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Highlights Lightweight dual-functional segregated nanocomposite foams are developed via the supercritical CO2 (SC-CO2) foaming combined with hydrogen bonding assembly and compression molding strategy The segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity. Excellent absorption-dominant electromagnetic interference shielding performances are achieved owing to the synchronous construction of microcellular structures and segregated structures

Traditional methods for evaluating the bioconversion capacity of organic solid waste are known for time-consuming property and often exhibit low prediction accuracy. However, leveraging fractal dimensions offers a more precise characterization of the complexity, irregularity, and spatial structure of organic solid waste. In this study, a novel and efficient method for evaluating the bio-accessibility of straw's anaerobic transformation, based on fractal dimensions, was introduced. To comprehensively compare the structural differences, this research encompasses the measurement of nine different varieties of straw under ten distinct pretreatment conditions. The regression sum of squares for these correlations consistently exceeds 0.83, highlighting the robustness of our findings. The results unequivocally demonstrate the close relationship between the fractal dimension and the structural characteristics of straw. This relationship underscores the utility of fractal dimension analysis as a reliable tool for evaluating the anaerobic bio-accessibility of organic solid waste.

In today’s power systems operation, the dual challenge of optimizing economic load distribution while minimizing power plant emissions is pivotal. This challenge is accentuated by the pressing environmental concerns and the finite nature of fossil fuel reserves. In this context, renewable energy sources, notably wind power, have emerged as indispensable alternatives due to their cost-effectiveness and environmental compatibility. However, the inherent variability of wind velocity introduces uncertainty into power output, necessitating innovative approaches to address this complexity. To tackle this issue, we propose a scenario-based probabilistic approach that dynamically considers the slope rate of power output. By leveraging the Blue Whale multi-objective algorithm and employing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) criterion, we identify significant solutions from the Pareto set across a spectrum of scenarios. Our method is rigorously evaluated across various systems and operational contexts, revealing its superiority over alternative algorithms. Specifically, our approach achieves lower objective function values, reduced standard deviation, and superior overall performance. These findings underscore the critical importance of efficient power system management in balancing environmental sustainability and economic viability. By embracing innovative methodologies, we can navigate the evolving energy landscape and contribute towards a more sustainable future.

In the present study, we investigated whether baicalin could reduce the damage caused to RAW264.7 cells following infection with H6N6 avian influenza virus. In addition, we studied the expression of autophagy-related genes. The morphological changes in cells were observed by hematoxylin and eosin (H&E) staining, and the inflammatory factors in the cell supernatant were detected by enzyme-linked immunosorbent assay (ELISA). Transmission electron microscopy (TEM) was used to detect the levels of RAW264.7 autophagosomes, and western blotting and immunofluorescence were used to detect the protein expression of autophagy marker LC3. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) was used to detect the mRNA transcription levels of autophagy key factors. The results showed that different doses of baicalin significantly reduced the H6N6 virus-induced damage of RAW264.7 cells. The contents of interleukin (IL)-1β, IL-2, IL-6, and tumor necrosis factor (TNF)-α in the cell supernatant significantly decreased. In addition, the protein expression of LC3 and Beclin-1, ATG12, ATG5 the mRNA levels were significantly decreased. This study showed that baicalin can reduce cell damage and affect the H6N6-induced autophagy level of RAW264.7 cells.

Highlights Comprehensive insights into Prussian blue analogs for aqueous sodium- and potassium-ion batteries. Unveiling the dissolution mechanism of transition metal ions in Prussian blue analogs. Innovative solutions to suppression transition metal ion dissolution, spanning electrolyte engineering, transition metal doping/substitution, minimize defects, and composite materials.

[Objective] To address the tram issues of needing speed deceleration at grade crossings, a vehicle-road cooperative speed control system for trams passing at grade crossings is proposed. [Method] The operational characteristics of tram at grade crossings are analyzed. The design concept of the vehicle-road cooperative speed control system for trams passing at grade crossings is introduced, along with the realization process of logic algorithm module. The implementation effects of the proposed control system are analyzed. [Result & Conclusion] The proposed control system uses vehicle positioning technology and clearance area conflict detection technology, combining communication with the intersection traffic signal to determine the method of tram passing through the crossing. When the tram obtains the right of way and the clearance area has no conflicts, a controllable physical isolation facility is temporarily adopted to create an exclusive closed interval for the tram, ensuring efficient and safe passage at the grade crossing. The proposed control system can realize tram passing intersection under green light condition without deceleration, and is well suited for non-platform grade crossings with a distance of over 250 meters between the front and rear platforms, as it can increase operating speed by approximately 15% and reduce interval operating energy consumption by 40%, while also reducing random deviations in inter-station travel time caused by grade crossing interference.

Abstract Background The available evidence regarding the association of antioxidants, minerals, and vitamins with the risk of metabolic syndrome (MetS) traits is currently limited and inconsistent. Therefore, the purpose of this Mendelian randomization (MR) study was to investigate the potential causal relationship between genetically predicted antioxidants, minerals, and vitamins, and MetS. Methods In this study, we utilized genetic variation as instrumental variable (IV) to capture exposure data related to commonly consumed dietary nutrients, including antioxidants (β-carotene, lycopene, and uric acid), minerals (copper, calcium, iron, magnesium, phosphorus, zinc, and selenium), and vitamins (folate, vitamin A, B6, B12, C, D, E, and K1). The outcomes of interest, namely MetS (n = 291,107), waist circumference (n = 462,166), hypertension (n = 463,010), fasting blood glucose (FBG) (n = 281,416), triglycerides (n = 441,016), and high-density lipoprotein cholesterol (HDL-C) (n = 403,943), were assessed using pooled data obtained from the most comprehensive genome-wide association study (GWAS) available. Finally, we applied the inverse variance weighting method as the result and conducted a sensitivity analysis for further validation. Results Genetically predicted higher iron (OR = 1.070, 95% CI 1.037–1.105, P = 2.91E−05) and magnesium levels (OR = 1.130, 95% CI 1.058–1.208, P = 2.80E−04) were positively associated with increased risk of MetS. For each component of MetS, higher level of genetically predicted selenium (OR = 0.971, 95% CI 0.957–0.986, P = 1.09E−04) was negatively correlated with HDL-C levels, while vitamin K1 (OR = 1.023, 95% CI 1.012–1.033, P = 2.90E−05) was positively correlated with HDL-C levels. Moreover, genetically predicted vitamin D (OR = 0.985, 95% CI 0.978–0.992, P = 5.51E−5) had a protective effect on FBG levels. Genetically predicted iron level (OR = 1.043, 95% CI 1.022–1.064, P = 4.33E−05) had a risk effect on TG level. Conclusions Our study provides evidence that genetically predicted some specific, but not all, antioxidants, minerals, and vitamins may be causally related to the development of MetS traits.

Abstract Background Porcine epidemic diarrhea (PED) is a contagious intestinal disease caused by porcine epidemic diarrhea virus (PEDV) characterized by vomiting, diarrhea, anorexia, and dehydration, which has caused huge economic losses around the world. However, it is very hard to find completely valid approaches to control the transmission of PEDV. At present, vaccine immunity remains the most effective method. To better control the spread of PED and evaluate the validity of different immunization strategies, 240 PED outbreak cases from 577 swine breeding farms were collected and analyzed. The objective of the present study was to analyze the epidemic regularity of PEDV and evaluate two kinds of different immunization strategies for controlling PED. Results The results showed that the main reasons which led to the outbreak of PED were the movement of pig herds between different pig farms (41.7%) and delaying piglets from the normal production flow (15.8%). The prevalence of PEDV in the hot season (May to October) was obviously higher than that in the cold season (January to April, November to December). Results of different vaccine immunity cases showed that immunization with the highly virulent live vaccine (NH-TA2020 strain) and the commercial inactivated vaccine could significantly decrease the frequency of swine breeding farms (5.9%), the duration of PED epidemic (1.70 weeks), and the week batches of dead piglets (0.48 weeks weaned piglets), compared with immunization with commercial attenuated vaccines and inactivated vaccine of PED. Meanwhile, immunization with the highly virulent live vaccine and the commercial inactivated vaccine could bring us more cash flows of Y̶275,274 per year than immunization with commercial live attenuated vaccine and inactivated vaccine in one 3000 sow pig farm within one year. Conclusion Therefore, immunization with highly virulent live vaccine and inactivated vaccine of PED is more effective and economical in the prevention and control of PED in the large-scale swine farming system.

Manganese-based layered oxides are promising cathode materials for potassium-ion batteries (PIBs) due to their low cost and high theoretical energy density. However, the Jahn-Teller effect of Mn3+ and sluggish diffusion kinetics lead to rapid electrode deterioration and a poor rate performance, greatly limiting their practical application. Here, we report a Co/Al co-substitution strategy to construct a P3-type K0.45Mn0.7Co0.2Al0.1O2 cathode material, where Co3+ and Al3+ ions occupy Mn3+ sites. This effectively suppresses the Jahn-Teller distortion and alleviates the severe phase transition during K+ intercalation/de-intercalation processes. In addition, the Co element contributes to K+ diffusion, while Al stabilizes the layer structure through strong Al-O bonds. As a result, the K0.45Mn0.7Co0.2Al0.1O2 cathode exhibits high capacities of 111 mAh g−1 and 81 mAh g−1 at 0.05 A g−1 and 1 A g−1, respectively. It also demonstrates a capacity retention of 71.6% after 500 cycles at 1 A g−1. Compared to the pristine K0.45MnO2, the K0.45Mn0.7Co0.2Al0.1O2 significantly alleviates severe phase transition, providing a more stable and effective pathway for K+ transport, as investigated by in situ X-ray diffraction. The synergistic effect of Co/Al co-substitution significantly enhances the structural stability and electrochemical performance, contributing to the development of new Mn-based cathode materials for PIBs.

Visualisation helps explain the operating mechanisms of deep learning models, but its applications are rarely seen in traffic analysis. This paper employs a convolu-tional neural network (CNN) to evaluate road network performance level (NPL) and visualises the model to en-lighten how it works. A dataset of an urban road network covering a whole year is used to produce performance maps to train a CNN. In this process, a pretrained network is introduced to overcome the common issue of inadequa-cy of data in transportation research. Gradient weighted class activation mapping (Grad-CAM) is applied to vi-sualise the CNN, and four visualisation experiments are conducted. The results illustrate that the CNN focuses on different areas when it identifies the road network as dif-ferent NPLs, implying which region contributes the most to the deteriorating performance. There are particular visual patterns when the road network transits from one NPL to another, which may help performance prediction. Misclassified samples are analysed to determine how the CNN fails to make the right decisions, exposing the model’s deficiencies. The results indicate visualisation’s potential to contribute to comprehensive management strategies and effective model improvement.

[This corrects the article DOI: 10.1371/journal.pone.0289473.].

The cytotoxicity of micro/nanoplastics (MNPs) is known to be strongly influenced by particle size, but the mechanism is not clear so far. We reported the ability of polystyrene MNPs to be internalized by HeLa cells could be a reason for the size dependent cytotoxicity of MNPs. We found that small MNPs (10 nm and 15 nm in radius) could be efficiently internalized by HeLa cells, MNPs of 25 nm in radius could be slightly internalized by the cells, and larger MNPs could not enter the cells at all. We showed that only MNPs, which could be internalized by cells, had a toxic effect on cell activity in a dose-dependent manner. In contrast, MNPs, which could not be internalized by cells, showed no cytotoxicity even if at extremely high concentrations. We attributed the correlation between the size-dependent uptake of MNPs and the size-dependent cytotoxicity of MNPs to the enhanced reactive oxygen species (ROS) level and abnormal gene expression. Our study pointed out that cellular uptake is one of the most fundamental mechanisms for the cytotoxicity of MNPs.

A two-loop acceleration autopilot is designed using the twin-delayed deep deterministic policy gradient (TD3) strategy to avoid the tedious design process of conventional tactical missile acceleration autopilots and the difficulty of meeting the performance requirements of the full flight envelope. First, a deep reinforcement learning model for the two-loop autopilot is developed. The flight state information serves as the state, the to-be-designed autopilot control parameters serve as the action, and a reward mechanism based on the stability margin index is designed. The TD3 strategy is subsequently used to offline learn the control parameters for the entire flight envelope. An autopilot control parameter fitting model that can be directly applied to the guidance loop is obtained. Finally, the obtained fitting model is combined with the impact angle constraint in the guidance system and verified online. The simulation results demonstrate that the autopilot based on the TD3 strategy can self-adjust the control parameters online based on the real-time flight state, ensuring system stability and achieving accurate acceleration command tracking.

Abstract The association between low density lipoprotein cholesterol (LDL-C) and all-cause mortality has been examined in many studies. However, inconsistent results and limitations still exist. We used the 1999–2014 National Health and Nutrition Examination Survey (NHANES) data with 19,034 people to assess the association between LDL-C level and all-cause mortality. All participants were followed up until 2015 except those younger than 18 years old, after excluding those who died within three years of follow-up, a total of 1619 deaths among 19,034 people were included in the analysis. In the age-adjusted model (model 1), it was found that the lowest LDL-C group had a higher risk of all-cause mortality (HR 1.708 [1.432–2.037]) than LDL-C 100–129 mg/dL as a reference group. The crude-adjusted model (model 2) suggests that people with the lowest level of LDL-C had 1.600 (95% CI [1.325–1.932]) times the odds compared with the reference group, after adjusting for age, sex, race, marital status, education level, smoking status, body mass index (BMI). In the fully-adjusted model (model 3), people with the lowest level of LDL-C had 1.373 (95% CI [1.130–1.668]) times the odds compared with the reference group, after additionally adjusting for hypertension, diabetes, cardiovascular disease, cancer based on model 2. The results from restricted cubic spine (RCS) curve showed that when the LDL-C concentration (130 mg/dL) was used as the reference, there is a U-shaped relationship between LDL-C level and all-cause mortality. In conclusion, we found that low level of LDL-C is associated with higher risk of all-cause mortality. The observed association persisted after adjusting for potential confounders. Further studies are warranted to determine the causal relationship between LDL-C level and all-cause mortality.

African swine fever (ASF) is a highly contagious hemorrhagic and transboundary animal disease, and it threatens global food security. A full necropsy to harvest the sample matrices for diagnosis in the farm may lead to contamination of the premises and directly threaten to the herds. In the present study, we compared the ASFV loads of the common samples that can be collected without necropsy. The unmatched nasal, throat, rectal samples were randomly taken using cotton swabs, and inguinal lymph node samples were collected by the minimally invasive samplers from the dead pigs of an ASF field outbreak farm. The ASFV loads of the samples were detected by qPCR and the results suggested that the overall ASFV nucleic acids levels of inguinal lymph node samples were higher than the swabs. What's more, sets of matched nasal swabs, rectal swabs, throat swabs, inguinal lymph nodes, serums, spleens and lungs samples were collected from 15 dead ASFV naturally infected pigs. Similarly, the results showed that inguinal lymph node samples, together with serum, spleen and lungs samples, contained more ASFV nucleic acids than the swabs. Our findings demonstrated that the inguinal lymph node collected by minimally invasive sampler is an ideal tissue for diagnosing ASFV infection in dead pigs without necropsy.

Abstract Background Complement factor H (CFH) has been found to be associated with insulin resistance. This study assessed the correlation between CFH and other clinical parameters, and determined whether CFH played a role in gestational diabetes mellitus (GDM) and adverse pregnancy outcomes. Methods A total of 397 pregnant women were included for analysis in this nested case-control study. Clinical parameters and serum were collected within the 11-17th gestational age at the first prenatal visit. At 24–28 weeks of gestation, a 75 g oral glucose tolerance test was performed and subjects were divided into a GDM (n = 80) and a non-GDM control group (n = 317). The delivery data were also followed. The serum CFH level was assayed by ELISA. Results CFH was higher in GDM than in non-GDM controls (280.02 [58.60] vs. 264.20 [68.77]; P = 0.014). CFH level was moderately associated with pre-pregnancy body mass index (BMI), BMI and total triglycerides (TG), and slightly associated with gestational age, low density lipoprotein cholesterol (LDL-C), total cholesterol (TC) in GDM and non-GDM (all P

Umami peptides enhance the umami taste of food and have good food processing properties, nutritional value, and numerous potential applications. Wet testing for the identification of umami peptides is a time-consuming and expensive process. Here, we report the iUmami-DRLF that uses a logistic regression (LR) method solely based on the deep learning pre-trained neural network feature extraction method, unified representation (UniRep based on multiplicative LSTM), for feature extraction from the peptide sequences. The findings demonstrate that deep learning representation learning significantly enhanced the capability of models in identifying umami peptides and predictive precision solely based on peptide sequence information. The newly validated taste sequences were also used to test the iUmami-DRLF and other predictors, and the result indicates that the iUmami-DRLF has better robustness and accuracy and remains valid at higher probability thresholds. The iUmami-DRLF method can aid further studies on enhancing the umami flavor of food for satisfying the need for an umami-flavored diet.

Phase-change materials (PCMs) have become as promising elements in silicon photonic systems. We propose an optical buffer device based on vanadium dioxide (VO2) embedded on silicon-on-insulator waveguides with a microring resonator. The upload straight waveguide is for coupling light signal from the input port into VO2 embedded on microring resonator and the download straight waveguide with VO2 films is for coupling the storage signal to the output port. The optical characteristics of optical buffer device under different structural parameters are analyzed by using finite difference mode simulation (MODE). By controlling the phase state of VO2 in two coupling regions, the buffer speed of the device can be up to 0.5 ps and buffer time up to 78.28 ps. The optical buffer based on VO2 is a new way for PCM optical buffer.

Abstract Background Mesenchymal stem cell (MSC)-derived exosomes emerge as promising candidates for treating delayed wound healing in diabetes due to the promotion of angiogenesis. Preconditioned MSC with chemical or biological factors could possibly enhance the biological activities of MSC-derived exosomes. The purpose of this research focused on whether exosomes derived from the bone marrow MSC (BMSC) pretreated with atorvastatin (ATV), could exhibit better pro-angiogenic ability in diabetic wound healing or not and its underlying molecular mechanism. Methods We isolated exosomes from non-pretreated BMSC (Exos) and ATV pretreated BMSC (ATV-Exos) and evaluated their characterization by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and Western blotting. In vivo, we made full-thickness skin defects in streptozotocin (STZ)-induced diabetic rats and the defects received multiple-point injection with PBS, Exos, or ATV-Exos. Two weeks later, histological analysis was conducted to evaluate the impact of different treatments on wound healing and the neovascularization was measured by micro-CT. In vitro, cell proliferation, migration, tube formation, and vascular endothelial growth factor (VEGF) secretion were measured in human umbilical vein endothelial cells (HUVEC). The role of miRNAs and AKT/eNOS signaling pathway in the promoted angiogenesis of ATV-Exos were assessed with their inhibitors. Results No significant difference in morphology, structure, and concentration was observed between ATV-Exos and Exos. In STZ-induced diabetic rats, ATV-Exos exhibited excellent abilities in facilitating the wound regeneration by promoting the formation of blood vessels compared with Exos without influencing liver and kidney function. Meanwhile, ATV-Exos promoted the proliferation, migration, tube formation, and VEGF level of endothelial cells in vitro. And AKT/eNOS pathway was activated by ATV-Exos and the pro-angiogenic effects of ATV-Exo were attenuated after the pathway being blocked. MiR-221-3p was upregulated by ATV-Exos stimulation, and miR-221-3p inhibitor suppressed the pro-angiogenesis effect of ATV-Exos. Conclusions Exosomes originated from ATV-pretreated MSCs might serve as a potential strategy for the treatment of diabetic skin defects through enhancing the biological function of endothelial cells via AKT/eNOS pathway by upregulating the miR-221-3p.

Nowadays, vehicle line pressure detection is an important function of an intelligent transportation system. At present, the line pressure detection algorithms mainly include algorithms based on traditional features and models and algorithms based on deep learning. However, these algorithms also have shortcomings such as low detection accuracy or relying on specific scenarios. In this regard, this paper proposes a fast and accurate vehicle line detection algorithm based on deep learning for vehicle images. The algorithm builds a GooleNet-based FCN semantic segmentation network and adds a BN layer, 1 × 1 convolution, and FPN structure to improve the segmentation effect of the GooleNet-FCN network and reduce network parameters. The MobileNet-SSD (no pretrained model) network structure is used for vehicle detection. According to the relationship between the receptive field and the anchor, and then combined with specific data, the prediction branch of the network and the Default Box on the branch are modified and the FPN structure is added for feature fusion to form the final improved MobileNet-SSD network. The experimental results show that the algorithm takes an average time of 67.8 ms per frame, the detection rate of line pressing for a vehicle is 96.6%, and the deep learning models are 25.5 M and 19.2 M, respectively. The experimental results verify the effectiveness and practicality of the detection algorithm proposed in this paper.

Abstract Epidemiological studies have a clear definition of the risk factors for breast cancer. However, it is unknown whether the distribution of these factors differs among breast cancer subtypes. We conducted a hospital‐based case‐only study consisting of 8067 breast cancer patients basing on the Tianjin Cohort of Breast Cancer Cases. Major breast cancer subtypes including luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)‐enriched and basal‐like were defined by estrogen receptor, progesterone receptor, HER2, and Ki‐67 status. Variables including demographic characteristics, reproductive factors, lifestyle habits, imaging examination, and clinicopathologic data were collected for patients. Chi‐square test and one‐way analysis of variance were used to compare the distributions of variables among the four breast cancer subtypes. Multivariate logistic regression was used to estimate the odds ratios and associated 95% confidence intervals where luminal A patients served as the reference group. Overall, more commonality rather than heterogeneity on the distributions of factors was found between the four molecular subtypes of breast cancer. The proportion of overweight and obesity were lower in HER2‐enriched subtype. Women with age at menarche ≤13 years were more likely to be found in basal‐like subtype. Postmenopausal women were more frequent in HER2‐enriched and basal‐like subtypes. Women with benign breast disease and higher breast density were more common in HER2‐enriched subtype. Risk factor scoring showed that total risk scores were similar among the four subtypes. HER2‐enriched and basal‐like subtypes were more frequently diagnosed with large tumors. Calcification was more likely to be found in luminal B and HER2‐enriched subtypes, whereas less distributed in basal‐like subtype. Most of the breast cancer risk factors were similarly distributed among the four major breast cancer subtypes; commonality is predominant.

The collector system in wind farm has a large number of cables. When one of the cable fails, the power generated by the wind turbine (WT) cannot be collected into the substation through the faulty cable. That would make the profits for the wind farm reduced. Therefore, it is necessary to find a more reliable cable structure, which can transfer power as much as possible even if the cable failure occurs. In this paper, a new cable connection method is proposed in two main steps to improve both the reliability of the cable connection and the economic. Two different wind farms with the same climatological information and high voltage substation location are investigated and compared in the case study. In the first step, the minimum spanning tree (MST) algorithm is adopted to connect all wind turbines (WTs) to the substation. The cables used in collector system are the 33-kV middle voltage alternating current (MVAC) cables. Then the power production generated by WTs is transmitted from substation to the high voltage substation via a 132-kV transmission cable. The initial cable connection layout is obtained in the first step and the total trenching length is optimized to be minimum. In addition, cable selection in each branch can be determined based on the cable current carrying capacity. In the second step, reliability assessment is implemented by analyzing the expected energy not supplied (EENS). Based on EENS, the evaluation index ${LPC}_{rel}$ is obtained. This index takes both reliability and economy into account. Additional cables found by particle swarm optimization (PSO) algorithm are added to the initial cable connection layout. Finally, a cable layout called hybrid structure is formed. What is more, by adding additional cables, the ${LPC}_{rel}$ is reduced by 1.5%. The simulation results clearly indicate that the proposed method is better when the cable failure is considered.

To address the shortcomings of weak confusion and high time complexity of the existing permutation algorithms, including the traditional Josephus ring permutation (TJRP), an improved Josephus ring-based permutation (IJRBP) algorithm is developed. The proposed IJRBP replaces the remove operation used in TJRP with the position exchange operation and employs random permutation steps instead of fixed steps, which can offer a better scrambling effect and a higher permutation efficiency, compared with various scrambling methods. Then, a new encryption algorithm based on the IJRBP and chaotic system is developed. In our scheme, the plaintext feature parameter, which is related to the plaintext and a random sequence generated by a chaotic system, is used as the shift step of the circular shift operation to generate the diffusion matrix, which means that a minor change in the source image will generate a totally different encrypted image. Such a strategy strikes a balance between plaintext sensitivity and ciphertext sensitivity to obtain the ability to resist chosen-plaintext attacks (CPAs) and the high robustness of resisting noise attacks and data loss. Simulation results demonstrate that the proposed image cryptosystem has the advantages of great encryption efficiency and the ability to resist various common attacks.

High-glucose induced retinal pigment epithelium (RPE) death by triggering oxidative stress, however, the underlying mechanisms are still not fully delineated. In this study, the RPE cell line ARPE-19 were treated with different concentrations of glucose, the results showed that high-glucose (50 mM) inhibited cell proliferation, promoted cell apoptosis and reactive oxygen species (ROS) production in a time-dependent manner. Notably, we found that high-glucose (50 mM) increased the expression levels of Caspase-1, Gasdermin D, NLRP3, IL-1β and IL-18 in ARPE-19 cells, which indicated that high-glucose triggered pyroptotic cell death. Further results validated that both ROS scavenger N-acetyl cysteine (NAC) and pyroptosis inhibitor necrosulfonamide (NSA) reversed the effects of high-glucose (50 mM) on ARPE-19 cell proliferation, apoptosis and pyroptosis. In addition, high-glucose (50 mM) significantly decreased the levels of miR-130a and superoxide dismutase (SOD) 1, and promoted tumor necrosis factor (TNF)-α expressions in ARPE-19 cells. Interestingly, upregulation of miR-130a increased SOD1 levels in a TNF-α dependent manner. Furthermore, overexpression of miR-130a abrogated the effects of high-glucose (50 mM) on the above cell functions, which were all reversed by either upregulating TNF-α or knocking down SOD1 in ARPE-19 cells. Taken together, upregulation of miR-130a alleviated the cytotoxic effects of high-glucose (50 mM) on ARPE-19 cells by regulating TNF-α/SOD1/ROS axis mediated pyroptotic cell death.

Crop productivity is typically affected by various soil–plant factors systematically as they influence plant photosynthesis, soil fertility, and root systems. However, little is known about how the productivity of legumes is related to crop rotation systems. The objectives of this study were to determine the effect of rotation systems on legume productivity and the relationships among legume productivity and soil–plant factors. Three annual legumes – chickpea (Cicer arietinum L.), pea (Pisum sativum L.), and lentil (Lens culinaris Medikus), were included in various diversified rotation systems and compared with legume monoculture in the 8-year rotation study. Soil N and water conditions, and canopy and root systems were evaluated at the end of 8-year rotation in the semiarid Canadian prairies. Results showed that diversified rotation systems improved leaf greenness by 4%, shoot biomass by 25%, nodule biomass by 44%, and seed yield by 95% for chickpea and pea, but such effects were not found for lentil. Pea monocultures increased root rot severity by threefold compared with diversified rotations, and chickpea monoculture increased shoot rot severity by 23%, root rot severity by 96% and nodule damage by 219%. However, all the legume monocultures improved soil N accumulation by an average 38% compared to diversified systems. Pea and chickpea displayed considerable sensitivity to plant biotic stresses, whereas lentil productivity had a larger dependence on initial soil N content. The 8-year study concludes that the rotational effect on legume productivity varies with legume species, the frequency of a legume appearing in the rotation, and the integration of relevant soil and plant indices.

[This corrects the article DOI: 10.1371/journal.pone.0183249.].

Enterocytozoon bieneusi is the most common pathogen of microsporidian species infecting humans worldwide. Although E. bieneusi has been found in a variety of animal hosts, information on the presence of E. bieneusi in captive kangaroos in China is limited. The present study was aimed at determining the occurrence and genetic diversity of E. bieneusi in captive kangaroos. A total of 61 fecal specimens (38 from red kangaroos and 23 from grey kangaroos) were collected from Nanjing Hongshan Forest Zoo and Hongshan Kangaroo Breeding Research Base, Jiangsu province, China. Using the nested PCR amplification ITS gene of rRNA of E. bieneusi, totally 23.0% (14/61) of tested samples were PCR-positive with three genotypes (i.e. one known genotype, CHK1, and two novel genotypes, CSK1 and CSK2). Multi-locus sequence typing using three microsatellites (MS1, MS3, and MS7) and one minisatellite (MS4) revealed one, five, two, and one types at these four loci, respectively. In phylogenetic analysis, the two genotypes, CHK1 and CSK1, were clustered into a new group of unknown zoonotic potential, and the novel genotype CSK2 was clustered into a separate clade with PtEb and PtEbIX. To date, this is the first report on the presence of E. bieneusi in captive red kangaroos in Jiangsu province, China. Furthermore, a high degree of genetic diversity was observed in the E. bieneusi genotype and seven MLGs (MLG1-7) were found in red kangaroos. Our findings suggest that infected kangaroo may act as potential reservoirs of E. bieneusi and be source to transmit infections to other animal.

Objectives: Periodontitis (PD) is one of the most common dental disorders. This chronic oral inflammation is caused by complicated interrelations between bacterial infections, dysregulated immune reactions, and environmental risk factors. A dysregulated immune response can lead to inflammatory bone resorption by allowing the recruitment of pro‐inflammatory immune cells to the periodontal tissues. Subjects: The recruitment of innate and adaptive immune cells in PD initiates the acute and following chronic inflammatory processes. The inflamed tissues, on the other hand, can be restored if the anti‐inflammatory lineages are predominantly established in the periodontal tissues. Therefore, we aimed to review the published literature to provide an overview of the existing knowledge about the role of immune cells in PD, as well as their possible therapeutic applications. Results: Experimental studies showed that drugs/systems that negatively regulate inflammatory cells in the body, as well as interventions aimed at increasing the number of anti‐inflammatory cells such as Tregs and Bregs, can both help in the healing process of PD. Conclusion: Targeting immune cells or their positive/negative manipulations has been demonstrated to be an effective therapeutic method. However, to use this sort of immunotherapy in humans, further pre‐clinical investigations, as well as randomized clinical trials, are required. [ABSTRACT FROM AUTHOR]

Abstract Background To investigate the mechanism of Golgi matrix protein 130(GM130) regulating the antiviral immune response of TLR3 after herpes simplex virus type 1(HSV-1) infection of microglia cells. We explored the regulatory effects of berberine on the immune response mediated by GM130 and TLR3. Methods An in vitro model of HSV-1 infection was established by infecting BV2 cells with HSV-1. Results Compared to the uninfected group, the Golgi apparatus (GA) fragmentation and GM130 decreased after HSV-1 infection; TLR3 increased at 6 h and began to decrease at 12 h after HSV-1 infection; the secretion of interferon-beta(IFN-β), tumour necrosis factor alpha(TNF-α), and interleukin-6(IL-6) increased after infection. Knockdown of GM130 aggravated fragmentation of the GA and caused TLR3 to further decrease, and the virus titer also increased significantly. GM130 knockdown inhibits the increase in TLR3 and inflammatory factors induced by TLR3 agonists and increases the viral titer. Overexpression of GM130 alleviated fragmentation of the GA induced by HSV-1, partially restored the levels of TLR3, and reduced viral titers. GM130 overexpression reversed the reduction in TLR3 and inflammatory cytokine levels induced by TLR3 inhibitors. Therefore, the decrease in GM130 levels caused by HSV-1 infection leads to increased viral replication by inhibiting TLR3-mediated innate immunity. Berberine can protect the GA and reverse the downregulation of GM130, as well as the downregulation of TLR3 and its downstream factors after HSV-1 infection, reducing the virus titer. Conclusions In microglia, one mechanism of HSV-1 immune escape is disruption of the GM130/TLR3 pathway. Berberine protects the GA and enhances TLR3-mediated antiviral immune responses.