Biotechnology advances · 2025
From dye exclusion to high-throughput screening: A review of cell viability assays and their applications.
СтатьяОбзорНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Naveen Kumar Vishven, Tyagi Akanksha, Ibrahium Omnia Mohammed Hamid, Fischer Rainer E A W, Ostafe Raluca
Аннотация
Cell viability assays (CVAs) are widely used in cell biology, biomedical research, drug development, and biotechnology to assess cell health, proliferation, cytotoxicity, and functional activity under various conditions. Key applications span from everyday cell culture monitoring to drug screening and toxicology studies, immunology, vaccine development, and stem cell and regenerative medicine. Despite the long history and widespread use of CVAs, selecting the right assay remains a challenge for researchers. The increasing number of available assay options has led to confusion and inefficiencies, as scientists struggle to navigate the differences, trade-offs, and technical limitations of each method. Many researchers continue using the assays they were trained with, rather than exploring newer, more sensitive, or more appropriate techniques. Lab protocols are often passed down without reassessment, and new projects frequently adopt assays based on convenience (e.g., reagent availability or existing equipment) rather than rational selection criteria. Some groups deliberately choose less sensitive assays under the assumption that they produce "better-distributed" data. However, this incorrect justification arises because assays with a high limit of detection (LOD) fail to capture small variations, creating the misleading perception of clean and well-distributed data. Ignoring small variations does not improve accuracy - it simply reduces sensitivity, potentially leading to incorrect conclusions. Hence, the purpose of this review is to provide a comprehensive overview of contemporary CVAs by categorizing detection methods and summarizing their concepts, applications, benefits, and limitations, while also highlighting the potential need for novel approaches in this field. To assist researchers in selecting the most appropriate assay for their experimental goals, we also present a visual decision tree that integrates mechanistic insights with practical considerations.