Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis.

Multiple sclerosis (MS) is a chronic autoimmune disease in the central nervous system (CNS) marked by inflammation, demyelination, and axonal loss. Currently available MS medication is limited, thereby calling for a strategy to accelerate new drug discovery. One of the strategies to discover new drugs is to utilize old drugs for new indications, an approach known as drug repurposing. Herein, we first identified 421 MS-associated SNPs from the Genome-Wide Association Study (GWAS) catalog (p-value < 5 × 10-8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r2 > 0.8. MS risk genes were then prioritized using bioinformatics analysis to identify biological MS risk genes. The prioritization was performed based on six defined categories of functional annotations, namely missense mutation, cis-expression quantitative trait locus (cis-eQTL), molecular pathway analysis, protein-protein interaction (PPI), genes overlap with knockout mouse phenotype, and primary immunodeficiency (PID). A total of 144 biological MS risk genes were found and mapped into 194 genes within an expanded PPI network. According to the DrugBank and the Therapeutic Target Database, 27 genes within the list targeted by 68 new candidate drugs were identified. Importantly, the power of our approach is confirmed with the identification of a known approved drug (dimethyl fumarate) for MS. Based on additional data from ClinicalTrials.gov, eight drugs targeting eight distinct genes are prioritized with clinical evidence for MS disease treatment. Notably, CD80 and CD86 pathways are promising targets for MS drug repurposing. Using in silico drug repurposing, we identified belatacept as a promising MS drug candidate. Overall, this study emphasized the integration of functional genomic variants and bioinformatic-based approach that reveal important biological insights for MS and drive drug repurposing efforts for the treatment of this devastating disease.

Development and validation of the World Health Organization disability Assessment Schedule 2.0 (WHODAS 2.0) Indonesian version in stroke survivors.

PURPOSE: Stroke is the third most common cause of disability worldwide. In order to effectively study the disability status experienced by stroke survivors, it is important to identify reliable and valid tools to measure disability that can be administered to this population. No previous study had been conducted on the Indonesian version of the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0). The aim of this study was to develop and validate the Indonesian version of the WHODAS 2.0 for stroke survivors in Indonesia. METHODS: Following translation and back-translation, the Indonesian version of the WHODAS 2.0 was administered to 183 stroke survivors. We used all six domains of the WHODAS 2.0, with the exception of four items of "work or school activities" in domain 5. Internal consistency was measured by Cronbach's alpha, the inter-rater reliability was measured by interclass correlations (ICCs), and the construct validity was tested with an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). RESULTS: The range of Cronbach's alpha was 0.86-0.92, which indicated excellent reliability, and ICC was very good at 0.87-0.99. The EFA and CFA for the main 32-item questionnaire exhibited a total variance of 95% (KMO) and a p value of <0.05. The factor loadings per items were >0.4, and all the model fit indices were acceptable. CONCLUSIONS: The WHODAS 2.0 was adapted for use in Indonesia and showed good results for all six domains. Therefore, the Indonesian version of the WHODAS 2.0 can be applied to assess disability in Indonesian stroke survivors.Implications for rehabilitationThe WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) was developed as a single, generic instrument for assessing the health status and disability in different cultures and settings.In this study, we adapted and validated an Indonesian version of the WHODAS 2.0 for stroke survivors in Indonesia.The WHODAS 2.0 was adapted for use in Indonesia and showed good results for all six domains.The Indonesian version of the WHODAS 2.0 can be applied to assess disability in Indonesian stroke survivors.

The Role of IGF/IGF-1R Signaling in Hepatocellular Carcinomas: Stemness-Related Properties and Drug Resistance.

Insulin-like Growth Factor (IGF)/IGF-1 Receptor (IGF-1R) signaling is known to regulate stem cell pluripotency and differentiation to trigger cell proliferation, organ development, and tissue regeneration during embryonic development. Unbalanced IGF/IGF-1R signaling can promote cancer cell proliferation and activate cancer reprogramming in tumor tissues, especially in the liver. Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death, with a high incidence and mortality rate in Asia. Most patients with advanced HCC develop tyrosine kinase inhibitor (TKI)-refractoriness after receiving TKI treatment. Dysregulation of IGF/IGF-1R signaling in HCC may activate expression of cancer stemness that leads to TKI refractoriness and tumor recurrence. In this review, we summarize the evidence for dysregulated IGF/IGF-1R signaling especially in hepatitis B virus (HBV)-associated HCC. The regulation of cancer stemness expression and drug resistance will be highlighted. Current clinical treatments and potential therapies targeting IGF/IGF-1R signaling for the treatment of HCC will be discussed.

Determination of fluoroquinolones in dried plasma spots by using microwave-assisted extraction coupled to ultra-high performance liquid chromatography-tandem mass spectrometry for therapeutic drug monitoring.

Therapeutic drug monitoring is important for achieving desirable outcomes in tuberculosis treatment. In this study, microwave-assisted extraction was used to extract levofloxacin, ciprofloxacin, and moxifloxacin from dried plasma spots for subsequent detection and quantification with ultra-high performance liquid chromatography-tandem mass spectrometry. Dried plasma spotting was performed by dropping 15 µL of plasma on a protein saver card. Analyte extraction was performed with microwave-assisted extraction at 400 W for 40 s in 90 % methanol. Samples were analyzed with a core-shell C18 column (100 mm × 2.1 mm, 2.6 µm, 100 Å). Multiple reaction monitoring was used and the ion source was operated in positive electrospray ionization mode. The correlation coefficients of the calibration curves were > 0.999 for all three drugs over a range of 0.2-20 µg/mL. The intraday precision (n = 5) of the peak area ratios of the analyte to the internal standard was between 1.3 and 4.0 % relative standard deviation (RSD). The intraday accuracy ranged from 93.6-106.9%. The interday (n = 3) precision of the peak area ratios ranged from 1.9 to 8.8 % RSD, and the accuracy ranged from 94.9-107.1%. Regarding clinical application, the quantification results for moxifloxacin from dried plasma spots (DPSs) were strongly similar to the results from the plasma samples, which showed that Pearson's rho > 0.949. The validation and application results showed that the developed method can be used as an efficient analytical technique for therapeutic drug monitoring of fluoroquinolones for patients with tuberculosis.

Gender differences in the relationships between sleep disturbances and academic performance among nursing students: A cross-sectional study.

BACKGROUND: Sleep disturbances, such as insomnia, excessive daytime sleepiness, and poor-quality sleep, are common among nursing students and are closely linked with academic performance. OBJECTIVES: To examine the prevalence of sleep disturbances and academic performances in male and female nursing students and to determine gender-specific effects on the relationship between sleep disturbances and academic performance. DESIGN: A cross-sectional study design was adopted. SETTINGS: This study was conducted in a school of nursing in Indonesia. PARTICIPANTS: A total of 492 undergraduate students (103 males and 389 females) were included. METHODS: Data pertaining to the biosociodemographic characteristics, Pittsburgh Sleep Quality Index, Insomnia Severity Index, Epworth Sleepiness Scale, Morningness-Eveningness Questionnaire, and Beck Depression Inventory were collected from July 1, 2018 to September 30, 2018. Academic performance was measured using grade point average of the academic year 2017-2018. A multivariate logistic regression model was used for data analyses. RESULTS: The prevalence of poor sleep quality, insomnia, and daytime sleepiness was 66.0%, 45.6%, and 24.3%, respectively, in male nursing students and 71.5%, 52.4%, and 28.8%, respectively, in female nursing students. For circadian rhythm preferences, 66% male and 51.7% female nursing students were categorized as intermediate- and morning-type people, respectively. Insomnia was the only variable among sleep disturbances that significantly correlated with the risk of poor academic performance in female nursing students even after adjustment of covariates. CONCLUSIONS: Sleep disturbances were highly prevalent among female and male nursing students, and insomnia was substantially associated with poor academic performance in female nursing students. Identifying sleep disturbances among nursing students and designing effective interventions to specifically target them are required to improve academic performance of female nursing students.