Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

Multi-Depot Pickup and Delivery Problem with Resource Sharing

Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. This study formulates and solves an MDPDP with RS (MDPDPRS). First, a bi-objective mathematical programming model that minimizes the logistics cost and the number of vehicles is constructed, in which vehicles are allowed to be used multiple times by one or multiple logistics facilities. Second, a two-stage hybrid algorithm composed of a k-means clustering algorithm, a Clark-Wright (CW) algorithm, and a nondominated sorting genetic algorithm II (NSGA-II) is designed. The k-means algorithm is adopted in the first stage to reallocate customers to logistics facilities according to the Manhattan distance between them, by which the computational complexity of solving the MDPDPRS is reduced. In the second stage, CW and NSGA-II are adopted jointly to optimize the vehicle routes and find the Pareto optimal solutions. CW algorithm is used to select the initial solution, which can increase the speed of finding the optimal solution during NSGA-II. Fast nondominated sorting operator and elite strategy selection operator are utilized to maintain the diversity of solutions in NSGA-II. Third, benchmark tests are conducted to verify the performance and effectiveness of the proposed two-stage hybrid algorithm, and numerical results prove that the proposed methodology outperforms the standard NSGA-II and multi-objective particle swarm optimization algorithm. Finally, optimization results of a real-world logistics network from Chongqing confirm the applicability of the mathematical model and the designed solution algorithm. Solving the MDPDPRS provides a management tool for logistics enterprises to improve resource configuration and optimize logistics operation efficiency

Piperine alleviates nonalcoholic steatohepatitis by inhibiting NF-κB-mediated hepatocyte pyroptosis.

PurposeNonalcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD), which has a high risk of cirrhosis, liver failure, and hepatocellular carcinoma. Piperine (Pip) is an extract of plants with powerful anti-inflammatory effects, however, the function of Pip in NASH remains elusive. Here, we aim to explore the role of Pip in NASH and to find the possible mechanisms.MethodsMethionine and choline-deficient (MCD) diets were used to induce steatohepatitis, methionine- and choline-sufficient (MCS) diets were used as the control. After Pip treatment, H&E staining, Oil Red O staining, hepatic triglyceride (TG) content and F4/80 expression were performed to analysis liver steatosis and inflammation; Masson's staining, COL1A1 and α-SMA were detected liver fibrosis. Lipopolysaccharide (LPS) -treated AML12 cells were used to as the cell model to induce pyroptosis. Then, pyroptosis-related proteins, IL-1β and LDH release were detected in vivo and in vitro. Finally, NF-κB inhibitor, BAY11-7082, was used to further demonstrate the mechanism of Pip in NASH.ResultsThe study found that Pip alleviated liver steatosis, inflammation, hepatocyte injury, and fibrosis in mice fed with MCD diets. Moreover, the pyroptosis markers (NLRP3, ASC, caspase-1 p20, and GSDMD), IL-1β and LDH release were decreased by Pip treatment. NF-κB activation was suppressed by Pip treatment and pyroptosis-related proteins were down regulated by BAY11-7082.ConclusionPip ameliorates NASH progression, and the therapeutical effect was associated with inhibition of hepatocyte pyroptosis induced by NF-κB

A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures microvascular perfusion by capturing the temporal changes of an MRI contrast agent in a target tissue, and it provides valuable information for the diagnosis and prognosis of a wide range of tumors. Quantitative DCE-MRI analysis commonly relies on the nonlinear least square (NLLS) fitting of a pharmacokinetic (PK) model to concentration curves. However, the voxel-wise application of such nonlinear curve fitting is highly time-consuming. The arterial input function (AIF) needs to be utilized in quantitative DCE-MRI analysis. and in practice, a population-based arterial AIF is often used in PK modeling. The contribution of intravascular dispersion to the measured signal enhancement is assumed to be negligible. The MR dispersion imaging (MRDI) model was recently proposed to account for intravascular dispersion, enabling more accurate PK modeling. However, the complexity of the MRDI hinders its practical usability and makes quantitative PK modeling even more time-consuming. In this paper, we propose fast MR dispersion imaging (fMRDI) to effectively represent the intravascular dispersion and highly accelerated PK parameter estimation. We also propose a deep learning-based, two-stage framework to accelerate PK parameter estimation. We used a deep neural network (NN) to estimate PK parameters directly from enhancement curves. The estimation from NN was further refined using several steps of NLLS, which is significantly faster than performing NLLS from random initializations. A data synthesis module is proposed to generate synthetic training data for the NN. Two data-processing modules were introduced to improve the model's stability against noise and variations. Experiments on our in-house clinical prostate MRI dataset demonstrated that our method significantly reduces the processing time, produces a better distinction between normal and clinically significant prostate cancer (csPCa) lesions, and is more robust against noise than conventional DCE-MRI analysis methods

CO<inf>2</inf> outgassing from the Yellow River network and its implications for riverine carbon cycle

©2015. American Geophysical Union. All Rights Reserved.CO2 outgassing across water-air interface is an important, but poorly quantified, component of riverine carbon cycle, largely because the data needed for flux calculations are spatially and temporally sparse. Based on compiled data sets measured throughout the Yellow River watershed and chamber measurements on the main stem, this study investigates CO2 evasion and assesses its implications for riverine carbon cycle. Fluxes of CO2 evasion present significant spatial and seasonal variations. High effluxes are estimated in regions with intense rock weathering or severe soil erosion that mobilizes organic carbon into the river network. By integrating seasonal changes of water surface area and gas transfer velocity (k), the CO2 efflux is estimated at 7.9±1.2TgCyr-1 with a mean k of 42.1±16.9cmh-1. Unlike in lake and estuarine environments where wind is the main generator of turbulence, k is more correlated with flow velocity changes. CO2 evasion in the Yellow River network constitutes an important pathway in its riverine carbon cycling. Analyzing the watershed-scale carbon budget indicates that 35% of the carbon exported into the Yellow River network from land is degassed during fluvial transport. The CO2 efflux is comparable to the carbon burial rate, while both larger than the fluvial export to the ocean. Comparing CO2 evasion with ecosystem productivity in the Yellow River watershed shows that its ecosystem carbon sink has previously been overestimated by >50%. Present efflux estimates are associated with uncertainty, and future work is needed to mechanistically understand CO2 evasion from the highly turbid waters.Link_to_subscribed_fulltex

Effect and potential mechanism of oncometabolite succinate promotes distant metastasis of colorectal cancer by activating STAT3

Abstract To investigate the effect of Oncometabolite succinate on colorectal cancer migration and invasion and to initially explore the underlying mechanism.Succinate acid detection kit detected the succinate content in tissues. The growth of colorectal cancer cells was measured by cck-8 assay, wound-healing migration assay and transwell migration and invasion assays, and then explored the level of epithelial-mesenchymal transition (EMT) and STAT3/ p-STAT3 expression by western blot analysis and quantitative real-time PCR for mRNA expression. We found that succinate levels were significantly higher in carcinoma tissues than paracancerous tissues. After succinate treatment, the colorectal cancer cell lines SW480 and HCT116 had enhanced migration and invasion, the expression of biomarkers of EMT was promoted, and significantly increased phosphorylation of STAT3. In vivo experiments also showed that succinate can increase p-STAT3 expression, promote the EMT process, and promote the distant metastasis of colorectal cancer in mice.Succinate promotes EMT through the activation of the transcription factor STAT3, thus promoting the migration and invasion of colorectal cancer

Split-Cre Complementation Restores Combination Activity on Transgene Excision in Hair Roots of Transgenic Tobacco

<div><p>The Cre/loxP system is increasingly exploited for genetic manipulation of DNA <i>in vitro</i> and <i>in vivo</i>. It was previously reported that inactive ‘‘split-Cre’’ fragments could restore Cre activity in transgenic mice when overlapping co-expression was controlled by two different promoters. In this study, we analyzed recombination activities of split-Cre proteins, and found that no recombinase activity was detected in the <i>in vitro</i> recombination reaction in which only the N-terminal domain (NCre) of split-Cre protein was expressed, whereas recombination activity was obtained when the C-terminal (CCre) or both NCre and CCre fragments were supplied. We have also determined the recombination efficiency of split-Cre proteins which were co-expressed in hair roots of transgenic tobacco. No Cre recombination event was observed in hair roots of transgenic tobacco when the NCre or CCre genes were expressed alone. In contrast, an efficient recombination event was found in transgenic hairy roots co-expressing both inactive split-Cre genes. Moreover, the restored recombination efficiency of split-Cre proteins fused with the nuclear localization sequence (NLS) was higher than that of intact Cre in transgenic lines. Thus, DNA recombination mediated by split-Cre proteins provides an alternative method for spatial and temporal regulation of gene expression in transgenic plants.</p></div

DNA oligo sequences utilizes in this report.

<p>DNA oligo sequences utilizes in this report.</p