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Obesity is thought to significantly impact the quality of life. In this study, we sought to evaluate the health consequences of obesity on the risk of a broad spectrum of human diseases. The causal effects of exposing to obesity on health outcomes were inferred using Mendelian randomization (MR) analyses using a fixed effects inverse-variance weighted model. The instrumental variables were SNPs associated with obesity as measured by body mass index (BMI) reported by GIANT consortium. The spectrum of outcome consisted of the phenotypes from published GWAS and the UK Biobank. The MR-Egger intercept test was applied to estimate horizontal pleiotropic effects, along with Cochran’s Q test to assess heterogeneity among the causal effects of instrumental variables. Our MR results confirmed many putative disease risks due to obesity, such as diabetes, dyslipidemia, sleep disorder, gout, smoking behaviors, arthritis, myocardial infarction, and diabetes-related eye disease. The novel findings indicated that elevated red blood cell count was inferred as a mediator of BMI-induced type 2 diabetes in our bidirectional MR analysis. Intriguingly, the effects that higher BMI could decrease the risk of both skin and prostate cancers, reduce calorie intake, and increase the portion size warrant further studies. Our results shed light on a novel mechanism of the disease-causing roles of obesity.

Background: Total white blood cell count (TWBCc), an index of chronic and low-grade inflammation, is associated with clinical symptoms and metabolic alterations in patients with schizophrenia. The effect of antipsychotics on TWBCc, predictive values of TWBCc for drug response, and role of metabolic alterations require further study. Methods: Patients with schizophrenia were randomized to monotherapy with risperidone, olanzapine,quetiapine, aripiprazole, ziprasidone, perphenazine or haloperidol in a 6-week pharmacological trial. We repeatedly measured clinical symptoms, TWBCc, and metabolic measures (body mass index, blood pressure, waist circumference, fasting blood lipids and glucose). We used mixed-effect linear regression models to test whether TWBCc can predict drug response. Mediation analysis to investigate metabolic alteration effects on drug response. Results: At baseline, TWBCc was higher among patients previously medicated. After treatment with risperidone, olanzapine, quetiapine, perphenazine, and haloperidol, TWBCc decreased significantly (p Conclusion: TWBCc is affected by certain antipsychotics among patients with schizophrenia, with decreases observed following short-term, but increases following long-term treatment. TWBCc is predictive of drug response, with lower TWBCc predicting better responses to antipsychotics. It also mediates the effects of certain metabolic measures on improvement of negative symptoms. This

Coronavirus disease 2019 (COVID-19), as well as its prevention and control measures, seriously affected the people's livehood, which may have affected the body's level of vitamin D (VD). This study aimed to investigate the effect of the COVID-19 pandemic on the VD status of children in Zhengzhou, China. In this study, we included 12,272 children in 2019 (before the COVID-19 pandemic) and 16,495 children in 2020 (during the COVID-19 pandemic) to examine the changes in VD levels and deficiency rates among children before and during the COVID-19 pandemic. Total VD levels in 2020 were significantly higher than those in 2019 (26.56 (18.15, 41.40) ng/ml vs. 25.98 (17.92, 40.09) ng/ml, P0.001). Further analysis revealed that during the COVID-19 pandemic control period in 2020, the VD levels in February, March, and April were lower than those in the same months of 2019, while the VD deficiency rates were significantly higher. Additionally, our data revealed that VD levels decreased significantly with age. Among children older than 6 years, the VD deficiency rate exceeded 50%. These results indicate that we should pay close attention to VD supplementation during the COVID-19 pandemic control period and in children older than 6 years of age. This article is protected by copyright. All rights reserved.

Characterized by strong acidity, chelating ability, and reducing ability, oxalic acid, a low molecular weight dicarboxylic organic acid, plays important roles in the regulation of plant growth and development, the response to both biotic and abiotic stresses such as plant defense and heavy metals detoxification, and food quality. The metabolism of oxalic acid has been well-studied in microorganisms, fungi, and animals but remains less understood in plants. However, excessive accumulation of oxalic acid is detrimental to plants. Therefore, the level of oxalic acid has to be precisely controlled in plant tissues. In this review, we summarize the metabolism, function, and regulation of oxalic acid in plants, and we discuss solutions such as agricultural practices and plant biotechnology to manipulate oxalic acid metabolism to regulate plant responses to both external stimuli and internal developmental cues.

Growing nonlinearity demands in mid-infrared applications place more outstanding requirements on fiber structure design. Chalcogenide suspended-core fibers (SCFs) are considered excellent candidates for mid-infrared applications due to their significant advantages in nonlinearity and dispersion management. However, traditional numerical methods for accurate modeling and optimization of SCFs often rely on the performance of computing devices and have many limitations when dealing with complex models. A machine learning algorithm is applied to calculate the optical properties of chalcogenide SCFs, including effective mode area, nonlinear coefficient, and dispersion. The established artificial neural network (ANN) model enables accurate prediction of the above optical properties of A s 2 S 3 SCF, for which in the wavelength range of 1.0 to 4.0 µm, the radius of the fiber core is 0.4 to 0.6 µm, and width of the cantilever is 0.06 to 0.09 µm. We demonstrate that this simple ANN model has considerable advantages over the traditional numerical calculation model in computational speed and resource utilization. In summary, the proposed model can quickly provide more accurate optical property predictions, providing a cost-effective solution for precise modeling and optimization of chalcogenide SCFs.

Yunnan Province is the main planting area of the precious Chinese herbal medicines (CHM) Panax notoginseng; however, it locates the geological area with high soil heavy metals in China. The frequent land replacement due to continuous cropping obstacles and excessive application of chemicals makes P. notoginseng prone to be contaminated by heavy metals under the farmland P. notoginseng (FPn) planting. To overcome farmland shortage, understory P. notoginseng (UPn) was developed as a new ecological planting model featured by no chemicals input. However, this newly developed planting system requires urgently the soil-plant heavy metal characteristics and risk assessment. This study aimed to evaluate the pollution status of eight heavy metals in the tillage layer (0-20 cm), subsoil layer (20-40 cm) and the plants of UPn in Lancang County, Yunnan Province. Pollution index (P

Myocardial infarction (MI) causes rapid and permanent damage to the heart muscle. Therefore, it can deteriorate the myocardial structure and function if not timely diagnosed and treated. However, it is difficult to determine the precise localization of MI based on vectorcardiogram (VCG) due to the existing studies ignore the spatiotemporal features of VCG.In this paper, a precise MI localization method was proposed based on Tucker decomposition. The multi-scale characteristics of wavelet transform and the spatiotemporal characteristics of VCG were used to construct the VCG tensor containing the local and the spatiotemporal information. The VCG tensor was compressed in the time dimension based on Tucker decomposition to remove redundant information and extract the local spatiotemporal features. The features were fed back to the TreeBagger classifier.The proposed method achieved a total accuracy of 99.80% for 11 types of MI on the benchmark Physikalisch-Technische Bundesanstalt database. The area under the receiver operating characteristic curves and precision-recall curves of each kind of ECG signal was more than 0.88.The proposed algorithm effectively realized the classification of normal ECG and 11 categories of MI using VCG.Therefore, this study provides new ideas for the intelligent diagnosis of MI based on VCG.

ST segment morphology is closely related to cardiovascular disease. It is used not only for characterizing different diseases, but also for predicting the severity of the disease. However, the short duration, low energy, variable morphology and interference from various noises make ST segment morphology classification a difficult task. In this paper, we address the problems of single feature extraction and low classification accuracy of ST segment morphology classification, and use the gradient of ST surface to improve the accuracy of ST segment morphology multi-classification. In this paper, we identify five ST segment morphologies: normal, upward-sloping elevation, arch-back elevation, horizontal depression, and arch-back depression. Firstly, we select an ST segment candidate segment according to the QRS wave group location and medical statistical law. Secondly, we extract ST segment area, mean value, difference with reference baseline, slope, and mean squared error features. In addition, the ST segment is converted into a surface, the gradient features of the ST surface are extracted, and the morphological features are formed into a feature vector. Finally, the support vector machine is used to classify the ST segment, and then the ST segment morphology is multi-classified. The MIT-Beth Israel Hospital Database (MITDB) and the European ST-T database (EDB) were used as data sources to validate the algorithm in this paper, and the results showed that the algorithm in this paper achieved an average recognition rate of 97.79% and 95.60%, respectively, in the process of ST segment recognition. Based on the results of this paper, it is expected that this method can be introduced in the clinical setting in the future to provide morphological guidance for the diagnosis of cardiovascular diseases in the clinic and improve the diagnostic efficiency.ST段的形态变化和心血管疾病息息相关，不仅能表征不同的疾病，并且能够预示患病的严重程度。但ST段持续时间短、能量低、形态多变并且受到多种噪声的干扰，导致ST段形态分类成为一个难题。本文针对目前ST段形态分类存在的特征提取单一、分类准确率低等问题，利用ST曲面的梯度来提高ST段形态多分类的精度。本文对正常、上斜型抬高、弓背型抬高、水平型压低、弓背型压低五种ST段形态进行识别，首先根据QRS波群位置及医学统计规律选定一个ST段候选段，其次提取ST段面积、均值、与参考基线差值、斜率、均方差特征。此外，将ST段转换成曲面，提取ST曲面的梯度特征，与形态学特征组成特征向量，最后使用支持向量机分类，进而实现ST段形态多分类。采用麻省理工学院-贝斯以色列医院数据库（MITDB）和欧盟ST-T数据库（EDB）为数据来源对本文算法进行验证，结果显示，本文算法在ST段识别过程中分别达到了97.79%和95.60%的平均准确率。基于本文研究结果，期望今后可在临床环境中引入本文方法，为临床中心血管疾病的诊断提供形态指导，提高诊断效率。.

Background: Since the early clinical efficacy of antipsychotics has not yet been well perceived, this study sought to decide whether the efficacy of antipsychotics at week 2 can predict subsequent responses at week 6 and identify how such predictive capacities vary among different antipsychotics and psychotic symptoms. Methods: A total of 3010 patients with schizophrenia enrolled in a randomized controlled trial (RCT) and received a 6-week treatment with one antipsychotic drug randomly chosen from five atypical antipsychotics (risperidone 2-6 mg/d, olanzapine 5-20 mg/d, quetiapine 400-750 mg/d, aripiprazole 10-30 mg/d, and ziprasidone 80-160 mg/d) and two typical antipsychotics (perphenazine 20-60 mg/d and haloperidol 6-20 mg/d). Early efficacy was defined as the reduction rate using the Positive and Negative Syndrome Scale (PANSS) total score at week 2. With cut-offs at 50% reduction, logistic regression, receiver operating characteristic (ROC) and random forests were adopted. Results: The reduction rate of PANSS total score and improvement of psychotic symptoms at week 2 enabled subsequent responses to 7 antipsychotics to be predicted, in which improvements in delusions, lack of judgment and insight, unusual thought content, and suspiciousness/ persecution were endowed with the greatest weight. Conclusions: It is robust enough to clinically predict treatment responses to antipsychotics at week 6 using the reduction rate of PANSS total score and symptom relief at week 2. Psychiatric clinicians had better determine whether to switch the treatment plan by the first 2 weeks. Clinical Trial Registration Number: This RCT was registered at the Chinese Clinical Trials Registry Identifier: ChiCTR-TRC-10000934).

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.

FBG array sensors have been widely used in the multi-point monitoring of large structures due to their excellent optical multiplexing capability. This paper proposes a cost-effective demodulation system for FBG array sensors based on a Neural Network (NN). The stress variations applied to the FBG array sensor are encoded by the array waveguide grating (AWG) as transmitted intensities under different channels and fed to an end-to-end NN model, which receives them and simultaneously establishes a complex nonlinear relationship between the transmitted intensity and the actual wavelength to achieve absolute interrogation of the peak wavelength. In addition, a low-cost data augmentation strategy is introduced to break the data size bottleneck common in data-driven methods so that the NN can still achieve superior performance with small-scale data. In summary, the demodulation system provides an efficient and reliable solution for multi-point monitoring of large structures based on FBG array sensors.

One of the major causes of the coronary heart disease is vascular stenosis and thrombosis that is generally caused by development of fibrous plaques. Therefore, detection of a fibrous plaque in coronary arteries for the diagnosis and treatment of coronary heart disease is of clinical significance. Technical challenges are in reading the optical coherence tomography (OCT) images which is tedious and inaccurate. In response, we propose an automated coronary artery fibrous plaque detection method based on deep learning with Convolutional Neural Networks (CNN). We present our novel techniques of identifying a contracting path to capture the context and a symmetric expanding path that enables the precise localization. The algorithm utilizes the features of the contracting path and the expanding path, so that the merged features can present the context and accurate localization, and uses the multi-scale feature maps for detection. Experimental results show that the proposed method achieved a coincidence of 91.04%, accuracy of 94.12%, and recall of 94.12%. Compared with the previously published work the proposed method is advantageous in both accuracy and robustness.

Iron (Fe) homeostasis is critical for plant growth, development, and stress responses. Fe levels are tightly controlled by intricate regulatory networks in which transcription factors (TFs) play a central role. A series of basic helix-loop-helix (bHLH) TFs have been shown to contribute to Fe homeostasis, but the regulatory layers beyond bHLH TFs remain largely unclear. Here, we demonstrate that the SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE (SPL) TF SlSPL-CNR negatively regulates Fe-deficiency responses in tomato (Solanum lycopersicum) roots. Fe deficiency rapidly repressed the expression of SlSPL-CNR, and Fe deficiency responses were intensified in two clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9-generated SlSPL-CNR knock-out lines compared to the wild-type. Comparative transcriptome analysis identified 47 Fe deficiency-responsive genes the expression of which is negatively regulated by SlSPL-CNR, one of which, SlbHLH101, helps regulate Fe uptake genes. SlSPL-CNR localizes the nucleus and interacts with the GTAC and BOX 4 (ATTAAT) motifs in the SlbHLH101 promoter to repress its expression. Inhibition of SlSPL-CNR expression in response to Fe deficiency was well correlated with the expression of the microRNA SlymiR157. SlymiR157-overexpressing tomato lines displayed enhanced Fe deficiency responses, as did SlSPL-CNR loss-of-function mutants. We propose that the SlymiR157-SlSPL-CNR module represents a novel pathway that acts upstream of SlbHLH101 to regulate Fe homeostasis in tomato roots.

A high-performance, low-cost FBG strain sensor demodulation system was studied, which can achieve ± 6 pm central wavelength interrogation precision without an optical spectrum analyzer, and with favorable repeatability.

In extreme space environments with alternating and uneven temperature variations, the surface accuracy of cable-net antennas deteriorates significantly, thereby inducing a periodic failure or a significant deviation in the electrical performance. This is because of the lack of effective methods for controlling the surface shape during the service of the cable-net antenna. In this study, a method based on ‘two-way memory spring’ is proposed to actively control the surface of a cable-net antenna. Herein, first, an electro-thermo-mechanical model of the shape memory alloy (SMA) spring is deduced by combining the intrinsic model of the two-way shape memory effect and the resistance property of the SMA. Subsequently, a principle prototype is developed, and experiments related to active control are conducted to confirm the feasibility and effectiveness of the proposed method.

The construction of electricity retail market poses unprecedented opportunities and challenges for the sale of electricity. The traditional mode of electricity business marketing is not suitable for the new market environment, and it needs change in many aspects. How to serve customers well in the competitive environment, seize the market, and improve their own operating efficiency is an urgent problem for power grid enterprises. This paper regards the development of electricity retail market as the diffusion process of innovation. Based on the diffusion of innovations theory, this paper analyzes the characteristics of different development stages, and formulates service strategies according to their characteristics, so as to provide reference for power grid enterprises to seize the market.

Introduction This study mainly investigated the role of miR‐199a‐5p in depression. Methods qRT‐PCR and western blotting were employed to detect the expressions of miR‐199a‐5p, CREB and BDNF. Sucrose preference test, forced swimming test, and tail suspension test were performed to evaluate depression‐related symptoms. MTT assays and flow cytometry were used to examine the cell reproduction and apoptotic cells of hippocampal neuron. Results The data demonstrated that the expression levels of miR‐199a‐5p in the cerebrospinal fluids and serums of depression patient and the hippocampus of chronic unpredictable mild stress (CUMS) mouse were significantly increased. However, the expressions of WNT2, p‐CREB, and BDNF were inhibited. In addition, miR‐199a‐5p‐inhibitor enhanced sucrose preferences of CUMS mouse and decreased immobile time in sucrose preference test and forced swimming test. Knockdown of WNT2 attenuated the effects of miR‐199a‐5p‐inhibitor on cell reproduction and apoptotic cells of hippocampal neuron and the expression of WNT2, p‐CREB, and BDNF. Conclusion MiR‐199a‐5p can target WNT2 to enhance the development of depression through regulation of the CREB/BDNF signaling. Trial registration: JNU‐Hos‐49284., miR‐199a‐5p can target WNT2 to enhance the developments of depressions through the regulations of CREB/BDNF signaling.

Identification of coronary atherosclerotic plaques and vulnerable plaques is of great clinical significance in the diagnosis and treatment of coronary artery diseases, such as myocardial infarction and sudden death. Optical coherence tomography (OCT) is a catheter-based intracoronary imaging technique with high resolution (

Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin4 receptor (MC4R) gene, one of the candidate genes for AIMD, has been under-studied in the Chinese patients. We conducted a pharmacogenetic study in a large cohort of Chinese patients with schizophrenia. In this study, we investigated the genetic variation of MC4R in Chinese population by genotyping two SNPs (rs489693 and rs17782313) in 1,991 Chinese patients and examined association of these variants with the metabolic effects that were often observed to be related to AIMD. Metabolic measures, including body mass index (BMI), waist circumference (WC), glucose, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were assessed at baseline and after 6-week antipsychotic treatment. We found that interaction of SNP×medication status (drug-naïve/medicated) was significantly associated with BMI, WC, and HDL change %, respectively. Both SNPs were significantly associated with baseline BMI and WC in the medicated group. Moderate association of rs489693 with WC, Triglyceride, and HDL change % were observed in the whole sample. In the drug-naïve group, we found recessive effects of rs489693 on BMI gain more than 7%, WC and Triglyceride change %, with AA incurring more metabolic adverse effects. In conclusion, the association between rs489693 and the metabolic measures is ubiquitous but moderate. Rs17782313 is less involved in AIMD. Two SNPs confer risk of AIMD to patients treated with different antipsychotics in a similar way.

To understand the role of hydrogen donation from solvents to the coal-generated free-radical fragments (coal radicals) in direct coal liquefaction (DCL), a coal with 72.4 wt % carbon was reacted at...

Two-dimensional Ruddlesden–Popper organic lead halide perovskites (2D RPPs) are semiconducting materials that have attracted widespread research attention recently. Fundamental understanding of heterovalent doping, a classical strategy to manipulate semiconductors′ optoelectronic and stability properties, is of great significance for their applications. Here we report the first series of heterovalent-doped 2D RPPs via Bi3+ doping for (BA)2(MA)n−1PbnI3n+1 (BA = n-C4H9NH3+; MA = CH3NH3+; n = 1, 2 and 3). Systematic experimental studies lead to the discovery of a positive correlation between the layer number and the doping level. Combined theoretical and experimental observations suggest the presence of two distinctive types of Bi3+ sites, a non-radiative recombination site at the organic/inorganic interface and a near-infrared (NIR) emission site at the middle Pb–I layer of the 3-layered 2D RPPs. Surprisingly, significantly improved photostability and environmental stability for the 2D RPPs were observed upon appropriate levels of Bi3+ doping. A fluorescence microscopy study suggests that a preferential doping-induced formation of 1L RPPs at the edges or cracks might act as a new mechanism to enhance the stability, providing an unprecedented strategy to improve the stability of perovskites and a new class of materials for device dimensionality engineering.

For FPI sensor demodulation systems to be used in actual engineering measurement, they must have high performance, low cost, stability, and scalability. Excellent performance, however, necessitates expensive equipment and advanced algorithms. This research provides a new absolute demodulation system for FPI sensors that is high-performance and cost-effective. The reflected light from the sensor was demultiplexed into distinct channels using an array waveguide grating (AWG), with the interference spectrum features change translated as the variation of the transmitted intensity in each AWG channel. This data was fed into an end-to-end neural network model, which was utilized to interrogate multiple interference peaks’ absolute peak wavelengths simultaneously. This architecturally simple network model can achieve remarkable generalization capabilities without training large-scale datasets using an appropriate data augmentation strategy. Experiments show that in simultaneous multi-wavelength and cavity length interrogations, the proposed system has the precision of up to ± 14 pm and ± 0.07 µm, respectively. The interrogation resolution can theoretically reach the pm level benefit from the neural network method. Furthermore, the system’s outstanding demodulation repeatability and suitability were demonstrated. The system is expected to provide a high-performance and cost-effective, reliable solution for practical engineering applications.

It has been recognized that drug addiction engages aberrant process of learning and memory, and substantial studies have focused on developing effective treatment to erase the enduring drug memories to reduce the propensity to relapse. Extinction, a behavioral intervention exposing the individuals to the drug-associated cues repeatedly, can weaken the craving and relapse induced by drug-associated cues, but its clinic efficacy is limited. A clear understanding of the neuronal circuitry and molecular mechanism underlying extinction of drug memory will facilitate the successful use of extinction therapy in clinic. As a key component of mesolimbic system, medial prefrontal cortex (mPFC) has received particular attention largely in that PFC stands at the core of neural circuits for memory extinction and manipulating mPFC influences extinction of drug memories and subsequent relapse. Here, we review the recent advances in both animal models of drug abuse and human addicted patients toward the understanding of the mechanistic link between mPFC and drug memory, with particular emphasis on how mPFC contributes to the extinction of drug memory at levels ranging from neuronal architecture, synaptic plasticity to molecular signaling and epigenetic regulation, and discuss the clinic relevance of manipulating the extinction process of drug memory to prevent craving and relapse through enhancing mPFC function.

Background Examining associations between viral genomic loads of enteroviruses and clinical severity is important for promoting and improving development of antiviral drugs related to hand, foot and mouth disease (HFMD). Methods Throat swabs were collected from HFMD cases at acute phase of illness using a standardized technique in a prospective study. The viral genomic load was categorized into low, medium, and high groups using parameters of real-time reverse transcription-polymerase chain reaction. The clinical severities were assessed with four indicators, respectively. Findings We analysed 1109 HFMD cases, including 538 children with CV-A6, 231 with CV-A16, 156 with EV-A71, 78 with CV-A10, 59 with CV-A4, and 47 with CV-A2. EV-A71 genomic load categories were associated with risks of diagnoses of CNS complications (p = 0.016), requiring systemic corticosteroids or IVIG (p = 0.011), intensive care unit admission (p = 0.002) and length of hospital stay over 5 days (p = 0.048). In the multivariate analyses, point estimates of adjusted odds ratio (OR) tended to increase with viral genomic loads for all four severe outcomes and ORs of highest viral genomic load were all significantly larger than one for EV-A71. Interpretation HFMD clinical severities positively associate with viral genomic loads of EV-A71 in throat swabs. Specific antiviral drugs should be developed to reduce enterovirus load and to alleviate the clinical severities for HFMD cases. Funding National Science Fund for Distinguished Young Scholars

Background Understanding the patterns of treatment response is critical for the treatment of patients with schizophrenia; one way to achieve this is through using a longitudinal dynamic process study design. Aims This study aims to explore the response trajectory of antipsychotics and compare the treatment responses of seven different antipsychotics over 6 weeks in patients with schizoprenia (trial registration: Chinese Clinical Trials Registry Identifier: ChiCTR-TRC-10000934). Method Data were collected from a multicentre, randomised open-label clinical trial. Patients were evaluated with the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up at weeks 2, 4 and 6. Trajectory groups were classified by the method of k-means cluster modelling for longitudinal data. Trajectory analyses were also employed for the seven antipsychotic groups. Results The early treatment response trajectories were classified into a high-trajectory group of better responders and a low-trajectory group of worse responders. The results of trajectory analysis showed differences compared with the classification method characterised by a 50% reduction in PANSS scores at week 6. A total of 349 patients were inconsistently grouped by the two methods, with a significant difference in the composition ratio of treatment response groups using these two methods (χ2 = 43.37, P < 0.001). There was no differential contribution of high- and low trajectories to different drugs (χ2 = 12.52, P = 0.051); olanzapine and risperidone, which had a larger proportion in the >50% reduction at week 6, performed better than aripiprazole, quetiapine, ziprasidone and perphenazine. Conclusions The trajectory analysis of treatment response to schizophrenia revealed two distinct trajectories. Comparing the treatment responses to different antipsychotics through longitudinal analysis may offer a new perspective for evaluating antipsychotics.

Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.肺结节是早期肺癌的主要表现形式，准确检测肺结节对肺癌的早期诊断和治疗具有重要意义。然而，由于肺部计算机断层扫描（CT）图像背景复杂、检测范围大，且肺结节大小不一、形态各异，所以快速准确检测肺结节是一项极具挑战的工作。为此，本文提出了一种融合多尺度特征的肺结节自动检测算法，实现了肺结节的准确检测。首先，在用于大规模图像识别的深度卷积网络（VGG16）上设计了具有三层模块结构的肺结节检测模型，利用网络第一层模块提取 CT 图像中肺结节特征并粗略地估计肺结节位置；然后利用网络第二层模块融合多尺度的图像特征信息进一步增强肺结节细节特征；而网络第三层模块融合分析第一层和第二层模块的特征，得到多尺度下肺结节候选框；最后利用非极大值抑制方法对多尺度下肺结节候选框进行概率分析，得到最终的肺结节位置。本文应用肺部影像数据库联盟（LIDC）公共数据集上的肺结节数据对所提算法进行了验证，平均检测精度达到 90.9%。本研究成果可应用于肺结节自动筛查系统，有助于提升肺结节筛查精度。.

Objectives Enterovirus A71 (EV-A71) is the main pathogen of severe hand, foot, and mouth disease (HFMD). Commercial enzyme-linked immunosorbent assays (ELISAs) are widely used in Chinese hospitals for the rapid diagnosis of acute EV-A71 infections. We present an evaluation of the diagnostic performance of a commercial anti-EV-A71 IgM-capture ELISA kit. Methods A prospective, hospital-based HFMD cohort was established in Henan Children's Hospital (February 2017 - February 2018). Stool and blood specimens were collected from 1413 participants for diagnosing EVA71 by quantitative Real-Time Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) and anti-EV-A71 ELISA. Results Detection yields of EV-A71 IgM increased from 6.5 % (95 % CI:3.3 %–11.4 %) at 0∼24 h, to 42 % (95 % CI:28.3 %–57.8) at 120∼144 h from onset to sampling, and stabilized at ∼40 % after 144 h. With increased time from onset to sampling, the sensitivity of the commercial ELISA increased from 0.54 (95 % CI:0.25−0.81) to 0.74 (95 % CI:0.43−0.66), while specificity decreased from 0.97 (95 % CI:0.93−0.99) to 0.80 (95 % CI:0.69−0.89), and PPV decreased from 0.96 (95 % CI:0.92−0.99) to 0.84 (95 % CI:0.73−0.92). Multivariate analysis found age, EV-A71 vaccination, previous HFMD/Herpangina infection, disease severity, infection during peak EV-A71 season, and sampling time after symptom onset were significantly associated with the diagnostic performance of this anti-EV-A71 IgM-capture ELISA. Conclusion Achieving satisfactory specificity and sensitivity scores, this commercial anti-EV-A71 IgM-capture ELISA kit is suitable for clinical EV-A71 diagnosis, particularly in resource-poor areas. However, clinicians should interpret results in the context of patient history and epidemiological setting.

To compare longitudinal metabolic effects of 7 antipsychotics, including body mass index (BMI), waist circumference (WC), blood pressure (BP), glucose, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C); to investigate risk factors for metabolic syndrome (MetS); and to make recommendations on frequency and timing of monitoring metabolic measurements.This randomized, open-label, pharmacologic trial was conducted among patients with schizophrenia (DSM-IV) in 32 hospitals across China. Patients were randomly assigned to 7 groups and assessed at baseline, 2, 4, and 6 weeks. Linear mixed-effect models were used to assess changes of metabolic measures over time. Multivariable logistic regression analysis was performed to investigate the risk factors for MetS.In total, 2,550 (718 drug-naïve) of 2,774 patients finished the study between July 6, 2010, and November 30, 2011. We found significant (P.05) changes for BMI, WC, TG, and LDL-C, with TG and LDL-C reaching a plateau. Interactions between baseline metabolic condition and changes over time were observed for BMI (χ² = 43.11, P.001), WC (χ² = 36.34, P.001), systolic BP (χ² = 11.92, P = .002), glucose (χ² = 6.09, P = .01), and TG (χ² = 6.01, P = .01). Antipsychotics generally had greater adverse effects on patients who were initially screened as metabolically normal. After controlling for other associated factors, we found that antipsychotics resulted in differing risk for incident MetS, with a similar pattern to findings in other populations: olanzapine (odds ratio [OR] = 3.36, P.001)quetiapine (OR = 3.29, P.001)perphenazine (OR = 2.73, P = .007)risperidone (OR = 2.21, P = .02)aripiprazole (OR = 1.74, P = .15) ≈ haloperidol (OR = 1.75, P = .22) ≈ ziprasidone (OR = 1, reference).Metabolic traits should be monitored frequently in early stages of antipsychotic treatment due to rapid and substantial changes. Clinicians should not assume low risk for patients with normal metabolic parameters at baseline.Chinese Clinical Trial Registry identifier: ChiCTR-TRC-10000934.

It is demonstrated that EBIC imaging technique is superior in quick localizing polysilicon defect of metal-oxide-semiconductor field-effect transistors (MOSFETs). Once polysilicon leakage phenomena are examined, relying on EBIC imaging analysis, we can rapidly isolate nanoscale defect in tens of microns length range. Although faulty polysilicon is employed by more than one MOSFET, it turns out to be unnecessary to characterize all devices after EBIC imaging analysis. By comparative studies, it is concluded that 2-probe EBIC imaging is preferred for mega-Ohm range resistive defect localization while 1-probe configuration is only applicable for kilo-Ohm range. Nanoprobe I-V measurement of the isolated device uncovers the abnormal electrical characteristic which fairly aligns with EBIC imaging analysis. Focused ion beam (FIB) and transmission electron microscopy (TEM) findings imply the EBIC imaging has submicron level spatial resolution toward resistive defects. Therefore it overcomes traditional limits in terms of technical method and lowers failure analysis (FA) difficulty considerably. Ultimately, a simplified model is proposed to explain the physical mechanism of this application. Our modeling describes the strong dependance of EBIC imaging on hot excess carrier behavior within shallow p-n junction when electron beam (e-beam) penetrates into bulk silicon. The work improves the understanding of excess minority carriers transport properties in p-n junction under scanning e-beam irradiation. And this paper may make EBIC imaging be a more promising way to identify minute material defect of future advanced MOSFET.

Optical coherence tomography (OCT) is a novel technology used in coronary artery disease diagnosis for its high resolution. It has numerous advantages in 3D vessel modeling and vulnerable plaque quantification. This paper proposes a robust vessel intimal extraction algorithm using active contours. A pre-processing module, that takes into consideration the characteristics of coronary OCT imagery, is introduced to eliminate a variety of visual disruptions. Then, a monotonically decreasing function is added into the Chan-Vese (CV) method in order to avoid over segmentation. This is done by controlling the evolution speed in closing the boundary area. A postprocess is followed after CV segmentation to weaken the rotation distortion influence on the extraction result. We use 281 clinical coronary OCT images gathered from Peking Union Medical College Hospital to validate our algorithm. Then we compare our results to manual expert evaluations and a conventional CV method. The extraction results can be used in clinical applications and can provide a basis to further plaque classification.

The swelling and sorption experiments were carried out simultaneously for two block coal samples under CO 2 and CH 4 pressure (up to 16 MPa) at three temperatures (25, 45 and 65 °C). The absolute sorption isotherms present type- II pattern and can be described by a modified BET model. The swelling isotherms present L -type pattern and can be described by a modified Langmuir model. The relationship between swelling ratio and absolute sorption amount presents S -type pattern and can be described by a modified Gompertz function (a logistic function). It is interesting to find that the correlations of normalized properties have a single relationship that is independent of experimental conditions, coals and gases. When the sorption amount approaches to the monolayer sorption coverage ( n a / n m = 1), the swelling ratio reaches ∼93% of the maximum swelling ratio. It implies the importance of the mutual contact between coal and sorbate. The differential characteristic of swelling process shows that the swelling rate with respect to sorption amount varies with the sorbate coverage; the swelling rate peaks at n a / n m ≈ 0.37 and approches zero at n a / n m ≈ 1.5. In addition, a theoretical model correlating swelling and sorption was established. The concept of reduction of surface free energy by sorption was taken into account. It is encouraged that the experiment data match of model is generally acceptable.