Advanced physiological maturation of iPSC-derived human cardiomyocytes using an algorithm-directed optimization of defined media components
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PROVIDER: PRJNA886404 | ENA |
REPOSITORIES: ENA
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Project description:Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) hold tremendous promise for in vitro modeling to assess native myocardial function and disease mechanisms as well as testing drug safety and efficacy. However, current iPSC-CMs are functionally immature, resembling in vivo CMs of fetal or neonatal developmental states. The use of targeted culture media and organoid formats have been identified as potential high-yield contributors to improve CM maturation. This study presents a novel iPSC-CM maturation medium formulation, designed using a differential evolutionary approach with oxidative capacity as an objective metric for iterative optimization. Relative to gold-standard reference formulations, our approach significantly matured morphology, Ca2+ handling, electrophysiology, and metabolism, which was further validated by multi-omic screening, for cells in either pure or co-cultured microtissue formats. Together, these findings not only provide a reliable workflow for highly functional iPSC-CMs for downstream use, but also demonstrate the power of high-dimensional optimization processes in evoking advanced biological function in vitro.
2022-10-05 | GSE214617 | GEO
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2012-02-27 | E-GEOD-34364 | biostudies-arrayexpress
Project description:ATAC-seq has been used for mapping open chromatin regions. Here we summarize our optimization methods.
2022-05-14 | GSE202791 | GEO
Project description:Background: With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research area, relatively little work has been reported on the optimization of microarray protocols. Results: As shown in this study, suboptimal conditions can have considerable impact on biologically relevant observations. For example, deviation from the optimal temperature by one degree Celsius lead to a loss of 44% of differentially expressed genes identified. While genes from thousands of Gene Ontology categories were affected, transcription factors and other low-copy-number regulators were disproportionately lost. Calibrated protocols are thus required in order to take full advantage of the large dynamic range of microarrays. For an objective optimization of protocols we introduce an approach that maximizes the amount of information obtained per experiment. A comparison of two typical samples is sufficient for this calibration. We ensure, however, that optimization results are independent of the samples and the specific measures used for calibration. Both simulations and spike-in experiments confirm an unbiased determination of generally optimal experimental conditions. Conclusions: Well calibrated hybridization conditions are thus easily achieved and necessary for the efficient detection of differential expression. They are essential for the sensitive profiling of low-copy-number molecules. This is particularly critical for studies of transcription factor expression, or the inference and study of regulatory networks. Supporting material, including source code and data, is available at http://bioinf.boku.ac.at/pub/optMA2010/. Optimization of hybridization temperature via an assessment of differential expression between two samples (male vs female Drosophila melanogaster) in 6 technical replicates (3 regular + 3 dye-swaps) for hybridizations at different temperatures (in two batches of 50, 52, 54, and 56; and 47, 49, 50, and 51 degree Celsius, with the repeated hybridization at 50 degree Celsius serving to demonstrate batch-to-batch stability).
2011-11-11 | E-GEOD-25625 | biostudies-arrayexpress
Project description:BackgroundA study was realised to evaluate and determine relative figures of merit of a new algorithm for photon dose calculation when applied to inhomogeneous media.MethodsThe new Acuros XB algorithm implemented in the Varian Eclipse treatment planning system was compared against a Monte Carlo method (VMC++), and the Analytical Anisotropic Algorithm (AAA). The study was carried out in virtual phantoms characterized by simple geometrical structures. An insert of different material and density was included in a phantom built of skeletal-muscle and HU = 0 (setting "A"): Normal Lung (lung, 0.198 g/cm3); Light Lung (lung, 0.035 g/cm3); Bone (bone, 1.798 g/cm3); another phantom (setting "B") was built of adipose material and including thin layers of bone (1.85 g/cm3), adipose (0.92 g/cm3), cartilage (1.4745 g/cm3), air (0.0012 g/cm3). Investigations were performed for 6 and 15 MV photon beams, and for a large (13 × 13 cm2) and a small (2.8 × 13 cm2) field.ResultsResults are provided in terms of depth dose curves, transverse profiles and Gamma analysis (3 mm/3% and 2 mm/2% distance to agreement/dose difference criteria) in planes parallel to the beam central axis; Monte Carlo simulations were assumed as reference. Acuros XB gave an average gamma agreement, with a 3 mm/3% criteria, of 100%, 86% and 100% for Normal Lung, Light Lung and Bone settings, respectively, and dose to medium calculations. The same figures were 86%, 11% and 100% for AAA, where only dose rescaled to water calculations are possible.ConclusionsIn conclusion, Acuros XB algorithm provides a valid and accurate alternative to Monte Carlo calculations for heterogeneity management.
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Project description:Sponges are rich sources of novel natural products. Production in cell cultures may be an option for supply of these compounds but there are currently no sponge cell lines. Because there is a lack of understanding about the precise conditions and nutritional requirements that are necessary to sustain sponge cells in vitro, there has yet to be a defined, sponge-specific nutrient medium. This study utilized a genetic algorithm approach to optimize the amino acid composition of a commercially available basal cell culture medium in order to increase the metabolic activity of cells of the marine sponge Dysidea etheria. Four generations of the algorithm were carried out in vitro in wet lab conditions and an optimal medium combination was selected for further evaluation. When compared to the basal medium control, there was a twofold increase in metabolic activity. The genetic algorithm approach can be used to optimize other components of culture media to efficiently optimize chosen parameters without the need for detailed knowledge on all possible interactions.
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Project description:The novelty of this article lies in introducing a novel stochastic technique named the Hippopotamus Optimization (HO) algorithm. The HO is conceived by drawing inspiration from the inherent behaviors observed in hippopotamuses, showcasing an innovative approach in metaheuristic methodology. The HO is conceptually defined using a trinary-phase model that incorporates their position updating in rivers or ponds, defensive strategies against predators, and evasion methods, which are mathematically formulated. It attained the top rank in 115 out of 161 benchmark functions in finding optimal value, encompassing unimodal and high-dimensional multimodal functions, fixed-dimensional multimodal functions, as well as the CEC 2019 test suite and CEC 2014 test suite dimensions of 10, 30, 50, and 100 and Zigzag Pattern benchmark functions, this suggests that the HO demonstrates a noteworthy proficiency in both exploitation and exploration. Moreover, it effectively balances exploration and exploitation, supporting the search process. In light of the results from addressing four distinct engineering design challenges, the HO has effectively achieved the most efficient resolution while concurrently upholding adherence to the designated constraints. The performance evaluation of the HO algorithm encompasses various aspects, including a comparison with WOA, GWO, SSA, PSO, SCA, FA, GOA, TLBO, MFO, and IWO recognized as the most extensively researched metaheuristics, AOA as recently developed algorithms, and CMA-ES as high-performance optimizers acknowledged for their success in the IEEE CEC competition. According to the statistical post hoc analysis, the HO algorithm is determined to be significantly superior to the investigated algorithms. The source codes of the HO algorithm are publicly available at https://www.mathworks.com/matlabcentral/fileexchange/160088-hippopotamus-optimization-algorithm-ho .
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