http://localhost:8080/xmlui/handle/123456789/11692 2026-04-14T20:49:39Z http://localhost:8080/xmlui/handle/123456789/11769 Title: In silico identification of potential inhibitors for the universal stress G4LZI3 protein from Schistosoma mansoni using molecular docking and molecular dynamics simulation analyses Authors: Mahamba, Lihle; Alhaji Isa, Mustafa Abstract: Human schistosomiasis is a debilitating, neglected tropical disease affecting millions worldwide. Control efforts primarily rely on health education, improved sanitation, snail host management, and mass drug administration with Praziquantel (PZQ). PZQ has some limitations, such as its lower effectiveness against immature parasites and the potential for developing resistance. This requires the urgent need for new treatment approaches. The universal stress protein G4LZI3 helps the Schistosoma mansoni parasite survive when it is under stress from its host. Because of this, it emerges as a promising target for developing new drugs. Despite its biological relevance, G4LZI3 has not been previously investigated as a druggable target, highlighting a significant research gap in schistosomiasis drug discovery. To find potential inhibitors of G4LZI3, we conducted a virtual screening using the RASPD+ tool, which led us to select 7889 ligands from the CoCoNut database. These ligands were filtered based on physicochemical properties (Lipinski’s Rule of Five, Veber’s Rule, Egan’s Filter, and the Ghose filter), pharmacokinetics, and Pan-Assay Interference Structures (PAINS) criteria, followed by molecular docking. Fifteen compounds demonstrated strong binding affinities, with binding energies ranging from 􀀀 10.6 to 􀀀 8.50 kcal/mol, exceeding that of PZQ (􀀀 8.4 kcal/mol). From these, six compounds were selected for further analysis, including molecular dynamics (MD) simulation, solvent-accessible surface area (SASA), and molecular mechanics generalized Born surface area (MM-GBSA) calculations. MD simulation of 200 ns revealed that CNP0475438, CNP0415153, and CNP0353858 achieved significant stability and favourable interactions with G4LZI3. These findings show these compounds as promising candidates for S. mansoni inhibition, pending experimental validation. The results identify novel scaffolds with vigorous predicted activity and provide a rational starting point for experimental optimization and development of new antiparasitic therapies that address praziquantel resistance and efficacy limitations in endemic regions 2025-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/11766 Title: Prevalence of pathogenic genetic variants associated with familial hypercholesterolemia in Ghanaian children Authors: Opoku-Agyeman, Philip; Ameyaw, Prince Abstract: Familial hypercholesterolemia (FH) is an important contributor to atherosclerotic cardiovascular disease (ASCVD) burden globally. FH disrupts cholesterol metabolism and causes lifelong elevation in low-density lipoprotein cholesterol (LDL-C). In sub-Saharan Africa (SSA), the increasing burden of ASCVD may be partly driven by genetic dyslipidemias of which FH is the commonest. However, there is absence of data on FH prevalence in SSA which delineates an important gap in the management of ASCVD. This study is the first to investigate the prevalence of pathogenic variants associated with FH in Ghana. We used 96 deidentified archived dried blood spot samples collected from a Ghanaian cohort, to determine the prevalence of pathogenic genetic variants associated with FH. These samples were collected from children under 9 years old as part of surveillance for antimalarial drug resistance in 2021. We searched the NCBI’s ClinVar database and used in silico tools to identify 500–800 nucleotide base pair regions of interest in 3 genes known to harbor the commonest genetic variants associated with FH. We selected these regions of interest from the LDLR gene exons 4, 9 and 10, APOB exon 26 and PCSK9 exon 2 loci. Next, we amplified these regions of interest using conventional polymerase chain reaction. Finally, we sequenced the amplicons using paired-end Sanger sequencing and called variants from the chromatogram files using an in-house custom built bash script utilizing the open access program Tracy. Subsequently, we did quality checks on all reported pathogenic variant calls manually using Benchling’s sequence alignment tool. We identified one pathogenic variant V523 M in the LDLR exon 10 region and report an FH prevalence of 1% (1/96), 95% CI: [0%,3.07%], in our Ghanaian cohort. Our finding underscores the importance of FH in driving ASCVD burden in Ghana and advocates the need for implementation science-driven programs to manage this genetic dyslipidemia in Ghana and SSA. 2025-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/11763 Title: Computational framework for analyzing miRNA-mRNA interactions in sarcopenia: Insights into age-related muscular degeneration Authors: Sabarathinam, Sarvesh; Jayaraman, Akash Abstract: Background: Sarcopenia, an age-related loss of skeletal muscle mass and function, impairs mobility, fragility, and quality of life. Despite progress in pathophysiology, molecular processes remain unknown. Recent research has investigated miRNAs as biomarkers for sarcopenia diagnosis and therapy. This work analyses differentially expressed genes (DEGs) and predicts miRNA-mRNA interactions using ML methods like XG-Boost and SHAP to find biomarkers. Objective: This work evaluated the function of miRNA-mRNA interactions in sarcopenia pathogenesis and identified possible biomarkers by transcriptome analysis utilizing machine learning. Methods: High-throughput mRNA sequencing datasets (GSE111006, GSE111010, and GSE111016) from GEO database were combined, pre-processed, and normalized using TPM and DESeq2 methods. XG-Boost regression analysis used 80/20 training and testing sets. SHAP analysis was used to evaluate model data and find significant DEGs. PPI networks were created using the STRING database, while miRNA-mRNA interactions were predicted using Encori and displayed with Cytoscape. The degree scores of miRNA-mRNA interactions were utilized to find biomarkers. Results: XG-Boost and SHAP analysis revealed 20 influential DEGs linked to sarcopenia. With 97% accuracy, the model predicted accurately. PPI network research identified six hub genes: NTRK2, PCK1, DSP, SCD, MMRN1, and EDIL3. MiRNA-mRNA interaction analysis found miR-186–5p as the highest-degree biomarker candidate (36). MiR-186–5p was linked to muscle metabolism, hypertrophy, and exercise response. Conclusion: The study found miR-186–5p to be a promising biomarker for sarcopenia using an integrated machine learning technique. The findings show that miR-186–5p may be a diagnostic and therapeutic target for sarcopenia, revealing its pathogenesis and enabling tailored treatments. Experimental research is needed to prove its therapeutic value. 2025-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/11761 Title: Exploring new Frontiers in dry eye Disease: Treatments, mechanisms, and diagnostic innovations a comprehensive review Authors: K. Narendra, K. Narendra Abstract: Dry Eye Disease (DED) significantly impacts quality of life through tear film instability and ocular surface inflammation. This review highlights advancements in treatments, mechanisms, and diagnostics. Emerging pharmacological therapies, including novel anti-inflammatory agents, secretagogues, corticosteroids, and autologous serum eye drops, alongside innovative devices like punctal plugs, thermal pulsation devices, and meibomian gland expression techniques. Lifestyle modifications and nutritional supplements, such as omega-3 fatty acids and antioxidants, are also explored. Mechanistic insights cover tear film instability, inflammatory pathways, neuropathic pain, and meibomian gland dysfunction, emphasizing recent findings on the ocular surface microbiome, genetic and epigenetic factors, and chronic inflammation. Diagnostic innovations include AI and machine learning integration, advanced imaging techniques, tear film analysis, and functional tests, enhancing early detection and monitoring. Emerging research on gene therapy, stem cell therapy, ocular surface microbiota, and gene editing technologies like CRISPR is examined for future treatment potential. Personalized medicine approaches, incorporating genomic and proteomic profiling and patient-reported outcomes, are emphasized for tailored therapies. Environmental and lifestyle factors, including pollution, climate change, diet, and behavioral modifications, are considered for their impact on DED management. Integrating these advancements into clinical practice aims to improve patient outcomes and quality of life, highlighting the future potential of cutting-edge research and innovations 2025-01-01T00:00:00Z