Optimized Two-Stage Ensemble Model for Mammography Mass Recognition

ObjectivesMammography mass recognition is considered as a very challenge pattern recognition problem due to the high similarity between normal and abnormal masses. Therefore, the main objective of this study is to develop an efficient and optimized two-stage recognition model to tackle this recognition task.Material and methodsBasically, the developed recognition model combines an ensemble of linear Support Vector Machine (SVM) classifiers with a Reinforcement Learning-based Memetic Particle Swarm Optimizer (RLMPSO) as RLMPSO-SVM recognition model. RLMPSO is used to construct a two-stage of an ensemble of linear SVM classifiers by performing simultaneous SVM parameters tuning, features selection, and training instances selection. The first stage of RLMPSO-SVM recognition model is responsible about recognizing the input ROI mammography masses as normal or abnormal mass pattern. Meanwhile, the second stage of RLMPSO-SVM model used to perform further recognition for abnormal ROIs as malignant or benign masses. In order to evaluate the effectiveness of RLMPSO-SVM, a total of 1187 normal ROIs, 111 malignant ROIs, and 135 benign ROIs were randomly selected from DDSM database images.ResultsReported results indicated that RLMPSO-SVM model was able to achieve performances of 97.57% sensitivity rate with 97.86% specificity rate for normal vs. abnormal recognition cases. For malignant vs. benign recognition performance it was reported of 97.81% sensitivity rate with 96.92% specificity rate.ConclusionReported results indicated that RLMPSO-SVM recognition model is an effective tool that could assist the radiologist during the diagnosis of the presented abnormalities in mammography images. The outcomes indicated that RLMPSO-SVM significantly outperformed various SVM-based models as well as other variants of computational intelligence models including multi-layer perceptron, naive Bayes classifier, and k-nearest neighbor.     

Efficient Editing of an Adenoviral Vector Genome with CRISPR/Cas9

Immunotherapy based on genetic modification of T cells has played an important role in the treatment of tumors and viral infections. Moreover, adenoviral vectors engineered with improved safety due to their inability to integrate into the host genome have been key in the clinical application of T cell therapy. However, the commonly used adenoviral vector Ad5 exhibits low efficiency of infection of human T cells and the details of the intracellular trafficking pathway of adenoviral vectors in human primary T cells remains unclear. Resolution of these issues will depend on successful modification of the adenoviral vector. To this end, here we describe the successful establishment of a simple and efficient method for editing adenoviral vectors in vitro using the CRISPR-Cas9 gene editing system to target the adenoviral fiber gene. Electronic supplementary materialThe online version of this article (10.1007/s12088-020-00905-3) contains supplementary material, which is available to authorized users.     

乳酸菌作为药物分子粘膜投递载体的研究进展

乳酸菌是被公认为安全的食品级微生物,广泛地应用于食品生产、保存以及作为益生菌促进人类健康。鉴于发展有效的投递药物分子策略的需要,乳酸菌成为了极有吸引力的用于口服、鼻饲及阴道进行粘膜投递药物分子的活载体。用乳酸菌作为药物分子的投递载体,安全性好,且可直接合成并投递目标蛋白,显著降低药物生产成本。到目前为止,乳酸菌作为粘膜投递载体,已成功地向粘膜组织投递了一系列功能蛋白用以治疗多种疾病。文中综述了近20年的数据,重点聚焦乳酸菌作为药物分子投递载体的发展和应用,为今后乳酸菌作为活载体的临床研究提供一定参考。     

A Self-Biomineralized Novel Adenovirus Vectored COVID-19 Vaccine for Boosting Immunization of Mice

Virologica Sinica - SARS-CoV-2 has caused more than 3.8 million deaths worldwide, and several types of COVID-19 vaccines are urgently approved for use, including adenovirus vectored vaccines....     

Quality Control Testing,Characterization and Critical Quality Attributes of Adeno-Associated Virus Vectors Used for Human Gene Therapy

For adeno-associated virus (AAV)-based human gene therapy, challenges for the translation of promising research results to successful clinical development include optimization of vector design and manufacturing processes to ensure that vectors prepared for administration to human subjects have attributes consistent with safe and durable expression. This article briefly reviews quality control methods for routine testing and supplemental characterization of AAV vectors for investigational product development. The relationship of vector and manufacturing process design with product critical quality attributes is discussed.     

Active and machine learning-based approaches to rapidly enhance microbial chemical production

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.     

西方马脑炎核酸疫苗表达载体构建及免疫原性研究

为构建西方马脑炎病毒(western equine encephalomyelitis virus,WEEV)结构基因C-E3-E2-6k-E1重组真核表达载体,并研究其作为核酸疫苗的免疫原性.采用PCR方法扩增目的基因,酶切之后连接到pcDNA3.1上构建真核表达载体pcDNA3.1-C-E,用酶切和测序分析方法鉴定正确后,重组质粒被转染到293T细胞,经电镜检测和间接免疫荧光方法证明基因可以表达后,用该重组质粒免疫小鼠,免疫后检测实验组小鼠外周血中CD4+T细胞/CD8+T细胞比例和血清中细胞因子IL-2、IL-4及IFN-γ浓度,以上实验组各项免疫指标与对照组相比差异均显著(P＜ 0.05);ELISA方法检测实验组小鼠血清中WEEV的IgG抗体效价是1∶16.研究结果表明重组质粒pcDNA3.1-C-E可在细胞中获得瞬时表达,并且重组质粒作为核酸疫苗能够刺激小鼠产生免疫反应,具有较强免疫原性,为今后WEEV核酸疫苗研制奠定了良好基础.     

4E-BP1、4E-BP1-4A 重组慢病毒载体的构建及对胃癌细胞 HGC27生长的影响

目的:构建4E-BP1及其 T37A、T46A、S65A、T70A 突变体4E-BP1-4A 基表达的重组慢病毒载体,研究其对胃癌 HGC27细胞生长的影响.方法:PCR 扩增4E-BP1基及其突变体4E-BP1-4A 基并克隆到 pCDH 载体,构建成 pCDH-4E-BP1、pCDH-4E-BP1-4A,将其与包装载体共转染293T 细胞,包装成 Lenti-4E-BP1及 Lenti-4E-BP1-4A重组慢病毒载体,将此慢病毒感染胃癌 HGC27细胞,Western 印迹鉴定病毒载体介导的4E-BP1、4E-BP1-4A 蛋白的表达,MTT、克隆形成和软琼脂方法研究过量表达4E-BP1、4E-BP1-4A 对胃癌 HGC27细胞生长的影响.结果:包装成 Lenti-4E-BP1及 Lenti-4E-BP1-4A 重组慢病毒载体,并将此慢病毒载体感染胃癌 HGC27细胞;MTT、克隆形成、软琼脂实验表明过量表达4E-BP1可抑制胃癌 HGC27细胞的生长,过量表达4E-BP1-4A 时抑制效果更明显.结论:构建了4E-BP1、4E-BP1-4A 的重组慢病毒表达载体,在胃癌 HGC27细胞中过量表达4E-BP1可抑制细胞生长,过量表达4E-BP1-4A 的抑制效果更明显.