AIMC Topic: HeLa Cells

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High-content video flow cytometry with digital cell filtering for label-free cell classification by machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Recent development of imaging flow cytometry (IFC) has enabled the measurements of single cells with high throughput, where fluorescent labels provide specificity for cellular diagnosis. The fluorescent labels may disturb the cell functions, and the ...

Carbon Dot Blinking Fingerprint Uncovers Native Membrane Receptor Organizations via Deep Learning.

Analytical chemistry
Oligomeric organization of G protein-coupled receptors is proposed to regulate receptor signaling and function, yet rapid and precise identification of the oligomeric status especially for native receptors on a cell membrane remains an outstanding ch...

Magnetic Biohybrid Microrobot Multimers Based on Cells for Enhanced Targeted Drug Delivery.

ACS applied materials & interfaces
Magnetic micro-/nanorobots have been regarded as a promising platform for targeted drug delivery, and tremendous strategies have been developed in recent years. However, realizing precise and efficient drug delivery in vivo still remains challenging,...

Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells.

Communications biology
Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power....

Manipulation of Multiple Cell-Cell Interactions by Tunable DNA Scaffold Networks.

Angewandte Chemie (International ed. in English)
Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. However, manipulation of the comprehensive and multiple intercellular interactions remains a challenge a...

Mitotic Index Determination on Live Cells From Label-Free Acquired Quantitative Phase Images Using a Supervised Autoencoder.

IEEE/ACM transactions on computational biology and bioinformatics
This interdisciplinary work focuses on the interest of a new auto-encoder for supervised classification of live cell populations growing in a thermostated imaging station and acquired by a Quantitative Phase Imaging (QPI) camera. This type of camera ...

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Nature cell biology
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...

Environmentally Adaptive Shape-Morphing Microrobots for Localized Cancer Cell Treatment.

ACS nano
Microrobots have attracted considerable attention due to their extensive applications in microobject manipulation and targeted drug delivery. To realize more complex micro-/nanocargo manipulation (., encapsulation and release) in biological applicati...

Machine Learning Assisted Classification of Cell Lines and Cell States on Quantitative Phase Images.

Cells
In this report, we present implementation and validation of machine-learning classifiers for distinguishing between cell types (HeLa, A549, 3T3 cell lines) and states (live, necrosis, apoptosis) based on the analysis of optical parameters derived fro...

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.

International journal of molecular sciences
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...