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Depressed patients suffered from severe psychological distress even after the first COVID-19 outbreak was initially controlled. The longitudinal changes and associations among stress and other psychological problems during this period remained unknown. In this study we investigated stress symptoms and the longitudinal impact of stress symptoms on other psychological symptoms in depressed patients after the first COVID-19 outbreak was initially controlled.A total of 5241 depressed patients at the outpatients of 56 hospitals across mainland China were recruited from May 18 to June 18, 2020. Five months later, 2113 of them responded again. Demographic characteristics were collected and psychological symptoms were evaluated at baseline and the follow-up. The longitudinal associations between stress symptoms at baseline and the changes of other psychological problems were assessed using Poisson regression.The prevalence of stress symptoms, depressive symptoms, anxiety symptoms and insomnia symptoms declined over time. Having stress symptoms at baseline was positively associated with the new occurrences of depressive symptoms, anxiety symptoms and insomnia symptoms (range, adjusted RRs 1.69-1.81).The sampling method and the high dropout rate are the major limitations. Additionally, the mental conditions of the participants were not obtained, which may lead to unavoidable bias.The prevalence of stress symptoms declined over time after the first COVID-19 outbreak was initially controlled. We found that having stress symptoms at baseline was a predictor for the new occurrences of depressive symptoms, anxiety symptoms and insomnia symptoms.

The random finite difference method (RFDM) is a popular approach to quantitatively evaluate the influence of inherent spatial variability of soil on the deformation of embedded tunnels. However, the high computational cost is an ongoing challenge for its application in complex scenarios. To address this limitation, a deep learning-based method for efficient prediction of tunnel deformation in spatially variable soil is proposed. The proposed method uses one-dimensional convolutional neural network (CNN) to identify the pattern between random field input and factor of safety of tunnel deformation output. The mean squared error and correlation coefficient of the CNN model applied to the newly untrained dataset was less than 0.02 and larger than 0.96, respectively. It means that the trained CNN model can replace RFDM analysis for Monte Carlo simulations with a small but sufficient number of random field samples (about 40 samples for each case in this study). It is well known that the machine learning or deep learning model has a common limitation that the confidence of predicted result is unknown and only a deterministic outcome is given. This calls for an approach to gauge the model's confidence interval. It is achieved by applying dropout to all layers of the original model to retrain the model and using the dropout technique when performing inference. The excellent agreement between the CNN model prediction and the RFDM calculated results demonstrated that the proposed deep learning-based method has potential for tunnel performance analysis in spatially variable soils.

Generalized anxiety disorder (GAD) is a common chronic mental disorder, and it also can cause depressive symptoms and cognitive impairment. The primary aim of this study was to determine whether inflow-frequency transcranial magnetic stimulation (ILF-TMS) improves anxiety symptoms in patients with GAD.Sixty-two patients with GAD were randomly divided into 2 groups. Thirty-one patients in the active ILF-TMS group and 31 patients in the sham ILF-TMS group. All participants were assessed at baseline, week 2, week 4 and week 12. The intention-to-treat methodology was used for the analysis.The response rate was higher in the active group than in the sham group, with a significant difference at week 12 (response rate: 80.6% vs. 54.8%, respectively; P = 0.03). Although the remission rate was higher in the active group at week 12, there was no statistically significant difference between the groups (remission rate: 71.0% vs. 48.4%; P 0.05). No statistically significant differences on the Hamilton Depression Rating Scale, Clinical Global Impression scale, and neurocognitive test between groups were observed (overall P 0.05). Adverse events that occurred in the active group were similar to those in the sham group, with no significant differences (P 0.05).The response rate was higher in the active group at the end of the trial, which indicated that ILF-TMS may be an effective and safe adjunctive tool to improve anxiety symptoms in patients with GAD.

Meningococcal disease caused by Neisseria meningitidis remains a major global public health concern. Serogroup A, B, C and W135 were the major disease-causing serogroups. It is vital to timely and efficiently detect and differentiate these four serogroups. Herein, we developed multiple cross displacement amplification-lateral flow biosensor (MCDA-LFB) assays targeting ctrA, sacB, siaD, siaD and synG gene respectively for detection and subtyping of four N. meningitidis serogroups. This assay utilizes LFB to detect FITC and biotin-labeled target amplicons produced by MCDA through double antibody sandwich principle, to allow sensitive and specific detection under a constant temperature. The detection limit was as low as 10 fg or 100 fg genomic DNA in pure cultures and 5.5 CFUs or 36 CFUs in spiked cerebrospinal fluid (CSF) specimens, which were overall 100 to 1000-fold more sensitive than conventional PCR. High specificity of these assays was also validated through type strains and clinical isolates, with no cross-reactions. MCDA-LFB testing procedure can be finished within 1 h. In conclusion, the N. meningitidis- and serogroup-MCDA-LFB assays established in this study are simple, rapid and efficient, providing valuable molecular methods for diagnosis and surveillance of meningococcal disease, especially in resource-limited regions and when specimen culture fails.

Artemisinin is an important frontline antimalarial. Fast, accurate detection of artemisinin in human serum is of importance in monitoring its clinical pharmaceutical effect. In this work, a strategy using microsensor array coupled with electrochemiluminescence (ECL) imaging technique was developed for detection of artemisinin. The microsensor array was constructed by integrating a patterned indium tin oxide glass plate with two perforated hydrophobic paper covers. By introducing the reactant of p-aminophenylboronic acid, luminol and artemisinin into the microsensor array, artemisinin would oxidize p-aminophenylboronic acid into p-aminophenol, a product which can efficiently inhibit the ECL of luminol. ECL signals decrease linearly with the increase of artemisinin. Based on the decreased ECL signal, artemisinin can be accurately detected. A good linearity (r = 0.994) was observed for artemisinin detection. The detection sensitivity is 0.48 μM for artemisinin. The detection selectivity and stability were also investigated. Results show that the present method shows a good selectivity and stability towards artemisinin detection. To evaluate the applicability of the present strategy for detecting artemisinin in real samples, the artemisinin content in human serum and Artemisia annua samples were analyzed. Results demonstrated that the present strategy shows excellent selectivity with high sensitivity towards artemisinin detection in real samples.

The combined use of selected Saccharomyces cerevisiae and non-Saccharomyces strains is becoming an effective way to achieve wine products with distinctive aromas. The purpose of this study was to further improve the wine aroma complexity through optimizing inoculation protocols of multi-starters. The three indigenous non-Saccharomyces strains (Torulaspora delbrueckii, Hanseniaspora vineae, and Lachancea thermotolerans) and their pairwise combinations (co-inoculation) were sequentially inoculated with S. cerevisiae in Petit Manseng grape must, respectively. Results evidenced a higher divergence in aroma compounds produced by two different non-Saccharomyces species compared to single species. Especially for the combination of T. delbrueckii and L. thermotolerans, the concentrations of most ethyl esters were further increased, contributing to a higher score of ‘pineapple’ note in agreement with sensory analysis. Our results highlighted that the inoculation of more than one non-Saccharomyces species is a potential strategy to improve the aroma diversity and quality of industrial wines.

Heart failure arises from diverse cardiovascular diseases, including hypertension, ischemic disease and atherosclerosis, valvular insufficiency, myocarditis, and contractile protein mutations. MicroRNAs are dysregulated in heart failure, but identification of the specific microRNAs involved remains incomplete. Here, we evaluate miR-25 expression in the peripheral blood from healthy, dilated cardiomyopathy (DCM), remote infarct (OMI), hypertensive heart disease (HHD), and HHD resulting in heart failure (HHDF) using q-PCR. Interestingly, we discovered miR-25 expression in humans is initially decreased at the onset of heart failure but is later increased in end-stage heart failure. We also show that overexpression of miR-25 in normal mice causes cardiomyocyte fibrosis and apoptosis. However, inhibition of miR-25 in normal mice led to activate renin-angiotensin system (RAS) and high blood pressure, mild heart dilation. Notably, the miR-25 cluster knock-out mice was also characterized high blood pressure and no obvious cardiac function alteration. RNA sequencing showed the alteration of miR-25 target genes in angomir-treated mice, including the renin secretion signal related gene. In vitro, cotransfection with the miR-25 antagomir repressed luciferase activity from a reporter construct containing the Pde3a and Cacnalc untranslated region. In summary, miR-25 expression during different stages of heart disease, offers a new perspective for the role of miR-25 function in heart failure.

The inherent spatial variability of soil properties is the main sauces of uncertainties in the site investigation, and it is commonly characterized using random field theory. In the context of random fields, the scale of fluctuation (SOF) is a significant parameter to reflect the spatial correlation between the two points of soil properties. However, it is challenging to estimate the SOF value accurately, especially when there are only limited project-specific test results, such as cone penetration test (CPT) data. This study aims to develop a convolutional neural network (CNN) approach to estimate the vertical SOF based on limited CPT data. The CNN model was constructed and trained by the simulated 15,000 CPT samples using random fields. The results show that the CNN model has excellent performance for estimating vertical SOF. The approach is validated and illustrated through newly simulated CPT data, eight real CPT data obtained from the literature, and three CPT data collected from the Shanghai site. The proposed scale factor method can solve the mismatch between the actual CPT depth and the required depth for input data of the CNN model, making the CNN model more widely applicable.

Prediction of ground movement adjacent to an excavation is critically important, especially in urban areas, to prevent any potential damage of neighboring buildings. In the present study, a closed-form solution for prediction of excavation-induced ground settlement profile is proposed based on elastic displacement theory. Superposition method is employed to adapt the basic solution for translation wall deflection mode to general wall deflection mode. By assuming the wall deflection in braced excavation to be subject to a piecewise quadratic function, the displacement boundary of the problem is determined. An easy-to-use explicit solution is then developed. The validity of and applicability of the proposed solution is verified with existing analytical solution, finite-element model and six well-documented case records. The ground settlement profiles predicted on the basis of the new approach are in good agreement with reported settlement data. The results show that the proposed solution can be used as a feasible approach to obtain ground settlement profile in clay.

This study investigates the coupled effect of the soil spatial variations and the disturbance of ground surface on the existing tunnel using random finite difference method (RFDM). The soil Young's modulus is highlighted and simulated with horizontally stratified anisotropic random field that is discretized by the Karhunen-Loeve expansion. The surface surcharge is characterized from the statistics of field cases. The 46,800 Monte Carlo simulations are adopted to quantitatively evaluate the deformational performance of the tunnel. It demonstrates that neglecting spatial variability will cause an underestimation of the tunnel convergence, especially when it is severely disturbed by nearby environments, such as the large surface surcharge in this paper. The surface surcharge mainly affects the mean value of tunnel convergence, and the coefficient of variation is largely influenced by the soil inherent spatial variability. In addition, an amplification factor is proposed to simplify considering the impact of spatial variability. The factor charts incorporating different randomness levels are given for practical use. Results show that an amplification coefficient of 2.5 can cover the most scenarios of soil formation considering the soil spatial variability with 95% confidence level.

This paper presents an improved algorithm for evaluating the reliability of three-dimensional soil slopes based on the Vanmarcke model (VM). In the development of the improved Vanmarcke model (IVM), the sliding mass is assumed to be a portion of a cylinder bounded by two ellipsoidal end sections. The soil spatial variability of both the cylindrical and ellipsoidal sections is considered. A set of equations is derived to determine critical failure surfaces and compute their reliability indices. Numerical studies are performed to examine the IVM. The results indicate that (1) the IVM predicts a similar critical failure length compared with that computed by the VM. However, a lower reliability index is obtained by the former. (2) The relative difference between the reliability indices computed by the two analytical models can reach 20% for practical situations. The horizontal scale of fluctuation (SOF) of soil properties is the main factor affecting the relative difference. (3) Compared to the random finite element method, the IVM still gives unconservative analysis results, especially at low horizontal SOFs. This is due to the prediction of smaller critical failure lengths by the IVM for small horizontal SOFs and some retained assumptions of the VM when developing the IVM.

This paper describes a simple and miniaturized microdroplet chip (μchip) that is constructed with a silica nanochannel (SNC)-assisted electrode array and a hydrophobic paper cover (SNC&P-μchip). Vertically aligned SNCs with uniform pore size of 2–3 nm in diameter and negatively charged surface can significantly accelerate the mass transport of the positively charged tris(2,2'-bipyridyl) ruthenium (II), resulting in a remarkably enhanced electrochemiluminescence (ECL) signal. The SNC-assisted electrode array was coupled to a low cost paper cover to achieve simultaneous detection of six samples in 1 min. The feasibility and universality of the SNC&P-μchip was evaluated by detecting a series of alkaloidal drugs both in buffers and in human serum. The performance of the SNC&P-μchip was fully validated with respect to linearity (0.9999 > R > 0.9939), sensitivity (limits of detection from 1.799 nM to 11.43 nM), and accuracy (recovery rate between 94.38% and 109.12%). The facile and economic SNC&P-μchip shows promising potential for rapid drug detection in complex biofluids.

The electric vehicle (EV) is becoming the main mode of intercity passenger transportation. The intercity passenger transportation company (IPTC) is envisioned to participate in the electricity market to maximize the operation profit. Hence, it is necessary to study some strategic operating behaviors of the IPTC, including EV scheduling and bidding, to ensure the efficient operation of intercity passenger transport. This paper develops a decision-making tool based on a bi-level programming model for a merchant price-maker IPTC to determine the most beneficial scheduling and trading actions in the day-ahead market. The upper level of the model considers the mobility characteristics of EVs by a modified time–space network (TSN) to help the IPTC formulate intercity passenger shifts and bidding strategies. In this level, the IPTC maximizes its profit in the day-ahead market through bidding strategies, transportation scheduling, and charging/discharging arrangement at each station. In the lower level of the model, the joint energy and reserve market is cleared with maximum social welfare. The bi-level model can be transformed into an easily solved mixed-integer linear programming problem by applying the strong duality theorem and a binary expansion method to handle the nonlinear constraints of the reformulated single-level problem based on Karush-Kuhn-Tucker theorems. Finally, case studies are carried out on a modified IEEE 39-bus system and a practical 714-bus power system in China. The numerical results indicate that the IPTC tends to schedule more EVs to park in cities directly connected to congested transit lines and increase the number of discharging vehicles, resulting in the growth of the scheduled energy of discharging in these cities and thus higher profits. The different operation strategies of the IPTC are also discussed in the day-ahead market.

Background Accumulating evidence has demonstrated that microRNAs (miRNAs) are associated with tumorigenesis. miR-216b can play a vital role in the genesis and development of gastric cancer (GC), and its molecular mechanisms require further elucidation. Methods The biological effects of miR-216b in GC cells were investigated by MTT, transwell assays, and cell cycle. Western blot and luciferase assay were performed to demonstrate the direct binding of miR-216b on PXN 3′UTR. Furthermore, MTT, colony formation assays, transwell assays, and flow cytometry analysis, as well as xenograft mice model, were used to measure the effects of miR-216b-PXN on GC cell proliferation, migration, and invasion indicated by in vitro and in vivo. Results Our results showed that miR-216b acted as a tumor suppressor in GC progression. miR-216b overexpression suppressed GC cell proliferation, migration, and invasion in vitro. Luciferase reporter assays identified paxillin (PXN) as a novel target gene of miR-216b. PXN overexpression could partially rescue miR-216b-induced the inhibitory effects in GC cells. Besides, overexpression of miR-216b contributed to the activation of PI3K/AKT signaling via partly regulating PXN in GC cells. Conclusions The above results showed that miR-216b could offer a novel therapeutic avenue by targeting PXN in GC.

Plug-in electric buses have great potential to enhance the profits of operators in multiple-microgrid systems via the use of vehicle-to-grid technology. In contrast to stationary energy storage units, a plug-in electric bus can move among different microgrids to provide not only passenger transportation service but also energy transportation service. In this paper, a single-leader and multiple-follower model based on the Stackelberg game method is proposed for the look-ahead dispatch of bus routes and power allocation in microgrids. First, a time-space trip model for a fleet of plug-in electric buses was established, and the total costs of the plug-in electric bus operator were optimized as a leader-level problem. Then a rolling energy management strategy was formulated as a follower-level problem to optimize the total costs of each microgrid operator and to deal with the prediction error of the distributed energy resources and loads. Next, the proposed bi-level optimization problem was transformed into a single-level mixed-integer linear programming problem. Finally, case studies were carried out on three real microgrids in China and on BYD-K9 plug-in electric buses. The simulation results indicated that the costs for a plug-in electric bus operator would decrease by 33.35% in the proposed bi-level model compared with the fixed charging model, and the costs for an isolated MG would decrease by 24.16% compared with the model regardless of the plug-in electric buses.

In this paper, the uplift behavior of helical anchors in clay is investigated using the finite element limit analysis. According to the observations on the failure mechanism, the factors that influence the model uncertainty of the cylindrical shear method are examined. The finite element limit analysis is used to remove the correlation between the model factor M for the cylindrical shear method, which is defined as a ratio between the measured capacities Qu,m and the capacities Qu,c calculated from the cylindrical shear method, with the input parameters. A regression equation f is then proposed. Using the load tests database including 78 laboratory model-scale tests and 25 field full-scale tests, the model factor M’ = Qu,m/[fQu,c] is represented as a lognormal random variable with mean = 0.92 and coefficient of variation (cov) = 0.16. Finally, the accuracy of the modified cylindrical shear method (i.e., fQu,c) is examined using 19 large-deformation analyses.

With the large scale of distributed energy resources integrated into distribution systems, the development of effective power management for controllable components is becoming an increasingly important concern. This paper focuses on solving the optimal power flow problem in a distribution network with a fully decentralized mode that has massive photovoltaics and electric vehicles. First, an optimal power flow model considering photovoltaics and electric vehicles as controllable agents was established to achieve low network loss, low curtailment of photovoltaic resources, and high satisfaction of electric vehicle owners. Second, a novel linearized power flow model was proposed to produce per-node granularity communication. Thus, each node only needed to exchange the voltage message with its neighboring nodes. Then a decentralized quadratically constrained quadratic programming model based on the alternating direction method of multipliers was built to solve the optimal power flow problem. Next, a closed-form iterative solution method for the decentralized optimization was developed to improve the calculation speed for each iteration. Finally, case studies for a real 35-bus distribution system and a real 110-bus distribution system in China were used to verify the effectiveness of the proposed method.

Based on the Hellinger-Reissner mixed variational principle, a second-order cone programming optimized finite element method for elastic and elastoplastic analyses of Cosserat continuum (named CosFEM-SOCP) is proposed. To examine the correctness and effectiveness of CosFEM-SOCP, three well-known numerical examples are revisited. In the plane-strain elastic problem of stress concentration around a circular hole, the stress concentration factors calculated by CosFEM-SOCP are in good agreement with the existing solutions, and the correctness of CosFEM-SOCP can be verified. In the analysis of load-displacement response of a flexible strip footing resting on the soil ground, it is found that load-displacement response may be affected by the internal characteristic length lc, and generally a larger lc may result in a wider and deeper slip surface as well as more elements being included in the shear bands. From the plane-strain soil strip with the Drucker-Prager (DP) failure criterion subjected to the prescribed incremental displacement, it can also be observed that the pathologically mesh-dependent problem can be partially or even completely removed by employing CosFEM-SOCP, as long as the mesh is fine enough so that the average element size in the mesh discretization is smaller than lc.

Since various types of distributed renewable energy resources are integrated into distribution systems in the form of microgrids, how to implement the coordinated operation between a distribution system and microgrids is a major concern. This paper focuses on solving the optimal power flow of a distribution system with multiple microgrids based on the decentralized saddle-point dynamics approach. First, the distribution system and the microgrids are regarded as separate entities and their external networks are replaced by Ward equivalent circuits. Hence, the distribution system and microgrids are decoupled so that their linearized power flow models can be built separately. Then, a decentralized quadratic programming model for optimal power flow with the distribution system and microgrids as separate entities is established to achieve low active power loss and high utilization of renewable energy resources. Next, the decentralized saddle-point dynamics approach is applied to solve this model from the viewpoint of the dynamic system control, which transforms the solution of Karsh-Kuhn-Tucker conditions into an asymptotically stable process. The proposed method only needs to exchange the border-bus voltages and equivalent injection powers between the distribution system and each microgrid, which can protect the privacy of different entities and possesses plug-and-play features. Finally, case studies on a real distribution system with two real microgrids are carried out to verify the effectiveness of the proposed method.

A Mg-8%Al-1%Si alloy with semisolid microstructure was fabricated by isothermal heat treatment process. The effects of isothermal process parameters such as holding temperature and holding time on the microstructure of Mg-8%Al-1%Si alloy were investigated. The results show that a non-dendritic microstructure could be obtained by isothermal heat treatment. With increasing holding temperature from 560 to 575 °C or holding time from 5 to 30 min, the liquid volume fraction increases, the average size of α-Mg grains grows larger and globular tendency becomes more obvious. In addition, the Mg2Si phase transforms from Chinese script shape to granule shape. The morphology modification mechanisium of Mg2Si phase in Mg-8%Al-1%Si alloy during the semisolid isothermal heat treatment was also studied.

A novel 2009 influenza A (H1N1) virus was transmitted from humans to humans worldwide. The live attenuated monovalent A H1N1 vaccine (LAMV) for intranasal administration has shown promising immunogenicity and safety in clinical trials and for human use, but the experimental data based on LAMV is incomplete. In this study, using reverse genetic technology, we produced a cold-adapted (ca), live attenuated BJ/AA ca that contained hemagglutinin (HA) and neuraminidase (NA) genes from a 2009 pandemic A H1N1 isolate, A/Beijing/501/2009 virus (BJ501), and the remaining six internal gene segments from the cold-adapted influenza H2N2 A/Ann Arbor/6/60 virus (AA virus). BJ/AA ca exhibited phenotypes of temperature sensitivity (ts), ca, and attenuation (att). The candidate BJ/AA ca was immunogenic in mice and induced strong mucosal secretory IgA (sIgA) in the respiratory tract. Two dosages of intranasal immunization induced robust HI antibodies and offered efficient protection against challenge by the wild-type (wt) 2009 pandemic A H1N1 (A/Beijing/501/2009 or A/California/07/2009) in mice and ferrets. These results support the evaluation of this vaccine made from a wt strain isolated in China for clinical trials.

The avian H5N1 influenza virus has the potential to cause a new pandemic. The increasing number of recent outbreaks of highly pathogenic avian influenza H5N1 in birds and humans emphasizes the urgent need to develop a potent H5N1 vaccine. Here, we studied the immunogenicity and protective effect of a vaccine prepared from H5N1 inactivated whole virus. This vaccine was intranasally co-administered in mice with phosphate buffered saline, recombinant cholera toxin B subunit (rCTB), cholera toxin (CT), rCTB containing a trace amount of holotoxin (rCTB/CT), polyinosinic:polycytidylic acid double-stranded RNA (polyI:C), or MF59 as an adjuvant. Intranasal administration of H5N1 inactivated whole virus vaccine with rCTB, CT, rCTB/CT, polyI:C, and MF59 elicited an immunological response with both secretory IgA (sIgA) in nasal, lung, and vaginal lavage, and IgG antibody in serum, showing protective immunity against lethal H5N1 infection. Cross-clade protection was also observed in animals immunized with a vaccine derived from Anhui/01/2005(H5N1) with rCTB, CT, rCTB/CT, polyI:C, or MF59 as adjuvants that were subsequently challenged with the A/OT/SZ/097/03 influenza strain.

High tibial osteotomy has been generally accepted as a useful treatment for unicompartment osteoarthritis of the knee to improve a patient's quality of life. Few studies have examined the outcome from the patient's perspective. A survival analysis of one to twenty-one years was conducted on 67 knees including analysis of the patients' satisfaction level with this procedure. Cumulative survival probability of 89.5% at 5 years, 74.7% at 10 years and 66.9 % for 15 and 20 years was reported. Ninety-one percent of patients had improvement in pain score and would choose to have this surgery again. Average patient satisfaction level was 75.5%. Forty-eight percent of patients were able to perform at a higher level of activity than before surgery, although none was able to perform at the level prior to the onset of knee pathology. It was concluded that this procedure was able to improve a patient's quality of life and achieved high satisfaction among patients. There is an increasing role of high tibial osteotomy as an adjunct to an autologous chondrocyte implantation procedure.