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Fluorescent Antibody Technique

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Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection.

Journal of visualized experiments : JoVE
A central question in developmental neurobiology is how neural stem and progenitor cells form the brain. To answer this question, one needs to label, manipulate, and follow single cells in the brain tissue with high resolution over time. This task is...

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Scientific reports
Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to ...

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...

Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation.

IEEE transactions on medical imaging
Separating and labeling each nuclear instance (instance-aware segmentation) is the key challenge in nuclear image segmentation. Deep Convolutional Neural Networks have been demonstrated to solve nuclear image segmentation tasks across different imagi...

Multiplex computational pathology for treatment response predication.

Cancer cell
Recently published in Science, AstroPath outlines a standardized workflow for multiplex immunofluorescence (mIF) panel development, imaging, and analysis; showcases its potential in biomarker discovery for predicting response to anti-PD-1 treatment; ...

DULoc: quantitatively unmixing protein subcellular location patterns in immunofluorescence images based on deep learning features.

Bioinformatics (Oxford, England)
MOTIVATION: Knowledge of subcellular locations of proteins is of great significance for understanding their functions. The multi-label proteins that simultaneously reside in or move between more than one subcellular structure usually involve with com...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Scientific reports
Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline t...

SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images.

Briefings in bioinformatics
With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular map of human proteins has become a central task in the spatial proteome. The cell atlas of the Human Protein Atlas (HPA) provides precious resources for recog...