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Diabetic retinopathy (DR) is a prevalent vision-threatening disease worldwide. Laser marks are the scars left after panretinal photocoagulation, a treatment to prevent patients with severe DR from losing vision. In this study, we develop a deep learning algorithm based on the lightweight U-Net to segment laser marks from the color fundus photos, which could help indicate a stage or providing valuable auxiliary information for the care of DR patients. We prepared our training and testing data, manually annotated by trained and experienced graders from Image Reading Center, Zhongshan Ophthalmic Center, publicly available to fill the vacancy of public image datasets dedicated to the segmentation of laser marks. The lightweight U-Net, along with two postprocessing procedures, achieved an AUC of 0.9824, an optimal sensitivity of 94.16%, and an optimal specificity of 92.82% on the segmentation of laser marks in fundus photographs. With accurate segmentation and high numeric metrics, the lightweight U-Net method showed its reliable performance in automatically segmenting laser marks in fundus photographs, which could help the AI assist the diagnosis of DR in the severe stage.

Due to the increasing focus on green consumerism, sustainability disclosure—company informing its stakeholders of its involvement in sustainability—is an integral part of stakeholder management. Nevertheless, the sustainability reports published by container shipping companies exhibit unique structures and content. Existing sustainability disclosure frameworks are generic and do not cater to B2B industries, such as container shipping. Moreover, limited studies have been conducted to explore the sustainability disclosure framework of the container shipping industry. With a hierarchical unsupervised text-mining method, the latent information of major listed container shipping companies' sustainability reports has been explored. A unified framework is produced comprising three primary dimensions: employee training and management, sustainable business management, and sustainable shipping operation. Each primary dimension has three secondary sub-dimensions. Theoretically, this research uncovers themes and patterns on how container shipping companies disclose sustainability. Managerially, this research guides container shipping companies on preparing and organizing sustainability disclosure. For regulators, policymakers, and global investors, this research also provides implications on evaluating container shipping companies’ sustainability performance and serves as a benchmark against broader sustainability goals such as sustainable development goals (SDGs). Ministry of Education (MOE) This research is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (Project ID, RS03/19).

Antimicrobial peptides (AMPs) are conventional antibiotic alternatives due to their broad-spectrum antimicrobial activities and special mechanisms of action against pathogens. The antifungal peptide CGA-N12 was originally derived from human chromogranin A (CGA) and consists of the 65th to 76th amino acids of the CGA N-terminal region. In the present study, we found that CGA-N12 had fungicidal activity and exhibited time-dependent inhibition activity against Candida tropicalis. CGA-N12 entered the cells to exert its antagonist activity. The internalization of CGA-N12 was energy-dependent and accompanied by actin cytoskeleton-, clathrin-, sulfate proteoglycan-, endosome-, and lipid-depleting agent-mediated endocytosis. Moreover, the CGA-N12 internalization pathway was related to the peptide concentration. The effects of CGA-N12 on the cell membrane were investigated. CGA-N12 at a low concentration less than 4 × MIC100 did not destroy the cell membrane. While with increasing concentration, the damage to the cell membrane caused by CGA-N12 became more serious. At concentrations greater than 4 × MIC100, CGA-N12 destroyed the cell membrane integrity. Therefore, the membrane activity of CGA-N12 is concentration dependant.

Objective: Unbalanced glucagon and insulin secretion may contribute to glucose fluctuations and inadequate glucose control in type 2 diabetic patients. This study aimed to investigate the relationship between the glucagon-to-C-peptide ratio and glycemic control. Methods: From January 2017 to December 2018, a total of 1128 type 2 diabetic patients were recruited. The fasting and postprandial glucagon-to-C-peptide ratios were calculated following a 75-g oral glucose tolerance test (OGTT). Subjects were divided into quartiles based on their fasting and postprandial glucagon-to-C-peptide ratios. Statistical analysis was then carried out. Results: HbA1c levels were significantly and positively correlated with fasting (r = 0.333, p < 0.001) and postprandial glucagon-C-peptide-ratio (r = 0.373, p < 0.001). The proportion of patients with uncontrolled hyperglucose significantly increased from 76.2% to 83.0%, 89.4% and 94.7% from the first to second, third and fourth quartiles of the fasting glucagon-C-peptide ratio and increased from 73.4% to 80.9%, 93.3% and 95.7% from the first to second, third and fourth quartiles of the postprandial glucagon-C-peptide ratio, respectively. After adjusting for potential influences, the mean difference (95% CI) in HbA1c between the patients in the lowest and highest quartiles of the fasting glucagon-C-peptide ratio was 1.925 (1.512, 2.338) %, and the mean difference in HbA1c between the patients in the lowest andhighest quartiles of the prandial glucagon-C-peptide ratio was 2.401 (1.981, 2.820) %. After adjusting for possible metabolic risks by multiple logistic regression analysis, the corresponding odds ratios (ORs) for uncontrolled hyperglucose of the second, third and fourth quartiles versus the first quartile of fasting glucagon-C-peptide-ratiowere 1.331 (95% CI 0.829–2.136), 2.818 (1.647–4.823) and 7.268 (3.573–14.784), respectively. When compared with the first quartile of the postprandial glucagon-C-peptide ratio, the corresponding ORs for uncontrolled hyperglucose of the second, third and fourth quartiles were 1.752 (95% CI 1.100–2.793), 6.304 (3.348–11.560) and 15.998 (7.353–34.805), respectively. Conclusions: For type 2 diabetic patients, an increased glucagon-to-C-peptide ratio is associated with an increased risk of uncontrolled hyperglucose.

Best-subset selection aims to find a small subset of predictors, so that the resulting linear model is expected to have the most desirable prediction accuracy. It is not only important and imperative in regression analysis but also has far-reaching applications in every facet of research, including computer science and medicine. We introduce a polynomial algorithm, which, under mild conditions, solves the problem. This algorithm exploits the idea of sequencing and splicing to reach a stable solution in finite steps when the sparsity level of the model is fixed but unknown. We define an information criterion that helps the algorithm select the true sparsity level with a high probability. We show that when the algorithm produces a stable optimal solution, that solution is the oracle estimator of the true parameters with probability one. We also demonstrate the power of the algorithm in several numerical studies.

Paeonia ostii seeds were identified as novel sources of edible plant oil with a high proportion of α-linolenic acid, a type of n-3 fatty acid with many health benefits. Due to the unreliability of seed oil content and quality, it is necessary to discover the mechanism underlying lipid biosynthesis in Paeonia ostii seeds. This study aimed to identify the key genes involved in lipid biosynthesis in Paeonia ostii seeds by analyzing the relationship among the seed characteristics and the expression patterns of lipid genes in Paeonia ostii during seed development. Preliminary research on Paeonia ostii seed development was carried out from 10 days after pollination until maturity, focusing on phenology, oil content and lipid profiles. In addition, we investigated the spatiotemporal expression of 36 lipid biosynthetic genes in Paeonia ostii by using quantitative real-time PCR. The results suggested that the development of Paeonia ostii seeds from pollination to maturity could be divided into three periods. The 36 lipid genes showed various spatiotemporal expression patterns and five gene groups with distinct temporal patterns during seed development were identified by clustering analysis of expression data. Furthermore, the relationships between gene expression and lipid/fatty acid accumulation and some candidate key lipid genes were discussed. This study provided the global patterns of fatty acid and lipid biosynthesis-related gene expression, which are critical to understanding the molecular basis of lipid biosynthesis and identifying the lipid accumulation rate-limiting genes during seed development.

We studied a Surface-enhanced Raman scattering (SERs) film by self-assembled deposition of Ag nanoparticles on the surface of PPy@PEDOT:PSS films to detect melamine molecules. The PPy@PEDOT:PSS film was prepared using an electrochemical polymerization method in a mixture solution of PPy and PEDOT:PSS. Then, Ag nanoparticles were directly deposited on the surface of PPy@PEDOT:PSS films by a chemical self-assembly method as an active SERs substrate to detect melamine molecules. The results showed that the density of Ag nanoparticles on the surface of PPy@PEDOT:PSS film was gradually increased due to the increase of depositional time of Ag nanoparticles. Accordingly, The SERs effect was also substantially enhanced. The signal of melamine was increased up to 440 times. The melamine molecules at 6.4 ng/ml concentration could be clearly identified. This preparing method of SERs film and detecting method of melamine molecules provide a new strategy for the design and application of chemical sensors and bio-sensors.

Advancing nanocatalytic therapies of tumors formed on non-toxic but catalytically active inorganic nanoparticles (NPs) have aroused great interest in tumor therapy recently, but the limited reactive oxygen species within tumors may limit treatment efficiency. Therefore, the combination of chemotherapy and chemodynamic therapy is a promising treatment strategy. Herein, poly(lactic acid-co-glycolic acid) (PLGA) grafted-γ-Fe2O3 nanoparticles (NPPLGA) with dual response of endogenous peroxidase (POD)- and catalase (CAT)-like activities has been reported. On the one hand, the NPPLGA could serve as a drug delivery system for doxorubicin (DOX), an anti-tumor drug used to treat lung adenocarcinoma A549 cells. On the other hand, based on the mimetic enzyme properties of NPPLGA, it can be combined with DOX to treat lung cancer. The results show that the NPPLGA could be simulated the CAT-like activity to decompose hydrogen peroxide (H2O2) into H2O and O2 under neutral tumor microenvironment, so as to reduce the oxidative damage caused by H2O2 to lung adenocarcinoma A549 cells. Under acidic microenvironment, NPPLGA could simulate POD-like activity to effectively catalyze the decomposition of H2O2 to produce highly toxic hydroxyl radicals (•OH) to induce the death of tumor-cell through regular catalytic reaction of Fenton. Furthermore, the POD-like activity of NPPLGA synergistic with DOX can promote the apoptosis and destruction of A549 cells and enhance the antitumor impact of DOX-NPPLGA. Therefore, this study provides an efficacious dual inorganic biomimetic nanozyme-based nanoplatform for lung tumor treatment.

Arising from the global COVID-19 pandemic, social distancing has become the new norm that shapes consumers’ shopping and consumption activities. In response, the contactless channel (i.e., shopping online, self-collecting and returning parcels via delivery lockers) is ideally positioned to fulfil consumers’ shopping/logistics needs while avoiding all unnecessary social interactions. Thus, this study examines the factors that motivate consumers’ migration to the contactless channel by viewing consumers’ channel choice as both health-related and shopping behaviours. Anchored on the synthesised insights of protection motivation theory and automation acceptance theory, the conceptual framework and a series of hypotheses are proposed. A survey instrument is used for data collection, and the data are analysed using structural equation modelling. Our findings reveal that perceived channel characteristics such as compatibility and trust directly contribute to the relative value of the contactless channel; these characteristics are also correlated where trust perception reinforces compatibility perception. The channel characteristics are further influenced by consumers’ perceived susceptibility of COVID-19; that is, susceptibility perception enhances channel compatibility but decreases consumers’ trust in the contactless channel. However, the impacts of susceptibility become insignificant with a low level of severity perception, confirming the stage-based conceptualisation of severity. Furthermore, the severity perception of COVID-19 is found to amplify the positive impacts of susceptibility perception but attenuate its negative impact. Our study promotes a deeper integration between the health and service literature and encourages more interdisciplinary studies in this nexus. Considering the practical context of social distancing, our findings suggest a struggle between compatibility perception and trust concern that shapes consumers’ behaviours. Nanyang Technological University This study was funded by Nanyang Technological University, CEE internal seed fund (2019), which provided financial support for research manpower and data collection.

With the intensification of global warming, rice production is facing new challenges. Field evidence indicates increased temperature during rice grain-filling lead to a further deterioration of grain quality. Clarifying the potential regulation mechanism of elevated temperature on rice development and quality formation will be contributed to develop suitable cultivation measures to better cope with climate warming in the future. In this study, open field warming and DIA mass spectrometry were conducted to explore the regulatory effects of high temperature on pathways related to grain development and material accumulation during the formation of rice quality. 840 differentially expressed proteins (fold change > 2, p-value < 0.05) were identified when exposed to high temperature. Among these, prolamin PPROL 14E, PSB28, granule-bound starch synthase 1 and 26.7 kDa heat shock protein were the most significantly regulated, and that ultimately affected the main substances accumulation of starch and protein in the kernel, and further degraded rice quality under high temperature. In addition, the results provided novel targets involved in regulating the metabolism of storage compounds under warming environment, and that will help us to better understand the regulation mechanism of global warming on the formation of rice quality.

We introduce a new R package, BeSS, for solving the best subset selection problem in linear, logistic and Cox's proportional hazard (CoxPH) models. It utilizes a highly efficient active set algorithm based on primal and dual variables, and supports sequential and golden search strategies for best subset selection. We provide a C++ implementation of the algorithm using an Rcpp interface. We demonstrate through numerical experiments based on enormous simulation and real datasets that the new BeSS package has competitive performance compared to other R packages for best subset selection purposes.

Public acceptance of autonomous vehicles (AVs) is vital for a society to reap their intended benefits such as reduced traffic accidents, land usage, congestion and environmental pollution. The purpose of this paper is to use the theory of planned behaviour to pinpoint and examine the components affecting public acceptance of AVs. A model consisting of a network of hypothesised relationships is introduced. Thereafter, 526 residents in Seoul, Korea, were given a survey created for this research. Subsequently, to evaluate the collected information and estimate the model, structural equation modelling was adopted. The outcomes show individuals&rsquo, mindset on AVs, subjective customs, and behavioural influence directly influencing the acceptance of AVs. Furthermore, cognitive and emotive factors, namely comparative advantage, compatibility, complexity and hedonic motivation indirectly influence the acceptance of AVs via mindset and behavioural manipulation. Based on analysing the cumulative effect, attitude emerged with the strongest effect on public acceptance of autonomous vehicles. After this is, in decreasing order of influence, behavioural control, relative advantage, subjective norms, compatibility, hedonic motivation and complexity. The findings of this study implicate the prioritisation and allocation of resources, and policies relating to marketing, education, subsidisation and infrastructure development to better public acceptance of AVs.

The confirmed cases of novel coronavirus disease (COVID-19) have been reported in the United States since late January 2020. There were over 4.8 million confirmed cases and about 320,000 deaths as of May 19, 2020 in the world. We examined the characteristics of the confirmed cases and deaths of COVID-19 in all affected counties of the United States. We proposed a COVID-Net combining the architecture of both Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) by using the trajectories of COVID-19 during different periods until May 19, 2020, as the training data. The validation of the COVID-Net was performed by predicting the numbers of confirmed cases and deaths in subsequent 3-day, 5-day, and 7-day periods. The COVID-Net produced relatively smaller Mean Relative Errors (MREs) for the 10 counties with the most severe epidemic as of May 19, 2020. On average, MREs were 0.01 for the number of confirmed cases in all validation periods, and 0.01, 0.01, and 0.03 for the number of deaths in the 3-day, 5-day, and 7-day periods, respectively. The COVID-Net incorporated five risk factors of COVID-19 and was used to predict the trajectories of COVID-19 in Hudson County, New Jersey and New York County, New York until June 28, 2020. The risk factors include the percentage of the population with access to exercise opportunities, average daily PM2.5, population size, preventable hospitalization rate, and violent crime rate. The expected number of cumulative confirmed cases and deaths depends on the dynamics of these five risk factors. Significance Statement A COVID-Net model was built to predict the trajectories of COVID-19, based on the percentage of the population with access to exercise opportunities, average daily PM2.5, population size, preventable hospitalization rate and violent crime rate in the metropolises areas. The increasing awareness of how these risk factors affect the pandemic helps policymakers develop plans that mitigate the spread of COVID-19.

BackgroundThe number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States.MethodsTo find out the risk factors associated with county-level mortality of COVID-19 with various levels of prevalence, a negative binomial design was applied to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies.Results3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153,PConclusionsThe mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may lead to the reduction in the mortality of COVID-19.

In this study, a polysaccharide (CGP-BG) was successfully produced from waste distillers' grain by Chaetomium globosum CGMCC 6882. Chemical analysis demonstrated that CGP-BG contained 3.49 ± 0.51 % protein. The molecular weight of CGP-BG was 52.37 KDa, which was composed of rhamnose, arabinose, galactose, glucose, xylose, mannose, galacturonic acid, and glucuronic acid in the molar ratio of 4.11:7.34:13.31:20.99:1.07:0.91:4.75:0.36. In vitro assay showed that CGP-BG had scavenging activities on hydroxyl radical, DPPH radical, superoxide anion, and ABTS radical in a dose-dependent manner. Meanwhile, CGP-BG significantly inhibited nitric oxide and pro-inflammatory cytokine (TNF-α, IL-6, and IL-1β) production in the lipopolysaccharide (LPS)-induced RAW 264.7 cells. Moreover, CGP-BG notably improved the antioxidant status of LPS-treated macrophages by enhancing superoxide dismutase, glutathione peroxidase, and antioxidant capacity and mitigating malondialdehyde. This work provided the basis for the application of CGP-BG as an anti-inflammatory and antioxidant agent.

The United States has the highest number of confirmed cases of COVID-19 in the world. The early hot spot states were New York, New Jersey, and Connecticut. The workforce in these states was required to work from home except for essential services. It was necessary to evaluate an appropriate date for resumption of business since the premature reopening of the economy would lead to a broader spread of COVID-19, while the opposite situation would cause greater loss of economy. To reflect the real-time risk of the spread of COVID-19, it was crucial to evaluate the population of infected individuals before or never being confirmed due to the pre-symptomatic and asymptomatic transmissions of COVID-19. To this end, we proposed an epidemic model and applied it to evaluate the real-time risk of epidemic for the states of New York, New Jersey, and Connecticut. We used California as the benchmark state because California began a phased reopening on May 8, 2020. The dates on which the estimated numbers of unidentified infectious individuals per 100,000 for states of New York, New Jersey, and Connecticut were close to those in California on May 8, 2020, were June 1, 22, and 22, 2020, respectively. By the practice in California, New York, New Jersey, and Connecticut might consider reopening their business. Meanwhile, according to our simulation models, to prevent the resurgence of infections after reopening the economy, it would be crucial to maintain sufficient measures to limit the social distance after the resumption of businesses. This precaution turned out to be critical as the situation in California quickly deteriorated after our analysis was completed and its interventions after the reopening of business were not as effective as those in New York, New Jersey, and Connecticut.

The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and societal importance to evaluate the effects of interventions in the pandemic of COVID-19. In this paper, with help of synthetic control method, regression discontinuity and a Susceptible-Infected and infectious without isolation-Hospitalized in isolation-Removed (SIHR) model, we evaluate the horizontal and longitudinal effects of stringent interventions implemented in Wenzhou, a representative urban city of China, where stringent interventions were enforced to curb its own epidemic situation with rapidly increasing newly confirmed cases. We found that there were statistically significant treatment effects of those stringent interventions which reduced the cumulative confirmed cases of COVID-19. Those reduction effects would increase over time. Also, if the stringent interventions were delayed by 2 days or mild interventions were implemented instead, the expected number of cumulative confirmed cases would have been nearly 2 times or 5 times of the actual number. The effects of stringent interventions are significant in mitigating the epidemic situation of COVID-19. The slower the interventions were implemented, the more severe the epidemic would have been, and the stronger the interventions would have been required., 29 pages, 6 figures, Ting Tian, Wenxiang Luo and Yukang Jiang contributed equally to this article

Objectives Since February 2020, COVID-19 has spread rapidly to more than 200 countries in the world. During the pandemic, local governments in China implemented different interventions to efficiently control the spread of the epidemic. Characterizing transmission of COVID-19 under some typical interventions is to help countries develop appropriate interventions. Methods We established compartmental model that allowed the number of infected and infectious to be unknown and the effective reproduction number to change over time, thus the effects of policies could be reasonably reflected and estimated. By using the epidemic data of three representative cities of China (Wuhan, Wenzhou and Shenzhen), we migrated the estimated policy modes to other countries. Results The smallest expected cumulative confirmed cases under different interventions would be 5936 with 95% CI (5012,6966) for South Korea, 146012 with 95% CI (140504, 154264) for Italy, and 400642 with 95% CI (390331,409431) for the United States until May 31, 2020, respectively. Conclusions Based on the simulation of epidemic in South Korea, Italy and the United States, it is reasonable that South Korea and Italy continue to maintain their current policies, while the implementation of interventions of Wenzhou may significantly decrease the magnitude of the outbreak of COVID-19 for the United States.

Oyster (Crassostrea talienwhanensis) protein was hydrolyzed by trypsin to produce peptides with different response values, and response surface methodology (RSM) was applied to optimize the hydrolysis conditions. The highest degree of hydrolysis (DH) of the oyster peptide (OP) was obtained at an enzyme concentration of 1593.2 U/g, a pH of 8.2, a hydrolysis temperature of 40.1 °C, a hydrolysis time of 6.0 h, and a water/material ratio of 8.2. The greatest hydroxyl-radical-scavenging activity of OP was obtained at an enzyme concentration of 1546.3 U/g, a pH of 9.0, a hydrolysis temperature of 50.2 °C, a hydrolysis time of 5.1 h, and a water/material ratio of 5.6. The largest branched-chain amino acid (BCAA) content of OP was obtained at an enzyme concentration of 1323.8 U/g, a pH of 8.3, a hydrolysis temperature of 41.7 °C, a hydrolysis time of 6.7 h, and a water/material ratio of 4.8. The three experimental values were significantly in agreement with the predicted values within the 95% confidence interval. Furthermore, ultrafiltration and chromatographic methods were used to purify the OP, and 13 peptides that were rich in Lys, Arg, His, and Thr were identified by LC-MS/MS. The results of this study offer different optimum hydrolysis conditions to produce target peptides from oyster protein by using RSM, and this study provide a theoretical basis for the high-value utilization of oyster protein.

In this paper, we consider the initial boundary value problem for generalized Zakharov equations. Firstly, we prove the existence and uniqueness of the global smooth solution to the problem by a priori integral estimates, the Galerkin method, and compactness theory. Furthermore, we discuss the approximation limit of the global solution when the coefficient of the strong nonlinear term tends to zero.

BackgroundSome recent studies examined the effect of ambient particulate matter (PM) pollution on depression and suicide. However, the results have been inconclusive.AimsTo determine the overall relationship between PM exposure and depression/suicide in the general population.MethodWe conducted a systematic review and meta-analysis of case-crossover and cohort studies to assess the association between PM2.5 (particles with an aerodynamic diameter of 2.5 µm or less) or PM10 (particles with an aerodynamic diameter between 2.5 and 10 µm) exposure and depression/suicide.ResultsA total of 14 articles (7 for depression and 7 for suicide) with data from 684 859 participants were included in the meta-analysis. With a 10 µg/m3 increase in PM2.5 we found a 19% (odds ratio [95% CI] 1.19 [1.07, 1.33]) increased risk of depression and a marginally increased risk of suicide (odds ratio [95% CI] 1.05 [0.99, 1.11]) in the general population. We did not observe any significant associations between increasing exposure to PM10 and depression/suicide. Sensitivity and subgroup analyses were used to determine the robustness of results. The strongest estimated effect of depression associated with PM2.5 appeared in a long-term lag pattern (odds ratio [95% CI] 1.25 [1.07, 1.45], P < 0.01) and cumulative lag pattern (odds ratio [95% CI] 1.26 [1.07, 1.48], P < 0.01).ConclusionsThe meta-analysis suggested that an increase in ambient PM2.5 concentration was strongly associated with increased depression risk in the general population, and the association appeared stronger at long-term lag and cumulative lag patterns, suggesting a potential cumulative exposure effect over time.Declaration of interestNone.

Creating adsorptive materials for the fast, efficient, and high-throughput adsorption and purification of proteins is critical to meet the great demands for highly purified proteins, yet it has proven to be a highly challenging task. Here, we report that cross-linked and highly carboxylated poly(vinyl alcohol) (PVA) nanofibrous membranes were fabricated by a combination of electrospinning and the in situ graft polymerization of PVA and maleic anhydride (MAH) under mild conditions. Taking advantage of the large surface area available for protein binding, the highly tortuous porous structure, and the robust mechanical properties, the resultant PVA/MAH nanofibrous membranes exhibited a good integrated adsorption performance towards lysozyme, including a superior adsorption capacity of 177 mg g-1, fast adsorption equilibrium within 4 h, good selectivity, and good reversibility. Moreover, the saturation dynamic adsorption amount towards lysozyme reached 159 mg g-1 under 750 Pa driven solely by gravity, which conformed to the specified requirements for high adsorption capacity under relatively low pressure drops. Furthermore, the adsorption performance towards a protein mixture was analyzed by sodium dodecyl sulphate-polyacrylamide gel electrophoresis and the resultant PVA/MAH nanofibrous membranes retained excellent stability under depyrogenation conditions. The successful fabrication of such fascinating nanofibrous materials by using this simple and intriguing approach may provide new insights into the design and development of adsorptive materials for the purification of proteins with superior adsorption performance.

Vascular smooth muscle cell (VSMC) phenotypic switching is a hallmark of vascular remodeling that contributes to atherosclerotic diseases. MicroRNA 4463 (miR-4463) has been implicated in the development of arteriosclerosis obliterans, whereas the underlying mechanisms in VSMCs have not been fully addressed. In this study, we assessed whether miR-4463 is involved in the phenotypic switching process in VSMCs. Oxidized low-density lipoprotein (Ox-LDL, 50 mg/L) was used to simulate the oxidative stress condition, and miR-4463 expression in VSMCs was detected by a quantitative polymerase chain reaction. To determine the effect of Ox-LDL-mediated regulation of miR-4463 on the phenotypic switching of VSMCs, cell counting kit-8, cell migration assays, and cytoskeleton test were performed. After using specific antagonists of c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK), the relationship between miR-4463 and its downstream signaling proteins was explored. Ox-LDL induced oxidative stress to promote VSMC transformation from contraction to secretion, which clearly decreased the level of miR-4463. Then, downregulated miR-4463 enhanced the migration and phenotypic transformation of VSMCs and activated the phosphorylation of JNK and ERK; these effects were increased after Ox-LDL induction. As expected, inhibiting the two signaling proteins blocked the effect of the miR-4463 inhibitor combined with Ox-LDL. In addition, inhibition of miR-4463 led to the upregulation of basic fibroblast growth factor (bFGF) expression. The results of this study demonstrate that miR-4463 is a novel regulator of VSMC function in hypoxic conditions and modulates VSMC phenotypic switching via the JNK and ERK signaling pathways; bFGF may be the target gene of miR-4463.

The selection of airport is an important consideration for low-cost carriers (LCCs) to remain cost competitive. The objective of this study is to identify and rank the airport selection criteria of LCCs. Based on reviewing the existing literature, five main factors comprising 16 sub-factors were developed. The factors were first validated by three industry experts from the aviation industry. Thereafter, a survey questionnaire requiring a comparison of the factors was administered on 28 executives who were involved in the strategy planning and formulation of LCCs based in China or Korea. The collected data were analysed using fuzzy analytical hierarchy process (FAHP). In descending order of their importance, the main factors influencing LCCs' selection of airport are (1) airport charges, (2) airport performance, (3) airport growth opportunities, (4) catchment area and (5) airport infrastructure. The top three sub-factors are airport costs, demand for LCC services and passenger throughput. The research contributes to academic research by providing a holistic assessment of the key considerations influencing LCCs' selection of airport. In addition, it implicates policy formulation of LCCs by providing a framework for assessment of airports that are suitable for LCCs’ operations.

GCP, a polysaccharide produced by endophytic fungus Chaetomium globosum CGMCC 6882, was found to be antibacterial against Staphylococcus aureus via disrupting cell permeability. However, the antibacterial mechanism of GCP has not been studied before. In present work, results showed that GCP could retard the growth of S. aureus by inducing the depolarization of cell membrane, decreasing the activity of Ca2+-Mg2+-ATPase on cell membrane, and increasing the accumulation of calcium ions in cytoplasm. Moreover, we found that GCP could also inhibit the synthesis of whole cell proteins of S. aureus. Overall, this study proved that the antibacterial mechanism of GCP could be diversified and more studies are needed in the investigation of the antibacterial mechanisms of various polysaccharides.

Summary A full understanding of the developmental process requires fine-scale characterization of cell divisions and cell types, which are naturally organized as the developmental cell lineage tree (CLT). Technological breakthroughs facilitated determination of more CLTs, but complete comprehension of the data remains difficult without quantitative comparison among CLTs. We hereby quantified phenotypic similarity between CLTs using a novel computational method that exhaustively searches for optimal correspondence between individual cells meanwhile retaining their topological relationships. The revealed CLT similarities allowed us to infer functional similarity at the transcriptome level, identify cell fate transformations, predict functional relationships between mutants, and find evolutionary correspondence between cell types of different species. By allowing quantitative comparison between CLTs, our work is expected to greatly enhance the interpretability of relevant data and help answer the myriad of questions surrounding the developmental process., Graphical Abstract, Highlights • Align cell lineage trees (CLTs) to search/quantify their phenotypic similarities • Aligning worm CLTs captured known genetic/developmental programs • Similarities between knockdown CLTs revealed functional relationships between genes • CLT alignments between species gave insight on the evolution of cell types, Cell Biology; Developmental Biology; Bioinformatics

Previously, an antioxidant xanthan-oligosaccharide (LW-XG) was successfully produced via bio-degradation of commercial xanthan. In present work, the antibacterial activity and mechanism action of LW-XG against Staphylococcus aureus were studied. Inhibition zone of LW-XG in agar diffusion test was evident and its minimal inhibitory concentration (MIC) against S. aureus was 0.63 mg/mL. Inhibitory mechanism investigation showed that LW-XG increased the cell membrane permeability of S. aureus. Meanwhile, we found that LW-XG could retard the formation of S. aureus biofilm and lower the transcriptional levels of genes (fnbA, fnbB and clfB) related to biofilm formation. Furthermore, LW-XG decreased the Ca2+-Mg2+-ATPase activity on S. aureus cell membrane and promoted the accumulation of calcium ions in cytoplasm. Overall, LW-XG could inhibit the growth of S. aureus and be regarded as a promising antibacterial substitute in food and pharmaceutical industries.

Polo-like kinase 4 (PLK4), a member of the polo-like kinase family, plays several important roles in mitotic regulation, including centrosome duplication, spindle formation, and cytokinesis. PLK4 overexpression is frequently detected in many human cancers, including ovarian cancer, and the inhibition of PLK4 activity results in cancer cell mitotic arrest and apoptosis. Therefore, PLK4 might be a valid therapeutic target for antitumor therapy. In the present study, we aimed to determine if YLZ-F5, a potent small-molecule inhibitor of PLK4, inhibits ovarian cancer cell growth. MTT assay showed that YLZ-F5 inhibited ovarian cancer cell proliferation in a concentration- and time-dependent manner. The results of colony formation assays were consistent with those of the MTT assay results. In addition, YLZ-F5 induced ovarian cancer cell apoptosis that was associated with activation of caspase-3/caspase-9. Moreover, YLZ-F5 caused aberrant in centriole duplication that was associated with the inhibition of PLK4 phosphorylation. Notably, we showed that YLZ-F5 promoted the accumulation of ovarian cancer cells with mitotic defects (> 4 N DNA content) in a concentration-dependent manner. Furthermore, YLZ-F5 markedly inhibited the migration of A2780 cells. Taken together, these findings suggest that YLZ-F5 is a potential drug candidate for human ovarian cancer.

Attributed to the recent COVID-19 pandemic, panic buying is now a frequent occurrence in many countries, leading to stockouts and supply chain disruptions. Consequently, it has received much attention from academics and the retail industry. The aim of this study is to review, identify, and synthesise the psychological causes of panic buying, which is a relatively new and unexplored area in consumer behaviour research. A systematic review of the related literature is conducted. The review suggests that panic buying is influenced by (1) individuals’ perception of the threat of the health crisis and scarcity of products; (2) fear of the unknown, which is caused by negative emotions and uncertainty; (3) coping behaviour, which views panic buying as a venue to relieve anxiety and regain control over the crisis; and (4) social psychological factors, which account for the influence of the social network of an individual. This study contributes to the literature by consolidating the scarce and scattered research on the causes of panic buying, drawing greater theoretical insights into each cause and also offers some implications for health professionals, policy makers, and retailers on implementing appropriate policies and strategies to manage panic buying. Recommendations for future research are also provided. Nanyang Technological University Published version This research was funded by Nanyang Technological University, Internal Funding, Start-Up Grant, College of Engineering.

China's Belt and Road Initiative (BRI) has attracted much attention in the field of transportation research. With a primary goal to improve regional and global connectivity, the initiative proposes a massive development programme of transportation infrastructure (TI) linking China with the rest of the world. While it creates a tremendous development opportunity, the unprecedented scale of TI construction also brings various challenges. In particular, the environmental impacts of the TI projects are of critical concern. Herein, smooth implementation of the TI projects would depend on the capacity of all the concerned actors to conduct collaborative planning and integrate environmental considerations. Therefore, from a multi-actor perspective, this paper aims to provide a unified framework of the environmental governance of the TI projects under the BRI. The goal is achieved through a focused review of relevant research articles and technical reports published in both English and Chinese. Based on the review findings, the framework along with four propositions are derived, focusing on the key actors (who), the environmental considerations (what) and the governance structures (how). The study concludes with theoretical and managerial implications. Accepted version

Purpose Public transport plays a crucial role in the movement of people. With the growing demand for public transport, the safety of public transport becomes a pertinent issue. Although collisions caused by drivers have been extensively investigated, passengers' safety behaviour is largely ignored. This study examines the determinants of passengers' safety behaviour on public transport. Method This study integrates Health Belief Model and Awareness-Interest-Desire-Action Model into theory of planned behaviour to examine the determinants of passengers’ safety behaviour on public transport. Survey data are collected from 342 passengers in Dalian, China, and structural equation modelling is employed for data analysis. Findings Results reveal that passengers' safety behaviour is positively influenced by their safety awareness, which is further determined by their attitude, subjective norms and perceived behavioural control. Furthermore, the relationship between safety awareness and safety behaviour is partially mediated by passengers' perceived threat (severity and susceptibility) of risky behaviour. Regarding the total effects, safety awareness is the strongest predictor of passengers' safety behaviour, followed by perceived behavioural control, perceived severity, perceived susceptibility, attitude and subjective norms. Practical implications By promoting passengers' safety behaviour, our research creates implications on safety education and communication to enhance road safety. Practical insights are discussed in relation to the transport planners and regulators, and general public.

Background: The outbreak of novel coronavirus disease (COVID-19) has spread around the world since it was detected in December 2019. The Chinese government executed a series of interventions to curb the pandemic. The "battle" against COVID-19 in Shenzhen, China is valuable because populated industrial cities are the epic centers of COVID-19 in many regions. Methods: We used synthetic control methods to compare the spread of COVID-19 between Shenzhen and its counterpart counties that didn't implement interventions for the total duration of 16 days starting from the day of the first reported case in compared locations. The hypothetical epidemic situations in Shenzhen were inferred by using time-varying reproduction numbers, assuming the interventions were delayed by 0 day to 5 days. Findings: The expected cumulative confirmed cases would be 1307, is which 4.86 times of 269 observed cumulative confirmed cases in Shenzhen on February 3, 2020, based on the data from the counterpart counties (mainly from Broward, New York, Santa Clara, Westchester and Orange) in the United States. If the interventions were delayed 5 days from the day when the interventions started, the expected cumulative confirmed cases of COVID-19 in Shenzhen on February 3, 2020 would be 676 with 95% CI (303,1959). Interpretation: Early implementation of mild interventions can subdue the epidemic of COVID-19. The later the interventions were implemented, the more severe the epidemic was in the hard-hit areas. Mild interventions are less damaging to the society but can be effective when implemented early. Funding: No funding applicable Declaration of Interests: Authors declare no competing interests.

Styrene was added dropwise to graphene dispersion solution by Pickering emulsion method to fabricate polystyrene @ graphene oxide layered composite microspheres (Pst@GO) for the removal of dye pollutants from water solution. Field emission scanning electron microscope, transmission electron microscopy, energy dispersive spectrometer, Brunauer emmett teller, zeta potential analyser and Fourier transform infrared spectrometer were adopted to analyse the changes in the microstructure and functional group of Pst@GO before and after the adsorption. The effects of initial concentration, adsorbent dose, pH, adsorption temperature and time on the adsorption behaviour of RhB and MB onto Pst@GO were studied by batch experiments. The results showed that a lot of folds on the surface of Pst@GO were beneficial to improve its adsorption capacity. The maximum adsorption capacity of RhB and MB onto Pst@GO was 49.70 and 59.07 mg g−1 at the initial concentration of 300 mg L−1, dose 0.1 g, pH = 7.0, adsorption temperature 55°C, adsorption time 2 h. The adsorption kinetics and thermodynamics analysis indicated that the adsorption of two dyes onto Pst@GO was endothermic reaction, while electrostatic attraction and hydrogen bonding are the main driving forces for the adsorption reaction. Polystyrene @ graphene oxide layered composite microspheres (Pst@GO) were prepared by Pickering emulsion method to remove dye pollutants in water. The preparation process of Pst@GO is as follows: Figure 1 Schematic fabrication process of Pst@GO.

Multidrug resistance (MDR) is a major challenge in successful chemotherapy treatment of ovarian cancer patients, and 50%–75% of ovarian cancer patients eventually relapse because of MDR. One of an effective strategy for treating MDR and improving therapeutic efficiency of ovarian cancer is to use nanotechnology-based targeted drug delivery systems. This study developed a novel hyaluronic acid (HA)-targeted co-delivery nanosystem using functionalized mesoporous silica nanoparticle–coated gold nanorods (HA-PTX/let-7a-GNR@MSN) to co-deliver paclitaxel (PTX), a hydrophobic chemotherapy drug, and lethal-7a (let-7a), a microRNA (miR), to overcome MDR in ovarian cancer. We also analyzed the molecular mechanism of miR let-7a in ovarian cancer treatment. The nanosystem enabled protective drug delivery and stable binding of PTX and miRs. Analysis of drug-resistant SKOV3TR cells and an SKOV3TR xenograft model in BALB/c-nude mice showed significant P-glycoprotein downregulation in heterogeneous tumor sites, PTX release, and apoptosis induction later. Results showed that HA-modified nanocomposites can specifically bind to the CD44 receptor, which is highly expressed in SKOV3/SKOV3 TR cells, achieving effective cell uptake and 150% enhancement of tumor site permeability. More importantly, this nanosystem resulted in synergistic inhibition of ovarian tumor growth. Overall, the data provide a model for overcoming PTX resistance in ovarian cancer.

The stochastic strongly dissipative Zakharov equations with white noise are studied. On the basis of the time uniform a priori estimates, we prove the existence and uniqueness of solutions in energy spaces E1 and E2, by using the standard Galerkin approximation method of stochastic partial differential equations.

With the rapid growth of e-commerce and technology-based self-services, consumers are increasingly encouraged to co-create individualised self-collection services. This study aims to conceptualise the multiple key facets of self-collection as viewed from consumers' perspectives and identify the latent consumer segments of the service. A total of 603 valid responses are collected, and the data are analysed using the latent class analysis. Adopting the paradigm of value co-creation, we conceptualised the self-collection service as service innovation, an empowerment tool, a green initiative and a value-based experience. Based on the conceptualisation, five latent segments of the service are identified, which are labelled as Patrons, Traditionalists, Self-enhancers, Green-lovers and Haters (from the largest to the smallest segment). By doing this, this study contributes to the literature by demonstrating the heterogeneity in consumers' participation patterns of value co-creation in e-commerce last-mile logistics. This work is supported by the Social Science Foundation of Zhejiang Province (No. 17NDJC194YB).

A type of Christiansen filter that takes the form of a smooth cylindrical lens of even symmetry is proposed. By varying the shape of the lens, the filter can be made to realize many common filtering responses, including the polynomial function response, the Gaussian function response, and the sinc function response. A systematic design technique based on inverse scattering is established, and a desired, prescribed response can be tailored by properly shaping the lens of the filter. Three prototypical Christiansen filters, namely, a second-order all-real-roots filter, a second-order sinc filter, and a Gaussian filter, are synthesized using the proposed method. A prescribed response at 545 nm with a FWHM of 2 nm is achieved systematically by all of the three Christiansen filters.

Graphene is a very attractive 2D carbon material, while the synthesis route of functional graphene is complex and complicated. The purpose of this study is to develop Co/N co-doped grapheme catalyst for ORR.Herein, a facile and universal pyrolysis method to explore the preparation of Co-N co-doped graphene through thermal exfoliation of 3D Co0.5Zn0.5-ZIF metal-organic framework by dimension reduction, and study the specific changes during process of dimensionality reduction, aiming at contributing to the transformation mode of 3D materials into 2D materials. The results showed that LiCl and KCl play different roles, namely the building carbon layer, pore-creating and exfoliation and acted simultaneously when they are added. A unique ultrathin 2D morphology of Co/N co-doped graphene, pores formed with the volatilization of zinc ions, and the appearance of abundant Co-N x active sites, which endow efficient catalytic activity of oxygen reduction reaction (ORR) in the alkaline electrolyte. Co/N-Go-Li/K-800 possesses the superior ORR activity among Co/N-Go-Li/K-T with an onset potential (0.15 V vs Ag/AgCl) and higher limiting current density(J@−0.8 V vs Ag/AgCl) (−5.20 mA·cm−2) closer to Pt/C (0.17 V vs Ag/AgCl and −5.86 mA·cm−2).

Panic buying behaviour is inherently undesirable due to its detrimental impact on community's resources and disruptions to supply chain systems. The prevailing COVID-19 pandemic has seen a resurgence of this phenomenon across the world, leaving supermarkets in stockout situations. While panic buying is largely reasoned as a psychological reaction to an extreme event, it is also a socially relevant behaviour as our perception of a crisis can be shaped by our observations and interactions within the society. The social determinants of panic buying behaviour, particularly on how these factors heighten one's perception of scarcity, and trigger panic buying behaviour, are studied. A theoretical model is developed to explain panic buying behaviour in a social context by synthesizing various social and behavioural theories, and the inter-relationship among the latent constructs is analysed using the structural equation modelling approach. Accordingly, an online survey was administered and analysis of the data confirmed that non-coercive social influence, social norm and observational learning directly influence one's perception of scarcity. Additionally, perceived scarcity can motivate panic buying behaviour directly or indirectly through feelings of anticipated regret. This study has contributed to the limited literature on panic buying. Understanding the underlying mechanisms of panic buying will aid policymakers and businesses in developing intervention or support strategies to cope with such behaviour.

The theory of audit pricing suggests that audit fees are positively associated with areas of higher inherent risk. Inventory is commonly cited as one such area, and many Western studies have reported a positive association between inventory and audit fees. However, most Chinese studies have reported a significant negative association. This study finds that this puzzling association is attributable to Chinese auditors charging a significant discount on the opening balance of inventory, whereas their U.S. counterparts charge a significant premium. Meanwhile, we show that opening-balance inventory is associated with higher inherent risk both in China and the U.S. On the other hand, both Chinese and U.S. auditors charge a significant discount on the net increase in inventory as of the current year end, and we show that this is associated with lower inherent risk. Therefore, Chinese auditors appear to underreact to the inherent risk associated with opening-balance inventory, which helps explain the puzzling negative association between inventory and audit fees in China.

It is traditionally believed that robustness is obtained by sacrificing efficiency. Estimators with high breakdown point and high efficiency are therefore highly desirable. We investigate a new estimation procedure based on Huber’s robust approach, but with tail functions replaced by the exponential squared loss. The tuning parameters are data-dependent to achieve high efficiency even in nonnormal cases. In the regression framework, we show that our hybrid estimator is of high efficiency, reaching the highest asymptotic breakdown point of 50%. We have also established the n−−√-consistency and asymptotic normality of our estimator under regularity conditions. Extensive numerical studies are carried out to compare the performances of our method and other existing methods in terms of the standard errors and relative efficiency, and the results reveal that the newly proposed method has smaller standard errors and higher relative efficiency than its competitors when the sample size is sufficiently large. Finally, we present three real examples for demonstration. Supplementary materials for the article are available online.

Depth functions have many applications in multivariate data analysis, including discriminant analysis and classification. In this paper, we introduce a novel class of data depth: exponential power depth (EPD) functions. Under some conditions, we show that the EPD functions are a statistical depth function, and the sample EPD functions are consistent and asymptotically normal. Based on the proposed EPD functions, we construct a DD-plot (depth-versus-depth plot), which can be applied to the classification problem. Since the EPD functions contain the two tuning parameters, we provide a data-driven approach to select these tuning parameters. The simulation studies and two real data analysis are conducted to assess the finite sample performance of the proposed method.

Fungal polysaccharides are mainly taken orally, so it is very important to study the absorption mechanism of which in vivo for understanding its biological activities. In this work, a polysaccharide fraction (GLP) was purified from G. lucidum by water extraction and alcohol precipitation. Physicochemical characterization indicated that GLP had a molecular weight of 108 kDa and consisted of glucose (35.56%), xylose (40.11%), rhamnose (16.45%) and l -arabinose (7.88%) in a molar radio of 4.51: 5.09: 2.88: 1.0. GLP was taken by Caco-2 cells through the pathway of macropinocytosis and it was a well-absorbed biological macromolecule testified by Papp value. Sugar transporters (SGLT1 and GLUT2) played different roles at different absorption stages of GLP, and the absorption of GLP during digestion in mice model was a time-dependent process. All these results could contribute to explore the absorption mechanism of polysaccharides in body.