Introduction: Hepatitis C virus (HCV) is considered a major public health problem, with 200 million people infected worldwide. The treatment for HCV chronic infection with pegylated interferon alpha plus ribavirin inhibitors is unspecific; consequently, the treatment is effective in only 50% of patients infected. This has prompted the development of direct-acting antivirals (DAA) that target virus proteins. These DAA have demonstrated a potent effect in vitro and in vivo; however, virus mutations associated with the development of resistance have been described.
Objective: To design and develop an online information system for detecting mutations in amino acids known to be implicated in resistance to DAA.
Materials And Methods: We have used computer applications, technological tools, standard languages, infrastructure systems and algorithms, to analyze positions associated with resistance to DAA for the NS3, NS5A, and NS5B genes of HCV.
Results: We have designed and developed an online information system named Biomedical Mutation Analysis (BMA), which allows users to calculate changes in nucleotide and amino acid sequences for each selected sequence from conventional Sanger and cloning sequencing using a graphical interface.
Conclusion: BMA quickly, easily and effectively analyzes mutations, including complete documentation and examples. Furthermore, the development of different visualization techniques allows proper interpretation and understanding of the results. The data obtained using BMA will be useful for the assessment and surveillance of HCV resistance to new antivirals, and for the treatment regimens by selecting those DAA to which the virus is not resistant, avoiding unnecessary treatment failures. The software is available at: http://bma.itiud.org.
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http://dx.doi.org/10.12688/f1000research.8740.2 | DOI Listing |
Gastric Cancer
January 2025
Department of Medical Oncology, Hospital Clinico Universitario, INCLIVA, Biomedical Research Institute, University of Valencia, Avenida Menendez Pelayo nro 4 accesorio, Valencia, Spain.
Introduction: Gastric cancer (GC) burden is currently evolving with regional differences associated with complex behavioural, environmental, and genetic risk factors. The LEGACy study is a Horizon 2020-funded multi-institutional research project conducted prospectively to provide comprehensive data on the tumour biological characteristics of gastroesophageal cancer from European and LATAM countries.
Material And Methods: Treatment-naïve advanced gastroesophageal adenocarcinoma patients were prospectively recruited in seven European and LATAM countries.
Ophthalmol Ther
January 2025
Dr. Rolf M. Schwiete Center for Limbal Stem Cell and Congenital Aniridia Research, Saarland University, Homburg, Saar, Germany.
Introduction: Congenital aniridia is increasingly recognized as part of a complex syndrome with numerous ocular developmental anomalies and non-ocular systemic manifestations. This requires comprehensive care and treatment of affected patients. Our purpose was to analyze systemic diseases in patients with congenital aniridia within the Homburg Aniridia Registry.
View Article and Find Full Text PDFCancer Lett
January 2025
Clinical and Health Sciences, University of South Australia, Adelaide, Australia; Department of Histopathology, Trinity College Dublin, St. James's Hospital, Dublin, Ireland. Electronic address:
Metabolic reprogramming is a hallmark of cancer, crucial for malignant transformation and metastasis. Chronic lymphocytic leukaemia (CLL) and prostate cancer exhibit similar metabolic adaptations, particularly in glucose and lipid metabolism. Understanding this metabolic plasticity is crucial for identifying mechanisms contributing to metastasis.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St, Charlestown, MA, 02129, USA.
Recent progress in deep learning (DL) is producing a new generation of tools across numerous clinical applications. Within the analysis of brain tumors in magnetic resonance imaging, DL finds applications in tumor segmentation, quantification, and classification. It facilitates objective and reproducible measurements crucial for diagnosis, treatment planning, and disease monitoring.
View Article and Find Full Text PDFAm J Hum Genet
January 2025
Institute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany; Center for Rare Disease, University of Tübingen, 72076 Tübingen, Germany; Genomics for Health in Africa (GHA), Africa-Europe Cluster of Research Excellence (CoRE).
Inborn errors of selenoprotein expression arise from deleterious variants in genes encoding selenoproteins or selenoprotein biosynthetic factors, some of which are associated with neurodegenerative disorders. This study shows that bi-allelic selenocysteine tRNA-specific eukaryotic elongation factor (EEFSEC) variants cause selenoprotein deficiency, leading to progressive neurodegeneration. EEFSEC deficiency, an autosomal recessive disorder, manifests with global developmental delay, progressive spasticity, ataxia, and seizures.
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