AIMC Topic: Cell Line, Tumor

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AI-powered transmitted light microscopy for functional analysis of live cells.

Scientific reports
Transmitted light microscopy can readily visualize the morphology of living cells. Here, we introduce artificial-intelligence-powered transmitted light microscopy (AIM) for subcellular structure identification and labeling-free functional analysis of...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Life science alliance
Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cel...

Comparing convolutional neural networks and preprocessing techniques for HEp-2 cell classification in immunofluorescence images.

Computers in biology and medicine
Autoimmune diseases are the third highest cause of mortality in the world, and the identification of an anti-nuclear antibody via an immunofluorescence test for HEp-2 cells is a standard procedure to support diagnosis. In this work, we assess the per...

Identification of Synthetic Activators of Cancer Cell Migration by Hybrid Deep Learning.

Chembiochem : a European journal of chemical biology
Deep convolutional neural networks (CNNs) are a method of choice for image recognition. Herein a hybrid CNN approach is presented for molecular pattern recognition in drug discovery. Using self-organizing map images of molecular pharmacophores as inp...

Multifunctional Nanorobot System for Active Therapeutic Delivery and Synergistic Chemo-photothermal Therapy.

Nano letters
Nanorobots are safe and exhibit powerful functionalities, including delivery, therapy, and diagnosis. Therefore, they are in high demand for the development of new cancer therapies. Although many studies have contributed to the progressive developmen...

Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...

Three-dimensional convolutional neural networks for simultaneous dual-tracer PET imaging.

Physics in medicine and biology
Dual-tracer positron emission tomography (PET) is a promising technique to measure the distribution of two tracers in the body by a single scan, which can improve the clinical accuracy of disease diagnosis and can also serve as a research tool for sc...

Growth Inhibitory and Pro-Apoptotic Effects of Ornamental Pomegranate Extracts in Du145 Human Prostate Cancer Cells.

Nutrition and cancer
Prostate cancer is the most common form of cancer in the male. Epidemiological studies have associated increased cancer incidence with reduced consumption of fruit and vegetables. This study was aimed to investigate the influence of dwarf pomegranat...

Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification.

Small (Weinheim an der Bergstrasse, Germany)
Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomarkers for cancer diagnostics. However, the present single-variate analysis of exosomes has greatly li...

Deep Learning Diffuse Optical Tomography.

IEEE transactions on medical imaging
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level. However, due to the complicated non-linear photon scattering physi...