Treating Arterial Ageing in Patients with Diabetes: From Mechanisms to Effective Drugs

Diabetes mellitus is a major healthcare problem. It is not only characterized by hyperglycemia and chronic complications, but in longer lasting diabetes and a longer living population, it is also associated with accelerated arterial ageing, which importantly contributes to cardiovascular complications. The accelerated arterial ageing in patients with diabetes should be considered separately from arterial ageing in patients without diabetes. Basic and clinical research have allowed better insight into the mechanisms of arterial ageing. In a simplified mechanistic way, it could be considered that the three tightly connected cornerstone characteristics of arterial ageing in patients with diabetes are: phenotypic presentation as endothelial dysfunction and arterial stiffness, and the underlying basic ageing-facilitating mechanism represented as the impaired expression of genetic longevity pathways. Currently, specific drugs for preventing/treating arterial ageing are not available. Therefore, we aimed to review the capacity of available drugs, particularly antidiabetic drugs, to interfere with the arterial ageing process. In the near future, these characteristics could help to guide therapy in patients with diabetes. Overall, it appears that arterial ageing could become a new target in diabetes. The expanding knowledge regarding the capability of antidiabetic drugs and other available drugs to inhibit/delay arterial aging is therefore essential.     

智能假肢膝关节的研发要点及其研究进展综述

目的 介绍国内外智能假肢膝关节研究的主要进展,为相关领域的研发提供可借鉴的思路.方法 基于机械结构、调控方式、驱动方式,对典型假肢膝关节进行了分类比较,并从假肢穿戴者的运动意图识别、驱动控制、人机协调控制等方面做了分析.此外,对假肢膝关节在智能化研究与安全性、个性化与通用性、人机共融技术、科学伦理、关键技术等方面需要注意的问题,提出了研发要点和技术思路.结论 智能假肢膝关节应注重安全性与稳定性,规避用户在使用过程中的潜在危险因素;实现假肢控制参数的自整定和灵活适配,在个性化与通用性上达到平衡;综合考虑人—机—环境因素,实现协调控制;坚持"以人为本",在技术方法和科学伦理两个方面开展医工结合的研究;突破关键技术限制,建立完善的社会医疗康复保障服务体系.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

Molecularly imprinted macroporous polymer monolithic layers for L-phenylalanine recognition in complex biological fluids

In present work, the development of macroporous monolithic layers bearing the artificial recognition sites toward L-phenylalanine has been carried out. The set of macroporous poly(2-aminoethyl methacrylate-co-2-hydroxyethyl methacrylate-co-ethylene glycol dimethacrylate) materials with average pore size ranged in 340–1200 nm was synthesized. The applicability of Hildebrand's and Hansen's theories for the prediction of polymer compatibility with porogenic solvents was evaluated. The dependences of average pore size on theoretically calculated parameters were plotted. The linear trend detected for Hansen's theory has indicated the high suitability of this approach to select appropriate porogens. The synthesized monolithic MIP layers were tested toward the ability to rebind phenylalanine-derivative in microarray format. The influence of such factors as average pore size of the material, the concentration of template molecule in polymerization mixture, interaction time of analyte with its imprinted sites on binding efficiency were studied. The developed materials demonstrated good analyte rebinding from buffer solution with recognition factors 2.5–3.4 depending on the MIP sample. The comparable rebinding efficiency was also detected when the analysis was carried using complex biological media. The selectivity of phenylalanine binding from the equimolar mixture of structural analogues was 81.9% for free amino acid and 91.2% for labeled one.     

Genome-Wide Analyses of the Temperature-Responsive Genetic Loci of the Pectinolytic Plant Pathogenic Pectobacterium atrosepticum

Temperature is one of the critical factors affecting gene expression in bacteria. Despite the general interest in the link between bacterial phenotypes and environmental temperature, little is known about temperature-dependent gene expression in plant pathogenic Pectobacterium atrosepticum, a causative agent of potato blackleg and tuber soft rot worldwide. In this study, twenty-nine P. atrosepticum SCRI1043 thermoregulated genes were identified using Tn5-based transposon mutagenesis coupled with an inducible promotorless gusA gene as a reporter. From the pool of 29 genes, 14 were up-regulated at 18 °C, whereas 15 other genes were up-regulated at 28 °C. Among the thermoregulated loci, genes involved in primary bacterial metabolism, membrane-related proteins, fitness-corresponding factors, and several hypothetical proteins were found. The Tn5 mutants were tested for their pathogenicity in planta and for features that are likely to remain important for the pathogen to succeed in the (plant) environment. Five Tn5 mutants expressed visible phenotypes differentiating these mutants from the phenotype of the SCRI1043 wild-type strain. The gene disruptions in the Tn5 transposon mutants caused alterations in bacterial generation time, ability to form a biofilm, production of lipopolysaccharides, and virulence on potato tuber slices. The consequences of environmental temperature on the ability of P. atrosepticum to cause disease symptoms in potato are discussed.     

Sirtuins as Important Factors in Pathological States and the Role of Their Molecular Activity Modulators

Sirtuins (SIRTs), enzymes from the family of NAD⁺-dependent histone deacetylases, play an important role in the functioning of the body at the cellular level and participate in many biochemical processes. The multi-directionality of SIRTs encourages scientists to undertake research aimed at understanding the mechanisms of their action and the influence that SIRTs have on the organism. At the same time, new substances are constantly being sought that can modulate the action of SIRTs. Extensive research on the expression of SIRTs in various pathological conditions suggests that regulation of their activity may have positive results in supporting the treatment of certain metabolic, neurodegenerative or cancer diseases or this connected with oxidative stress. Due to such a wide spectrum of activity, SIRTs may also be a prognostic markers of selected pathological conditions and prove helpful in assessing their progression, especially by modulating their activity. The article presents and discusses the activating or inhibiting impact of individual SIRTs modulators. The review also gathered selected currently available information on the expression of SIRTs in individual disease cases as well as the biological role that SIRTs play in the human organism, also in connection with oxidative stress condition, taking into account the progress of knowledge about SIRTs over the years, with particular reference to the latest research results.     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

赤红球菌组氨酸激酶的融合表达和功能分析

对赤红球菌的组氨酸激酶基因进行密码子优化，将优化后的组氨酸激酶基因（rhks）构建重组表达质粒pGEX-4T-2-rhks。将此质粒导入到大肠杆菌BL21（DE3）中进行异源表达。在25 ℃和1 mmol/L异丙基-β-D-硫代吡喃半乳糖苷诱导条件下，组氨酸激酶融合蛋白（GST-RHK）获得成功表达，并具有催化活性。经谷胱甘肽琼脂糖亲和层析纯化，获得电泳纯的GST-RHK，其中纯化倍数为3.1，得率为19.5%。该蛋白大小约为72.75 kDa，Km、Vmax和Kcat值分别为20.92 μmol/L、0.17 μmol/（L·min）和1.4 min－1。野生型赤红球菌、组氨酸激酶基因增强株sdrhkE和组氨酸激酶基因敲减株sdrhkD在分别含有苯酚、甲苯、氯苯、异辛烷4 种有机溶剂的培养基中培养，菌株sdrhkD的生长情况都优于野生型赤红球菌，菌株sdrhkE的生长情况都低于野生型赤红球菌。本研究为进一步揭示赤红球菌SD3中组氨酸激酶涉及的信号转导途径与赤红球菌有机溶剂耐受性的关联机制提供一定参考依据。