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In this paper, we design and fabricate dual-tunable waveguides in a two-dimensional periodic plate with threaded holes. Dual tunability is realized by using rods held with nuts as well as assembly prestress of the nuts. A straight waveguide, a bent waveguide, and a wave splitter are designed by changing the distribution of rods and nuts in different circuits. The experimental and numerical results show that the frequencies of guided waves can be tuned by the assembly prestress. By increasing the amount of prestress, the frequency range of the passing band can be shifted upward. Confinements, guiding, and splitting of Lamb waves are clearly observed in both experimental measurements and numerical simulations. This work is essential for the practical design of reconfigurable phononic devices.
Rodents and shrews are major reservoirs of various pathogens that are related to zoonotic infectious diseases. The purpose of this study was to investigate co-infections of zoonotic pathogens in rodents and shrews trapped in four provinces of China. We sampled different rodent and shrew communities within and around human settlements in four provinces of China and characterised several important zoonotic viral, bacterial, and parasitic pathogens by PCR methods and phylogenetic analysis. A total of 864 rodents and shrews belonging to 24 and 13 species from RODENTIA and EULIPOTYPHLA orders were captured, respectively. For viral pathogens, two species of hantavirus (Hantaan orthohantavirus and Caobang orthohantavirus) were identified in 3.47% of rodents and shrews. The overall prevalence of Bartonella spp., Anaplasmataceae, Babesia spp., Leptospira spp., Spotted fever group Rickettsiae, Borrelia spp., and Coxiella burnetii were 31.25%, 8.91%, 4.17%, 3.94%, 3.59%, 3.47%, and 0.58%, respectively. Furthermore, the highest co-infection status of three pathogens was observed among Bartonella spp., Leptospira spp., and Anaplasmataceae with a co-infection rate of 0.46%. Our results suggested that species distribution and co-infections of zoonotic pathogens were prevalent in rodents and shrews, highlighting the necessity of active surveillance for zoonotic pathogens in wild mammals in wider regions.
Zinc (Zn) is an essential mineral and its deficiency manifests in non-specific clinical signs that require long time to develop. The response of swine intestine to Zn restriction was evaluated to identify early changes that can be indicative of Zn deficiency. Twenty-seven pigs (body weight = 77⋅5 ± 2⋅5 kg) were assigned to one of three diets: diet without added Zn (Zn-restricted diet, ZnR), and ZnR-supplemented with either 50 (Zn50) or 100 mg of Zn/kg of diet (Zn100) of Zn supplied by ZnCl2. After 32 d consuming the diets, serum Zn concentration in ZnR pigs was below the range of 0⋅59–1⋅37 μg/ml considered sufficient, thereby confirming subclinical Zn deficiency. Pigs showed no obvious health or growth changes. RNA-seq analysis followed by qPCR showed decreased expression of metallothionein-1 (MT1) (P < 0⋅05) and increased expression of Zn transporter ZIP4 (P < 0⋅05) in jejunum and ileum of ZnR pigs compared with Zn-supplemented pigs. Ingenuity pathway analysis revealed that Zn50 and Zn100 induced changes in genes related to nucleotide excision repair and integrin signalling pathways. The top gene network in the ZnR group compared with Zn100 was related to lipid and drug metabolism; and compared with Zn50, was related to cellular proliferation, assembly and organisation. Dietary Zn concentrations resulted in differences in genes related to immune pathways. Our analysis showed that small intestine presents changes associated with Zn deficiency after 32 d of Zn restriction, suggesting that the intestine could be a sentinel organ for Zn deficiency.
With the rapid development of the national economy, the demand for electricity is also growing. Thermal power generation accounts for the highest proportion of power generation, and coal is the most commonly used combustion material. The massive combustion of coal has led to serious environmental pollution. It is significant to improve energy conversion efficiency and reduce pollutant emissions effectively. In this paper, an extreme learning machine model based on improved Kalman particle swarm optimization (ELM-IKPSO) is proposed to establish the boiler combustion model. The proposed modeling method is applied to the combustion modeling process of a 300 MWe pulverized coal boiler. The simulation results show that compared with the same type of modeling method, ELM-IKPSO can better predict the boiler thermal efficiency and NOx emission concentration and also show better generalization performance. Finally, multi-objective optimization is carried out on the established model, and a set of mutually non-dominated boiler combustion solutions is obtained.
Due to the lack of research between the inner layers in the structure of colonic mucous and the metabolism of fatty acid in the constipation model, we aim to determine the changes in the mucous phenotype of the colonic glycocalyx and the microbial community structure following treatment with Rhubarb extract in our research. The constipation and treatment models are generated using adult male C57BL/6N mice. We perform light microscopy and transmission electron microscopy (TEM) to detect a Muc2-rich inner mucus layer attached to mice colon under different conditions. In addition, 16S rDNA sequencing is performed to examine the intestinal flora. According to TEM images, we demonstrate that Rhubarb can promote mucin secretion and find direct evidence of dendritic structure-linked mucus structures with its assembly into a lamellar network in a pore size distribution in the isolated colon section. Moreover, the diversity of intestinal flora has noticeable changes in constipated mice. The present study characterizes a dendritic structure and persistent cross-links have significant changes accompanied by the alteration of intestinal flora in feces in models of constipation and pretreatment with Rhubarb extract.
Residents of long-term care facilities face significantly greater risk of contracting or dying from coronavirus disease 2019 (COVID-19). However, little is known about COVID-19 in assisted living communities (ALCs) and the potential determinants of its spread. We examined the association between COVID-19 cases in ALCs and the proportion of Medicare-Medicaid (dual) eligible minority residents, neighborhood area deprivation, and state COVID-19 policy stringency.
We conducted longitudinal analyses employing data on confirmed COVID-19 cases in ALCs in 5 states. We sought to determine the weekly cumulative number of COVID-19 cases in ALCs. Covariates were ALC characteristics, area deprivation index, and state COVID-19 policy stringency. Multivariate 2-part models were used to determine the associations between independent variables and the likelihood of an outbreak and the overall count of cases.
In our study sample, 201 ALCs (7.04%) reported 1 or more COVID-19 cases as of August 17, 2020. A higher percentage of minority residents was associated with an increased likelihood of an ALC reporting at least 1 COVID-19 case (odds ratio [OR], 1.06; P = .032). Conditional on having at least 1 case, ALCs in states with stricter social distancing policies had lower case counts (incidence rate ratio [IRR], 0.98; P < .001). Greater neighborhood deprivation was associated with higher case count (IRR, 1.36; P = .049).
ALCs with higher proportions of dual-eligible minority residents were more likely to have COVID-19 outbreaks within their communities. ALCs located in more socioeconomically deprived neighborhoods, and in states with less stringent state social distancing policies, tended to have more COVID-19 cases.
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.
Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.
Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.
Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical−striatal−thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.
MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.
The effect and the mechanism of high glucose on fish muscle cells are not fully understood. In the present study, muscle cells of olive flounder (Paralichthys olivaceus) were treated with high glucose (33 mM) in vitro. Cells were incubated in three kinds of medium containing 5 mM glucose, 5 mM glucose and 28 mM mannitol (as an isotonic contrast) or 33 mM glucose named the Control group, the Mannitol group and the high glucose (HG) group, respectively. Results showed that high glucose increased the ADP:ATP ratio and the reactive oxygen species (ROS) level, decreased mitochondrial membrane potential (MMP), induced the release of cytochrome C (CytC) and cell apoptosis. High glucose also led to cell glycogen accumulation by increasing the glucose uptake ability and affecting the mRNA expressions of glycogen synthase and glycogen phosphorylase. Meanwhile, it activated AMP-activated protein kinase (AMPK), inhibited the activity of mammalian target of rapamycin (mTOR) signalling pathway and the expressions of myogenic regulatory factors (MRF). The expressions of myostatin-1 (mstn-1) and E3 ubiquitin ligases including muscle RING-finger protein 1 (murf-1) and muscle atrophy F-box protein (mafbx) were also increased by the high glucose treatment. No difference was found between the Mannitol group and the Control group. These results demonstrate that high glucose has the effects of inducing apoptosis, increasing glycogen accumulation and inhibiting protein synthesis on muscle cells of olive flounder. The mitochondria-mediated apoptotic signalling pathway, AMPK and mTOR pathways participated in these biological effects.
To establish optimal gestational weight gain (GWG) in Chinese pregnant women by Chinese-specific BMI categories and compare the new recommendations with the Institute of Medicine (IOM) 2009 guidelines.
Multicentre, prospective cohort study. Unconditional logistic regression analysis was used to evaluate the OR, 95 % CI and the predicted probabilities of adverse pregnancy outcomes. The optimal GWG range was defined as the range that did not exceed a 1 % increase from the lowest predicted probability in each pre-pregnancy BMI group.
From nine cities in mainland China.
A total of 3731 women with singleton pregnancy were recruited from April 2013 to December 2014.
The optimal GWG (ranges) by Chinese-specific BMI was 15·0 (12·8–17·1), 14·2 (12·1–16·4) and 12·6 (10·4–14·9) kg for underweight, normal weight and overweight pregnant women, respectively. Inappropriate GWG was associated with several adverse pregnancy outcomes. Compared with women gaining weight within our proposed recommendations, women with excessive GWG had higher risk for macrosomia, large for gestational age and caesarean section, whereas those with inadequate GWG had higher risk for low birth weight, small for gestational age and preterm delivery. The comparison between our proposed recommendations and IOM 2009 guidelines showed that our recommendations were comparable with the IOM 2009 guidelines and could well predict the risk of several adverse pregnancy outcomes.
Inappropriate GWG was associated with higher risk of several adverse pregnancy outcomes. Optimal GWG recommendations proposed in the present study could be applied to Chinese pregnant women.
Biological materials represent a major source of inspiration to engineer protein-based polymers that can replicate the properties of living systems. Combined with our ability to control the molecular structure of proteins at the single amino acid level, this results in a vast array of attractive possibilities for materials science, an interest that is undeniably related to simplified procedures in gene synthesis, cloning, and biotechnological production. In parallel, it has been increasingly appreciated that living organisms exploit liquid–liquid phase separation (LLPS) to fabricate extracellular structures. In this article, we discuss the central role of protein LLPS in the fabrication of selected biological structures, including biological adhesives and hard biomolecular composites, and how physicochemical lessons from these systems are being replicated in synthetic analogs. Recent translational applications of protein LLPS are highlighted, notably aqueous-resistant adhesives, stimuli-responsive therapeutics carriers, and matrix materials for green structural composites.
Little is known about poverty trends in people with severe mental illness (SMI) over a long time span, especially under conditions of fast socioeconomic development.
This study aims to unravel changes in household poverty levels among people with SMI in a fast-changing rural community in China.
Two mental health surveys, using ICD-10, were conducted in the same six townships of Xinjin county, Chengdu, China. A total of 711 and 1042 people with SMI identified in 1994 and 2015, respectively, participated in the study. The Foster-Greer-Thorbecke poverty index was adopted to measure the changes in household poverty. These changes were decomposed into effects of growth and equity using a static decomposition method. Factors associated with household poverty in 1994 and 2015 were examined and compared by regression analyses.
The proportion of poor households, as measured by the headcount ratio, increased significantly from 29.8% in 1994 to 39.5% in 2015. Decomposition showed that poverty in households containing people with SMI had worsened because of a redistribution effect. Factors associated with household poverty had also changed during the study period. The patient's age, ability to work and family size were of paramount significance in 2015.
This study shows that the levels of poverty faced by households containing people with SMI has become more pressing with China's fast socioeconomic development. It calls for further integration of mental health recovery and targeted antipoverty interventions for people with SMI as a development priority.
Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Wi-Fi based indoor localisation has become attractive due to its extensive distribution and low cost properties. IEEE 802.11-2016 now includes a Wi-Fi Fine Time Measurement (FTM) protocol which can be used for Wi-Fi ranging between intelligent terminal and Wi-Fi access point. This paper introduces a framework of Wi-Fi FTM data acquisition and processing that can be used for indoor localisation. We analyse the main factors that affect the accuracy of Wi-Fi ranging and propose a calibration, filtering and modelling algorithm that can effectively reduce the ranging error caused by clock deviation, non-line-of-sight (NLOS) and multipath propagation. Experimental results show that the proposed calibration and filtering method is able to achieve metre-level ranging accuracy in case of line-of-sight by using large bandwidth. Estimation results also show that the proposed Wi-Fi ranging model provides an accurate ranging performance in NLOS and multipath contained indoor environment; the final positioning error is less than 2·2 m with a stable output frequency of 3 Hz.
Plasmonic nanostructures possess broadly tunable optical properties with catalytically active surfaces. They offer new opportunities for achieving efficient solar-to-chemical energy conversion. Plasmonic metal–semiconductor heterostructures have attracted heightened interest due to their capability of generating energetic hot electrons that can be collected to facilitate chemical reactions. In this article, we present a detailed survey of recent examples of plasmonic metal–semiconductor heterostructures for hot-electron-driven photochemistry, including plasmonic metal–oxide, plasmonic metal–two-dimensional materials, and plasmonic metal–metal–organic frameworks. We conclude with a discussion on the remaining challenges in the field and an outlook regarding future opportunities for designing high-performance plasmonic metal–semiconductor heterostructures for photochemistry.
Identifying risk factors and mortality of individuals with Alzheimer’s disease (AD) could have important implications for the clinical management of AD.
This pilot study aimed to examine the overall mortality of AD patients over a 10-year surveillance period in Shanghai, China. This study is an extension of our previous investigation on mortality of neurodegenerative diseases.
One hundred and thirty-two AD patients recruited from the memory clinics of two hospitals in Shanghai in 2007 were followed up until December 31, 2017 or death, representing a follow-up period of up to 10 years. Overall standardized mortality ratios (SMRs) were calculated, and predictors for survival at recruitment were estimated.
Sixty-seven patients had died by December 31, 2017, and the SMR at 10 years of follow-up was 1.225 (95% confidence interval 0.944–1.563). Employing Cox’s proportional hazard modeling, lower Mini-Mental State Examination score, and comorbid diabetes predicted poor survival in this cohort.
This pilot study suggests a similar survival trend of patients with AD compared to the general population in Shanghai urban region. Poor cognitive status and comorbid diabetes had a negative impact on the survival of AD patients.
Prior data on long-term association between legume consumption and hypertension risk are sparse. We aimed to evaluate whether total legume and subtype intakes prospectively associate with hypertension incidence among 8758 participants (≥30 years) from the China Health and Nutrition Survey 2004–2011. Diet was assessed by interviews combining 3-d 24-h food recalls and household food inventory weighing at each survey round. Incident hypertension was identified by self-reports or blood pressure measurements. We applied multivariable Cox regressions to estimate hazard ratios (HR) with corresponding 95 % CI for hypertension across increasing categories of cumulatively averaged legume intakes. For 35 990 person-years (median 6·0 years apiece), we documented 944 hypertension cases. After covariate adjustment, higher total legume intakes were significantly associated with lower hypertension risks, with HR comparing extreme categories being 0·56 (95 % CI 0·43, 0·71; Ptrend < 0·001). Then we found that intakes of dried legumes (HR 0·53 (95 % CI 0·43, 0·65); Ptrend < 0·001) and fresh legumes (HR 0·67 (95 % CI 0·55, 0·81); Ptrend < 0·001) were both related to decreased hypertension hazards. However, further dried legume classification revealed that negative association with hypertension substantially held for soyabean (HR 0·51 (95 % CI 0·41, 0·62); Ptrend < 0·001) but not non-soyabean intakes. In stratified analyses, the association of interest remained similar within strata by sex, BMI, physical activity, smoking and drinking status; rather, significant heterogeneity showed across age strata (Pinteraction = 0·02). Total legume consumption among the over-65s was related to a more markedly reduced hypertension risk (HR 0·47 (95 % CI 0·30, 0·73); Ptrend < 0·001). Our findings suggest an inverse association of all kinds of legume (except non-soyabean) intakes with hypertension risks.
Muscle fiber characteristics comprise a set of complex traits that influence the meat quality and lean meat production of livestock. However, the genetic and biological mechanisms regulating muscle fiber characteristics are largely unknown in pigs. Based on a genome-wide association study (GWAS) performed on 421 Large White × Min pig F2 individuals presenting well-characterized phenotypes, this work aimed to detect genome variations and candidate genes for five muscle fiber characteristics: percentage of type I fibers (FIB1P), percentage of type IIA fibers (FIB2AP), percentage of type IIB fibers (FIB2BP), diameter of muscle fibers (DIAMF) and number of muscle fibers per unit area (NUMMF). The GWAS used the Illumina Porcine SNP60K genotypic data, which were analyzed by a mixed model. Seven and 10 single nucleotide polymorphisms (SNPs) were significantly associated with DIAMF and NUMMF, respectively (P < 1.10E-06); no SNP was significantly associated with FIB1P, FIB2AP or FIB2B. For DIAMF, the significant SNPs on chromosome 4 were located in the previously reported quantitative trait loci (QTL) interval. Because the significant SNPs on chromosome 6 were not mapped in the previously reported QTL interval, a putative novel QTL was suggested for this locus. None of the previously reported QTL intervals on chromosomes 6 and 14 harbored significant SNPs for NUMMF; thus, new potential QTLs on these two chromosomes are suggested in the present work. The most significant SNPs associated with DIAMF (ALGA0025682) and NUMMF (MARC0046984) explained 12.02% and 11.59% of the phenotypic variation of these traits, respectively. In addition, both SNPs were validated as associated with DIAMF and NUMMF in Beijing Black pigs (P < 0.01). Some candidate genes or non-coding RNAs, such as solute carrier family 44 member 5 and miR-124a-1 for DIAMF, and coiled-coil serine rich protein 2 for NUMMF, were identified based on their close location to the significant SNPs. This study revealed some genome-wide association variants for muscle fiber characteristics, and it provides valuable information to discover the genetic mechanisms controlling these traits in pigs.
The effect of maternal folate intake on small-for-gestational-age (SGA) births remains inconclusive. The present study aimed to investigate the associations of maternal folate intake from diet and supplements with the risk of SGA births using data from a cross-sectional study in Shaanxi Province of Northwest China. A total of 7307 women who were within 12 months (median 3; 10th–90th percentile 0–7) after delivery were included. Two-level models were adopted to examine the associations of folate (dietary folate, supplemental folic acid and total folate) intake with the risk of SGA births and birth weight Z score, controlling for a minimum set of confounders that were identified in a directed acyclic graph. Results showed that a higher supplemental folic acid intake during the first trimester was negatively associated with the risk of SGA births (≤60 d v. non-use: OR 0·80; 95 % CI 0·66, 0·96; >60 d v. non-use: OR 0·78; 95 % CI 0·65, 0·94; Ptrend = 0·010; per 10-d increase: OR 0·97; 95 % CI 0·95, 0·99). A higher total folate intake during pregnancy was associated with a reduced risk of SGA births (highest tertile v. lowest tertile: OR 0·77; 95 % CI 0·64, 0·94; Ptrend = 0·010; per one-unit increase in the log-transformed value: OR 0·81; 95 % CI 0·69, 0·95). A similar pattern was observed for the birth weight Z score. Our study suggested that folic acid supplementation during the first trimester and a higher total folate intake during pregnancy were associated with a reduced risk of SGA births.