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Screening of Oncogenic Proteins and Development of a Multiepitope Peptide Vaccine Targeting AKT1 and PARP1 for Breast Cancer by Integrating Reverse Vaccinology and Immune-Informatics Approaches.
Asian Pac J Cancer Prev
January 2025
Parul Institute of Applied Sciences, Parul University, Vadodara, India.
Background: Breast cancer remains a significant global health challenge, requiring innovative therapeutic strategies. In silico methods, which leverage computational tools, offer a promising pathway for vaccine development. These methods facilitate antigen identification, epitope prediction, immune response modelling, and vaccine optimization, accelerating the design process.
View Article and Find Full Text PDFInvestigating the Anticancer Properties of Bacterial Toxoid in Combination Vaccines.
Asian Pac J Cancer Prev
January 2025
Experimental Therapy Department, Iraqi Center for Cancer and Medical Genetic Research. Mustansiriyah University, Baghdad, Iraq.
Background: The use of bacterial vaccines as a potential Bacterial-Based Cancer Therapy (BBCT) presents an innovative approach, transforming these vaccines into multifunctional tools capable of serving dual roles in medicine.
Materials And Methods: This study aimed to conduct in vitro, immunity-independent experiments to investigate the anticancer properties of vaccine-derived bacterial toxoids on various cancer cell lines. Six concentrations of the DTP vaccine (5 x 10-4, 25 x 10-5, 125 x 10-6, 625 x 10-7, 312 x 10-7, and 15 x 10-6 µg/ml) were tested on two cancer cell lines (SKG and HCAM) and a normal Rat Embryonic Fibroblast (REF) cell line.
An Automated Tool for Glycosimilarity Assessment of mAb Therapeutic Biosimilars: Trastuzumab and Bevacizumab as Case Studies.
BioDrugs
January 2025
Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
Background: With the expiration of patents for multiple biotherapeutics, biosimilars are gaining traction globally as cost-effective alternatives to the original products. Glycosylation, a critical quality attribute, makes glycosimilarity assessment pivotal for biosimilar development. Given the complexity of glycoanalytical profiles, assessing glycosimilarity is nontrivial.
View Article and Find Full Text PDFLarge-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports.
Radiology
January 2025
From the Departments of Biomedical Systems Informatics (S.K., Jaewoong Kim, C.H., D.Y.) and Neurology (Joonho Kim, J.Y.), Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; Department of Radiology, Central Draft Physical Examination Office of Military Manpower Administration, Daegu, Republic of Korea (D.K.); Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (H.J.S. Y.K., S.J.), and Center for Digital Health (H.J.S., D.Y.), Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea; Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.H.L.); Departments of Radiology (M.H.) and Neurology (S.J.L.), Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea; and Institute for Innovation in Digital Healthcare, Severance Hospital, Seoul, Republic of Korea (D.Y.).
Background The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers.
View Article and Find Full Text PDFMetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.
Front Neurosci
January 2025
Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX, United States.
Introduction: In the rapidly advancing field of 'omics research, there is an increasing demand for sophisticated bioinformatic tools to enable efficient and consistent data analysis. As biological datasets, particularly metabolomics, become larger and more complex, innovative strategies are essential for deciphering the intricate molecular and cellular networks.
Methods: We introduce a pioneering analytical approach that combines Principal Component Analysis (PCA) with Graphical Lasso (GLASSO).
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