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Publikasjoner (10 av 19) Visa alla publikasjoner
Röding, M., Lacroix, L., Krona, A., Gebäck, T. & Loren, N. (2019). A Highly Accurate Pixel-Based FRAP Model Based on Spectral-Domain Numerical Methods. Biophysical Journal, 116(7), 1348-1361
Åpne denne publikasjonen i ny fane eller vindu >>A Highly Accurate Pixel-Based FRAP Model Based on Spectral-Domain Numerical Methods
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2019 (engelsk)Inngår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 116, nr 7, s. 1348-1361Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We introduce a new, to our knowledge, numerical model based on spectral methods for analysis of fluorescence recovery after photobleaching data. The model covers pure diffusion and diffusion and binding (reaction-diffusion) with immobile binding sites, as well as arbitrary bleach region shapes. Fitting of the model is supported using both conventional recovery-curve-based estimation and pixel-based estimation, in which all individual pixels in the data are utilized. The model explicitly accounts for multiple bleach frames, diffusion (and binding) during bleaching, and bleaching during imaging. To our knowledge, no other fluorescence recovery after photobleaching framework incorporates all these model features and estimation methods. We thoroughly validate the model by comparison to stochastic simulations of particle dynamics and find it to be highly accurate. We perform simulation studies to compare recovery-curve-based estimation and pixel-based estimation in realistic settings and show that pixel-based estimation is the better method for parameter estimation as well as for distinguishing pure diffusion from diffusion and binding. We show that accounting for multiple bleach frames is important and that the effect of neglecting this is qualitatively different for the two estimation methods. We perform a simple experimental validation showing that pixel-based estimation provides better agreement with literature values than recovery-curve-based estimation and that accounting for multiple bleach frames improves the result. Further, the software developed in this work is freely available online.

HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-38231 (URN)10.1016/j.bpj.2019.02.023 (DOI)2-s2.0-85062705820 (Scopus ID)
Merknad

 Funding details: Vetenskapsrådet, 2016-03809; Funding details: Stiftelsen för Strategisk Forskning; Funding text 1: The financial support of the VINN Excellence Centre SuMo Biomaterials , the Swedish Foundation for Strategic Research project “Material structures seen through microscopes and statistics,” and the Swedish Research Council (grant number 2016-03809 ) is acknowledged. The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering provided by the Swedish National Infrastructure for Computing.

Tilgjengelig fra: 2019-03-27 Laget: 2019-03-27 Sist oppdatert: 2019-06-28bibliografisk kontrollert
Longfils, M., Smisdom, N., Ameloot, M., Rudemo, M., Lemmens, V., Fernández, G., . . . Särkkä, A. (2019). Raster Image Correlation Spectroscopy Performance Evaluation. Biophysical Journal, 117(10), 1900-1914
Åpne denne publikasjonen i ny fane eller vindu >>Raster Image Correlation Spectroscopy Performance Evaluation
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2019 (engelsk)Inngår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 117, nr 10, s. 1900-1914Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 μm2 s−1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (≪50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM–μM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient. 

sted, utgiver, år, opplag, sider
Biophysical Society, 2019
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-40865 (URN)10.1016/j.bpj.2019.09.045 (DOI)2-s2.0-85074365080 (Scopus ID)
Merknad

Funding details: KU Leuven, C14/16/053; Funding details: Fonds Wetenschappelijk Onderzoek, FWO; Funding details: Knut och Alice Wallenbergs Stiftelse; Funding text 1: Dr. Kris Janssen (Chemistry, KU Leuven) is thanked for programming the acquisitioning software of the homebuilt microscope. Johan Hofkens (Molecular Imaging and Photonics, KU Leuven) is gratefully acknowledged for the usage of his imaging facilities. Financial support from the Swedish Foundation for Strategic Research and Knut and Alice Wallenberg Foundation is highly appreciated. J.H. acknowledges the KU Leuven for funding ( C14/16/053 ). V.L. acknowledges the UHasselt Bijzonder Onderzoeksfonds fund ( BOF17DOC11 ) for a PhD scholarship. Guillermo Solís Fernández is grateful for a PhD scholarship from the Research Foundation Flanders.

Tilgjengelig fra: 2019-12-10 Laget: 2019-12-10 Sist oppdatert: 2019-12-10bibliografisk kontrollert
Normann, A., Röding, M. & Wendin, K. (2019). Sustainable fruit consumption: The influence of color, shape and damage on consumer sensory perception and liking of different apples. Sustainability, 11(17), Article ID 4626.
Åpne denne publikasjonen i ny fane eller vindu >>Sustainable fruit consumption: The influence of color, shape and damage on consumer sensory perception and liking of different apples
2019 (engelsk)Inngår i: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 11, nr 17, artikkel-id 4626Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Sustainable food production and consumption are currently key issues. About one third of food produced for human consumption is wasted. In developed countries, consumers are responsible for the largest amount of food waste throughout the supply chain. The unwillingness to purchase and consume suboptimal food products is an important cause of food waste, however, the reasons behind this are still insufficiently studied. Our research addresses the question of how combinations of color, shape and damage of apples influence consumer liking and perceived sensory attributes. In a laboratory study based on factorial design of visual appearance (color, shape and damage varied from optimal to suboptimal) a total of 130 consumers evaluated sensory perception of flavor and texture attributes in apple samples. Liking was also evaluated. The results showed a significant difference in liking between an optimal apple and all apple categories with at least two out of three suboptimal properties. Further, it was a clear trend that the optimal apple was perceived as sweeter, crispier, less bitter, and less earthy than all the other apples by the participating consumers, however, the results were not statistically significant. A suboptimal appearance, therefore, had a negative effect on both perception and liking..

sted, utgiver, år, opplag, sider
MDPI AG, 2019
Emneord
Appearance, Apples, Consumer, Perception, Suboptimality, Malus x domestica
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-39919 (URN)10.3390/su11174626 (DOI)2-s2.0-85071963535 (Scopus ID)
Merknad

 Funding details: Sveriges Lantbruksuniversitet, SLU; Funding details: Svenska Forskningsrådet Formas, 2014-00051; Funding text 1: Laura Andreea Bolos and Carl-Johan Lagerkvist, Swedish University of Agricultural Sciences, are acknowledged for their participation in discussions and experimental issues. This research was funded by the Swedish Research Council FORMAS as part of the project Consumers in a Sustainable Food Supply Chain (COSUS), grant number 2014-00051.

Tilgjengelig fra: 2019-09-27 Laget: 2019-09-27 Sist oppdatert: 2019-10-14bibliografisk kontrollert
Röding, M. (2018). Effective diffusivity in lattices of impermeable superballs. Physical Review E. Statistical, Nonlinear, and Soft Matter Physics: Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 98(5), Article ID 052908.
Åpne denne publikasjonen i ny fane eller vindu >>Effective diffusivity in lattices of impermeable superballs
2018 (engelsk)Inngår i: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics: Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, ISSN 1063-651X, E-ISSN 1095-3787, Vol. 98, nr 5, artikkel-id 052908Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Granular materials constitute a broad class of two-phase media with discrete, solid par-ticles i.e. granules surrounded by a continuous void phase. They have properties that arekey for e.g. separation and chromatography columns, cathode materials for batteries, andpharmaceutical coatings for controlled release. Controlling mass transport properties suchas effective diffusivity is crucial for these applications and the subject of targeted designand optimization. The prototypical granule is a sphere, but current manufacturingtechniques allow for more complicated shapes to be produced in a highly controlled manner,including ellipsoids, cubes, and cubes with rounded edges and corners. The impactof shape for self-assembly, phase transitions, crystallization, and random close packing hasalso been studied for these shapes

Emneord
Volume fraction, Approximate analytical expressions, Body-centered cubic, Correlation function, Effective diffusivities, Face centered cubic lattice, Microstructural parameters, Obstructed diffusion, Solid volume fraction, Diffusion
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-36618 (URN)10.1103/PhysRevE.98.052908 (DOI)2-s2.0-85057395051 (Scopus ID)
Forskningsfinansiär
Swedish Research Council, 2016-03809
Tilgjengelig fra: 2018-12-10 Laget: 2018-12-10 Sist oppdatert: 2018-12-14bibliografisk kontrollert
Röding, M. & Billeter, M. (2018). Massively parallel approximate Bayesian computation for estimating nanoparticle diffusion coefficients, sizes and concentrations using confocal laser scanning microscopy. Journal of Microscopy, 271(2), 174-182
Åpne denne publikasjonen i ny fane eller vindu >>Massively parallel approximate Bayesian computation for estimating nanoparticle diffusion coefficients, sizes and concentrations using confocal laser scanning microscopy
2018 (engelsk)Inngår i: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 271, nr 2, s. 174-182Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We implement a massively parallel population Monte Carlo approximate Bayesian computation (PMC-ABC) method for estimating diffusion coefficients, sizes and concentrations of diffusing nanoparticles in liquid suspension using confocal laser scanning microscopy and particle tracking. The method is based on the joint probability distribution of diffusion coefficients and the time spent by a particle inside a detection region where particles are tracked. We present freely available central processing unit (CPU) and graphics processing unit (GPU) versions of the analysis software, and we apply the method to characterize mono- and bidisperse samples of fluorescent polystyrene beads.

Emneord
Concentration, Confocal laser scanning microscopy, Diffusion coefficient, Nanoparticles, Particle tracking
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-33847 (URN)10.1111/jmi.12706 (DOI)29676793 (PubMedID)2-s2.0-85045743188 (Scopus ID)
Tilgjengelig fra: 2018-05-08 Laget: 2018-05-08 Sist oppdatert: 2019-08-13bibliografisk kontrollert
Longfils, M., Röding, M., Altskar, A., Schuster, E., Loren, N., Sarkka, A. & Rudemo, M. (2018). Single particle raster image analysis of diffusion for particle mixtures. Journal of Microscopy, 269(3), 269-281
Åpne denne publikasjonen i ny fane eller vindu >>Single particle raster image analysis of diffusion for particle mixtures
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2018 (engelsk)Inngår i: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 269, nr 3, s. 269-281Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Recently we complemented the raster image correlation spectroscopy (RICS) method of analysing raster images via estimation of the image correlation function with the method single particle raster image analysis (SPRIA). In SPRIA, individual particles are identified and the diffusion coefficient of each particle is estimated by a maximum likelihood method. In this paper, we extend the SPRIA method to analyse mixtures of particles with a finite set of diffusion coefficients in a homogeneous medium. In examples with simulated and experimental data with two and three different diffusion coefficients, we show that SPRIA gives accurate estimates of the diffusion coefficients and their proportions. A simple technique for finding the number of different diffusion coefficients is also suggested. Further, we study the use of RICS for mixtures with two different diffusion coefficents and investigate, by plotting level curves of the correlation function, how large the quotient between diffusion coefficients needs to be in order to allow discrimination between models with one and two diffusion coefficients. We also describe a minor correction (compared to published papers) of the RICS autocorrelation function. Lay description Diffusion is a key mass transport mechanism for small particles. Efficient methods for estimating diffusion coefficients are crucial for analysis of microstructures, for example in soft biomaterials. The sample of interest may consist of a mixture of particles with different diffusion coefficients. Here, we extend a method called Single Particle Raster Image Analysis (SPRIA) to account for particle mixtures and estimation of the diffusion coefficients of the mixture components. SPRIA combines elements of classical single particle tracking methods with utilizing the raster scan with which images obtained by using a confocal laser scanning microscope. In particular, single particles are identified and their motion estimated by following their center of mass. Thus, an estimate of the diffusion coefficient will be obtained for each particle. Then, we analyse the distribution of the estimated diffusion coefficients of the population of particles, which allows us to extract information about the diffusion coefficients of the underlying components in the mixture. On both simulated and experimental data with mixtures consisting of two and three components with different diffusion coefficients, SPRIA provides accurate estimates and, with a simple criterion, the correct number of mixture components is selected in most cases.

Emneord
Bootstrap; Confocal laser scanning microscopy; Diffusion; Fluorescent beads; Maximum likelihood; Particle mixtures; Single particle tracking
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-33367 (URN)10.1111/jmi.12625 (DOI)2-s2.0-85041951653 (Scopus ID)
Tilgjengelig fra: 2018-03-05 Laget: 2018-03-05 Sist oppdatert: 2019-01-10bibliografisk kontrollert
Williamson, N. H., Röding, M., Liu, H., Galvosas, P., Miklavcic, S. J. & Nydén, M. (2018). The pseudo 2-D relaxation model for obtaining T1-T2 relationships from 1-D T1 and T2 measurements of fluid in porous media. Microporous and Mesoporous Materials, 269, 191-194
Åpne denne publikasjonen i ny fane eller vindu >>The pseudo 2-D relaxation model for obtaining T1-T2 relationships from 1-D T1 and T2 measurements of fluid in porous media
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2018 (engelsk)Inngår i: Microporous and Mesoporous Materials, ISSN 1387-1811, E-ISSN 1873-3093, Vol. 269, s. 191-194Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

NMR spin-lattice (T1) and spin-spin (T2) relaxation times and their inter-relation possess information on fluid behaviour in porous media. To elicit this information we utilize the pseudo 2-D relaxation model (P2DRM), which deduces the T1-T2 functional relationship from independent 1-D T1 and T2 measurements. Through model simulations we show empirically that the P2DRM accurately estimates T1-T2 relationships even when the marginal distributions of the true joint T1-T2 distribution are unknown or cannot be modeled. Estimates of the T1:. T2 ratio for fluid interacting with pore surfaces remain robust when the P2DRM is applied to simulations of rapidly acquired data. Therefore, the P2DRM can be useful in situations where experimental time is limited.

Emneord
Heterogeneity, Inverse-gamma distribution, Lognormal distribution, Magnetic resonance in porous media, Multidimensional distribution function, Relaxation correlation, Magnetic resonance, Nuclear magnetic resonance, Porous materials, Inverse gamma distribution, Log-normal distribution, Multidimensional distributions, Relaxation correlations, Distribution functions
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-30984 (URN)10.1016/j.micromeso.2017.05.056 (DOI)2-s2.0-85026815139 (Scopus ID)
Tilgjengelig fra: 2017-09-04 Laget: 2017-09-04 Sist oppdatert: 2019-01-03bibliografisk kontrollert
Shen, Z., Röding, M., Kröger, M. & Li, Y. (2017). Carbon nanotube length governs the viscoelasticity and permeability of buckypaper. Polymers, 9(4), Article ID 115.
Åpne denne publikasjonen i ny fane eller vindu >>Carbon nanotube length governs the viscoelasticity and permeability of buckypaper
2017 (engelsk)Inngår i: Polymers, ISSN 2073-4360, E-ISSN 2073-4360, Vol. 9, nr 4, artikkel-id 115Artikkel i tidsskrift (Fagfellevurdert) Published
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-29271 (URN)10.3390/polym9040115 (DOI)2-s2.0-85017091399 (Scopus ID)
Tilgjengelig fra: 2017-04-07 Laget: 2017-04-07 Sist oppdatert: 2019-01-07bibliografisk kontrollert
Röding, M., Gaska, K., Kádár, R. & Loren, N. (2017). Computational Screening of Diffusive Transport in Nanoplatelet-Filled Composites: Use of Graphene To Enhance Polymer Barrier Properties. ACS Applied Nano Materials, 1(1), 160-167
Åpne denne publikasjonen i ny fane eller vindu >>Computational Screening of Diffusive Transport in Nanoplatelet-Filled Composites: Use of Graphene To Enhance Polymer Barrier Properties
2017 (engelsk)Inngår i: ACS Applied Nano Materials, ISSN 2574-0970, Vol. 1, nr 1, s. 160-167Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Motivated by the substantial interest in various fillers to enhance the barrier properties of polymeric films, especially graphene derivatives, we perform a computational screening of obstructed diffusion to explore the design parameter space of nanoplatelet-filled composites synthesized in silico. As a model for the nanoplatelets, we use circular and elliptical nonoverlapping and impermeable flat disks, and diffusion is stochastically simulated using a random-walk model, from which the effective diffusivity is calculated. On the basis of ∼1000 generated structures and diffusion simulations, we systematically investigate the impact of different nanoplatelet characteristics such as orientation, layering, size, polydispersity, shape, and amount. We conclude that the orientation, size, and amount of nanoplatelets are the most important parameters and show that using nanoplatelets oriented perpendicular to the diffusion direction, under reasonable assumptions, with approximately 0.2% (w/w) graphene, we can reach 90% reduction and, with approximately 1% (w/w) graphene, we can reach 99% reduction in diffusivity, purely because of geometrical effects, in a defect-free matrix with perfect compatibility. Additionally, our results suggest that the existing analytical models have some difficulty with extremely large aspect ratio (extremely flat) nanoplatelets, which calls for further development.

Emneord
composites; computational screening; diffusivity; graphene; nanoplatelets
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-32845 (URN)10.1021/acsanm.7b00067 (DOI)2-s2.0-85060928829 (Scopus ID)
Forskningsfinansiär
Swedish Research Council, 2016-03809
Tilgjengelig fra: 2017-12-11 Laget: 2017-12-11 Sist oppdatert: 2020-02-03bibliografisk kontrollert
Röding, M., Svensson, P. & Loren, N. (2017). Functional regression-based fluid permeability prediction in monodisperse sphere packings from isotropic two-point correlation functions. Computational materials science, 134, 126-131
Åpne denne publikasjonen i ny fane eller vindu >>Functional regression-based fluid permeability prediction in monodisperse sphere packings from isotropic two-point correlation functions
2017 (engelsk)Inngår i: Computational materials science, ISSN 0927-0256, E-ISSN 1879-0801, Vol. 134, s. 126-131Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We study fluid permeability in random sphere packings consisting of impermeable monodisperse hard spheres. Several different pseudo-potential models are used to obtain varying degrees of microstructural heterogeneity. Systematically varying solid volume fraction and degree of heterogeneity, virtual screening of more than 10,000 material structures is performed, simulating fluid flow using a lattice Boltzmann framework and computing the permeability. We develop a well-performing functional regression model for permeability prediction based on using isotropic two-point correlation functions as microstructural descriptors. The performance is good over a large range of solid volume fractions and degrees of heterogeneity, and to our knowledge this is the first attempt at using two-point correlation functions as functional predictors in a nonparametric statistics/machine learning context for permeability prediction.

Emneord
Correlation functions, Functional regression, Granular materials, Permeability, Sphere packings, Flow of fluids, Forecasting, Packing, Regression analysis, Spheres, Volume fraction, Correlation function, Microstructural descriptors, Microstructural heterogeneity, Non-parametric statistics, Permeability prediction, Two point correlation functions, Mechanical permeability
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-30877 (URN)10.1016/j.commatsci.2017.03.042 (DOI)2-s2.0-85017093852 (Scopus ID)
Tilgjengelig fra: 2017-09-06 Laget: 2017-09-06 Sist oppdatert: 2018-08-17bibliografisk kontrollert
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-5956-9934
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