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A universally applicable and rapid method for measuring the growth of streptomyces and other filamentous microorganisms by methylene blue adsorption-desorption.

ABSTRACT: Quantitative assessment of growth of filamentous microorganisms, such as streptomycetes, is generally restricted to determination of dry weight. Here, we describe a straightforward methylene blue-based sorption assay to monitor microbial growth quantitatively, simply, and rapidly. The assay is equally applicable to unicellular and filamentous bacterial and eukaryotic microorganisms.

SUBMITTER: Fischer M

PROVIDER: S-EPMC3697523 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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A universally applicable and rapid method for measuring the growth of streptomyces and other filamentous microorganisms by methylene blue adsorption-desorption.

Fischer Marco M Sawers R Gary RG

Applied and environmental microbiology 20130510 14

Quantitative assessment of growth of filamentous microorganisms, such as streptomycetes, is generally restricted to determination of dry weight. Here, we describe a straightforward methylene blue-based sorption assay to monitor microbial growth quantitatively, simply, and rapidly. The assay is equally applicable to unicellular and filamentous bacterial and eukaryotic microorganisms. ...[more]

PMID: 23666340

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Project description:BackgroundMany studies have successfully identified radiomics features reflecting macroscale tumor features and tumor microenvironment for various organs. There is an increased interest in applying these radiomics features found in a given organ to other organs. Here, we explored whether common radiomics features could be identified over target organs in vastly different environments.MethodsFour datasets of three organs were analyzed. One radiomics model was constructed from the training set (lungs, n = 401), and was further evaluated in three independent test sets spanning three organs (lungs, n = 59; kidneys, n = 48; and brains, n = 43). Intensity histograms derived from the whole organ were compared to establish organ-level differences. We constructed a radiomics score based on selected features using training lung data over the tumor region. A total of 143 features were computed for each tumor. We adopted a feature selection approach that favored stable features, which can also capture survival. The radiomics score was applied to three independent test data from lung, kidney, and brain tumors, and whether the score could be used to separate high- and low-risk groups, was evaluated.ResultsEach organ showed a distinct pattern in the histogram and the derived parameters (mean and median) at the organ-level. The radiomics score trained from the lung data of the tumor region included seven features, and the score was only effective in stratifying survival for other lung data, not in other organs such as the kidney and brain. Eliminating the lung-specific feature (2.5 percentile) from the radiomics score led to similar results. There were no common features between training and test sets, but a common category of features (texture category) was identified.ConclusionAlthough the possibility of a generally applicable model cannot be excluded, we suggest that radiomics score models for survival were mostly specific for a given organ; applying them to other organs would require careful consideration of organ-specific properties.

Dataset Information

A universally applicable and rapid method for measuring the growth of streptomyces and other filamentous microorganisms by methylene blue adsorption-desorption.

Publications

A universally applicable and rapid method for measuring the growth of streptomyces and other filamentous microorganisms by methylene blue adsorption-desorption.

Similar Datasets

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