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According to a WHO report, the number of patients with coronavirus disease 2019 (COVID-19) has reached 456,797,217 worldwide as of 15 March, 2022. In Wuhan, China, large teams of health-care personnel were dispatched to respond to the COVID-19 emergency. This study aimed to determine the sociodemographic and psychological predictors of resilience among frontline nurses fighting the current pandemic.
A total of 143 nurses were recruited from February 15 to February 20, 2020, to participate in this study. The 10-item Connor-Davidson Resilience Scale and the 21-item Depression Anxiety Stress Scale were used to estimate the participants’ resilience and mental wellbeing.
Results showed that the nurses displayed a moderate resilience level. Their median depression, anxiety, and stress scores were 1, 2, and 3, respectively, which were negatively correlated with resilience. Female gender, being dispatched to Wuhan, and depression levels were the significant predictors of resilience.
The results suggest that particular attention should be given to nurses who were dispatched to Wuhan and who exhibited depression symptoms, and appropriate measures should be taken to boost their resilience.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.
Drilling and sampling are the most direct and effective methods available to study Antarctic subglacial lakes. Based on the Philberth probe, a Recoverable Autonomous Sonde (RECAS) allows for in situ lake water measurement and sampling, through the addition of an upper thermal tip and a cable recoiling mechanism. RECAS-200, a prototype of RECAS, has a drilling depth of 200 m, a surface supply voltage of 800 VAC and a downhole power of ~9.6 kW during drilling. In this study, a heating control system for RECAS-200 was designed. The system avoids the need for high-power step-down converters, by separating heating power from control power, thereby reducing the overall weight of the probe and avoiding the need to increase cable diameter. We also introduce a self-developed, small, solid-state, 800 VAC power regulator and a fuzzy PID temperature control algorithm. Their purpose was to manage the power adjustment of each heating element and to provide closed-loop temperature control of certain heating elements which can easily burn out due to overheating. Test results indicated that the proposed RECAS-200 heating control system met all our design specifications and could be easily assembled into the RECAS-200 probe.
Subglacial lake exploration is of great interest to the science community. RECoverable Autonomous Sonde (RECAS) provides an exploration tool to measure and sample subglacial lake environments while the subglacial lake remains isolated from the glacier surface and atmosphere. This paper presents an electronic control system design of 200 m prototype of RECAS. The proposed electronic control system consists of a surface system, a downhole control system, and a power transfer and communication system. The downhole control system is the core element of RECAS, and is responsible for sonde status monitoring, sonde motion control, subglacial water sampling and in situ analysis. A custom RS485 temperature sensor was developed to cater for the limited size and depth requirements of the system. We adopted a humidity-based measurement to monitor for a housing leak. This condition is because standard leak detection monitoring of water conductivity may be inapplicable to pure ice in Antarctica. A water sampler control board was designed to control the samplers and monitor the on/off state. A high-definition camera system with built-in storage and self-heating ability was designed to perform the video recording in the subglacial lake. The proposed electronic control system is proven effective after a series of tests.
Much progress has been made in understanding the environmental and hormonal systems regulating winter diapause. However, transcriptional regulation of summer diapause is still largely unknown, making it difficult to understand an all-around regulation profile of seasonal adaptation. To bridge this gap, comparison RNA-seq to profile the transcriptome and to examine differential gene expression profiles between non-diapause, summer diapause, and winter diapause groups were performed. A total number of 113 million reads were generated and assembled into 79,117 unigenes, with 37,492 unigenes categorized into 58 functional gene ontology groups, 25 clusters of orthologous group categories, and 256 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG analysis mapped 2108 differentially expressed genes to 48 and 67 pathways for summer and winter diapauses, respectively. Enrichment statistics showed that 11 identical pathways similarly overlapped in the top 20 enriched functional groups both related to summer and winter diapauses. We also identified 35 key candidate genes for universal and differential functions related to summer and winter diapause preparation. Furthermore, we identified some genes involved in the signaling and metabolic pathways that may be the key drivers to integrate environmental signals into the summer and winter diapause preparation. The current study provided valuable insights into global molecular mechanisms underpinning diapause preparation.
The associations between sugar-sweetened beverage (SSB) and artificially sweetened beverage (ASB) consumption and the risk of metabolic syndrome (MetS) remain controversial. A quantitative assessment of dose–response associations has not been reported. This study aims to assess the associations between the risk of MetS and SSB, ASB, and total sweetened beverage (TSB, the combination of SSB and ASB) consumption by reviewing population-based epidemiological studies.
We searched PubMed, Embase and Web of Science databases prior to 4 November 2019, for relevant studies investigating the SSB–MetS and ASB–MetS associations. A random effects model was used to estimate pooled relative risks (RR) and 95 % CI. Dose–response association was assessed using a restricted cubic splines model.
We identified seventeen articles (twenty-four studies, including 93 095 participants and 20 749 MetS patients).
The pooled RR for the risk of MetS were 1·51 (95 % CI 1·34, 1·69), 1·56 (1·32, 1·83) and 1·44 (1·19, 1·75) in high consumption group of TSB, SSB and ASB, respectively; and 1·20 (1·13, 1·28), 1·19 (1·11, 1·28) and 1·31 (1·05, 1·65) per 250 ml/d increase in TSB, SSB and ASB consumption, respectively. Additionally, we found evidence of non-linear, TSB–MetS and SSB–MetS dose–response associations and a linear ASB–MetS dose–response association.
TSB, SSB and ASB consumption was associated with the risk of MetS. The present findings provide evidence that supports reducing intake of these beverages to lower the TSB-, SSB- and ASB-related risk of MetS.
The edge surface warping defect seriously affect the surface quality of strips. In this paper, a technology for diagnosis of warping defects in hot-rolled strip based on data-driven methods is studied. Based on the mechanism analysis of the warping defects, the process parameters affecting the warping defects were sorted out and used as the original input parameters of the defect diagnosis model. Firstly, a diagnostic model that combines the deep belief network and contribution plots of each dimensionality reduction layer is proposed. The deep belief network that integrates each dimensionality reduction layer can predict product defects more accurately and stably than the traditional deep belief network. Meanwhile, on the basis of the pre-judgment model, the method of contribution plot is further introduced to trace the defects, and the comprehensive diagnosis function of model pre-judgment and traceability is realized. Finally, collected the production data from a hot rolling production line for a period of time. Tested the model and predicted a hit rate of 85%. The main influencing factors of edge surface warping defects were determined that the rate of defect decrease with the increase of furnace temperature. When the heating temperature of the second stage of the heating furnace is higher than 1160°C, the incidence of defects is significantly reduced. Defect rate is relatively low within 240min of total furnace time. With the first and third pass phosphorus removal equipment turned on, the incidence of defects was relatively low.
A gravity-driven water film falling down an ice sheet is considered within the framework of a long-wave approximation. The integral-boundary-layer method, modified with the account of the phase transition, is adopted to describe the evolution of both the free surface of a water film and the interface between the ice and water. A set of governing equations consisting of five coupled nonlinear partial differential equations is established. The linear instability analysis of the uniform base flow is performed, and the result is in good agreement with the Orr–Sommerfeld analysis of the linearized Navier–Stokes equations. The phase transition at the interface between the ice and water plays a role in stabilizing the system linearly with long-wavelength perturbations. The nonlinear solutions of the steady travelling waves are constructed numerically. The phase transition tends to suppress the dispersion of the interfacial wave. Comparisons to direct numerical simulation of the Navier–Stokes equations, which are performed with an extended marker and cell method, show a remarkable agreement. The integral-boundary-layer method captures the water film thickness and the topography of the ice sheet satisfactorily. The phase transition is observed to enhance the backflow phenomenon in the capillary region of the solitary-like interfacial wave.
Electrospun membranes have potential applications in the field of waterproof and breathable textile products. However, challenges still exist to improve the breathability, and waterproof and mechanical properties of these microporous membranes. In this paper, a novel hydrophobic microporous nanofiber membrane was prepared via side-by-side electrospinning of fluorosilane-modified silica nanoparticles (F–SiO2) blended with synthesized polyurethane (PU) solution and composited with the polyacrylonitrile (PAN) solution. To prepare F–SiO2, SiO2 nanoparticles were hydrophobically modified by fluorosilane. Composite nanofiber membranes with different blending ratios of PU(F–SiO2)/PAN were fabricated via side-by-side electrospinning by controlling the extruding speed of two spinnerets. Experimental results indicated that regarding F–SiO2 as hydrophobic inorganic particle can improve the hydrophobic properties of PU nanofiber membrane. The prepared PAN/(F–SiO2/PU) nanofiber microporous membranes exhibit relatively excellent waterproof and mechanical properties as that robust tensile strength (19.5 MPa), preferable water vapor permeability [10.3 kg/(m2 d)], favorable water contact angle (137.2°), and superior mechanical properties. It was believed that the reinforced PAN/(F–SiO2/PU) nanofibrous composite membranes have potential applications in chemical protective clothing, army combat uniforms, self-cleaning materials, and other medical products.
Multiple neurotrophic factors, including vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF)-2, nerve growth factor (NGF) and insulin-like growth factor(IGF)-1, have been shown to play important roles in the pathophysiology of mood disorders. However, insufficient clinical data supporting the importance of these neurotrophic factors in mood disorders, especially manic episode, have made inconclusive to make a connection between these factors and the disorder.
This study intended to investigate possible peripheral biomarkers in serum of manic episode of bipolar disorder.
We aimed to investigate whether or not serum levels of VEGF, FGF-2, NGF and IGF-1 varied in manic state.
Serum levels of VEGF, FGF-2, NGF and IGF-1 were examined in 70 drug-naïve patients with manic episode of bipolar disorder (BM) as well as 50 healthy controls, using an ELISA method.
The mean serum levels of VEGF, FGF-2, NGF and IGF-1 were 168.13±225.61pg/ml, 279.09±378.62pg/ml, 61.38±171.67pg/ml and 162.01±72.00ng/ml in BM patients, and 140.80±143.71pg/ml, 275.46±235.29pg/ml, 36.34±15.14pg/ml and 138.90±80.11ng/ml in healthy controls, respectively. Serum levels of FGF-2, NGF and IGF-1 in patients were significantly higher than those in healthy controls (Z=−2.896, P=0.004; Z=− 2.050, P=0.040; Z=−2.188, P=0.029; respectively), although there was no statistical difference in the serum levels of VEGF between two groups (Z=-0.468, P=0.639). Moreover, serum levels of NGF in patients correlated with the duration of disorder (rs=−0.241, P=0.044).
The increase in serum levels of FGF-2, NGF and IGF-1 in manic state may reflect a neuroprotective role for these factors, and these factors may be considered biological markers for manic episode.
Bloodstream infection (BSI), caused by Klebsiella pneumoniae, is associated with high morbidity and mortality, where the pks gene cluster plays a major role in their occurrence and prevalence. Information on the prevalence and characteristics of this gene cluster in K. pneumoniae is currently limited in mainland China. We therefore undertook a multicentre longitudinal study which revealed the prevalence, overall, community-onset and hospital-acquired BSI to be 20.5%, 28.3% and 13.0%, respectively. Compared to pks-negative, pks-positive isolates were significantly more susceptible to antimicrobial agents with a low incidence (5.1%) of multidrug-resistance and with infrequent extended-spectrum beta-lactamase (ESBL) production. Among pks-positive isolates, ST23 (78/117) and ST65 (20/117) were the dominant sequence types, and the majority harboured virulence genes. Community-onset BSI patients infected with pks-positive isolates had a higher proportion of liver abscesses and a lower proportion of biliary obstructions (P < 0.05). The pks-positive isolates were mostly sporadic in the phylogenetic tree, with a 65.8 and 47.0 average allele difference between Clade 1 and Clade 2, respectively. We concluded that although pks-positive K. pneumoniae were generally susceptible to antimicrobials, the high prevalence of such isolates in community cases and the genotoxicity, merits further investigation.
Intelligent control of friction and adhesion has attracted much attention for use in soft robotics, human-sensor interfaces, and bionics. Here we introduce a shape memory photonic crystal (SMPC) polymer that can be programmed and recovered by solvent to realize switchable surface friction. Micro sliding test show that the friction coefficient on this SMPC in the programmed and recovered state can vary by three times. We also show that the mechanism behind this switchable friction coefficient is the surface roughness related adhesion.
The cao vit gibbon Nomascus nasutus, also known as eastern black crested gibbon, is categorized as Critically Endangered on the IUCN Red List and was considered one of the world's 25 most threatened primates. The only known population occurs along the border between China and Viet Nam. Accurate information on population size and dynamics is critical for the species’ conservation, but population surveys conducted in only one country may over- or underestimate total population size because the home ranges of cao vit gibbon groups often cross the international border. In 2007 and 2016 we conducted two collaborative transboundary censuses of the cao vit gibbon populations in the Trung Khanh Cao Vit Gibbon Species and Habitat Conservation Area in Viet Nam and the Bangliang Gibbon National Nature Reserve in China. The results showed a population size of 102–110 in 2007, which increased to 107–136 in 2016. Our results indicate that previous surveys conducted separately in Viet Nam and China underestimated the global population size of this species. According to our more comprehensive surveys, the gibbon population is increasing slowly. The gibbons and their habitat are legally protected in both countries. Hunting and charcoal making have not been reported in this area since 2007. As habitat carrying capacity is a limiting factor, habitat restoration is required. However, lack of funding to protect the cao vit gibbon remains a challenge.
Schizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated.
To investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia.
Genomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant.
The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus–medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia.
These findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.
Underground Nuclear Astrophysics in China (JUNA) will take the advantage of the ultra-low background in Jinping underground lab. High current accelerator with an ECR source and detectors were commissioned. JUNA plans to study directly a number of nuclear reactions important to hydrostatic stellar evolution at their relevant stellar energies. At the first period, JUNA aims at the direct measurements of 25Mg(p,γ)26 Al, 19F(p,α) 16 O, 13C(α, n) 16O and 12C(α,γ) 16O near the Gamow window. The current progress of JUNA will be given.
The plerocercoid (sparganum) of Spirometra erinaceieuropaei is the main aetiological agent of human sparganosis. To improve the current knowledge on S. erinaceieuropaei evolution, we performed multi-locus microsatellite typing of sparganum isolates from China for the first time. All available expressed sequence tag (EST) sequences for the Spirometra were downloaded from the GenBank. The identification and localization of microsatellites in ESTs was accomplished by MISA. Based on the selected microsatellites, the genetic structure of 64 sparganum isolates collected from 11 geographical locations in southwest China were investigated through principal component analysis, STRUCTURE analysis and neighbour-joining clustering. A total of 522 non-redundant ESTs containing 915 simple sequence repeats were identified from 12 481 ESTs screened. Five primer pairs were finally selected. Using these loci, a total of 12 alleles were detected in 64 sparganum isolates. Little variability was observed within each of geographical population, especially among isolates derived from Kunming of Yunnan (YN-KM) province. Both STRUCTURE analysis and the clustering analysis supported that two genotypes existed among the sparganum isolates from southwest China. In conclusion, five microsatellite markers were successfully developed, and sparganum population was observed to harbour low genetic variation, further investigation with deeper sampling was needed to elucidate the population structure.
Imaging studies have shown that the subcallosal region (SCR) volume was decreased in patients with major depressive disorder (MDD). However, whether the volumetric reductions in the SCR are due to thinning of the cortex or a loss of surface area (SA) remains unclear. In addition, the relationship between cortical measurements of the SCR and age through the adult life span in MDD remains unclear.
We used a cross-sectional design from 114 individuals with MDD and 112 matched healthy control (HC) individuals across the adult life span (range: 18–74 years). The mean cortical volume (CV), SA and cortical thickness (CT) of the SCR were computed using cortical parcellation based on FreeSurfer software. Multivariate analyses of covariance models were performed to compare differences between the MDD and HC groups on cortical measurements of the SCR. Multiple linear regression models were used to test age-by-group interaction effects on these cortical measurements of the SCR.
The MDD had significant reductions in the CV and SA of the left SCR compared with HC individuals after controlling of other variables. The left SCR CV and SA reductions compared with matched controls were observed only in early adulthood patients. We also found a significant age-related CT reduction in the SCR both in the MDD and HC participants.
The SCR volume reduction was mainly driven by SA in MDD. The different trajectories between the CT and SA of the SCR with age may provide valuable information to distinguish pathological processes and normal ageing in MDD.
Hepatitis B constitutes a severe public health challenge in China. The Community-based Collaborative Innovation hepatitis B (CCI-HBV) project is a national epidemiological study of hepatitis B and has been conducting a comprehensive intervention in southern Zhejiang since 2009.
The comprehensive intervention in CCI-HBV areas includes the dynamic hepatitis B screening in local residents, the normalised treatment for hepatitis B infections and the upcoming full-aged hepatitis B vaccination. After two rounds of screening (each round taking for 4 years), the initial epidemiological baseline of hepatitis B in Qinggang was obtained, a coastal community in east China. By combining key data and system dynamics modelling, the regional hepatitis B epidemic in 20 years was predicted.
There were 1041 HBsAg positive cases out of 12 228 people in Round 1 indicating HBV prevalence of 8.5%. Of the 13 146 people tested in Round 2, 1171 people were HBsAg positive, with a prevalence of 8.9%. By comparing the two rounds of screening, the HBV incidence rate of 0.192 per 100 person-years was observed. By consulting electronic medical records, the HBV onset rate of 0.533 per 100 person-years was obtained. We generated a simulated model to replicate the real-world situation for the next two decades. To evaluate the effect of interventions on regional HBV prevalence, three comparative experiments were conducted.
In this study, the regional hepatitis B epidemic in 20 years was predicted and compared with HBV prevalence under different interventions. Owing to the existing challenges in research methodology, this study combined HBV field research and simulation to provide a system dynamics model with close-to-real key data to improve prediction accuracy. The simulation also provided a prompt guidance for the field implementation.