AIMC Topic: Induced Pluripotent Stem Cells
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Scalable 96-well Plate Based iPSC Culture and Production Using a Robotic Liquid Handling System.
Journal of visualized experiments : JoVE
May 14, 2015
Continued advancement in pluripotent stem cell culture is closing the gap between bench and bedside for using these cells in regenerative medicine, drug discovery and safety testing. In order to produce stem cell derived biopharmaceutics and cells fo...
High-throughput robotic isolation of human iPS cell clones reveals frequent homozygous induction of identical genetic manipulations by CRISPR-Cas9.
Stem cell research & therapy
Jun 7, 2025
BACKGROUND: Genome editing in human iPS cells is a powerful approach in regenerative medicine. CRISPR-Cas9 is the most common genome editing tool, but it often induces byproduct insertions and deletions in addition to the desired edits. Therefore, ge...
Single-cell mitochondrial morphomics reveals cellular heterogeneity and predicts complex I, III, and ATP synthase Inhibition responses.
Scientific reports
May 14, 2025
Mitochondrial heterogeneity drives diverse cellular responses in neurodegenerative diseases, complicating the evaluation of mitochondrial dysfunction. In this study, we describe a high-throughput imaging and analysis approach to investigate cell-to-c...
AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing.
Communications biology
May 13, 2025
Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered by batch-to-batch variability and inefficient purification processes. Here, we introduce CM-AI, a no...
Deep Learning Method for Estimating Germ-layer Regions of Early Differentiated Human Induced Pluripotent Stem Cells on Micropattern Using Bright-field Microscopy Image.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Live cell staining is expensive and may bring potential safety issues in downstream clinical applications, bright-field images rather than staining images should be more suitable to reveal time-series changes of differentiating hiPSCs (human induced ...
Prediction of Human Induced Pluripotent Stem Cell Formation Based on Deep Learning Analyses Using Time-lapse Brightfield Microscopy Images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
We use deep learning methods to predict human induced pluripotent stem cell (hiPSC) formation using time-lapse brightfield microscopy images taken from a cell identified as the beginning of entered into the reprogramming process. A U-net is used to s...
Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.
Stem cell reports
May 11, 2021
Lineage tracing is a powerful tool in developmental biology to interrogate the evolution of tissue formation, but the dense, three-dimensional nature of tissue limits the assembly of individual cell trajectories into complete reconstructions of devel...
Calcific aortic valve disease: turning therapeutic discovery up a notch.
Nature reviews. Cardiology
May 1, 2021
Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.
The Journal of clinical investigation
Feb 3, 2020
Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and noninvasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodolo...
Human Induced Pluripotent Stem Cell Reprogramming Prediction in Microscopy Images using LSTM based RNN.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
We present a LSTM (Long Short-Term Memory) based RNN (recurrent neural network) method for predicting human induced Pluripotent Stem (hiPS) cells in the reprogramming process. The method uses a trained LSTM network by time-lapse microscopy images to ...
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