87 research outputs found

    Toxic Effects of Silica Nanoparticles on Zebrafish Embryos and Larvae

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    Silica nanoparticles (SiNPs) have been widely used in biomedical and biotechnological applications. Environmental exposure to nanomaterials is inevitable as they become part of our daily life. Therefore, it is necessary to investigate the possible toxic effects of SiNPs exposure. In this study, zebrafish embryos were treated with SiNPs (25, 50, 100, 200 μg/mL) during 4-96 hours post fertilization (hpf). Mortality, hatching rate, malformation and whole-embryo cellular death were detected. We also measured the larval behavior to analyze whether SiNPs had adverse effects on larvae locomotor activity. The results showed that as the exposure dosages increasing, the hatching rate of zebrafish embryos was decreased while the mortality and cell death were increased. Exposure to SiNPs caused embryonic malformations, including pericardial edema, yolk sac edema, tail and head malformation. The larval behavior testing showed that the total swimming distance was decreased in a dose-dependent manner. The lower dose (25 and 50 μg/mL SiNPs) produced substantial hyperactivity while the higher doses (100 and 200 μg/mL SiNPs) elicited remarkably hypoactivity in dark periods. In summary, our data indicated that SiNPs caused embryonic developmental toxicity, resulted in persistent effects on larval behavior. © 2013 Duan et al.published_or_final_versio

    Correlation of lifestyle behaviors during pregnancy with postpartum depression status of puerpera in the rural areas of South China

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    BackgroundPostpartum depression (PPD) is among the most common postpartum complications. Its prevalence is associated with strong regional variability. Women in rural areas of China have a high risk of PPD. The aim of this study was to investigate the PPD status of women in rural South China and explore the effects of modifiable lifestyle behaviors during pregnancy on their PPD status, thereby providing a scientific basis for the prevention and intervention of PPD in rural China.MethodsA cohort study was conducted on 261 women from four maternal health institutions situated in rural areas of Guangdong Province and the Guangxi Zhuang Autonomous Region from October 2021 to December 2022. The questionnaires were administered to these women to obtain data about sociodemographic characteristics, health literacy, physical activity during pregnancy, and sleep and dietary status during pregnancy, as well as depression status on the 42nd day after delivery. The lifestyle behaviors during pregnancy and the PPD status of the study population were analyzed. Multiple linear regression models were used to determine the correlation between lifestyle behaviors and PPD status. Path analysis was performed to explore the interaction between various lifestyle behaviors.ResultsA total of 14.6% of women had a PPD status. Women who continued to work during pregnancy had an Edinburgh Postpartum Depression Scale (EPDS) score of 1.386 points higher than that of women who did not (В = 1.386, β = 0.141, p = 0.029). For every 1-point increase in the infant feeding-related knowledge score and pregnancy diet diversity score, the EPDS score decreased by 0.188 and 0.484 points, respectively, and for every 1-point increase in the Pittsburgh sleep quality index score, the EPDS score increased by 0.288 points. Age was related to infant feeding-related knowledge (indirect path coefficient = 0.023). During pregnancy, sedentary time was correlated with sleep quality (indirect path coefficient = 0.031) and employment status (indirect path coefficient = 0.043).ConclusionEmployment status, infant feeding-related knowledge, sleep quality, and diet diversity during pregnancy directly influenced the PPD status, while age and sedentary time during pregnancy indirectly influenced the PPD status. Promoting healthy lifestyle behaviors, including reducing sedentary time, improving sleep quality, and increasing dietary diversity, may be effective in reducing PPD occurrence

    Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery

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    Monitoring and discriminating co-epidemic diseases and pests at regional scales are of practical importance in guiding differential treatment. A combination of vegetation and environmental parameters could improve the accuracy for discriminating crop diseases and pests. Different diseases and pests could cause similar stresses and symptoms during the same crop growth period, so combining growth period information can be useful for discerning different changes in crop diseases and pests. Additionally, problems associated with imbalanced data often have detrimental effects on the performance of image classification. In this study, we developed an approach for discriminating crop diseases and pests based on bi-temporal Landsat-8 satellite imagery integrating both crop growth and environmental parameters. As a case study, the approach was applied to data during a period of typical co-epidemic outbreak of winter wheat powdery mildew and aphids in the Shijiazhuang area of Hebei Province, China. Firstly, bi-temporal remotely sensed features characterizing growth indices and environmental factors were calculated based on two Landsat-8 images. The synthetic minority oversampling technique (SMOTE) algorithm was used to resample the imbalanced training data set before model construction. Then, a back propagation neural network (BPNN) based on a new training data set balanced by the SMOTE approach (SMOTE-BPNN) was developed to generate the regional wheat disease and pest distribution maps. The original training data set-based BPNN and support vector machine (SVM) methods were used for comparison and testing of the initial results. Our findings suggest that the proposed approach incorporating both growth and environmental parameters of different crop periods could distinguish wheat powdery mildew and aphids at the regional scale. The bi-temporal growth indices and environmental factors-based SMOTE-BPNN, BPNN, and SVM models all had an overall accuracy high than 80%. Meanwhile, the SMOTE-BPNN method had the highest G-means among the three methods. These results revealed that the combination of bi-temporal crop growth and environmental parameters is essential for improving the accuracy of the crop disease and pest discriminating models. The combination of SMOTE and BPNN could effectively improve the discrimination accuracy of the minor disease or pest

    Hypophosphorylated pRb knock-in mice exhibit hallmarks of aging and vitamin C-preventable diabetes

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    Despite extensive analysis of pRB phosphorylation in vitro, how this modification influences development and homeostasis in vivo is unclear. Here, we show that homozygous Rb∆K4 and Rb∆K7 knock-in mice, in which either four or all seven phosphorylation sites in the C-terminal region of pRb, respectively, have been abolished by Ser/Thr-to-Ala substitutions, undergo normal embryogenesis and early development, notwithstanding suppressed phosphorylation of additional upstream sites. Whereas Rb∆K4 mice exhibit telomere attrition but no other abnormalities, Rb∆K7 mice are smaller and display additional hallmarks of premature aging including infertility, kyphosis, and diabetes, indicating an accumulative effect of blocking pRb phosphorylation. Diabetes in Rb∆K7 mice is insulin-sensitive and associated with failure of quiescent pancreatic β-cells to re-enter the cell cycle in response to mitogens, resulting in induction of DNA damage response (DDR), senescence-associated secretory phenotype (SASP), and reduced pancreatic islet mass and circulating insulin level. Pre-treatment with the epigenetic regulator vitamin C reduces DDR, increases cell cycle re-entry, improves islet morphology, and attenuates diabetes. These results have direct implications for cell cycle regulation, CDK-inhibitor therapeutics, diabetes, and longevity

    Cloning, expression and characterization of alcohol dehydrogenases in the silkworm Bombyx mori

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    Alcohol dehydrogenases (ADH) are a class of enzymes that catalyze the reversible oxidation of alcohols to corresponding aldehydes or ketones, by using either nicotinamide adenine dinucleotide (NAD) or nicotinamide adenine dinucleotide phosphate (NADP), as coenzymes. In this study, a short-chain ADH gene was identified in Bombyx mori by 5′-RACE PCR. This is the first time the coding region of BmADH has been cloned, expressed, purified and then characterized. The cDNA fragment encoding the BmADH protein was amplified from a pool of silkworm cDNAs by PCR, and then cloned into E. coli expression vector pET-30a(+). The recombinant His-tagged BmADH protein was expressed in E. coli BL21 (DE3), and then purified by metal chelating affinity chromatography. The soluble recombinant BmADH, produced at low-growth temperature, was instrumental in catalyzing the ethanol-dependent reduction of NAD+, thereby indicating ethanol as one of the substrates of BmADH

    A deep learning-based approach for automated yellow rust disease detection from high resolution hyperspectral UAV images

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    Yellow rust in winter wheat is a widespread and serious fungal disease, resulting in significant yield losses globally. Effective monitoring and accurate detection of yellow rust are crucial to ensure stable and reliable wheat production and food security. The existing standard methods often rely on manual inspection of disease symptoms in a small crop area by agronomists or trained surveyors. This is costly, time consuming and prone to error due to the subjectivity of surveyors. Recent advances in Unmanned Aerial Vehicles (UAVs) mounted with hyperspectral image sensors have the potential to address these issues with low cost and high efficiency. This work proposed a new deep convolutional neural network (DCNN) based approach for automated crop disease detection using very high spatial resolution hyperspectral images captured with UAVs. The proposed model introduced multiple Inception-Resnet layers for feature extraction and was optimized to establish the most suitable depth and width of the network. Benefiting from the ability of convolution layers to handle three-dimensional data, the model used both spatial and spectral information for yellow rust detection. The model was calibrated with hyperspectral imagery collected by UAVs in five different dates across a whole crop cycle over a well-controlled field experiment with healthy and rust infected wheat plots. Its performance was compared across sampling dates and with random forest, a representative of traditional classification methods in which only spectral information was used. It was found that the method has high performance across all the growing cycle, particularly at late stages of the disease spread. The overall accuracy of the proposed model (0.85) was higher than that of the random forest classifier (0.77). These results showed that combining both spectral and spatial information is a suitable approach to improving the accuracy of crop disease detection with high resolution UAV hyperspectral images

    Targeting YAP1 to improve the efficacy of immune checkpoint inhibitors in liver cancer: mechanism and strategy

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    Liver cancer is the third leading of tumor death, including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Immune checkpoint inhibitors (ICIs) are yielding much for sufferers to hope for patients, but only some patients with advanced liver tumor respond. Recent research showed that tumor microenvironment (TME) is critical for the effectiveness of ICIs in advanced liver tumor. Meanwhile, metabolic reprogramming of liver tumor leads to immunosuppression in TME. These suggest that regulating the abnormal metabolism of liver tumor cells and firing up TME to turn “cold tumor” into “hot tumor” are potential strategies to improve the therapeutic effect of ICIs in liver tumor. Previous studies have found that YAP1 is a potential target to improve the efficacy of anti-PD-1 in HCC. Here, we review that YAP1 promotes immunosuppression of TME, mainly due to the overstimulation of cytokines in TME by YAP1. Subsequently, we studied the effects of YAP1 on metabolic reprogramming in liver tumor cells, including glycolysis, gluconeogenesis, lipid metabolism, arachidonic acid metabolism, and amino acid metabolism. Lastly, we summarized the existing drugs targeting YAP1 in the treatment of liver tumor, including some medicines from natural sources, which have the potential to improve the efficacy of ICIs in the treatment of liver tumor. This review contributed to the application of targeted YAP1 for combined therapy with ICIs in liver tumor patients

    The impact of disturbance from photographers on the Blue-crowned Laughingthrush (Garrulax courtoisi)

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    Human disturbance may cause significant declines in animal populations. The Blue-crowned Laughingthrush (Garrulax courtoisi) is critically endangered and restricted to a small area in Wuyuan, Jiangxi Province, China. Disturbance from photographers in the main breeding sites were severe in the past few years. We studied nest-site selection in nine breeding colonies in relation to disturbance by bird photographers. We compared the nest tree species and nest height above ground in Shimen (SM), the largest and most disturbed site, with the other eight sites. Birds in SM were more selective in nest tree species than in the other sites, they also nested much further from the nearest village building. Nest height above ground at SM was greater than at the other sites and itself in 2004 when there were almost no visitors. These results suggest that disturbance from birding visitors may exacerbate the endangered status of this bird. Management of bird visitors in a small breeding area of endangered species should be considered

    PriSign, A Privacy-Preserving Single Sign-On System for Cloud Environments

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    Anonymous single sign-on systems allow users to use a single credential to access multiple services protected by verifiers without revealing their personal information, which is especially important due to privacy regulations such as GDPR. In this paper, we introduce a new strong privacy-preserving single sign-on scheme, dubbed PriSign, based on our proposed attribute-based credential with traceability (ABCT), attribute-based credential with blindness (ABCB), and threshold inner-product functional encryption (TIPFE). Compared with the existing state-of-the-art solutions, PriSign presents three improvements: (1) users can obtain different types of tickets according to the attribute disclosure policies enforced by the ticket issuer to support fine-grained access control; (2) users can hide access tokens and designate a verifier for tokens according to a verifier’s policy jointly issued by multiple policymakers, meaning that non-designated verifiers cannot obtain any information about the tokens; (3) we innovatively use a threshold approach to issue policy keys online in order for verifiers to achieve proxy re-verification services in an unstable cloud environment. We implement PriSign and compare the performance with other ASSO systems in the personal laptop, and the results prove its practicability

    Can we control potato fungal and bacterial diseases? — microbial regulation

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    The potato plant is one of the main crops in the world. However, relatively little is known about key virulence factors of major fungal and bacterial diseases in potatoes, biocontrol measures to improve activity and stability, and the core driving forces in the control process. Here, we focus on analyzing the mechanisms by which genes, proteins, or (and) metabolites of potato pathogens as key virulence factors. Then, the single strain biocontrol agents, synthetic microbial communities, microbial microcapsule strategies were introduced, and the latter two strategies can improve stability and activity in biocontrol. Meanwhile, summarized the defense mechanisms of biocontrol and their specific issues in practical applications. Furthermore, explore how potato crop management, soil management, and climate effects, as crucial driving forces affect potato biocontrol in the system. Dynamic and systematic research, excavation of biocontrol strain resources, find the causes of regional disease resistance and exploration of biocontrol mechanism will provide promising solutions for biotic stress faced by potato in the future
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