Search

【Objective】 The presence of undigested antibiotics used in livestock farming poses significant environmental concerns, as their disposal into water and soil can lead to contamination of the food chain. This paper presents the analysis of the distribution and concentration of these antibiotics in both soil and groundwater. 【Method】 Soil and groundwater samples were collected from an intensive livestock farming area in H county. Antibiotics and hormones in these samples were analysed using the high-performance liquid chromatography-triple quadrupole mass spectrometry. 【Result】 ① On average, there was more sulfonamide (SAs) in soil than in groundwater. All but megestrone acetate hormones were found in soil and groundwater, although there were more in soil than in groundwater. ② Sulfamethiazole, sulfonamide intermethacil, sulfonamide and sulfoamine were found in soil. In the groundwater, the concentrations of sulfonamide intermethacil and sulfamquinoxine were higher than the concentration of other antibiotics. ③ The concentration of hormone KTY04 was higher in the 0-20 cm soil layer than in the 60-80 cm layer. In the studied area, adrenocorticoid, testosterone, and notestosterone were the dominant hormones, with their mass concentration reaching 325 ng/L. 【Conclusion】 Our study found higher mass concentrations of sulfonamides in soil than in groundwater, except estrogen whose concentration was high in groundwater and moderate in soil. The presence of antibiotics and hormones from livestock farming could lead to increased contamination of both soil and groundwater, particularly sulfonamides and estrogens. Continuous monitoring is needed to assess their potential impacts on ecosystems.

Unmeasured confounding is a key challenge for causal inference. In this paper, we establish a framework for unmeasured confounding adjustment with negative control variables. A negative control outcome is associated with the confounder but not causally affected by the exposure in view, and a negative control exposure is correlated with the primary exposure or the confounder but does not causally affect the outcome of interest. We introduce an outcome confounding bridge function that depicts the relationship between the confounding effects on the primary outcome and the negative control outcome, and we incorporate a negative control exposure to identify the bridge function and the average causal effect. We also consider the extension to the positive control setting by allowing for the nonzero causal effect of the primary exposure on the control outcome. We illustrate our approach with simulations and apply it to a study about the short-term effect of air pollution on mortality. Although a standard analysis shows a significant acute effect of PM2.5 on mortality, our analysis indicates that this effect may be confounded, and after double negative control adjustment, the effect is attenuated toward zero.

Summary: Background: Since 1992, when recombinant hepatitis B vaccine was introduced in China, government health officials have used nationally representative serological surveys to monitor progress in prevention and control of hepatitis B. In 2020, we conducted the fourth seroepidemiological survey, which for the first time included medical evaluation of the clinical status of HBsAg positive subjects over the age of 15 and their medical management. We report survey results in comparison with the three previous surveys. Methods: Consistent with previous national surveys, the 2020 survey used a stratified, three-stage cluster random sampling method to select for evaluation 1-69-year-olds in 120 national disease surveillance points. Blood samples were tested for HBsAg, anti-HBV surface antigen (anti-HBs), and anti-HBV core antigen (anti-HBc) in the National Hepatitis Laboratory of the Institute for Viral Disease Control and Prevention of China CDC. HBsAg positive subjects aged ≥15-year were evaluated for evidence of liver disease, and through face-to-face questionnaire-based survey, we determined the healthcare management cascade of HBV-infected individuals. Findings: HBsAg prevalence in 1–69-year-olds was 5.86%; in children 1–4 years of age, seroprevalence was 0.30%; 75 million people were living with HBV nationwide. Among HBsAg-positive individuals 15 years and older, expert medical examination found that 78.03% were HBsAg carriers with no evidence of liver damage, 19.63% had chronic HBV with liver enzyme abnormalities, 0.84% had evidence of cirrhosis, and 0.15% had evidence of liver cancer. 59.78% of HBsAg + individuals were aware that they were positive before the survey, 30 million were unaware; 38.25% of those who knew they were positive (17 million) had medical indications for antiviral treatment, and 17.33% of these individuals (3 million) were being treated with antivirals. Interpretation: The decline in HBsAg prevalence in the general population, from 9.72% in 1992 to 5.86% in 2020, and in 1–4-year-olds from 9.67% in 1992 to 0.30% in 2020, shows progress that continues on track toward WHO targets for prevention of new infections. Implementation of acceptable strategies to identify infected individuals and offer long-term medical monitoring and management will be important to prevent complications from hepatitis B infection and for meeting WHO cascade-of-care targets. Funding: The study was funded by the Major Science and Technology Special Project of China’s 13th 5-Year Plan (grant no. 2017ZX10105015); Central finance-operation of public health emergency response mechanism of Chinese Center for Disease Control and Prevention (131031001000200001, 102393220020010000017).

Introduction Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters for invasiveness prediction.Methods Patients with stage 0–IB NSCLC after surgical resection were retrospectively analysed. Preoperative CTs were evaluated with specialized software for nodule segmentation and CT quantification. Pathology was the reference for invasiveness. Univariate and multivariate logistic regression assessed predictors of high-risk SPN.Results Three hundred and fifty-five SPN were included. On multivariate analysis, CT value mean and nodule type (ground glass opacity vs. solid) were independent predictors of high-risk SPN. The area under the curve (AUC) was 0.811 for identifying high-risk nodules.Conclusions Quantitative CT measures and nodule type correlated with invasiveness. Software-based CT assessment shows potential for noninvasive prediction to guide extent of resection. Further prospective validation is needed, including comparison with benign nodules.

ABSTRACTPreviously, we reported a cohort of Japanese encephalitis (JE) patients with Guillain–Barré syndrome. However, the evidence linking Japanese encephalitis virus (JEV) infection and peripheral nerve injury (PNI) remains limited, especially the epidemiology, clinical presentation, diagnosis, treatment, and outcome significantly differ from traditional JE. We performed a retrospective and multicenter study of 1626 patients with JE recorded in the surveillance system of the Chinese Center for Disease Control and Prevention, spanning the years 2016–2020. Cases were classified into type 1 and type 2 JE based on whether the JE was combined with PNI or not. A comparative analysis was conducted on demographic characteristics, clinical manifestations, imaging findings, electromyography data, laboratory results, and treatment outcomes. Among 1626 laboratory confirmed JE patients, 230 (14%) were type 2 mainly located along the Yellow River in northwest China. In addition to fever, headache, and disturbance of consciousness, type 2 patients experienced acute flaccid paralysis of the limbs, as well as severe respiratory muscle paralysis. These patients presented a greater mean length of stay in hospital (children, 22 years [range, 1–34]; adults, 25 years [range, 0–183]) and intensive care unit (children, 16 years [range, 1–30]; adults, 17 years [range, 0–102]). The mortality rate was higher in type 2 patients (36/230 [16%]) compared to type 1 (67/1396 [5%]). The clinical classification of the diagnosis of JE may play a crucial role in developing a rational treatment strategy, thereby mitigating the severity of the disease and potentially reducing disability and mortality rates among patients.

ObjectiveTo analyze an acute gastroenteritis outbreak caused by co-infection with Vibrio parahaemolyticus （V. parahaemolyticus） and non-O1/O139 Vibrio cholerae （V. cholerae）.MethodsFour anal swabs， 12 food samples， and 8 environmental samples enriched in liquid culture media were subjected to pathogen screening with real-time PCR. V. parahaemolyticus and V. cholerae strains isolated were subjected to whole genome sequencing， and virulence and antibiotic resistance genes were screened. Cladograms were constructed based on core genome single nucleotide polymorphisms.ResultsV. parahaemolyticus strains were detected in anal swab samples with real-time PCR that were toxRVP+/tdh+/trh-， and two of them were positive for V. cholerae. The positive rate of V. parahaemolyticus in the anal swab samples was 100% （4/4）， the isolates were toxRVP+/tdh+/trh-， and their serotype was O4：KUT. The positive rate of V. cholerae culture in the anal swabs of patients was 50% （2/4）. The serogroup of the isolates was non-O1/O139， and one of them was toxRVC+/ctx/t3ss+. The positive rate of V. parahaemolyticus in the food samples was 66.67% （8/12）， and that in the environment samples was 12.50% （1/8）. The strains isolated from food and environmental samples were toxRVP+/tdh-/trh-. The positive rate of V. cholerae culture in the food samples was 25.00% （3/12） and the isolated strains were toxRVC+/ctx/t3ss-. The V. parahaemolyticus strains isolated from patient， food， and environment samples formed 10 distinct lineages. The four patient isolates were highly clonal. The V. cholerae strains isolated from two patients and three food samples formed five distinct lineages.ConclusionThe outbreak was caused by co-infection with V. parahaemolyticus and non-O1/O139 V. cholerae. Real-time PCR and whole-genome sequence analysis of strains should be performed in the detection and analysis of outbreaks caused by vibrio co-infection. Additionally， optimization of vibrio culture pathways is recommended.

Remote sensing image object detection with deep neural networks has been highly successful, but it heavily relies on a large number of labeled samples for optimal performance. Unfortunately, when faced with limited labeled samples, the performance of object detection deteriorates. In order to overcome these limitations, we propose a few-shot object detection (FSOD) method based on the reweighting of contrastive class-attention features for remote sensing images. A Siamese representation embedding model based on contrastive learning with a distinguishing operator is proposed to deal with interclass feature ambiguity between base classes and novel classes under complex backgrounds. At the same time, the attention class weights method on region of interest (ROI) features is utilized to boost the discrimination of the novel class features. We conducted comprehensive experiments on two widely used remote sensing object detection datasets, RSOD and DIOR. The proposed FSOD model demonstrated superior performance compared to MM-RCNN, achieving an improvement of approximately 4.7% in terms of mAP on the DIOR dataset. In addition, in comparison to the self-adaptive attention network (SAAN), the FSOD model exhibited an improvement of approximately 3.4% in mAP on the RSOD dataset.

ObjectivesTo investigate the risk factors of pulmonary infection in patients with severe myelitis and construct a prediction model.MethodsThe clinical data of 177 patients with severe myelitis at admission from the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2022 were retrospectively analyzed. The predicting factors associated with pulmonary infection were screened by multivariate logistic regression analysis, and the nomogram model was constructed, and the predictive efficiency of the model was evaluated, which was verified by calibration curve, Hosmer–Lemeshow goodness-of-fit test and decision curve analysis.ResultsOf the 177 patients with severe myelitis, 38 (21.5%) had pulmonary infection. Multivariate logistic regression analysis showed that neutrophil percentage to albumin ratio (NPAR) (OR = 6.865, 95%CI:1.746–26.993, p = 0.006) and high cervical cord lesion (OR = 2.788, 95%CI:1.229–6.323, p = 0.014) were independent risk factors for pulmonary infection, and the combined nomogram could easily predict the occurrence of pulmonary infection, with a C-index of 0.766 (95% CI: 0.678–0.854). The calibration curve, Hosmer-Lemeshow goodness-of-fit test (χ2 = 9.539, p = 0.299) and decision curve analysis showed that the model had good consistency and clinical applicability.ConclusionThe nomogram model constructed based on NPAR combined with high cervical cord lesion at admission has good clinical application value in predicting pulmonary infection in patients with severe myelitis, which is conducive to clinicians’ evaluation of patients.

With the increasing complexity of hardware design, verification has become the difficulty of chip design. In order to effectively shorten the overall working time of the design process, it is necessary to work out a method to quickly find design errors in the verification that takes up a lot of time in the design. The design under test is an ARM Chisel compatible with the ARM V4 instruction set architecture (ISA) processor model. The processor model is built with a new hardware language Chisel and is a highly complex hardware design. Based on this embedded processor model, ①a random instruction generator supporting all instructions of the ARM V4 ISA architecture is designed to increase the speed of generating test stimuli; ②based on the characteristics of the new construction language Chisel, designed for the processor model under test four verification stages: primary verification at the Chisel level, rapid verification of coverage, direct test verification and verification of complex applications, to ensure that the expected coverage is achieved; ③built in the Chisel environment and Verilog environment based on the embedded processor model Test platform. The test platform can quickly and accurately find errors and locate errors while collecting coverage, which improves the verification speed. Finally, the FPGA acceleration method is used to accelerate the verification of large-scale application programs and shorten the verification cycle.

With the current-assisted bonding technology, the rapid brazing of SiC ceramics was realized at 1125℃ with CoFeCrNiCuTi2 high-entropy alloy as the bonding layer material, which improves the bonding efficiency and ensures the full diffusion of elements. The influence of brazing temperature on the microstructure and mechanical properties of the bonding interface was studied. The results show that the obtained brazed joint has no obvious defects and the weld microstructure is mainly composed of high-entropy FCC, TiC phase and Cr23C6 phase. The formation of TiC reaction layer with dense interface inhibits the decomposition of high-entropy alloy and the formation of intermetallic compounds to a certain extent, and relieves the thermal stress between interface matrix SiC and high-entropy alloy filler. At the same time, due to the delayed diffusion effect of high-entropy alloy filler, the filler in the center of weld still keeps the FCC structure of high-entropy alloy. The mechanical test shows that the strength of brazed joint decreases at first and then increases. When the joining temperature is 1125℃, the maximum bending strength of SiC joint is 37 MPa, which is higher than that of ordinary Ni-based filler by about 21.3 MPa.

This paper develops a cognitive map of the Yan’an spirit that is based on the performance characteristics of the Yan’an spirit. An entity boundary perception model based on multi-task learning is proposed, and the traditional named entity recognition task is decomposed into entity boundary perception and entity classification, which completes the entity recognition based on MTBA-NER. The entity-oriented relationship extraction is based on the Bi-LSTM network to classify the expression of features, and the softmax function is used to extract the classification results. The political value has always been the value of Yan’an spirit, which has a value of 0.274 today, while the economic value, cultural value and educational value have a value of 0.322, 0.367 and 0.245, respectively. The analysis of the connotation of the Yan’an spirit based on cognitive mapping can help reflect and promote its value in contemporary times.

As an important part of the wing, the skin deformation accuracy directly affect the aerodynamic performance of the aircraft in different environments. Based on the idea of easy processing and easy deformation, a method for designing variable section thickness skin for trailing edge of variable camber wings is proposed. In this paper, firstly, the thickness and length of each segment of 3~8 segments of trailing edge skin are optimized. Then the deformation results of different segments of skin are compared and analyzed. Finally, the correctness of the design results and the effectiveness of the method are verified by using stacked skin experiment.

The hyperspectral imaging technology has the feature of “image and spectrum in one”, which brings together the features of traditional imaging and spectroscopic techniques, and both image information and spectral information of the agricultural products could be obtained. Therefore, this technology can not only detect the external characteristics of objects by imaging technology, but also obtain the internal quality and food safety information of agricultural products by the spectral technology, including variety classification, physical and chemical index determination, fungal infection detection and pesticide residue detection, etc. Compared with traditional detection methods, hyperspectral imaging has been applied in the field of non-destructive testing of agricultural products due to its simple pretreatment, non-pollution and non- destructive characteristics in the detection process. This review started from the theoretical basis of hyperspectral imaging, and summarized its image acquisition and analysis methods, followed by expounding the research progress of hyperspectral imaging technology in the field of nondestructive testing of agricultural products in the past five years. This review could provide information on the classification and nutritional quality of agricultural products and food safety assessment methods to provide reference.

The inversion of directions is an important operation with directions which plays an important role in qualitative spatial reasoning and spatial queries. In this work, we address on the inversion operation of the basic cardinal direction relations in the model of Goyal. The direction relation matrix model proposed by Goyal is a projection-based model for spatial direction relations between regions. This model is simple in calculation and easy to carry out formal reasoning, which is considered as currently one of the most excellent models for representation and qualitative reasoning with cardinal direction relations in two-dimensional space. This work aims to realize the automatic inference and calculation of the inverse of the basic cardinal direction relations in the model of Goyal and further to improve the ability of spatial reasoning and spatial analysis of spatial database. In order to avoid the complicated manual reasoning, an algorithm for automatically performing the inverse operation on this model is devised by means of the operations of direction relation matrix. Theorems are provided to prove formally that our algorithm is correct and complete, which is also verified by comparing the result of our algorithm with that of manual reasoning for each basic cardinal direction relation. This study realized the automatic inference and calculation of the inverse of the basic cardinal direction relations in the model of Goyal and further improved the ability of spatial reasoning and spatial analysis of spatial database.

For different kinds of plants, the distribution of lateral roots is highly plastic in different growth environments. In particular, the branching distance of the roots plays a decisive role in the formation of the root system architecture. In many root-system architecture models, constant branching distances of different branching orders usually are used to simulate the dynamics of a root system architecture. However, little is known about the formation of lateral roots, and branching distances for different branching orders are variable in the actual root system. The resource allocation model for predicting the lateral root distribution in individual plants has been established based on Parrondo's game. The root branching data predicted by the model is compared with the actual root branching data. The results show that the proposed method can cause serious changes in the spacing and distribution of lateral root formation. A parameter called development window can be used to override interbranch distance in the root-system architecture models.

BACKGROUND Sandstone-type uranium deposits contain a large number of pyrites of different shapes and stages. It is difficult to accurately discriminate the pyrite formed before, during or after the metallogenic period solely by observation of pyrite morphology by mineralogy and electron probe microanalysis. Pyrites during the metallogenic period are important information carriers for the genesis and formation process of uranium deposits, and their accurate identification is of great significance. Previous studies both domestically and internationally have used the LA-MC-ICP-MS method to analyze Pb isotopes, but this method has low analytical precision for low-content Pb samples and it is difficult to obtain 204Pb data. OBJECTIVES To identify metallogenic and non-metallogenic pyrites by in situ micro-scale Pb isotopes. METHODS Femtosecond laser ablation multi-collector inductively coupled plasma-mass spectrometry (fs-LA-MC-ICP-MS) was used to determine the lead isotope of pyrite in uranium ores. RESULTS Under the mineralogy microscope, it is clear that the pyrite is related to mineralization and its 206Pb/204Pb ratio is more than ten times or even dozens of times larger than the normal Clark value. 207Pb/204Pb ratio is slightly different, and 208Pb/204Pb ratio is constant. The occurrence of strawberry-shaped pyrites, and non-metallogenic pyrites with uranium minerals growing around them but not interspersed, have normal a 206Pb/204Pb ratio. Pyrites without any contact relationship have no obvious regularity in its Pb isotopes. CONCLUSIONS In-situ micro-scale Pb isotopic difference of pyrites was combined with appropriate observation of mineralogy morphology and occurrence, resulting in pyrites in the metallogenic period being more accurately identified than previously.

ObjectiveThe purpose of this research was to evaluate the influence of immunity on infection in patients with severe hemorrhagic stroke and explore the mechanism underlying this connection.MethodsClinical data obtained from 126 patients with severe hemorrhagic stroke were retrospectively analyzed, and the factors affecting infection were screened by multivariable logistic regression models. Nomograms, calibration curves, the Hosmer–Lemeshow goodness-of-fit test, and decision curve analysis were used to examine the effectiveness of the models in evaluating infection. The mechanism underlying the reduction in CD4+ T-cell levels in blood was explored by analysis of lymphocyte subsets and cytokines in cerebrospinal fluid (CSF) and blood.ResultsThe results showed that CD4+ T-cell levels of

Nitrogen doped porous carbon nanopolyhedra (NPC) derived from ZIF-8 was firstly prepared by high temperature carbonization. Subsequently, copper and cobalt were decorated on NPC to form novel nanocomposite by one-step chemical reduction method. Cu@Co/NPC hybrid material was characterized using X-ray powder diffraction, transmission electron microscopy and X-ray photoelectron spectroscopy. The composite was modified on the surface of glassy carbon electrode to study its electrochemical response to hydrazine. The results show that Cu@Co /NPC nanocomposites play a synergistic role, which shows better electrocatalytic effect on hydrazine than single component modified electrode. Under the optimum conditions, the concentration of composite modified electrode and hydrazine in the range of 5-1850 μmol/L exhibits good linear relationship, and the detection limit is 0.08 μmol/L. In addition, the composite modified electrode has good stability, reproducibility and selectivity for the determination of hydrazine. It has been successfully used for the determination of hydrazine in environmental water samples with satisfactory results.

ObjectiveTo understand the contamination status and antibiotics resistance of Arcobacter isolated from commercial fresh whole chicken in Shunyi District.MethodsSixty fresh whole chicken from retail markets and supermarkets in Shunyi District were randomly purchased. The Bacterial isolation was carried out using the membrane filtration methods. The strains were identified by matrix-assisted laser desorption ionization-time of flight mass spectrometery and real-time fluorescent PCR. The mass spectra of the strains were clustered. The isolated Arcobacter strains were subjected to a susceptibility test for 11 antibiotics using agar dilution method.ResultsThe detection rate of Arcobacter in 60 samples of commercially available fresh whole chicken was 26.67% （16/60） and all of them were Arcobacter butzleri. The detection rate of Arcobacter in June and July was significantly higher than that in May. Sixteen strains of Arcobacter were clustered by time-of-flight mass spectrometry and were divided into two clusters with a relative distance of 1 000. The relative distance was negatively correlated with the similarity of the strains， and the clustering map had a certain suggestive effect on the regional origin of the samples. The Arcobacter isolates were highly resistant to quinolone antibiotics and the resistance rates to nalidixic acid and ciprofloxacin were 81.25% and 43.75%， respectively. The resistance rate to gentamicin （12.50%） and erythromycin （12.50%）， azithromycin （12.50%）， telithromycin （12.50%） and streptomycin （6.25%） was relatively low.ConclusionThe detection rate of Arcobacter in raw chickens in Shunyi District is high. It should be alert to the risk of food-borne diseases caused by undercooked cooking and cross-contamination.

Mitophagy affects the activation of hepatic stellate cells (HSCs). Mitochondria-targeted ubiquinone (MitoQ) is a mitochondria-targeted antioxidant that reduces the production of intracellular reactive oxygen species (ROS). However, its relationship with mitophagy remains unclear. This study evaluated mitophagy during HSC activation and the effects of MitoQ on mitophagy in cell culture and in an animal model of the activation of HSCs. We found that MitoQ reduced the activation of HSCs and alleviated hepatic fibrosis. PINK1 (PTEN-induced putative kinase 1) is a putative serine/threonine kinase located in the mitochondria’s outer membrane. While the activation of primary HSCs or LX-2 cells was associated with reduced PINK1/parkin-mediated mitophagy, MitoQ reduced intracellular ROS levels, enhanced PINK1/parkin-mediated mitophagy, and inhibited the activation of HSCs. After knocking down the key mitophagy-related protein, PINK1, in LX-2 cells to block mitophagy, MitoQ intervention failed to inhibit HSC activation. Our results showed that MitoQ inhibited the activation of HSCs and alleviated hepatic fibrosis by enhancing PINK1/parkin-mediated mitophagy.

BackgroundHuman parvovirus B19 (HPV B19) is a single-stranded DNA virus. The detection rate of HPV B19 in the blood of healthy blood donors using PCR technology was reported to be 6.323/100000. However, that among hospitalized patients suspected of being infected with a pathogenic microorganism is unknown.MethodsA retrospective analysis was conducted on 2,182 high-throughput NGS results for 1,484 inpatients admitted to the First Affiliated Hospital of Zhengzhou University from January 2020 to October 2021 who were suspected of being infected with a pathogenic microorganism, as well as on clinical data of some HPV B19-positive patients.ResultsHuman parvovirus B19 was detected in 39 samples from 33 patients. The positivity rate was 2.22% among patients and 1.78% among samples. HPV B19 was detected in 20 cerebrospinal fluid samples, 13 blood samples, 3 alveolar lavage fluid samples, 2 tissue samples, and 1 throat swab. Based on clinical symptoms and NGS results, 16 patients were diagnosed with HPV B19 infection. The number of HPV B19 sequences in these patients was greater than 6, and the patients showed common symptoms such as fever (14 cases), anemia (11 cases), and severe nervous system symptoms such as meningoencephalitis (9 cases) and Guillain–Barré syndrome with peripheral motor and sensory nerve axon damage (4 cases). All 16 patients had experienced events likely to lead to decreased immunity (11 had a history of trauma/surgery/major disease, 4 had a history of precursor infection, and 3 had used immunosuppressants) and 7 had a history of blood transfusion during hospitalization. After treatment with antiviral drugs (12 cases) and intravenous human immunoglobulin (3 cases), of the 16 patients, 14 patients improved.ConclusionThe HPV B19 infection rate in hospitalized patients suspected of microbial infection was 2.22%. Most patients with HPV B19 infection had a history of low immunity and blood transfusion. HPV B19 could be detected in various bodily fluids and tissues (especially cerebrospinal fluid) using NGS. Patients with severe HPV B19 infection may have nervous system damage such as Guillain–Barré syndrome and meningoencephalitis. Early diagnosis using NGS and treatment with antiviral drugs and immunoglobulin can improve prognosis.

Ceramics and metals have large differences in thermal expansion coefficients, which can easily lead to large residual stresses in the joints. The researchers used the method of adding an intermediate layer to successfully reduce the residual stress in the joints. In the present work, using AgCu/Cu foam/AgCu composite filler as interlayer, brazing ZrB2-SiC ceramics and Inconel 600 alloy has been studied. Microstructure, shear strength and residual stress were studied in details for conditions with different thickness of Cu foam. The results show that with or without the addition of Cu foam, the brazed joints consists of Agss, Cuss and (Cr, Fe)7C3 phases without obvious defects. Shear strength of brazed joint is improved after introducing the Cu foam. With the increase of Cu foam thickness, the Cuss is quantitatively increased, and shear strength is increased first and then decreased. When thickness of Cu foam is 1 mm, the maximum shear strength is obtained as 72.5 MPa. The residual stresses of joint were calculated by using ABAQUS. The residual stress on the metals side is reduced by 50.6 MPa, and the ZrB2-SiC side by 110.3 MPa of the brazed joint with Cu foam. The results further prove that the addition of Cu foam can effectively reduce the residual stress and improve the shear strength of joints.

Autoimmune encephalitis (AE) is a severe inflammatory disease of the brain. Patients with AE demonstrate amnesia, seizures, and psychosis. Recent studies have identified numerous associated autoantibodies (e.g., against NMDA receptors (NMDARs), LGI1, etc.) involved in the pathogenesis of AE, and the levels of diagnosis and treatment are thus improved dramatically. However, there are drawbacks of clinical diagnosis and treatment based solely on antibody levels, and thus the application of additional biomarkers is urgently needed. Considering the important role of immune mechanisms in AE development, we summarize the relevant research progress in identifying cerebrospinal fluid (CSF) biomarkers with a focus on cytokines/chemokines, demyelination, and nerve damage.

For several months, the invasion of SARS-CoV-2 has brought great challenges to the human health. China has taken immediate act to prevent and control the pandemic. So far, the prevention and control of the pandemic situation in our country has achieved a great success in terms of controlling the spread of the virus. During this period, Traditional Chinese medicine has made great contributions to the treatment and prevention of COVID-19. This article summarizes the progress in the diagnosis and treatment of COVID-19 by using combination of Chinese and Western medicine.

The root system architecture (RSA) displays complex morphological characteristics because of diverse root growth behaviors. Recent studies have revealed that swarming behavior among roots is particularly important for RSA to adapt to environmental stimuli. However, few models are proposed to simulate RSA based on swarming behavior of roots. To analyze plasticity of RSA affected by swarming behavior, we propose viewing it as a swarm of single roots. A swarming behavior model is proposed by considering repulsion, alignment, and preference of individual single roots. Then, the swarming behavior model is integrated into a simple and generic RSA model (called ArchiSimple). Lastly, characteristics of RSA affected by swarming behavior model and non-swarming behavior model are compared and analyzed under three different virtual soil sets. The characteristics of RSA (such as primary root length, lateral root length, lateral roots, and resource uptake) are significantly promoted by swarming behavior. Root system distributions can also be greatly affected by swarming behavior. These results show that root foraging and exploration in soil can be regarded as collective behavior of individual single root.

Causal inference is a powerful modeling tool for explanatory analysis, which might enable current machine learning to become explainable. How to marry causal inference with machine learning to develop explainable artificial intelligence (XAI) algorithms is one of key steps toward to the artificial intelligence 2.0. With the aim of bringing knowledge of causal inference to scholars of machine learning and artificial intelligence, we invited researchers working on causal inference to write this survey from different aspects of causal inference. This survey includes the following sections: “Estimating average treatment effect: A brief review and beyond” from Dr. Kun Kuang, “Attribution problems in counterfactual inference” from Prof. Lian Li, “The Yule–Simpson paradox and the surrogate paradox” from Prof. Zhi Geng, “Causal potential theory” from Prof. Lei Xu, “Discovering causal information from observational data” from Prof. Kun Zhang, “Formal argumentation in causal reasoning and explanation” from Profs. Beishui Liao and Huaxin Huang, “Causal inference with complex experiments” from Prof. Peng Ding, “Instrumental variables and negative controls for observational studies” from Prof. Wang Miao, and “Causal inference with interference” from Dr. Zhichao Jiang. Keywords: Causal inference, Instructive variables, Negative control, Causal reasoning and explanation, Causal discovery, Counterfactual inference, Treatment effect estimation

A severely comatose female patient was diagnosed with Japanese encephalitis (JE). Her condition was complicated by Hashimoto’s thyroiditis (HT) and Guillain-Barré syndrome (GBS). After antiviral, glucocorticoid, and immunoglobulin treatment, the patient’s consciousness was restored, and she could breathe spontaneously. Following this, new-onset, primarily demyelinating GBS developed, which progressed to demyelination combined with axonal injury. The patient was switched to protein A immunoadsorption (PAIA) therapy, and her Hughes score decreased rapidly, from 4 to 1 after 6 months. This patient is the first to receive PAIA combined with an antiviral-glucocorticoid-immunoglobulin regimen to treat encephalitis, meningitis, HT, and GBS caused by JE infection, thereby reflecting the importance of clinical application of PAIA in the treatment of immunological complications of JE.

Objective: There is currently no effective treatment for Japanese encephalitis, which has a high rate of morbidity and mortality. This study assessed the effectiveness of a ganciclovir, methylprednisolone, and immunoglobulin combination (TAGMIC) therapy in decreasing cognitive impairment and mortality among patients with Japanese encephalitis.Methods: We retrospectively assessed the clinical data of 31 patients diagnosed with Japanese encephalitis, who were admitted to an intensive care unit. Patients were divided into the TAGMIC and non-TAGMIC group according to their treatment regime. We compared the 60-day, 6-month, and overall mortality and survival curves between groups. We also compared Barthel Index scores, Montreal Cognitive Assessment (MoCA) scores, and diffusion tensor imaging (DTI) results.Results: There was no significant difference in the 30-day mortality rate or Kaplan–Meier survival curve between groups. The 60-day, 6-month, and overall mortality rates in the TAGMIC group were significantly reduced (P = 0.043, P = 0.018, and P = 0.018, respectively) compared with the non-TAGMIC group (0, 0, 0 vs. 31.25, 37.5, 37.5%, respectively). The 60-day, 6-month, and overall Kaplan–Meier survival curves were significantly different between groups (P = 0.020, P = 0.009, P = 0.009, respectively). There was no significant difference in the Barthel Index scores of surviving patients. Among the five patients who underwent MoCA and DTI, four had a score of 0/5 for delayed recall (no cue), while the remaining patient had a score of 2/5. All five patients were able to achieve a score of 5/5 with classification and multiple-choice prompts, and had sparse or broken corpus callosum (or other) fibre bundles.Conclusion: TAGMIC treatment can reduce mortality due to severe Japanese encephalitis. The memory loss of surviving patients is mainly due to a disorder of the memory retrieval process, which may be related to the breakage of related fibre bundles.

A large amount of evidence suggest that vegetarian dietary pattern can significantly reduce the incidence of various malignancies, especially colorectal cancer; while high fat diet and meat are the risk factors for cancer. Different dietary structures directly affect the gut microbiota and their metabolites, thus inducing a tumor prone or tumor suppressive effect. In this article, we reviewed the influence of dietary factors on tumor occurrence, development, and therapeutic effect through regulating the gut microbiota and their metabolic products, in order to provide ideas for the prevention and treatment of malignant tumor.

[Objectives] This paper aims to analyze the dynamic cooling loads of ship on fixed routes and conclude with their changing laws.[Methods] To this end,the ship cabin is modelled to compare the dynamic cooling load changes in 6 different regions of the route(i.e. Hong Kong,Shantou,Fuzhou, Wenzhou,Shanghai,Dalian). Besides,the relation between the course angle and the sun azimuth angle is established to analyze the variation of dynamic cooling loads due to change of these angles.[Results] It is shown that the maximum total cooling load in Wenzhou area can reach 9.63 kW,while that in Shantou area only accounts for 53% of Wenzhou area,i.e. 5.11 kW. Course angle has great influence on the dynamic cooling load. At the course angle of 40° east by north,the total dynamic cooling load,the cooling load resulted from the heat penetration on wall surfaces(including windows)and the cooling load resulted from absorption of solar radiation increase by up to 21%,43% and 62% respectively. The greater the deviation from the normal north direction is,the greater the increase of the total dynamic cooling load will be. The increase of cooling load is related to the concentration time and the course angle.[Conclusions] The load variation caused by course angle during navigation should be considered, to accuately calculate the maximum load of air conditioning, and to select proper equipment model or optimal controlling strategy. Moreover,the air conditioning load calculation of each voyage should take into account the environmental conditions of covered areas.

[Objectives] Autonomous Underwater Vehicle (AUV) is an important tool for ocean exploration and exploitation,which plays an important role in ocean resources exploration,underwater equipment maintenance,underwater search and rescue,etc. Heading control of AUV is the fundamental function to accomplish underwater mission. At present, conventional Integer-Order PID (IOPID) controller is widely used for heading control in domestic engineering. However,its robustness is poor and parameter setting is complex.[Methods] Due to the shortcomings mentioned above,a heading controller based on Fractional-Order PID(FOPID)technology is proposed,and Genetic Algorithm(GA)is adopted to automatically tune the control gains and enable the practical implementation of the controller. The numerical simulations for PID,GA based IOPID and GA based FOPID are compared respectively by trial-and-error method.[Results] The results showed that,compared with the other two controllers,the GA based FOPID heading controller has a significantly reduced overshoot when the rise time and the steady-state error are basically equal,[Conclusions] which indicates that the AUV applying the GA based FOPID is more effective and advantageous.

The study of land use change and its driving forces at urban agglomeration scale is one of the most urgent issues to be studied.Based on GlobeLand30 data set of 2000, 2010 and 2020, this paper uses ArcGIS and other software to calculate and process land use change in Chengdu- Chongqing urban agglomeration and its driving forces through dynamic attitude and transfer matrix.The results showed that :(1) the land use change in chengdu-chongqing urban agglomeration was significant from 2000 to 2020, and the area of construction land continued to increase and the change rate was fast, while the area of cropland and grassland decreased.(2) The main drivers are population growth, socio-economic development and policy factors.The results provide references for the allocation of land resources and sustainable land use in this region.

The thickness of the methane hydrate stable zone is mainly controlled by the stability of methane hydrate. The temperature, pressure, pore water salinity, and gas component affect the thickness of the hydrate stable zone. The formation of methane hydrate is closely related to the formation of water. Various salt ions in formation water (Cl-, Na+, Mg2+, SO42-, Ca2+, and transition metals Fe, Mn, Cu, Co, Ni) can affect the formation and decomposition conditions of natural gas hydrate. Therefore, studying the effect of salts on the stability of methane hydrates is helpful to better understand the reservoir-forming conditions of methane hydrate. The effects of chloride, sulfate and carbonate on the stability of methane hydrate are evaluated in this paper. With the increase of salinity, the phase equilibrium curve of methane hydrate migrates to low temperature and high pressure under the same salinity condition. The inhibitory effects of different salts and anion and cation on methane hydrate are summarized. Under conditions of the same concentration and different types of salts, when the concentration of salt ranges from 1 to 1.5 mol/L, the inhibition effect of salt on methane hydrate is MgCl2 > CaCl2 > NaCl > KCl. When the concentration of salt is larger than 1.5 mol/L, the inhibitory effect of CaCl2 on methane hydrate is stronger. The inhibitory effect of anions on methane hydrate is controversial, and the inhibitory effect of Mg2+ on methane hydrate is the strongest. From available research results, there is still a gap between the existing data and the actual geological conditions. It is necessary to strengthen the detailed study on chloride-sulfate-carbonate-methane-water systems under actual experimental conditions. It is proposed that the combination of the high-voltage visual reaction chamber with Micro Laser Raman Spectroscopy is likely to accurately obtain the stable temperature and pressure conditions of gas hydrate formation, clarify the inhibitory effect of cations and anions, and understand how salts and ion affect the formation of hydrate and its stability, which will provide reference for the future exploration and development of hydrate.

Background/Aims: Ginsenoside Rb1 (Rb1) has been reported to have varieties of neuroprotective effects. This study aimed to evaluate the effects of Rb1 on pentylenetetrazol (PTZ)-induced rat brain injury and Mg2+ free-induced neuron injury and analyzed the detailed molecular mechanisms in vivo and in vitro. Methods: Seizure duration and latency were measured in epilepsy kindled rat. The cognitive impairment was assessed by Morris water maze (MWM) test. Oxidative stress parameters, malondialdehyde (MDA) and glutathione (GSH) were measured by the 2-thiobarbituric acid methods and the DTNB-GSSG reductase recycling methods. Neuronal damage was assessed by hematoxylin and eosin (H&E) and Nissl staining. Neuronal apoptosis was measured by Annexin V-FITC and propidium iodide (PI) staining. Immunohistochemistry and immunofluorescence staining were performed to evaluate Nrf2 and HO-1 expressions. Expression of Nrf2, HO-1, Bcl-2, iNOS and LC3 were evaluated by western blot. Results: The PTZ-injured rats presented longer seizure duration and shorter seizure latency. Rb1 ameliorated these effects, as well as the cognitive deficits caused by PTZ exposure. Besides, Rb1 dose-dependently increased GSH levels, decreased MDA levels and alleviated neuronal damage in PTZ-treated rats. In vitro, Rb1 increased cell viability and decreased neuronal apoptosis in a dose-dependent manner under Mg2+ free condition. Moreover, in vivo and in vitro, Rb1 enhanced both the Nrf2 and HO-1 expressions. Furthermore, upregulation of the expression of Bcl-2 and downregulation of the expression of iNOS and LC3 were observed. However, knockdown of Nrf2 adversely affected the protective effects of Rb1 in epileptic hippocampal neurons. Conclusion: Rb1 conferred neuroprotective effects against PTZ-induced brain damage and Mg2+ free-induced neuron injury by activating Nrf2/ARE signaling.

With the proliferation of Unmanned Aerial Vehicles (UAVs) to provide diverse critical services, such as surveillance, disaster management, and medicine delivery, the accurate detection of these small devices and the efficient classification of their flight modes are of paramount importance to guarantee their safe operation in our sky. Among the existing approaches, Radio Frequency (RF) based methods are less affected by complex environmental factors. The similarities between UAV RF signals and the diversity of frequency components make accurate detection and classification a particularly difficult task. To bridge this gap, we propose a joint Feature Engineering Generator (FEG) and Multi-Channel Deep Neural Network (MC-DNN) approach. Specifically, in FEG, data truncation and normalization separate different frequency components, the moving average filter reduces the outliers in the RF signal, and the concatenation fully exploits the details of the dataset. In addition, the multi-channel input in MC-DNN separates multiple frequency components and reduces the interference between them. A novel dataset that contains ten categories of RF signals from three types of UAVs is used to verify the effectiveness. Experiments show that the proposed method outperforms the state-of-the-art UAV detection and classification approaches in terms of 98.4% and F1 score of 98.3%.