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Patent
Applied Proteomics | Date: 2015-03-27

Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.


Patent
Applied Proteomics | Date: 2017-02-01

Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.


Otto A.,University of Greifswald | Becher D.,Applied Proteomics | Schmidt F.,Applied Proteomics
Proteomics | Year: 2014

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


The TaqMan real-time PCR has the highest potential for automation, therefore representing the currently most suitable method for screening, allowing the detection of fraudulent or unintentional mislabeling of species. This work describes the development of a real-time polymerase chain reaction (RT-PCR) system for the detection and identification of common octopus (Octopus vulgaris) and main substitute species (Eledone cirrhosa and Dosidicus gigas). This technique is notable for the combination of simplicity, speed, sensitivity and specificity in an homogeneous assay. The method can be applied to all kinds of products; fresh, frozen and processed, including those undergoing intensive processes of transformation. This methodology was validated to check how the degree of food processing affects the method and the detection of each species. Moreover, it was applied to 34 commercial samples to evaluate the labeling of products made from them. The methodology herein developed is useful to check the fulfillment of labeling regulations for seafood products and to verify traceability in commercial trade and for fisheries control. © 2012 Elsevier Ltd. All rights reserved.


Patent
Applied Proteomics | Date: 2014-10-28

The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.


Patent
Applied Proteomics | Date: 2014-10-28

The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.


Patent
Applied Proteomics | Date: 2014-10-28

The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.


Patent
Applied Proteomics | Date: 2014-10-28

The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.


Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.


Patent
Applied Proteomics | Date: 2013-12-02

The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

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