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This review summarizes our current understanding of the underlying pathomechanism, diagnosis of RA, as well as the mode of action, clinical benefits, and side-effects of the currently available DMARDs.The identification of potential microRNA (miRNA)-disease associations enables the elucidation of the pathogenesis of complex human diseases owing to the crucial role of miRNAs in various biologic processes and it yields insights into novel prognostic markers. In the consideration of the time and costs involved in wet experiments, computational models for finding novel miRNA-disease associations would be a great alternative. However, computational models, to date, are biased towards known miRNA-disease associations; this is not suitable for rare miRNAs (i.e., miRNAs with a few known disease associations) and uncommon diseases (i.e., diseases with a few known miRNA associations). This leads to poor prediction accuracies. The most straightforward way of improving the performance is by increasing the number of known miRNA-disease associations. However, due to lack of information, increasing attention has been paid to developing computational models that can handle insufficient data via a technical approach. In this paper, we present a general framework-improved prediction of miRNA-disease associations (IMDN)-based on matrix completion with network regularization to discover potential disease-related miRNAs. The success of adopting matrix factorization is demonstrated by its excellent performance in recommender systems. This approach considers a miRNA network as additional implicit feedback and makes predictions for disease associations relevant to a given miRNA based on its direct neighbors. Our experimental results demonstrate that IMDN achieved excellent performance with reliable area under the receiver operating characteristic (ROC) area under the curve (AUC) values of 0.9162 and 0.8965 in the frameworks of global and local leave-one-out cross-validations (LOOCV), respectively. Further, case studies demonstrated that our method can not only validate true miRNA-disease associations but also suggest novel disease-related miRNA candidates.Suitable immobilization of a biorecognition element, such as an antigen or antibody, on a transducer surface is essential for development of sensitive and analytically reliable immunosensors. In this review, we report on (1) methods of antibody prefunctionalization using electroactive probes, (2) methods for immobilization of such conjugates on the surfaces of electrodes in electrochemical immunosensor construction and (3) the use of antibody-electroactive probe conjugates as bioreceptors and sensor signal generators. We focus on different strategies of antibody functionalization using the redox active probes ferrocene (Fc), anthraquinone (AQ), thionine (Thi), cobalt(III) bipyridine (Co(bpy)33+), Ru(bpy)32+ and horseradish peroxidase (HRP). In addition, new possibilities for antibody functionalization based on bioconjugation techniques are presented. We discuss strategies of specific, quantitative antigen detection based on (i) a sandwich format and (ii) a direct signal generation scheme. Further, the integration of different nanomaterials in the construction of these immunosensors is presented. Lastly, we report the use of a redox probe strategy in multiplexed analyte detection.Microorganisms have begun to develop resistance because of inappropriate and extensive use of antibiotics in the hospital setting. Therefore, it seems to be necessary to find a way to tackle these pathogens by developing new and effective antimicrobial agents. Carbon nanotubes (CNTs) have attracted growing attention because of their remarkable mechanical strength, electrical properties, and chemical and thermal stability for their potential applications in the field of biomedical as therapeutic and diagnostic nanotools. However, the impact of carbon nanotubes on microbial growth has not been fully investigated. The primary purpose of this research study is to investigate the antimicrobial activity of CNTs, particularly double-walled and multi-walled nanotubes on representative pathogenic strains such as Gram-positive bacteria Staphylococcus aureus, Gram-negative bacteria Pseudomonas aeruginosa, Klebsiella pneumoniae, and fungal strain Candida albicans. The dispersion ability of CNT types (double-walled and muts ability to disperse in aqueous solution. Non-covalent method of CNTs dispersion preserved their structure and increased microbial growth inhibition as a result. Multi-walled CNTs exhibited higher antimicrobial activity compared to double-walled CNTs against selected pathogens. Vector competence is an important parameter in evaluating whether a species plays a role in transmission of an arbovirus. click here Although the protocols are similar, interpretation of results is unique given the specific interactions that exist between a mosquito population and a viral genotype. Here, we assessed the infection (IR), dissemination (DR), and transmission (TR) rates of Cx. pipiens s.l., collected from Iran, for West Nile virus (WNV) lineage 1a. We showed that Cx. pipiens s.l. mosquitoes in Iran were susceptible to WNV with IR up to 89.7%, 93.6%, and 83.9% at 7, 14, and 21 days post-infection (dpi) respectively. In addition, DR and TR reached respectively 92.3% and 75.0% at 21 dpi, and the number of viral particles delivered with saliva reached up to 1.33 × 105 particles. Therefore, an unexpected high risk of WNV dissemination in the region where Cx. pipiens s.l. mosquitoes are well established should be considered carefully and surveillance measures implemented accordingly.Background and Objectives An essential part of occupational stress management is identifying target groups and developing a wellbeing program that tailors interventions to the specific needs of the target groups. This study aims to explore whether psychosocial risk determinants and organizational intervention objects differ across employees' groups based on sociodemographic factors in a Lithuanian public primary healthcare institution. Methods All 690 health workers of the institution were invited to participate (response rate 68 %) in a cross-sectional survey between February and March 2017. The questionnaire contained items related to sociodemographic factors (gender, age, job seniority, education, and occupation), 14 psychosocial risk determinants, and 10 organisational intervention objects. Results The results of the study showed that differences by gender were not statistically significant except for one organisational intervention object (work-life balance). Only a few organisational intervention objects (justice of reward, matching to the job demand, and variety of tasks) had mean rank scores differing statistically across age and job seniority groups.