Multiple Iteractive Labeling by Antibody Neodeposition (MILAN)

2019 ◽  
Author(s):  
Giorgio Cattoretti ◽  
Francesca Maria Bosisio ◽  
Lukas Marcelis ◽  
Maddalena Maria Bolognesi
Keyword(s):  
Image Analysis ◽  
Tissue Section ◽  
Indirect Immunofluorescence ◽  
Analysis Software ◽  
Tissue Sections ◽  
Image Analysis Software ◽  
Single Section ◽  
Fluorescent Image ◽  
Secondary Antibodies

Abstract Multiplexing, labeling for multiple immunostains the very same cell or tissue section in situ, is of considerable interest. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, scarcity of specialized skills or facilities. We have validated and detail here a method based on common primary and secondary antibodies, diffusely available fluorescent image scanners and routinely processed tissue sections \(FFPE). It entails rounds of four-color indirect immunofluorescence, image acquisition and removal \(stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulphide cleavage. In excess of 50 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software.

scholarly journals Multiple Iterative Labeling by Antibody Neodeposition (MILAN)

2019 ◽  
Author(s):  
Giorgio Cattoretti ◽  
Francesca Maria Bosisio ◽  
Lukas Marcelis ◽  
Maddalena Maria Bolognesi
Keyword(s):  
Image Analysis ◽  
Tissue Section ◽  
Indirect Immunofluorescence ◽  
Analysis Software ◽  
Tissue Sections ◽  
Image Analysis Software ◽  
Single Section ◽  
Fluorescent Image ◽  
Secondary Antibodies

Abstract Multiplexing, labeling for multiple immunostains the very same cell or tissue section in situ, is of considerable interest. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, scarcity of specialized skills or facilities. We have validated and detail here a method based on common primary and secondary antibodies, diffusely available fluorescent image scanners and routinely processed tissue sections \(FFPE). It entails rounds of four-color indirect immunofluorescence, image acquisition and removal \(stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulphide cleavage. In excess of 50 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software.

scholarly journals Multiple Iterative Labeling by Antibody Neodeposition (MILAN)

2019 ◽  
Author(s):  
Giorgio Cattoretti ◽  
Francesca Maria Bosisio ◽  
Lukas Marcelis ◽  
Maddalena Maria Bolognesi
Keyword(s):  
Image Analysis ◽  
Tissue Section ◽  
Indirect Immunofluorescence ◽  
Analysis Software ◽  
Tissue Sections ◽  
Image Analysis Software ◽  
Single Section ◽  
Fluorescent Image ◽  
Secondary Antibodies

Abstract (What’s new in protocol Version 5: an expanded troubleshooting section, more validated antibodies)Multiplexing, labeling for multiple immunostains the very same cell or tissue section in situ, is of considerable interest. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, scarcity of specialized skills or facilities. We have validated and detail here a method based on common primary and secondary antibodies, diffusely available fluorescent image scanners and routinely processed tissue sections \(FFPE). It entails rounds of four-color indirect immunofluorescence, image acquisition and removal \(stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulphide cleavage. In excess of 50 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software.

scholarly journals Multiple Iterative Labeling by Antibody Neodeposition (MILAN)

2019 ◽  
Author(s):  
Giorgio Cattoretti ◽  
Francesca Maria Bosisio ◽  
Lukas Marcelis ◽  
Maddalena Maria Bolognesi
Keyword(s):  
Image Analysis ◽  
Tissue Section ◽  
Indirect Immunofluorescence ◽  
Analysis Software ◽  
Tissue Sections ◽  
Image Analysis Software ◽  
Single Section ◽  
Fluorescent Image ◽  
Secondary Antibodies

Abstract Multiplexing, labeling for multiple immunostains the very same cell or tissue section in situ, is of considerable interest. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, scarcity of specialized skills or facilities. We have validated and detail here a method based on common primary and secondary antibodies, diffusely available fluorescent image scanners and routinely processed tissue sections \(FFPE). It entails rounds of four-color indirect immunofluorescence, image acquisition and removal \(stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulphide cleavage. In excess of 50 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software.

scholarly journals Multiplex Staining by Sequential Immunostaining and Antibody Removal on Routine Tissue Sections

2017 ◽  
Vol 65 (8) ◽  
pp. 431-444 ◽  
Author(s):  
Maddalena Maria Bolognesi ◽  
Marco Manzoni ◽  
Carla Rossana Scalia ◽  
Stefano Zannella ◽  
Francesca Maria Bosisio ◽  
...  
Keyword(s):  
Analysis Software ◽  
In Situ Characterization ◽  
Salt Treatment ◽  
Tissue Sections ◽  
Single Section ◽  
Fluorescent Image ◽  
Spectral Separation ◽  
Secondary Antibodies

Multiplexing, labeling for multiple immunostains in the very same cell or tissue section in situ, has raised considerable interest. The methods proposed include the use of labeled primary antibodies, spectral separation of fluorochromes, bleaching of the fluorophores or chromogens, blocking of previous antibody layers, all in various combinations. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, and scarcity of specialized skills or facilities. We have validated a method based on common primary and secondary antibodies and diffusely available fluorescent image scanners. It entails rounds of four-color indirect immunofluorescence, image acquisition, and removal (stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulfide cleavage and a detergent or by a chaotropic salt treatment, this latter followed by antigen refolding. More than 30 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software. Multiplexing on routine tissue sections is a high throughput tool for in situ characterization of neoplastic, reactive, inflammatory, and normal cells.

scholarly journals Multiplex staining by sequential immunostaining and antibody removal on routine tissue sections

2017 ◽  
Author(s):  
Maddalena Maria Bolognesi ◽  
Marco Manzoni ◽  
Carla Rossana Scalia ◽  
Stefano Zannella ◽  
Francesca Maria Bosisio ◽  
...  
Keyword(s):  
Analysis Software ◽  
In Situ Characterization ◽  
Salt Treatment ◽  
Tissue Sections ◽  
Single Section ◽  
Fluorescent Image ◽  
Spectral Separation ◽  
Secondary Antibodies

ABSTRACTMultiplexing (mplx), labeling for multiple immunostains the very same cell or tissue section in situ, has raised considerable interest. The methods proposed include the use of labelled primary antibodies, spectral separation of fluorochromes, bleaching of the fluorophores or chromogens, blocking of previous antibody layers, all in various combinations. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, scarcity of specialized skills or facilities.We have validated a method based on common primary and secondary antibodies and diffusely available fluorescent image scanners. It entails rounds of four-color indirect immunofluorescence, image acquisition and removal (stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulphide cleavage and a detergent or by a chaotropic salt treatment, this latter followed by antigen refolding. More than thirty different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software. Mplx on routine tissue sections is a high throughput tool for in situ characterization of neoplastic, reactive, inflammatory and normal cells.

scholarly journals ChromaWizard: An open source image analysis software for multicolor fluorescence in situ hybridization analysis

2018 ◽  
Vol 93 (7) ◽  
pp. 749-754
Author(s):  
Norbert Auer ◽  
Astrid Hrdina ◽  
Chaitra Hiremath ◽  
Sabine Vcelar ◽  
Martina Baumann ◽  
...  
Keyword(s):  
Image Analysis ◽  
In Situ Hybridization ◽  
Fluorescence In Situ Hybridization ◽  
Open Source ◽  
Hybridization Analysis ◽  
Source Image ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Multicolor Fluorescence

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning

2017 ◽  
Vol 49 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Nayana Damiani Macedo ◽  
Aline Rodrigues Buzin ◽  
Isabela Bastos Binotti Abreu de Araujo ◽  
Breno Valentim Nogueira ◽  
Tadeu Uggere de Andrade ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Analysis ◽  
Light Microscopy ◽  
Renal Tissue ◽  
Analysis Software ◽  
Tissue Sections ◽  
Image Analysis Software ◽  
Objective Detection

scholarly journals Image Analysis Software Based on Color Segmentation for Characterization of Viability and Physiological Activity of Biofilms

2009 ◽  
Vol 75 (6) ◽  
pp. 1734-1739 ◽  
Author(s):  
Luis E. Chávez de Paz
Keyword(s):  
Image Analysis ◽  
Structural Parameters ◽  
Physiological Activity ◽  
The Novel ◽  
Analysis Software ◽  
Image Analysis Software ◽  
Dual Channel ◽  
Fluorescent Markers ◽  
Oral Biofilms

ABSTRACT The novel image analysis software package bioImage_L was tested to calculate biofilm structural parameters in oral biofilms stained with dual-channel fluorescent markers. By identifying color tonalities in situ, the software independently processed the color subpopulations and characterized the viability and metabolic activity of biofilms.

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