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A pixel-based likelihood framework for analysis of fluorescence recovery after photobleaching data
RISE., SP – Sveriges Tekniska Forskningsinstitut, SP Sveriges tekniska forskningsinstitut, SIK – Institutet för livsmedel och bioteknik.ORCID-id: 0000-0001-9979-5488
Vise andre og tillknytning
2008 (engelsk)Inngår i: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 232, nr 2, s. 260-269Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A new framework for the estimation of diffusion coefficients from data on fluorescence recovery after photobleaching (FRAP) with confocal laser scanning microscopy (CLSM) is presented. It is a pixel-based statistical methodology that efficiently utilizes all information about the diffusion process in the available set of images. The likelihood function for a series of images is maximized which gives both an estimate of the diffusion coefficient and a corresponding error. This framework opens up possibilities (1) to obtain localized diffusion coefficient estimates in both homogeneous and heterogeneous materials, (2) to account for time differences between the registrations at the pixels within each image, and (3) to plan experiments optimized with respect to the number of replications, the number of bleached regions for each replicate, pixel size, the number of pixels, the number of images in each series etc. To demonstrate the use of the new framework, we have applied it to a simple system with polyethylene glycol (PEG) and water where we find good agreement with diffusion coefficient estimates from NMR diffusometry. In this experiment, it is also shown that the effect of the point spread function is negligible, and we find fluorochrome-concentration levels that give a linear response function for the fluorescence intensity. © 2008 The Authors.

sted, utgiver, år, opplag, sider
2008. Vol. 232, nr 2, s. 260-269
Emneord [en]
Food Engineering
Emneord [sv]
Livsmedelsteknik
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-9012DOI: 10.1111/j.1365-2818.2008.02097.xPubMedID: 19017225OAI: oai:DiVA.org:ri-9012DiVA, id: diva2:966886
Tilgjengelig fra: 2016-09-08 Laget: 2016-09-08 Sist oppdatert: 2023-05-26bibliografisk kontrollert

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Loren, Niklas

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