AIMC Topic: Cell Differentiation

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Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

ACS applied materials & interfaces
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale...

Development of convolutional neural networks for recognition of tenogenic differentiation based on cellular morphology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The use of automated systems for image recognition is highly preferred for regenerative medicine applications to evaluate stem cell differentiation early in the culturing state with non-invasive methodologies instead of inva...

Effects of galectin-1 on immunomodulatory properties of human monocyte-derived dendritic cells.

Growth factors (Chur, Switzerland)
Our study aimed to evaluate the effects of Gal-1 in dose depending manner on maturation and immunomodulatory properties of monocyte-derived (Mo) DCs . The effects were analyzed by monitoring their phenotypic characteristics, cytokine profile, and the...

A deep learning algorithm to translate and classify cardiac electrophysiology.

eLife
The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network ...

Regression plane concept for analysing continuous cellular processes with machine learning.

Nature communications
Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool e...

Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.

Stem cells (Dayton, Ohio)
Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop quality control methods to standardize stem cell manufacturing. Here, we report a deep learning-based automated cell tracking (DeepACT) technology fo...

Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture.

STAR protocols
Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over existing technologies and providing for the discovery of new biological insights. Functional neural netwo...

Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status.

Computers in biology and medicine
Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of high quality hiPSCs, obtai...