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Cells, Cultured

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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...

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...

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...

Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...

Deep Learning-Enabled Label-Free On-Chip Detection and Selective Extraction of Cell Aggregate-Laden Hydrogel Microcapsules.

Small (Weinheim an der Bergstrasse, Germany)
Microfluidic encapsulation of cells/tissues in hydrogel microcapsules has attracted tremendous attention in the burgeoning field of cell-based medicine. However, when encapsulating rare cells and tissues (e.g., pancreatic islets and ovarian follicles...

Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.

Stem cell reports
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...

Deep learning-based predictive identification of neural stem cell differentiation.

Nature communications
The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is...

An active learning approach for clustering single-cell RNA-seq data.

Laboratory investigation; a journal of technical methods and pathology
Single-cell RNA sequencing (scRNA-seq) data has been widely used to profile cellular heterogeneities with a high-resolution picture. Clustering analysis is a crucial step of scRNA-seq data analysis because it provides a chance to identify and uncover...

Deep learning of gene relationships from single cell time-course expression data.

Briefings in bioinformatics
Time-course gene-expression data have been widely used to infer regulatory and signaling relationships between genes. Most of the widely used methods for such analysis were developed for bulk expression data. Single cell RNA-Seq (scRNA-Seq) data offe...

Evaluation of machine learning approaches for cell-type identification from single-cell transcriptomics data.

Briefings in bioinformatics
Single-cell transcriptomics technologies have vast potential in advancing our understanding of cellular heterogeneity in complex tissues. While methods to interpret single-cell transcriptomics data are developing rapidly, challenges in most analysis ...