The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Thangavel Balasubramanian - One of the best experts on this subject based on the ideXlab platform.
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Toxicity Study of Silver Nanoparticles Synthesized from Suaeda monoica on Hep-2 Cell Line
Avicenna journal of medical biotechnology, 2012Co-Authors: K. Satyavani, S. Gurudeeban, Thiruganasambandam Ramanathan, Thangavel BalasubramanianAbstract:Recently there has been fabulous excitement in the nano-biotechnological area for the study of nanoparticles synthesis using some natural biological system, which has led the growth advanced nanomaterials. This intention made us to assess the biologically synthesized silver nanoparticles from the leaf of Suaeda monoica (S.monoica) using 1 mM silver nitrate. The leaf extract of S.monoica incubated with 1 mM silver nitrate solution and characterized by UV- spectrometer and AFM. The effect of synthesized silver nanoparticles on Human Epidermoid Larynx Carcinoma cell line was evaluated by the MTT colorimetric technique. As a result we observed gradual change in the colour of extract from greenish to brown. The synthesized silver nanoparticles confirmed by UV at 430 nm and spherical shape identified in the range of 31 nm under AFM. The effect of silver nanoparticles on Human Epidermoid Larynx Carcinoma cell line exhibits a dose-dependent toxicity for the cell tested and the viability of Hep-2 cells decreased to 50% (IC50) at the concentration of 500 nM. Further findings will be determined the exact mechanisms of this cost effective Nano-treatments.
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Biomedical potential of silver nanoparticles synthesized from calli cells of Citrullus colocynthis (L.) Schrad
Journal of nanobiotechnology, 2011Co-Authors: K. Satyavani, S. Gurudeeban, T. Ramanathan, Thangavel BalasubramanianAbstract:Background An increasingly common application is the use of silver nanoparticles for antimicrobial coatings, wound dressings, and biomedical devices. In this present investigation, we report, biomedical potential of silver nanopaticles synthesized from calli extract of Citrullus colocynthis on Human epidermoid Larynx Carcinoma (HEp -2) cell line.
Theodore Alexandrov - One of the best experts on this subject based on the ideXlab platform.
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MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human Larynx Carcinoma
Journal of Cancer Research and Clinical Oncology, 2013Co-Authors: Theodore Alexandrov, Michael Becker, Orlando Guntinas-lichius, Günther Ernst, Ferdinand EggelingAbstract:Purpose For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a Larynx Carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section. Methods Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating spatial a segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image. Results The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the Larynx Carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way. Conclusions The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing Carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.
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MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human Larynx Carcinoma.
Journal of cancer research and clinical oncology, 2012Co-Authors: Theodore Alexandrov, Michael Becker, Orlando Guntinas-lichius, Günther Ernst, Ferdinand Von EggelingAbstract:For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a Larynx Carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section. Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating spatial a segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image. The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the Larynx Carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way. The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing Carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.
K. Satyavani - One of the best experts on this subject based on the ideXlab platform.
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Toxicity Study of Silver Nanoparticles Synthesized from Suaeda monoica on Hep-2 Cell Line
Avicenna journal of medical biotechnology, 2012Co-Authors: K. Satyavani, S. Gurudeeban, Thiruganasambandam Ramanathan, Thangavel BalasubramanianAbstract:Recently there has been fabulous excitement in the nano-biotechnological area for the study of nanoparticles synthesis using some natural biological system, which has led the growth advanced nanomaterials. This intention made us to assess the biologically synthesized silver nanoparticles from the leaf of Suaeda monoica (S.monoica) using 1 mM silver nitrate. The leaf extract of S.monoica incubated with 1 mM silver nitrate solution and characterized by UV- spectrometer and AFM. The effect of synthesized silver nanoparticles on Human Epidermoid Larynx Carcinoma cell line was evaluated by the MTT colorimetric technique. As a result we observed gradual change in the colour of extract from greenish to brown. The synthesized silver nanoparticles confirmed by UV at 430 nm and spherical shape identified in the range of 31 nm under AFM. The effect of silver nanoparticles on Human Epidermoid Larynx Carcinoma cell line exhibits a dose-dependent toxicity for the cell tested and the viability of Hep-2 cells decreased to 50% (IC50) at the concentration of 500 nM. Further findings will be determined the exact mechanisms of this cost effective Nano-treatments.
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Biomedical potential of silver nanoparticles synthesized from calli cells of Citrullus colocynthis (L.) Schrad
Journal of nanobiotechnology, 2011Co-Authors: K. Satyavani, S. Gurudeeban, T. Ramanathan, Thangavel BalasubramanianAbstract:Background An increasingly common application is the use of silver nanoparticles for antimicrobial coatings, wound dressings, and biomedical devices. In this present investigation, we report, biomedical potential of silver nanopaticles synthesized from calli extract of Citrullus colocynthis on Human epidermoid Larynx Carcinoma (HEp -2) cell line.
Ferdinand Eggeling - One of the best experts on this subject based on the ideXlab platform.
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MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human Larynx Carcinoma
Journal of Cancer Research and Clinical Oncology, 2013Co-Authors: Theodore Alexandrov, Michael Becker, Orlando Guntinas-lichius, Günther Ernst, Ferdinand EggelingAbstract:Purpose For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a Larynx Carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section. Methods Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating spatial a segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image. Results The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the Larynx Carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way. Conclusions The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing Carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.
Ferdinand Von Eggeling - One of the best experts on this subject based on the ideXlab platform.
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MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human Larynx Carcinoma.
Journal of cancer research and clinical oncology, 2012Co-Authors: Theodore Alexandrov, Michael Becker, Orlando Guntinas-lichius, Günther Ernst, Ferdinand Von EggelingAbstract:For several decades, conventional histological staining and immunohistochemistry (IHC) have been the main tools to visualize and understand tissue morphology and structure. IHC visualizes the spatial distribution of individual protein species directly in tissue. However, a specific antibody is required for each protein, and multiplexing capabilities are extremely limited, rarely visualizing more than two proteins simultaneously. With the recent emergence of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-imaging), it is becoming possible to study more complex proteomic patterns directly in tissue. However, the analysis and interpretation of large and complex MALDI-imaging data requires advanced computational methods. In this paper, we show how the recently introduced method of spatial segmentation can be applied to analysis and interpretation of a Larynx Carcinoma section and compare the spatial segmentation with the histological annotation of the same tissue section. Matrix-assisted laser desorption/ionization imaging is a label-free spatially resolved analytical technique, which allows detection and visualization of hundreds of proteins at once. Spatial segmentation of the MALDI-imaging data by clustering of spectra by their similarity was performed, automatically generating spatial a segmentation map of the tissue section, where regions of similar proteomic patterns were highlighted. The tissue was stained with the hematoxylin and eosin (H&E), histopathologically analyzed and annotated. The segmentation map was interpreted after its overlay with the H&E microscopy image. The automatically generated segmentation map exhibits high correspondence to the detailed histological annotation of the Larynx Carcinoma tissue section. By superimposing, the segmentation map based on the proteomic profiles with H&E-stained microscopic images, we demonstrate precise localization of complex and histopathologically relevant tissue features in an automated way. The combination of MALDI-imaging and automatic spatial segmentation is a useful approach in analyzing Carcinoma tissue and provides a deeper insight into the functional proteomic organization of the respective tissue.
