Aflatoxin B1 Degradation and Detoxification by Escherichia coli CG1061 Isolated From Chicken Cecum

Aflatoxin B1 (AFB1) is one of the most hazardous mycotoxins contamination in food and feed products, which leads to hepatocellular carcinoma in humans and animals. In the present study, we isolated and characterized an AFB1 degrading bacteria CG1061 from chicken cecum, exhibited an 93.7% AFB1 degradation rate by HPLC. 16S rRNA gene sequence analysis and a multiplex PCR experiment demonstrated that CG1061 was a non-pathogenic Escherichia coli. The culture supernatant of E. coli CG1061 showed an 61.8% degradation rate, whereas the degradation rates produced by the intracellular extracts was only 17.6%, indicating that the active component was constitutively secreted into the extracellular space. The degradation rate decreased from 61.8 to 37.5% when the culture supernatant was treated with 1 mg/mL proteinase K, and remained 51.3% when that treated with 100°C for 20 min. We postulated that AFB1 degradation was mediated by heat-resistant proteins. The content of AFB1 decreased rapidly when it was incubated with the culture supernatant during the first 24 h. The optimal incubation pH and temperature were pH 8.5 and 55°C respectively. According to the UPLC Q-TOF MS analysis, AFB1 was bio-transformed to the product C16H14O5 and other metabolites. Based on the results of in vitro experiments on chicken hepatocellular carcinoma (LMH) cells and in vivo experiments on mice, we confirmed that CG1061-degraded AFB1 are less toxic than the standard AFB1. E. coli CG1061 isolated from healthy chicken cerum is more likely to colonize the animal gut, which might be an excellent candidate for the detoxification of AFB1 in food and feed industry

The Role of Early Growth Response Family Members 1–4 in Prognostic Value of Breast Cancer

Early growth response family members (EGRs), EGR1–4, have increasingly attracted attention in multiple cancers. However, the exact expression patterns and prognostic values of EGRs in the progress of breast cancer (BRCA) remain largely unknown. The mRNA expression and prognostic characteristics of EGRs were examined by the Cancer Genome Atlas (TCGA), Oncomine, and Kaplan-Meier plotter. Enrichment analyses were conducted based on protein-protein interaction (PPI) network. The Tumor Immune Estimation Resource (TIMER) database and MethSurv were further explored. The protein expression of EGR1 in BRCA was measured by western blotting and immunohistochemistry. The migration of mammary epithelial cells was determined by Boyden chamber assay. The transcriptional levels of EGR1/2/3 displayed significantly low expression in BRCA compared with that in normal tissues, while EGR4 was shown adverse expression pattern. Survival analysis revealed upregulated EGR1–4 were remarkably associated with favorable relapse-free survival (RFS). A close correlation with specific tumor-infiltrating immune cells (TIICs) and several CpG sites of EGRs were exhibited. Immunohistochemistry assays showed that the protein expression of EGR1 was remarkably downregulated in BRCA compared with that in paracancerous tissues. The migration of MCF10A mammary epithelial cells was increased after the silence of EGR1 by siRNA transfection. This study provides a novel insight to the role of EGRs in the prognostic value of BRCA

Cobalt-doped porous carbon nanosheets derived from 2D hypercrosslinked polymer with CoN₄ for high performance electrochemical capacitors

Cobalt-doped graphene-coupled hypercrosslinked polymers (Co-GHCP) have been successfully prepared on a large scale, using an efficient RAFT (Reversible Addition-Fragmentation Chain Transfer Polymerization) emulsion polymerization and nucleophilic substitution reaction with Co (II) porphyrin. The Co-GHCP could be transformed into cobalt-doped porous carbon nanosheets (Co-GPC) through direct pyrolysis treatment. Such a Co-GPC possesses a typical 2D morphology with a high specific surface area of 257.8 m2 g−1. These intriguing properties of transition metal-doping, high conductivity, and porous structure endow the Co-GPC with great potential applications in energy storage and conversion. Utilized as an electrode material in a supercapacitor, the Co-GPC exhibited a high electrochemical capacitance of 455 F g−1 at a specific current of 0.5 A g−1. After 2000 charge/discharge cycles, at a current density of 1 A g−1, the specific capacitance increased by almost 6.45%, indicating the excellent capacitance and durability of Co-GPC. These results demonstrated that incorporation of metal porphyrin into the framework of a hypercrosslinked polymer is a facile strategy to prepare transition metal-doped porous carbon for energy storage applications

Qishen Yiqi dripping pills for chronic ischaemic heart failure:results of the CACT-IHF randomized clinical trial

10.1002/ehf2.12980ESC Heart Failure763881-389

High-Resolution Imaging Of Electric Field Enhancement And Energy-Transfer Quenching By A Single Silver Nanowire Using Qd-Modified Afm Tips

Plasmonic nanostructures can profoundly affect the optical properties of light absorbers and emitters. Using quantum dot-modified-atomic force microscopy (AFM) tips as a nanoscale light source, the topological features of a Ag nanowire and its effect on the fluorescence intensity and lifetime of the QDs can be simultaneously imaged with AFM spatial resolution. Modeling of the QD-nanowire interaction and the contrasts in the fluorescence intensity and lifetime images suggests that this novel method can be used for direct high-resolution mapping of the electric field distributions and energy-transfer quenching near metallic nanostructures. © 2013 American Chemical Society

Dynamics of Carbon and Water Fluxes over Cropland and Agroforest Ecosystems on the Southern Chinese Loess Plateau

Studies on the spatiotemporal dynamics in ecosystem carbon and water exchanges are essential in predicting the effects of climate change on regional carbon and energy budgets. Using the eddy covariance technique, carbon and water fluxes were observed in a typical winter wheat ecosystem (WWE) and an agroforest ecosystem (AFE) in the southern Loess Plateau from 2004 to 2010. The seasonal and inter-annual variability in gross primary productivity (GPP), net ecosystem exchange (NEE), evapotranspiration (ET), and water use efficiency (WUE) were examined and the main influencing factors were identified using the Pearson correlation. The results indicate that the seasonal GPP and NEE showed a bimodal distribution in WWE, while this was unimodal in AFE. The sinusoidal function did well in the characterization of seasonal ET dynamics for both ecosystems, with the determination coefficients being 0.85 and 0.94, respectively. In WWE and AFE, the annual mean GPP were 724.33 and 723.08 g C m−2 a−1, respectively, and the corresponding ET were 392.22 and 410.02 mm a−1. However, the difference in NEE between the two ecosystems was obvious, NEE were −446.28 and −549.08 g C m−2 a−1, respectively, showing a stronger carbon sink in AFE. There were strong coupling relationships between the GPP and ET of both ecosystems; the overall slopes were 1.71 and 1.69, respectively. The seasonal trend of WUE was bimodal in WWE, with peak values of 3.94 and 3.65 g C kg−1 H2O, occurring in November and April, respectively. However, the monthly WUE in AFE had one single peak of 4.07 g C kg−1 H2O in January. Photosynthetically active radiation (PAR) and soil temperature (Ts) were most positively correlated with GPP, net radiation (Rn) and Ts were the major factors influencing ET, while vapor pressure deficit (VPD) and soil water content (SWC) were the major influencing factors for WUE. These results provide observational support for regional carbon neutrality simulations

Convenient isolation of strictinin-rich tea polyphenol from Chinese green tea extract by zirconium phosphate

Zirconium phosphate (ZrP) was prepared and employed to separate strictinin-rich tea polyphenol from Chinese green tea extracts. The influences of ZrP calcination temperatures, green tea extraction conditions, and the amounts of ZrP on the isolation of strictinin-rich tea polyphenol were evaluated; the absorption and desorption dynamics of strictinin on ZrP were also determined. Our results revealed that the HPLC content of strictinin increased from 4.96% in 70% ethanol extract of green tea to 58.2% in isolated strictinin-rich tea polyphenol obtained by ZrP-900 (ZrP calcined at 900°C). Furthermore, the suitable time for both strictinin absorption and desorption was 4 hours at 37°C. The method developed here consisted of easy steps such as ZrP absorption, water washing, and 0.4% phosphoric acid solution desorption, which may facilitate the detection and isolation of strictinin from different samples

The characterization and expression analysis under stress conditions of PCST1 in Arabidopsis

Analysis of PCST1 expression characteristics and the role of PCST1 in response to osmotic stress in Arabidopsis thaliana. The structure of PCST1 was analyzed using Bioinformatics method. Real-time PCR, GUS tissue localization and subcellular localization were adopted to analyze the expression pattern of PCST1 in Arabidopsis. To validate the transgenic positive strain of PCST1 using Real-time PCR, overexpression experiments were performed in wild type. Full-length cDNA was cloned and connected into a binary vector with 35S promoter, and the construction was transformed into wild type. With NaCl and mannitol treatments, the germination rate, green leaves rate, physiological indexes were carried out and counted in Arabidopsis with overexpression of PCST1 and T-DNA insertion mutants. The molecular mechanism of PCST1 in response to osmotic stress in Arabidopsis was analyzed. Based on the bioinformatic analysis, PCST1 is a hydrophobin with 403 amino acids, and the molecular weight is 45.3236 KDa. It contains only the START (the lipid/sterol – binding StAR – related lipid transfer protein domains) conservative domain. PCST1 possesses phosphatidylcholine binding sites and transmembrane region. Expression pattern analysis showed that expression of PCST1 increased with time. The PCST1 widely expressed in Arabidopsis, including roots, axils of stem leaves, flowers (sepal, conductive tissue of the petal, thrum, anther and stigmas), and the top and basal parts of the siliquas. It mainly localized in cell membrane. The overexpression of PCST1 enhanced the sensitivity to osmotic stress in Arabidopsis based on the germination rate. While expression of PCST1 decreased, and the sensitivity to osmotic stress had no obvious change in Arabidopsis. Its molecular mechanism study showed, that PCST1 response to osmotic stress resistance by regulating the proline, betaine synthesis, as well as the expression of key genes SOS, NCED, CIPK. PCST1 is composed of 403 amino acids. The START conservative domain, a transmembrane structure, the phosphatidyl choline binding sites are contained in PCST1. It is localized in cytoplasmic membrane. The PCST1 widely expressed in the root, leaf, flower and siliquas. NaCl and mannitol suppressed the expression of PCST1 and PCST1 can negatively control action of Arabidopsis in the osmotic stress. PCST1 regulates the synthetic pathway of proline, betaine and the expression of SOS, NCED and CIPK in response to the osmotic stress resistance

Research on driver’s anger recognition method based on multimodal data fusion

This paper aims to address the challenge of low accuracy in single-modal driver anger recognition by introducing a multimodal driver anger recognition model. The primary objective is to develop a multimodal fusion recognition method for identifying driver anger, focusing on electrocardiographic (ECG) signals and driving behavior signals. Emotion-inducing experiments were performed employing a driving simulator to capture both ECG signals and driving behavioral signals from drivers experiencing both angry and calm moods. An analysis of characteristic relationships and feature extraction was conducted on ECG signals and driving behavior signals related to driving anger. Seventeen effective feature indicators for recognizing driving anger were chosen to construct a dataset for driver anger. A binary classification model for recognizing driving anger was developed utilizing the Support Vector Machine (SVM) algorithm. Multimodal fusion demonstrated significant advantages over single-modal approaches in emotion recognition. The SVM-DS model using decision-level fusion had the highest accuracy of 84.75%. Compared with the driver anger emotion recognition model based on unimodal ECG features, unimodal driving behavior features, and multimodal feature layer fusion, the accuracy increased by 9.10%, 4.15%, and 0.8%, respectively. The proposed multimodal recognition model, incorporating ECG and driving behavior signals, effectively identifies driving anger. The research results provide theoretical and technical support for the establishment of a driver anger system.</p