Identification of novel bioactive proteins and their produced oligopeptides from Torreya grandis nuts using proteomic based prediction

Torreya grandis nut is a chief functional food in China consumed for centuries. Besides its rich protein composition, increasing studies are now focusing on T. grandis functional proteins that have not yet identified. In this study, liquid chromatography coupled with mass spectrometry detection of smaller and major proteins, revealed that the major peptide was 36935.00 Da. Proteome sequencing annotated 142 proteins in total. Bioactive proteins such as defensin 4 was annotated and its anti-microbial function was verified. Finally, functional oligopeptides were predicted by searching sequences of digested peptides in databases. Ten group of oligopeptides were suggested to exhibit antioxidant, Angiotensin-converting enzyme inhibition, anti-inflammatory. The predicted antioxidant activity was experimentally validated. It is interesting that a peptide GYCVSDNN digested from defensin 4 showed antioxidant activity. This study reports novel functional peptides from T. grandis nuts that have not been isolated and/or included as functional ingredients in nutraceuticals and in food industry

Analysis on the Filament Structure Evolution in Reset Transition of Cu/HfO2/Pt RRAM Device

The resistive switching (RS) process of resistive random access memory (RRAM) is dynamically correlated with the evolution process of conductive path or conductive filament (CF) during its breakdown (rupture) and recovery (reformation). In this study, a statistical evaluation method is developed to analyze the filament structure evolution process in the reset operation of Cu/HfO₂/Pt RRAM device. This method is based on a specific functional relationship between the Weibull slopes of reset parameters' distributions and the CF resistance (R on). The CF of the Cu/HfO₂/Pt device is demonstrated to be ruptured abruptly, and the CF structure of the device has completely degraded in the reset point. Since no intermediate states are generated in the abrupt reset process, it is quite favorable for the reliable and stable one-bit operation in RRAM device. Finally, on the basis of the cell-based analytical thermal dissolution model, a Monte Carlo (MC) simulation is implemented to further verify the experimental results. This work provides inspiration for RRAM reliability and performance design to put RRAM into practical application

CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke

Segmenting stroke lesions from T1-weighted MR images is of great value for large-scale stroke rehabilitation neuroimaging analyses. Nevertheless, there are great challenges with this task, such as large range of stroke lesion scales and the tissue intensity similarity. The famous encoder-decoder convolutional neural network, which although has made great achievements in medical image segmentation areas, may fail to address these challenges due to the insufficient uses of multi-scale features and context information. To address these challenges, this paper proposes a Cross-Level fusion and Context Inference Network (CLCI-Net) for the chronic stroke lesion segmentation from T1-weighted MR images. Specifically, a Cross-Level feature Fusion (CLF) strategy was developed to make full use of different scale features across different levels; Extending Atrous Spatial Pyramid Pooling (ASPP) with CLF, we have enriched multi-scale features to handle the different lesion sizes; In addition, convolutional long short-term memory (ConvLSTM) is employed to infer context information and thus capture fine structures to address the intensity similarity issue. The proposed approach was evaluated on an open-source dataset, the Anatomical Tracings of Lesions After Stroke (ATLAS) with the results showing that our network outperforms five state-of-the-art methods. We make our code and models available at https://github.com/YH0517/CLCI_Net

Theoretical Analysis of Double Logistic Distributed Activation Energy Model for Thermal Decomposition Kinetics of Solid Fuels

The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well since the thermal decomposition normally involves multiple sub-processes of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above

Identification of a HIV Gp41-Specific Human Monoclonal Antibody With Potent Antibody-Dependent Cellular Cytotoxicity

Antibody-Dependent Cellular Cytotoxicity (ADCC) is a major mechanism of protection against viral infections in vivo. Identification of HIV-1-specific monoclonal antibodies (mAbs) with potent ADCC activity may help develop an effective HIV-1 vaccine. In present study, we isolated such human mAb, designated E10, from an HIV-1-infected patient sample by single B cell sorting and single cell PCR. E10 bound to gp140 trimer and linear peptides derived from gp41 membrane proximal external region (MPER). E10 epitope (QEKNEQELLEL) overlapped with mAb 2F5 epitope. However, E10 differentiated from 2F5 in neutralization breadth and potency, as well as ADCC activity. E10 showed low neutralization activity and narrow spectrum of neutralization compared to 2F5, but it mediated higher ADCC activity than 2F5 at low antibody concentration. Fine mapping of E10 epitope may potentiate MPER-based subunit vaccine development

The value of diffusion kurtosis imaging, diffusion weighted imaging and 18F-FDG PET for differentiating benign and malignant solitary pulmonary lesions and predicting pathological grading

ObjectiveTo explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs.Material and methodsChest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUVmax), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors.ResultsThe MK and SUVmax were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10-3 mm2/s] and 1.35 ± 0.33 [×10-3 mm2/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10-3 mm2/s] and 1.67 ± 0.33 [×10-3 mm2/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10-3 mm2/s], 1.35 ± 0.33 [×10-3 mm2/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10-3 mm2/s], 1.67 ± 0.33[×10-3 mm2/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUVmax and MK were independent predictors, the AUCs of the combination of SUVmax and MK, SUVmax, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively.ConclusionDWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs

Raw rehmannia radix polysaccharide can effectively release peroxidative injury induced by duck hepatitis A virus

Background: Duck viral hepatitis (DVH), caused by duck hepatitis A virus (DHAV), is a fatal contagious infectious disease which spreads rapidly with high morbidity and high mortality, and there is no effective clinical drug against DVH.Materials and Methods: Raw Rehmannia Radix Polysaccharide (RRRP), Lycii Fructus polysaccharides and Astragalus Radix polysaccharides were experimented in vitro and in vivo. Mortality rate, livers change, liver lesion scoring, peroxidative injury evaluation indexes in vitro and in vivo, and hepatic injury evaluation indexes of optimal one were detected and observed in this experiment.Results: RRRP could reduce mortality with the protection rate about 20.0% compared with that of the viral control (VC) group, finding that RRRP was the most effective against DHAV. The average liver scoring of the VC, blank control (BC), RRRP groups were 3.5, 0, 2.1. Significant difference (P<0.05) appeared between any two groups, demonstrating that it can alleviate liver pathological change. RRRP could make the hepatic injury evaluation indexes similar to BC group while the levels of the VC group were higher than other two groups in general. The levels of SOD, GSH-Px, CAT of RRRP group showed significant higher than that of VC group while the levels of NOS and MDA showed the opposite tendency, thus, RRRP could release peroxidative injury.Conclusion: RRRP was the most effective against duck hepatitis A virus (DHAV). RRRP could reduce mortality, alleviate liver pathological change, down-regulate liver lesion score, release peroxidative injury and hepatic injury. The antiviral and peroxidative injury releasing activity of RRRP for DHAV provided a platform to test novel drug strategies for hepatitis A virus in human beings.Keywords: Raw Rehmannia Radix Polysaccharide; duck hepatitis A virus; peroxidative injury; hepatic injur