AIMC Topic: Cell Differentiation

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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...

Machine Learning of Hematopoietic Stem Cell Divisions from Paired Daughter Cell Expression Profiles Reveals Effects of Aging on Self-Renewal.

Cell systems
Changes in stem cell activity may underpin aging. However, these changes are not completely understood. Here, we combined single-cell profiling with machine learning and in vivo functional studies to explore how hematopoietic stem cell (HSC) division...

Neuronal differentiation strategies: insights from single-cell sequencing and machine learning.

Development (Cambridge, England)
Neuronal replacement therapies rely on the differentiation of specific cell types from embryonic or induced pluripotent stem cells, or on the direct reprogramming of differentiated adult cells via the expression of transcription factors or signaling...