In this issue

In this issue Microbial community fingerprinting of river watersFlow cytometric fingerprinting has been successfully tested to provide new ecological information, possibly suitable for better managing both natural and engineered aquatic systems. Current approaches to resolve cytometric profiles of aquatic microbial communities are still under development and have not yet been integrated into either water monitoring practices or ecosystems modelling. Amalfitano and coworkers established a novel data‐driven procedure to deconvolve bivariate cytometric profiles into cohesive microbial subgroups, in order to outline quantitative changes of the microbial community along a river perturbed by a wastewater feed. As for other low‐cost bioinformatics approaches suitable for automation, this technique holds the potential of becoming a powerful tool for water monitoring and microbial ecology studies, by providing a more objective way to evaluate phenotypic diversity in aquatic systems.In this issue: page 194FCM: Classifying native maize starchParticle size distribution, internal granular structure and composition significantly affect physicochemical properties, rheological properties and nutritional function of starch. It is of vital importance to study the methodology to classify native starch on the basis of different principles. Much tentative work has been proposed, mainly depending on either density or gravity gradients such as sieving, sedimentation, centrifugation and so on. However, FMC can empirically distinguish populations in terms of general characteristics in relation with particle size, particle shape, particle orientation, refractive index, surface topography and its structure. Although Clédat, Battu, Mokrini and Cardot have successfully applied FCM to characterize rice starch, starch samples have to undergo the pre‐treatment by SdFFF (sedimentation field‐flow fractionation). Fortunately, the technique by Zhang and Guo shows how native maize starch can be immediately suspended, classified and sorted by FCM. It provides an innovative perspective to evaluate the characterization of starch fractions.In this issue: page 213 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cytometry Wiley

In this issue

Cytometry , Volume 93 (2) – Jan 1, 2018
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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 International Society for Advancement of Cytometry
ISSN
1552-4922
eISSN
1552-4930
D.O.I.
10.1002/cyto.a.23341
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Abstract

Microbial community fingerprinting of river watersFlow cytometric fingerprinting has been successfully tested to provide new ecological information, possibly suitable for better managing both natural and engineered aquatic systems. Current approaches to resolve cytometric profiles of aquatic microbial communities are still under development and have not yet been integrated into either water monitoring practices or ecosystems modelling. Amalfitano and coworkers established a novel data‐driven procedure to deconvolve bivariate cytometric profiles into cohesive microbial subgroups, in order to outline quantitative changes of the microbial community along a river perturbed by a wastewater feed. As for other low‐cost bioinformatics approaches suitable for automation, this technique holds the potential of becoming a powerful tool for water monitoring and microbial ecology studies, by providing a more objective way to evaluate phenotypic diversity in aquatic systems.In this issue: page 194FCM: Classifying native maize starchParticle size distribution, internal granular structure and composition significantly affect physicochemical properties, rheological properties and nutritional function of starch. It is of vital importance to study the methodology to classify native starch on the basis of different principles. Much tentative work has been proposed, mainly depending on either density or gravity gradients such as sieving, sedimentation, centrifugation and so on. However, FMC can empirically distinguish populations in terms of general characteristics in relation with particle size, particle shape, particle orientation, refractive index, surface topography and its structure. Although Clédat, Battu, Mokrini and Cardot have successfully applied FCM to characterize rice starch, starch samples have to undergo the pre‐treatment by SdFFF (sedimentation field‐flow fractionation). Fortunately, the technique by Zhang and Guo shows how native maize starch can be immediately suspended, classified and sorted by FCM. It provides an innovative perspective to evaluate the characterization of starch fractions.In this issue: page 213

Journal

CytometryWiley

Published: Jan 1, 2018

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