Development of algorithms for automated analysis of neuronal survival assay using BioStation CT and CL-Quant. (A) Workflow diagram showing the development of automated algorithms for neuronal survival analysis. iPSC-derived human neurons were transfected at DIV8 and maintained in BioStation CT with images taken every 12 h. The collected images were quantified by manual counting to create a reference data set for the subsequent development of automated algorithms. (B) Representative fluorescence and brightfield images acquired by the automated imaging system of BioStation CT. Neurons were transfected with red fluorescence tracer plasmid (pSF-MAP2-mApple). (C) Example of automated detection shows cell bodies in red, neurites in yellow and nodes in blue. The information can be plotted to show cell survival, neurite outgrowth and neuronal health over time in culture.
News — Oak Brook, IL – The April 2023 issue of SLAS Technology contains four original research articles and one technical brief covering the development of robotic systems, ultrasound frequency sonification, automated algorithm development and other laboratory automation technology.
Featured in this issue is the article “ ” by Choi, et al, which focuses on the use of longitudinal single-cell tracking to evaluate induced pluripotent stem cell (iPSC)derived human neurons to study Parkinson’s disease, dementia with Lewy bodies and other synucleinopathies.
Previous drug discovery assays in this area have required manual cell counting to track cell death and markers of neuronal fitness, which are historically time-consuming, tedious and prone to error. To overcome these challenges, the researchers developed an algorithm capable of measuring these parameters with accuracy comparable to manual counting with better consistency, demonstrated through an evaluation of the neuroprotective effects of brain-derived neurotrophic factor (BDNF) on neurons overexpressing Α-synuclein (A53T).
Access the April issue of SLAS Technology to learn more about the future applications of this automated algorithm and other laboratory automation technology research articles.
The of SLAS Technology includes these additional articles:
Access to the April issue of SLAS Technology is available at
SLAS Technology reveals how scientists adapt technological advancements for life sciences exploration and experimentation in biomedical research and development. The journal emphasizes scientific and technical advances that enable and improve:
- Life sciences research and development
- Drug delivery
- Diagnostics
- Biomedical and molecular imaging
- Personalized and precision medicine
SLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.
SLAS Technology: Translating Life Sciences Innovation, 2021 Impact Factor 2.813. Editor-in-Chief Edward Kai-Hua Chow, Ph.D., National University of Singapore (Singapore).
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