Publications associées à Coloration à l'argent

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Demetri Psaltis, Joowon Lim, Daniele Pirone

The accurate identification of the three-dimensional quantitative shape of a cell nucleus is now possible without fluorescent staining by applying computational segmentation to refractive index tomograms recorded in the flow cytometry mode. Quantitative ph ...

NATURE PORTFOLIO2022

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

Michaël Unser, Cathrin Brisken, Daniel Sage, Olivier Burri, Martin Weigert, Fabio De Martino, Quentin Juppet

Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis gener ...

2021

Dual-Activatable Cell Tracker for Controlled and Prolonged Single-Cell Labeling

Pablo Rivera Fuentes, Salome Riccarda Püntener

Cell trackers are fluorescent chemical tools that facilitate imaging and tracking cells within live organisms. Despite their versatility, these dyes lack specificity, tend to leak outside of the cell, and stain neighboring cells. Here, we report a dual-act ...

AMER CHEMICAL SOC2020

Using flow cytometry and light-induced fluorescence to characterize the variability and characteristics of bioaerosols in springtime in Metro Atlanta, Georgia

Athanasios Nenes

The abundance and speciation of primary biological aerosol particles (PBAP) is important for understanding their impacts on human health, cloud formation, and ecosystems. Towards this, we have developed a protocol for quantifying PBAP collected from large ...

COPERNICUS GESELLSCHAFT MBH2020

Digital staining through the application of deep neural networks to multi-modal multi-photon microscopy

Demetri Psaltis, Navid Borhani

Deep neural networks have been used to map multi-modal, multi-photon microscopy measurements of a label-free tissue sample to its corresponding histologically stained brightfield microscope colour image. It is shown that the extra structural and functional ...

OPTICAL SOC AMER2019

High-content, cell-by-cell assessment of HER2 overexpression and amplification: a tool for intratumoral heterogeneity detection in breast cancer

Martinus Gijs, Daniel Migliozzi, Huu Tuan Nguyen

Immunohistochemistry and fluorescence in situ hybridization are the two standard methods for human epidermal growth factor receptor 2 (HER2) assessment. However, they have severe limitations to assess quantitatively intratumoral heterogeneity (ITH) when mu ...

NATURE PUBLISHING GROUP2019

Microfluidic-based immunohistochemistry for breast cancer diagnosis: a comparative clinical study

Martinus Gijs, Diego Gabriel Dupouy, Saska Brajkovic, Fabio Aimi

Breast cancer is a highly heterogeneous disease. The efficacy of tailored therapeutic strategies relies on the precise detection of diagnostic biomarkers by immunohistochemistry (IHC). Therefore, considering the increasing incidence of breast cancer cases, ...

2019

Design and Synthesis of Gatekeeper Coated Dendritic Silica/Titania Mesoporous Nanoparticles with Sustained and Controlled Drug Release Properties for Targeted Synergetic Chemo-Sonodynamic Therapy

Saba Rezakhani, Samira Malekmohammadi

New dendritic silica/titania mesoporous nanoparticles (DSTNs) loaded with curcumin (CUR) were synthesized and coated with polyethylenimine-folic acid groups (PEI-FA) for an ultrasound (US)-triggered drug release and combined chemo-sonodynamic therapy. The ...

2019

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Coloration à l'argent

Protocol for live imaging of intracellular nanoscale structures using atomic force microscopy with nanoneedle probes

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

Dual-Activatable Cell Tracker for Controlled and Prolonged Single-Cell Labeling

Using flow cytometry and light-induced fluorescence to characterize the variability and characteristics of bioaerosols in springtime in Metro Atlanta, Georgia

MarrowQuantAcross Aging and Aplasia: A Digital Pathology Workflow for Quantification of Bone Marrow Compartments in Histological Sections

Digital staining through the application of deep neural networks to multi-modal multi-photon microscopy

High-content, cell-by-cell assessment of HER2 overexpression and amplification: a tool for intratumoral heterogeneity detection in breast cancer

Microfluidic-based immunohistochemistry for breast cancer diagnosis: a comparative clinical study

Design and Synthesis of Gatekeeper Coated Dendritic Silica/Titania Mesoporous Nanoparticles with Sustained and Controlled Drug Release Properties for Targeted Synergetic Chemo-Sonodynamic Therapy

Graph Chatbot

Chattez avec Graph Search

Protocol for live imaging of intracellular nanoscale structures using atomic force microscopy with nanoneedle probes

Design and Synthesis of Gatekeeper Coated Dendritic Silica/Titania Mesoporous Nanoparticles with Sustained and Controlled Drug Release Properties for Targeted Synergetic Chemo-Sonodynamic Therapy

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

MarrowQuantAcross Aging and Aplasia: A Digital Pathology Workflow for Quantification of Bone Marrow Compartments in Histological Sections

Dual-Activatable Cell Tracker for Controlled and Prolonged Single-Cell Labeling

Digital staining through the application of deep neural networks to multi-modal multi-photon microscopy

Microfluidic-based immunohistochemistry for breast cancer diagnosis: a comparative clinical study

High-content, cell-by-cell assessment of HER2 overexpression and amplification: a tool for intratumoral heterogeneity detection in breast cancer

Using flow cytometry and light-induced fluorescence to characterize the variability and characteristics of bioaerosols in springtime in Metro Atlanta, Georgia

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features