Identification of drug candidate for osteoporosis by computational bioinformatics analysis of gene expression profile

Gastrointestinal Bleeding in Patients With Acute Ischemic Stroke: A Literature Review

Stroke is an infarction of the central nervous system (brain, spinal cord, or retina) that results from a disruption in cerebral blood flow either due to ischemia or hemorrhage. Complications of acute stroke are common and include pneumonia, urinary tract infection, myocardial infarction, deep vein thrombosis, and pulmonary embolism, among several others, all of which increase the risk of poor clinical outcomes. Gastrointestinal bleeding is a well-known complication that can occur during the acute phase of stroke. In this review, we have summarized the existing data regarding the incidence, pathophysiology, risk factors, morbidity, mortality, and management strategies for gastrointestinal bleeding in patients with acute ischemic stroke.

Ataluren prevented bone loss induced by ovariectomy and aging in mice through the BMP-SMAD signaling pathway

Both estrogen deficiency and aging may lead to osteoporosis. Developing novel drugs for treating osteoporosis is a popular research direction. We screened several potential therapeutic agents through a new deep learning-based efficacy prediction system (DLEPS) using transcriptional profiles for osteoporosis. DLEPS screening led to a potential novel drug examinee, ataluren, for treating osteoporosis. Ataluren significantly reversed bone loss in ovariectomized mice. Next, ataluren significantly increased human bone marrow-derived mesenchymal stem cell (hBMMSC) osteogenic differentiation without cytotoxicity, indicated by the high expression index of osteogenic differentiation genes (OCN , BGLAP, ALP, COL1A, BMP2, RUNX2). Mechanistically, ataluren exerted its function through the BMP-SMAD pathway. Furthermore, it activated SMAD phosphorylation but osteogenic differentiation was attenuated by BMP2-SMAD inhibitors or small interfering RNA of BMP2. Finally, ataluren significantly reversed bone loss in aged mice. In summary, our findings suggest that the DLEPS-screened ataluren may be a therapeutic agent against osteoporosis by aiding hBMMSC osteogenic differentiation.

Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry

With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical-medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.

Characterization of Dysregulated lncRNA-Associated ceRNA Network Reveals Novel lncRNAs With ceRNA Activity as Epigenetic Diagnostic Biomarkers for Osteoporosis Risk

The altered expression of long non-coding RNAs (lncRNAs) has been implicated in the development and human diseases. However, functional roles and regulatory mechanisms of lncRNA as competing endogenous RNAs (ceRNAs) in osteoporosis and their potential clinical implication for osteoporosis risk are largely unexplored. In this study, we performed integrated analysis for paired expression profiles and regulatory relationships of dysregulated lncRNAs, mRNAs, and miRNAs based on “ceRNA hypothesis,” and constructed an osteoporosis-related dysregulated miRNA-mediated lncRNA–mRNA ceRNA network (DysCeNet) composed of 105 nodes (including eight miRNAs, 24 mRNAs, and 73 lncRNAs) and 515 edges. Functional analysis suggested that the DysCeNet was involved in known osteoporosis or bone metabolism-related biological processes and pathways. Then, we performed random forest-based feature selection for 73 lncRNAs with ceRNA activity and identified 25 of 73 lncRNAs as potential diagnostic biomarkers. A random forest-based classifier composed of 25 lncRNA biomarkers (RF-25lncRNA) was developed for predicting osteoporosis risk. Performance evaluation with the leave-one-out cross-validation (LOOCV) procedure showed that the RF-25lncRNA achieved a good performance in distinguishing high- and low-bone mineral density (BMD) subjects in different osteoporosis datasets. Our study for the first time revealed a global view of lncRNA-associated ceRNA regulation in osteoporosis and provided novel lncRNAs with ceRNA activity as candidate epigenetic diagnostic biomarkers for early detection of osteoporosis risk.