacement algorithms (composed of an active cache replacement algorithm and a passive cache replacement algorithm) are proposed to reduce the cache redundancy on the delivery path and improve the utilization of data packets in the nodes. Finally, an effective cache mechanism and data packet migration scheme are proposed to further improve the cache performance according to the different types of cache nodes. The performance evaluation shows that the proposed scheme performs better in terms of cache hit rate, latency, and link load compared with some existing strategies.

BackgroundMetabolic syndrome (MetS) in non-overweight/obese people is insidiously associated with cardiovascular disease. Novel anthropometric indices can reflect central obesity better than the traditional anthropometric indices. Therefore, we hypothesize that these newly developed anthropometric indices can better identify MetS in non-overweight/obese people than conventional indices.MethodsCross-sectional data of sociodemographic, biochemical and anthropometric indices were collected from 2916 non-overweight/obese Chinese people. A body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI) and abdominal volume index (AVI) were calculated. Partial correlation analysis was used to clarify the correlation between anthropometric indices and MetS variables. Binary logistic regression analysis was applied to assess the association between anthropometric indices and MetS and its components. Receiver-operating characteristic curve was used to identify the diagnostic ability of anthropometric indices for MetS and its components. The area under curve (AUC) difference between WHtR and each new anthropometric index was compared in pairs.ResultsAfter adjusting for covariates, AVI had the optimal ability of identifying MetS (AUC: 0.743 for male, 0.819 for female) and the strongest correlation with high-density lipoprotein cholesterol (HDL-C) (coe: − 0.227 for male, − 0.207 for female) and the highest odds rations (OR) with low HDL-C group (male: OR = 1.37, female: OR = 1.55). The WHtR was comparable to BRI in assessing MetS (AUC: 0.739 for male, 0.817 for female). WHtR or BRI could also well identify hypertension (AUC: 0.602 for male, 0.688 for female) and dysglycemia (AUC: 0.669 for male, 0.713 for female) and female’s high triglyceride level (AUC 0.712). The recognition ability of the two was equivalent. The ability of ABSI and WWI to identify MetS was weak.ConclusionsAVI is the optimal anthropometric indices to identify MetS in non-overweight/obese Chinese adults. BRI and WHtR can also be considered as discriminators, while ABSI and WWI are weak discriminators. WHtR is easy to measure. So, it is recommended as an early preliminary screening method for the MetS in non-overweight/obese people.

In this paper, a vertically stacked nanosheet gate-all-around field-effect transistor (GAA-NSFET) as a label-free biosensor has been proposed and investigated. The influences of different biomolecules on the biosensor’s electrical properties are analyzed, and the proposed biosensor exhibits good sensitivity for both neutral and charged biomolecules. Furthermore, a deep sensitivity analysis is performed to evaluate the sensing ability of biosensors with different channel structures. The sensitivity variation of biosensors is analyzed in terms of subthreshold swing ( $SS $ ), threshold voltage ( $V_{\text {th}}$ ), and current switching ratio ( $I_{\text {on}} / I_{\text {off}}$ ). The results show that GAA-NSFET-based biosensor obtains the best sensitivity compared with other biosensors (including nanowire FET-based biosensor and vertically stacked nanowire FET-based biosensor) due to its larger channel width and multi-channels. Also, the influences of filling position on sensitivity are analyzed in various cases for the proposed biosensor. Its sensitivity depends on the filling amounts of biomolecules instead of the filling position. Finally, a status map is presented, which plots the sensitivity of some important works in biosensing application along with the sensitivity of the proposed biosensor, and GAA-NSFET-based biosensor is more sensitive compared with those works in terms of $I_{\text {on}}/I_{\text {off}}$ sensitivity.