Relaxed acceptor site specificity of bacterial oligosaccharyltransferase in vivo

A number of proteobacteria carry the genetic information to perform N-linked glycosylation, but only the protein glycosylation (pgl) pathway of Campylobacter jejuni has been studied to date. Here, we report that the pgl gene cluster of Campylobacter lari encodes for a functional glycosylation machinery that can be reconstituted in Escherichia coli. We determined that the N-glycan produced in this system consisted of a linear hexasaccharide. We found that the oligosaccharyltransferase (OST) of C. lari conserved a predominant specificity for the primary sequence D/E-X−1-N-X+1-S/T (where X−1 and X+1 can be any amino acid but proline). At the same time, we observed that this enzyme exhibited a relaxed specificity toward the acceptor site and modified asparagine residues of a protein at sequences DANSG and NNNST. Moreover, C. lari pgl glycosylated a native E. coli protein. Bacterial N-glycosylation appears as a useful tool to establish a molecular description of how single-subunit OSTs perform selection of glycosyl acceptor site

Relaxed acceptor site specificity of bacterial oligosaccharyltransferase in vivo

A number of proteobacteria carry the genetic information to perform N-linked glycosylation, but only the protein glycosylation (pgl) pathway of Campylobacter jejuni has been studied to date. Here, we report that the pgl gene cluster of Campylobacter lari encodes for a functional glycosylation machinery that can be reconstituted in Escherichia coli. We determined that the N-glycan produced in this system consisted of a linear hexasaccharide. We found that the oligosaccharyltransferase (OST) of C. lari conserved a predominant specificity for the primary sequence D/E-X−1-N-X+1-S/T (where X−1 and X+1 can be any amino acid but proline). At the same time, we observed that this enzyme exhibited a relaxed specificity toward the acceptor site and modified asparagine residues of a protein at sequences DANSG and NNNST. Moreover, C. lari pgl glycosylated a native E. coli protein. Bacterial N-glycosylation appears as a useful tool to establish a molecular description of how single-subunit OSTs perform selection of glycosyl acceptor site

Salvianolic Acid B Prevents Arsenic Trioxide-Induced Cardiotoxicity In Vivo and Enhances Its Anticancer Activity In Vitro

Clinical attempts to reduce the cardiotoxicity of arsenic trioxide (ATO) without compromising its anticancer activities remain to be an unresolved issue. In this study, we determined whether Sal B can protect against ATO-induced cardiac toxicity in vivo and increase the toxicity of ATO toward cancer cells. Combination treatment of Sal B and ATO was investigated using BALB/c mice and human hepatoma (HepG2) cells and human cervical cancer (HeLa) cells. The results showed that the combination treatment significantly improved the ATO-induced loss of cardiac function, attenuated damage of cardiomyocytic structure, and suppressed the ATO-induced release of cardiac enzymes into serum in BALB/c mouse models. The expression levels of Bcl-2 and p-Akt in the mice treated with ATO alone were reduced, whereas those in the mice given the combination treatment were similar to those in the control mice. Moreover, the combination treatment significantly enhanced the ATO-induced cytotoxicity and apoptosis of HepG2 cells and HeLa cells. Increases in apoptotic marker cleaved poly (ADP-ribose) polymerase and decreases in procaspase-3 expressions were observed through western blot. Taken together, these observations indicate that the combination treatment of Sal B and ATO is potentially applicable for treating cancer with reduced cardiotoxic side effects

Forest stand spectrum reconstruction using spectrum spatial feature gathering and multilayer perceptron

IntroductionThree-dimensional spectral distributions of forest stands can provide spatial information on the physiological and biochemical status of forests, which is vital for forest management. However, three-dimensional spectral studies of forest stands are limited.MethodsIn this study, LiDAR and multispectral data were collected from Masson pine stands in southern Fujian Province, China, and a method was proposed for inverting forest spectra using point clouds as a unit. First, multispectral values were mapped to a point cloud, and the isolated forest algorithm combined with K-means clustering was applied to characterize fusion data. Second, five deep learning algorithms were selected for semantic segmentation, and the overall accuracy (oAcc) and mean intersection ratio (mIoU) were used to evaluate the performance of various algorithms on the fusion data set. Third, the semantic segmentation model was used to reconfigure the class 3D spectral distribution, and the model inversion outcomes were evaluated by the peaks and valleys of the curve of the predicted values and distribution gaps.ResultsThe results show that the correlations between spectral attributes and between spatial attributes were both greater than 0.98, while the correlation between spectral and spatial attributes was 0.43. The most applicable method was PointMLP, highest oAcc was 0.84, highest mIoU was 0.75, peak interval of the prediction curve tended to be consistent with the true values, and maximum difference between the predicted value and the true value of the point cloud spectrum was 0.83.DiscussionExperimental data suggested that combining spatial fusion and semantic segmentation effectively inverts three-dimensional spectral information for forest stands. The model could meet the accuracy requirements of local spectral inversion, and the NIR values of stands in different regions were correlated with the vertical height of the canopy and the distance from the tree apex in the region. These findings improve our understanding of the precise three-dimensional spectral distribution of forests, providing a basis for near-earth remote sensing of forests and the estimation of forest stand health

A producer-retailer incorporated multi-item EPQ problem with delayed differentiation, the expedited rate for common parts, multi-delivery and scrap

Transnational producers facing the present-day competitive global supply-chain environments need to pursue the most appropriate manufacturing scheme, quality screening task, and stock shipping plan to satisfy customer’s timely multi-item requirements under minimum overall product fabrication-delivery expenses. This study develops a producer-retailer incorporated multi-item two-stage economic production quantity- (EPQ-) based system with delayed differentiation, expedited-rate for common parts, multiple deliveries plan, and random scrap. It aims to assist current manufacturing firms in achieving the aforementioned operating goals. Mathematical methods help us build an analytical model to explicitly portray the studied problem’s features and derive its overall system expenses. Hessian matrix equations and optimization approaches help us prove convexity and derive the cost-minimized fabrication- delivery decision. This study gives a simulated example to illustrate the research outcome’s applicability and the proposed model’s capabilities numerically. Consequently, diverse crucial information becomes obtainable to the manufacturers to facilitate various operating decision makings as follows: (i) the cost-minimized fabrication-delivery policy; (ii) the behavior of system’s overall expenses and operating policy regarding mean scrap rate, and different relationships between common part’s values and completion-rate; (iii) the system’s detailed cost components; (iv) the system’s overall expenses, utilization, and common part’s uptime concerning different common part’s expedited rates; and (v) the collective effects of critical system features on the overall expenses, uptime, and optimal cycle length, etc

CD100 up-Regulation Induced by Interferon-α on B Cells Is Related to Hepatitis C Virus Infection

Objectives: CD100, also known as Sema4D, is a member of the semaphorin family and has important regulatory functions that promote immune cell activation and responses. The role of CD100 expression on B cells in immune regulation during chronic hepatitis C virus (HCV) infection remains unclear. Materials and Methods: We longitudinally investigated the altered expression of CD100, its receptor CD72, and other activation markers CD69 and CD86 on B cells in 20 chronic HCV-infected patients before and after treatment with pegylated interferon-alpha (Peg-IFN-α) and ribavirin (RBV) by flow cytometry. Results: The frequency of CD5+ B cells as well as the expression levels of CD100, CD69 and CD86 was significantly increased in chronic HCV patients and returned to normal in patients with sustained virological response after discontinuation of IFN-α/RBV therapy. Upon IFN-α treatment, CD100 expression on B cells and the two subsets was further up-regulated in patients who achieved early virological response, and this was confirmed by in vitro experiments. Moreover, the increased CD100 expression via IFN-α was inversely correlated with the decline of the HCV-RNA titer during early-phase treatment. Conclusions: Peripheral B cells show an activated phenotype during chronic HCV infection. Moreover, IFN-α therapy facilitates the reversion of disrupted B cell homeostasis, and up-regulated expression of CD100 may be indirectly related to HCV clearance

Bemisia tabaci vesicle-associated membrane protein 2 interacts with begomoviruses and plays a role in virus acquisition

Begomoviruses cause substantial losses to agricultural production, especially in tropical and subtropical regions, and are exclusively transmitted by members of the whitefly Bemisia tabaci species complex. However, the molecular mechanisms underlying the transmission of begomoviruses by their whitefly vector are not clear. In this study, we found that B. tabaci vesicle-associated membrane protein 2 (BtVAMP2) interacts with the coat protein (CP) of tomato yellow leaf curl virus (TYLCV), an emergent begomovirus that seriously impacts tomato production globally. After infection with TYLCV, the transcription of BtVAMP2 was increased. When the BtVAMP2 protein was blocked by feeding with a specific BtVAMP2 antibody, the quantity of TYLCV in B. tabaci whole body was significantly reduced. BtVAMP2 was found to be conserved among the B. tabaci species complex and also interacts with the CP of Sri Lankan cassava mosaic virus (SLCMV). When feeding with BtVAMP2 antibody, the acquisition quantity of SLCMV in whitefly whole body was also decreased significantly. Overall, our results demonstrate that BtVAMP2 interacts with the CP of begomoviruses and promotes their acquisition by whitefl

Differential transmission of Sri Lankan cassava mosaic virus by three cryptic species of the whitefly Bemisia tabaci complex

In recent years, Sri Lankan cassava mosaic virus (SLCMV), a begomovirus (genus Begmovirus, family Geminiviridae) causing cassava mosaic disease in Asia, poses serious threats to cassava cultivation in Asia. However, the transmission of SLCMV in the areas into which it has recently been introduced remain largely unexplored. Here we have compared the transmission efficiencies of SLCMV by three widely distributed whitefly species in Asia, and found that only Asia II 1 whiteflies were able to transmit this virus efficiently. The transmission efficiencies of SLCMV by different whitefly species were found to correlate positively with quantity of virus in whitefly whole body. Further, the viral transmission efficiency was found to be associated with varied ability of virus movement within different species of whiteflies. These findings provide detailed information regarding whitefly transmission of SLCMV, which will help to understand the spread of SLCMV in the field, and facilitate the prediction of virus epidemics

Unsupervised Domain Adaptation for Automated Knee Osteoarthritis Phenotype Classification

Purpose: The aim of this study was to demonstrate the utility of unsupervised domain adaptation (UDA) in automated knee osteoarthritis (OA) phenotype classification using a small dataset (n=50). Materials and Methods: For this retrospective study, we collected 3,166 three-dimensional (3D) double-echo steady-state magnetic resonance (MR) images from the Osteoarthritis Initiative dataset and 50 3D turbo/fast spin-echo MR images from our institute (in 2020 and 2021) as the source and target datasets, respectively. For each patient, the degree of knee OA was initially graded according to the MRI Osteoarthritis Knee Score (MOAKS) before being converted to binary OA phenotype labels. The proposed UDA pipeline included (a) pre-processing, which involved automatic segmentation and region-of-interest cropping; (b) source classifier training, which involved pre-training phenotype classifiers on the source dataset; (c) target encoder adaptation, which involved unsupervised adaption of the source encoder to the target encoder and (d) target classifier validation, which involved statistical analysis of the target classification performance evaluated by the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy. Additionally, a classifier was trained without UDA for comparison. Results: The target classifier trained with UDA achieved improved AUROC, sensitivity, specificity and accuracy for both knee OA phenotypes compared with the classifier trained without UDA. Conclusion: The proposed UDA approach improves the performance of automated knee OA phenotype classification for small target datasets by utilising a large, high-quality source dataset for training. The results successfully demonstrated the advantages of the UDA approach in classification on small datasets.Comment: Junru Zhong and Yongcheng Yao share the same contribution. 17 pages, 4 figures, 4 table