ADAR Expression and Single Nucleotide Variants in Multiple Sclerosis Patients Affect the Response to Interferon Beta Therapy.

Interferon (IFN)-ß is the first-line disease management choice in multiple sclerosis (MS) with profound effects; however, in up to 50% of patients, clinical response does not occur. Ascertaining the responding state, need a long-term clinical follow-up, and this may lead to delay in use of other effective medications. IFN-induced cascade and its regulation is considered to play a major role in MS. Adenosine deaminase, RNA-specific (ADAR) dysregulation is important to IFN signaling pathway as an activity suppressor. Hence, we investigated the expression of ADAR and its single nucleotide variants of rs2229857 association with response to IFN-ß in relapsing-remitting MS patients. mRNA levels and genotyping of rs2229857 in 167 MS patients were investigated via SYBR Green real-time (RT)-quantitative polymerase chain reaction and high-resolution melting RT PCR, respectively. The allele-A in rs2229857 and higher expression of ADAR were associated with poor response to IFN-ß. Two response groups were significantly different in terms of annualized relapse rate, first symptoms, first extended disability status scale (EDSS), current EDSS, and the MS severity score. According to this study's findings, assessment of transcript levels and also variants in ADAR may be useful in identifying patients' response to IFN-ß before starting treatment. Further investigations are needed to determine the potency of ADAR to be a predictive biomarker in drug responsiveness.

miR-504 expression level is increased in multiple sclerosis patients responder to interferon-beta.

Multiple sclerosis is immune-mediated disease of the central nervous system characterized by demyelination in axons. IFN-ß is first-line treatment of MS. Biomarkers are needed for early prediction of responders and non-responders to therapy in the first month of treatment to avoid further disabilities. In this study, we analyzed the expression level of miR-504 and miR-711 in 52 IFN-ß responder patients in comparison to 53 non-responders. In the next step, the in-silico analysis was used to enrich related signaling pathways. The expression level of miR-504 was significantly higher in patients who respond to IFN-ß therapy, compared with non-responders and we obtain related statistically significant KEGG molecular signaling pathways. Our findings suggest that miR-504 can be considered as a novel biomarker for response to IFN-b therapy.

Optimal waste load allocation using graph model for conflict resolution.

In this paper, a new methodology is proposed for waste load allocation in river systems using the decision support system (DSS) for the graph model for conflict resolution II (GMCRII), multi-criteria decision making (MCDM) analysis and the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Minimization of total treatment and penalty costs and minimization of biological oxygen demand violation of standards at the check point are considered as the main objectives of this study. At first, the water quality along the river was simulated using the Streeter-Phelps (S-P) equation coupled with the MOPSO model. Thereby a trade-off curve between the objectives is obtained and a set of non-dominated solutions is selected. In the next step, the best alternative is chosen using MCDM techniques and the GMCRII DSS package and non-cooperative stability definitions. The applicability and efficiency of the methodology are examined in a real-world case study of the Sefidrud River in the northern part of Iran.