Gardy Loo 2010 Fall

https://commons.lib.jmu.edu/gardyloo201019/1015/thumbnail.jp

Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in chinese patients with lung squamous cell carcinoma

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy

Diagnosis of mixed infection and a primary immunodeficiency disease using next-generation sequencing: a case report

Major Histocompatibility Complex Class II (MHC II) deficiency is a rare primary immunodeficiency disorder (PID) with autosomal recessive inheritance pattern. The outcome is almost fatal owing to delayed diagnosis and lacking of effective therapy. Therefore, prompt diagnosis, timely and effective treatment are critical. Here, we report a 117-day-old boy with diarrhea, cough, cyanosis and tachypnea who was failed to be cured by empiric antimicrobial therapy initially and progressed to severe pneumonia and respiratory failure. The patient was admitted to the pediatric intensive care unit (PICU) immediately and underwent a series of tests. Blood examination revealed elevated levels of inflammatory markers and cytomegalovirus DNA. Imaging findings showed signs of severe infection of lungs. Finally, the diagnosis was obtained mainly through next-generation sequencing (NGS). We found out what pathogenic microorganism he was infected via repeated conventional detection methods and metagenomic next-generation sequencing (mNGS) of sputum and bronchoalveolar lavage fluid (BALF). And his whole exome sequencing (WES) examination suggested that CIITA gene was heterozygous mutation, a kind of MHC II deficiency diseases. After aggressive respiratory support and repeated adjustment of antimicrobial regimens, the patient was weaned from ventilator on the 56th day of admission and transferred to the immunology ward on the 60th day. The patient was successful discharged after hospitalizing for 91 days, taking antimicrobials orally to prevent infections post-discharge and waiting for stem cell transplantation. This case highlights the potential importance of NGS in providing better diagnostic testing for unexplained infection and illness. Furthermore, pathogens would be identified more accurately if conventional detection techniques were combined with mNGS

Urban Green Space Planning and Design Based on Big Data Analysis and BDA-UGSPD Model

Green cities are described as the environmental influences by expanding recycling, decreasing waste, increasing housing density, lowering emissions while intensifying open space, and boosting sustainable local businesses. Green infrastructures (GI) are progressively related to urban water management for long-term transitions and immediate solutions towards sustainability. Urban green spaces (UGS) play a vital role in conserving urban environment sustainability by giving various ecology services. In this study, big data analytics-based urban green space planning design (BDA-UGSPD) has been introduced. Luohe city and the Shali River area have been chosen as the study area owing to the high number and a considerable assortment of UGS. Monitoring has been conducted in the Shali river to evaluate water quality for irrigation for agriculture. The Master Plan Scenario had a compact green space system, and the urban land use layout has been categorized by systematization and networking, and it did not consider the service capacity of green spaces. The Planning Guidance Scenario initialized constraint states, which provide more rigorous and effective urban spaces. It enhanced the service functions of the green space model layout. The simulation findings illustrate that the proposed BDA-UGSPD model enhances the land-use classification accuracy ratio by 92.0%, probability ratio by 90.6%, decision-making ratio by 95.0%, climate change adaptation ratio by 94.5%, water quality assessment ratio by 95.9%, and reduces the root mean square error ratio by 9.7% compared to other popular approaches

Efficiency Evaluation and Influencing Factors Analysis of Logistics Industry based on Multiobjective Intelligent Computing

In logistics industry of 12 provinces along China’s new western land-sea corridor from 2010 to 2019, this research employed three-stage SBM model that considers undesirable output to measure logistics industrial efficiency and the panel Tobit model to investigate variables impacting logistics efficiency. The study found that after controlling for environmental variables and statistical noise, the logistics industrial efficiency in China’s new western land-sea corridor has improved, and the logistics sector efficiency of each province has spatial variability. Generally speaking, the south part goes up and the north part goes down; industrial structure, logistics transportation intensity, and economic development have a favorable influence on logistics sector efficiency. The urbanization rate, government support level, level of infrastructure, and degree of openness all have a negative influence on efficiency. Finally, relevant policy considerations such as logistics transport intensity, pure technical efficiency, scale efficiency, and external environment are proposed

Silencing of a Cotton Actin-Binding Protein GhWLIM1C Decreases Resistance against <i>Verticillium dahliae</i> Infection

LIM proteins are widely spread in various types of plant cells and play diversely crucial cellular roles through actin cytoskeleton assembly and gene expression regulation. Till now, it has not been clear whether LIM proteins function in plant pathogen defense. In this study, we characterized a LIM protein, GhWLIM1C, in upland cotton (Gossypium hirsutum). We found that GhWLIM1C could bind and bundle the actin cytoskeleton, and it contains two LIM domains (LIM1 and LIM2). Both the two domains could bind directly to the actin filaments. Moreover, the LIM2 domain additionally bundles the actin cytoskeleton, indicating that it possesses a different biochemical activity than LIM1. The expression of GhWLIM1C responds to the infection of the cotton fungal pathogen Verticillium dahliae (V. dahliae). Silencing of GhWLIM1C decreased cotton resistance to V. dahliae. These may be associated with the down regulated plant defense response, including the PR genes expression and ROS accumulation in the infected cotton plants. In all, these results provide new evidence that a plant LIM protein functions in plant pathogen resistance and the assembly of the actin cytoskeleton are closely related to the triggering of the plant defense response

Energy absorption within elastic range for AZ31 magnesium alloy

Energy absorption for AZ31 magnesium Alloy was investigated with Split Hopkinson Pressure Bar using single stress wave so as to avoid multiple stress wave loading. The stress wave amplitude, which was in elastic stress range and propagated along the AZ31 magnesium bar, was reduced with increasing propagating distance, and with increasing stress wave amplitude, the stress wave amplitude reduction along the magnesium bar was increased losing more energy as compared with that of the stress wave with lower amplitude. The drastically decreased stress wave amplitude could be explained based on dislocations movements, which was similar to the established theory of damping for the explanation of the energy loss during cyclic loading. However, it was not the case for LY12 aluminum alloy: the stress wave amplitude changed slightly without drastic energy loss regardless of the variation of stress wave amplitude

A Novel Fault-Tolerant Approach for Dynamic Redundant Path Selection Service Migration in Vehicular Edge Computing

Vehicular Edge Computing (VEC) provides users with low-latency and highly responsive services by deploying Edge Servers (ESs) close to applications. In practice, vehicles are usually moving rapidly. To ensure the continuity of services, edge service migration technology is in high need, by which an application, infrastructure or any edge-hosted applications or services are not locked into a single vendor and allowed to shift between different edge resource vendors. Nevertheless, due to their complex and dynamic nature, real edge computing environments are error and fault prone and thus the reliability of edge service migrations can be easily compromised if the proactive measures are not taken to counter failures at different levels. In this paper, we propose a novel fault-tolerant approach for Dynamic Redundant Path Selection service migration (DRPS). The DRPS approach consists of path selection algorithm and service migration algorithm. The path selection algorithm is capable of evaluating time-varying failure rates of ESs by leveraging a sliding window-based model and identifying a set of service migration paths. The service migration algorithm incorporates resubmission and replication mechanisms as well and decides edge service migration schemes by choosing multiple redundant migration paths. We also conduct extensive simulations and show that our proposed method outperforms traditional solutions by 17.45%, 13.17%, and 7.22% in terms of ACT, TCR, and AFC, respectively