Feasibility study to assess lesion repair in relapsing-remitting multiple sclerosis: A randomized controlled pilot clinical trial of domperidone add-on treatment.

BACKGROUND: Identification of therapies to promote repair in multiple sclerosis is challenged by the lack of an accepted trial model and associated outcome measures. The goal of this study was to determine the feasibility of a new trial model that enrolls disease modifying therapy (DMT)-treated relapsing-remitting multiple sclerosis (RRMS) participants who have enhancing lesions on clinically indicated brain MRI, and to explore estimates of lesion repair using MRI. METHODS: This was a single site randomized controlled clinical trial. Recruitment took place between November 2015 and January 2019, with final follow-up in February 2019. DMT-treated RRMS participants aged 18-60 years with at least one gadolinium-enhancing lesion on clinically indicated brain MRI were included. Participants were randomized 2:1 to oral domperidone add-on 10-mg three times daily for 16 weeks or no add-on treatment (control). The primary outcomes were feasibility of the model pre-defined as recruitment of 24 participants within 36 months with a 79 % completion rate, and MRI outcomes of lesion repair measured at 16 and 32 weeks using texture analysis, magnetization transfer imaging (MTI), and diffusion tensor imaging (DTI). The impact of domperidone on serum prolactin at 6 and 16 weeks was also evaluated. RESULTS: Of 237 RRMS participants screened, 17 (14 women) were randomized: 12 to domperidone add-on and 5 to control. All completed the study. Median (range) age was 38.9 (26.7-55.9) years; EDSS was 1.5 (1.0-3.5); and disease duration was 12.9 (2.9-23.3) years. Both groups showed improvement in MRI texture and diffusion fractional anisotropy (FA) at 32 weeks, and the domperidone group demonstrated additional recovery at 16 weeks in both texture and FA. There was no significant group difference in any MRI outcome. Of the 12 domperidone participants, 7 had ≥4x higher serum prolactin than normal. There were no serious adverse events. CONCLUSION: The recruitment target was not met and therefore the trial model was not feasible despite a full completion rate. The imaging techniques performed well, especially MRI texture analysis, suggesting the sample size being sufficient for estimating lesion repair. The main challenge of this trial model may be recruiting gadolinium-enhancing lesions in DMT-treated RRMS participants. Prolactin is safe and may hold promise as a remyelination therapy. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02493049.

Distinct characteristics and severity of brain magnetic resonance imaging lesions in women and men with multiple sclerosis assessed using verified texture analysis measures.

Background and goal: In vivo characterization of brain lesion types in multiple sclerosis (MS) has been an ongoing challenge. Based on verified texture analysis measures from clinical magnetic resonance imaging (MRI), this study aimed to develop a method to identify two extremes of brain MS lesions that were approximately severely demyelinated (sDEM) and highly remyelinated (hREM), and compare them in terms of common clinical variables. Method: Texture analysis used an optimized gray-level co-occurrence matrix (GLCM) method based on FLAIR MRI from 200 relapsing-remitting MS participants. Two top-performing metrics were calculated: texture contrast and dissimilarity. Lesion identification applied a percentile approach according to texture values calculated: ≤ 25 percentile for hREM and ≥75 percentile for sDEM. Results: The sDEM had a greater total normalized volume yet smaller average size, and worse MRI texture than hREM. In lesion distribution mapping, the two lesion types appeared to overlap largely in location and were present the most in the corpus callosum and periventricular regions. Further, in sDEM, the normalized volume was greater and in hREM, the average size was smaller in men than women. There were no other significant results in clinical variable-associated analyses. Conclusion: Percentile statistics of competitive MRI texture measures may be a promising method for probing select types of brain MS lesion pathology. Associated findings can provide another useful dimension for improved measurement and monitoring of disease activity in MS. The different characteristics of sDEM and hREM between men and women likely adds new information to the literature, deserving further confirmation.

Stage Analysis of Breast Cancer Metabolomics: A System Biology Approach.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women worldwide. Altered miRNA profile can disturb the metabolic homeostatic via regulation of gene expression in BC. METHODS: In the present study to evaluate which miRNA, regulate metabolic pathways according to their stage, we performed comprehensive analysis of BC expression (mRNA and miRNA) of a set of patients by comparing samples of solid tumor tissue and adjacent tissue. The mRNA and miRNA data of breast cancer were downloaded from the cancer genome database (TCGA) using TCGAbiolinks package. Differentially expressed (mRNAs and miRNAs) was determined by DESeq2 package and predict valid miRNA-mRNA pairs using multiMiR package. All analyses were performed using the R software.  Compound-reaction-enzyme-gene network was constructed using the Metscape a plugin for Cytoscape software. Then, core subnetwork computed by CentiScaPe, another plugin for Cytoscape. RESULTS: In Stage I, hsa-miR-592, hsa-miR-449a and hsa-miR-1269a targeted HS3ST4, ACSL1 and USP9Y genes respectively. In stage II, hsa-miR-3662, Hsa-miR-429, and hsa-miR-1269a targeted GYS2, HAS3, ASPA, TRHDE, USP44, GDA, DGAT2, and USP9Y genes. In stage III, hsa-miR-3662 targeted TRHDE, GYS2, DPYS, HAS3, NMNAT2, ASPA genes. In stage IV, hsa-miR-429, has-miR-23c, and hsa-miR-449a targeted genes GDA, DGAT2, PDK4, ALDH1A2, ENPP2, and KL. Those miRNAs and their targets were identified as the discriminative elements for the four stages of breast cancer. CONCLUSION: The most notable differences between BC and normal tissue in four stages  involved multiple pathways and metabolites include: carbohydrate metabolism (e.g., Amylose, N-acetyl-D-glucosamin, beta-D-Glucuronoside, ""g""-CEHC-glucuronide, ""a""-CEHC-glucuronide, Heparan-glucosamine, 5,6-Dihydrouracil, 5,6-Dihydrothymine), branch-chain amino acid metabolism (e.g., N-Acetyl-L-aspartate, N-Formyl-L-aspartate, N`-acetyl-L-asparagine), Retinal metabolism (e.g., Retinal, 9-`cis`-retinal, 13-`cis`-retinal) and (FAD, NAD) as central coenzymes of metabolism. Set of crucial microRNAs and targeted genes plus the related metabolites were introduced for four stages of BC that can be consider for therapeutic and diagnostic purposes in the different stages of disease.

Targeting colon cancer via antimicrobial RT2 peptide: a system biology study.

Aim: This study aims to investigate the anticancer molecular mechanism of RT2 through protein-protein interaction (PPI) network analysis. For this aim, a bioinformatics evaluation of the proteome profile of colon cancer is carried out. Background: Antimicrobial peptides such as RT2 showed anticancer properties against various tumors. The molecular mechanism of the anticancer effect of RT2 is a challenging subject. Methods: By applying Cytoscape V.3.9.1 and integrated apps, the profile of the interaction network and related centrality is analyzed. An enrichment analysis of hub bottlenecks was also performed, and highlighted biological processes were visualized and determined. Results: Several 207 differentially expressed proteins were retrieved by PPI network analysis, and 10 hub bottlenecks were introduced. Among these differentially expressed proteins (DEPs), only AKT1 is from the queried DEPs. Key biological processes contributing to RT2 targeting mechanism include "Regulation of fibroblast proliferation", "Positive regulation of cyclin-dependent protein serine/threonine kinase activity", "positive regulation of miRNA transcription", and "fungiform papilla formation". Conclusion: In conclusion, central proteins Tp53, MYC, EGFR, AKT1, HDAC1, and SRC can be introduced as a targeted biomarker panel of bioactive peptide treatments. However, extensive research is required to establish this claim before clinical application.

Bioinformatic Identification of Hub Genes Related to Menopause-Obesity Paradox in Breast Cancer.

Background: Breast cancer (BC) is one of the most common cancers in women, significantly contributing to cancer-related death in the modern world. Obesity, as a worldwide epidemic besides the menopausal status, has a paradoxical association with BC. Objectives: To determine the molecular mechanisms underlying the paradoxical effects of obesity on BC, a comprehensive systems biology analysis was performed. Methods: Data retrieval, data preprocessing, and differential expression analysis were conducted. Weighted correlation network analysis (WGCNA) identified the gene modules associated with clinical traits. Network analysis and hub gene identification techniques revealed key regulatory genes, and functional enrichment analysis uncovered biological pathways related to hub genes. A logistic regression model was developed to predict menopausal status based on hub genes. Additionally, gene expression analysis of two important genes was performed by qPCR. Results: The study identified the hub genes and molecular pathways (the PI3K-Akt signaling pathway, proteoglycans in cancer, and lipid metabolic and atherosclerosis pathways) associated with the obesity paradox in BC based on menopausal statutes. Conclusions: These results may improve our understanding of the underlying mechanisms of the effects of body mass on BC and assist in identifying biomarkers and potential therapeutic targets for treating obese postmenopausal women with BC.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a co mplex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods. NEW METHOD: We originated novel texture analysis and machine learning approaches for classifying MS pathology subtypes as compared with 2 common advanced MRI measures: magnetization transfer ratio (MTR) and fractional anisotropy (FA). Texture analysis used an optimized grey level co-occurrence matrix method with histology-informed 7T T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) from 15 MS and 12 control brain specimens. DTI analysis took an innovative approach that assessed the texture across diffusion directions upsampled from 30 to 90. Tissue types included de- and re-myelinated lesions and normal-appearing areas in both grey and white matter, and diffusely abnormal white matter. Data analyses were stepwise, including: (1) group-wise classification using random forest algorithms based on all or individual imaging parameters; (2) parameter importance ranking; and (3) pairwise analysis using top-ranked features. RESULTS: Texture analysis performed better than MTR and FA, with T2 texture performed the best. T2 texture measures ranked the highest in classifying most grey and white matter tissue types, including de- versus re-myelinated lesions and among grey matter lesion subtypes (accuracy=0.86-0.59; kappa=0.60-0.41). Diffusion texture best differentiated normal appearing and control white matter. COMPARISON WITH EXISTING METHODS: There is no established method in imaging for differentiating MS pathology subtypes. In combined texture analysis and machine learning studies, there is also no direct evidence comparing conventional with advanced MRI measures for assessing MS pathology. Further, this study is unique in conducting innovative texture analysis with DTI following data-augmentation using robust methods. CONCLUSIONS: T2 and diffusion MRI texture analysis integrated with machine learning may be valuable approaches for characterizing MS pathology.

Pathogen Presence in Wild Birds Inhabiting Landfills in Central Iran.

Wild birds are important in the transmission of many zoonotic pathogens such as salmonella and avian influenza virus (AIV). The current study investigated the presence of bacterial and viral pathogens in birds foraging at an open landfill located in Central Iran. We collected blood and intestinal samples from five abundant species, including rook (Corvus frugilegus), European starling (Sturnus vulgaris), house sparrow (Passer domesticus), black-headed gull (Chroicocephalus ridibundus) and slender-billed gull Chroicocephalus genei for bacteriological and serological examinations. Escherichia coli was present in all of the five species, while Salmonella spp. was found in four species. Campylobacter jejuni, Yersinia spp., Cytrobacter spp., and Klebsiella spp. were other bacteria isolated from all of the five species. Competitive ELISA showed that 19 samples (32%) from the two gull species were positive for AIV. There was no detection of West Nile virus, or Newcastle disease virus in the 150 birds sampled. The prevalence of these pathogens in landfill birds indicated that a potential risk is posed to landfill workers and the surrounding community, adding to our limited knowledge of the potential for landfills to support disease vectors.

Stress distribution in maxillary first molar periodontium using straight pull headgear with vertical and horizontal tubes: A finite element analysis.

BACKGROUND: One of the most effective ways for distal movement of molars to treat Class II malocclusion is using extraoral force through a headgear device. The purpose of this study was the comparison of stress distribution in maxillary first molar periodontium using straight pull headgear in vertical and horizontal tubes through finite element method. MATERIALS AND METHODS: Based on the real geometry model, a basic model of the first molar and maxillary bone was obtained using three-dimensional imaging of the skull. After the geometric modeling of periodontium components through CATIA software and the definition of mechanical properties and element classification, a force of 150 g for each headgear was defined in ABAQUS software. Consequently, Von Mises and Principal stresses were evaluated. The statistical analysis was performed using T-paired and Wilcoxon nonparametric tests. RESULTS: Extension of areas with Von Mises and Principal stresses utilizing straight pull headgear with a vertical tube was not different from that of using a horizontal tube, but the numerical value of the Von Mises stress in the vertical tube was significantly reduced (P < 0/05). On the other hand, the difference of the principal stress between both tubes was not significant (P > 0/05). CONCLUSION: Based on the results, when force applied to the straight pull headgear with a vertical tube, Von Mises stress was reduced significantly in comparison with the horizontal tube. Therefore, to correct the mesiolingual movement of the maxillary first molar, vertical headgear tube is recommended.

Analysis of killer cell immunoglobulin-like receptors (KIRs) and their HLA ligand genes polymorphisms in Iranian patients with systemic sclerosis.

Genetic factors have a great role in the pathogenesis of autoimmune diseases by cooperating with environmental stimuli. Killer immunoglobulin-like receptors (KIRs) are cell surface proteins on NK cells whose association with major histocompatibility complex-I regulates their killing function. The aim of this study was to provide information on the possible association between KIR and human leukocyte antigen (HLA) genes with systemic sclerosis disease in Iranian population. A total of 279 systemic sclerosis patients and 451 healthy controls were enrolled in this case-control study in order to determine the presence or absence of 19 KIR genes and 6 specific HLA class I ligands. DNA was analyzed by polymerase chain reaction using the specific sequence primer method (PCR-SSP). Among 11 discovered KIR genotypes, 6 genotypes showed a considerable role and 4 genotypes could preclude the risk of systemic sclerosis (SSc) disease. The gene-gene interactions were also analyzed, and significant confounding effects were seen between involved genes in these two combinations: "KIR3DL1; HLA-BW4-Thr80" and "KIR3DL1 -HLA-BW4-A1." None of single KIR genes showed significant effect on the risk of SSc. We conclude that there is an important relationship between KIR genes and their HLA ligands with incidence rate of systemic sclerosis in Iranian population. The powerful role of a number of discovered KIR/HLA compounds such as activating KIR genotype 3 and HLA-BW4-A1 confirmed the provocative hypothesis of the interplay between activating or inhibitory KIR genes with HLA ligands as a critical index of systemic sclerosis predisposition.

Morphology-Dependent Electrochemical Properties of CuS Hierarchical Superstructures.

Hierarchical superstructures formed by self-assembled nanoparticles exhibit interesting electrochemical properties that can potentially be exploited in Li-ion batteries (LIBs) as possible electrode materials. In this work, we tested two different morphologies of CuS superstructures for electrodes, namely, tubular dandelion-like and ball-like assemblies, both of which are composed of similar small covellite nanoparticles. These two CuS morphologies are characterized by their markedly different electrochemical performances, suggesting that their complex structures/morphologies influence the electrochemical properties. At 1.12 A g(-1), the cells made with CuS tubular structures delivered about 420 mAh g(-1), and at 0.56 A g(-1), the capacity was as high as about 500 mAh g(-1) with good capacity retention. Their ease of preparation and processing, together with good electrochemical performance, make CuS tubular dandelion-like clusters attractive for developing low-cost LIBs based on conversion reactions.