AIMC Topic: HeLa Cells

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Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network.

Analytical chemistry
Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the c...

Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

Journal of the American Chemical Society
The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging based photobleaching event counting is a new approach for protein stoichiometry determination under phy...

Light-driven ultrasensitive self-powered cytosensing of circulating tumor cells via integration of biofuel cells and a photoelectrochemical strategy.

Journal of materials chemistry. B
Herein, a light-driven, membrane-less and mediator-less self-powered cytosensing platform via integration of biofuel cells (BFCs) and a photoelectrochemical strategy was developed for ultrasensitive detection of circulating tumor cells (CTCs). To con...

Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells.

ACS nano
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...

Defining host-pathogen interactions employing an artificial intelligence workflow.

eLife
UNLABELLED: For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentati...

Fluorescence microscopy image classification of 2D HeLa cells based on the CapsNet neural network.

Medical & biological engineering & computing
The development of computer technology now allows the quick and efficient automatic fluorescence microscopy generation of a large number of images of proteins in specific subcellular compartments using fluorescence microscopy. Digital image processin...

Deep learning enables cross-modality super-resolution in fluorescence microscopy.

Nature methods
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on ...

Cell Segmentation Using a Similarity Interface With a Multi-Task Convolutional Neural Network.

IEEE journal of biomedical and health informatics
Even though convolutional neural networks (CNN) have been used for cell segmentation, they require pixel-level ground truth annotations. This paper proposes a multitask learning algorithm for cell detection and segmentation using CNNs. We use dot ann...

Investigation of magnetic silica with thermoresponsive chitosan coating for drug controlled release and magnetic hyperthermia application.

Materials science & engineering. C, Materials for biological applications
In this study, a drug delivery system for chemo-hyperthermia applications is proposed and fabricated. The delivery system consists of magnetic-silica (MagSi) particles being encapsulated within a pH/thermo-responsive chitosan‑g‑N‑isopropylacrylamide ...

Sensitive detection of uracil-DNA glycosylase (UDG) activity based on terminal deoxynucleotidyl transferase-assisted formation of fluorescent copper nanoclusters (CuNCs).

Talanta
As an important base excision repair (BER) enzyme, uracil-DNA glycosylase (UDG) can repair the uracil-induced DNA lesion and maintain the genomic integrity. Herein, we have proposed a sensitive UDG assay based on the terminal deoxynucleotidyl transfe...