| 1. |
- MacGregor-Ramiasa, M., et al.
(author)
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Magnetic alignment of nontronite dispersions
- 2015
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In: Applied Clay Science. - : Elsevier BV. - 0169-1317. ; 116-117, s. 167-174
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Journal article (peer-reviewed)abstract
- The time dependent alignment of exfoliated nontronite dispersions subjected to moderate magnetic field strengths (B.
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| 2. |
- Nordin, Matias, 1981, et al.
(author)
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Estimation of mass thickness response of embedded aggregated silica nanospheres from high angle annular dark-field scanning transmission electron micrographs
- 2014
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In: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 253:2, s. 166-170
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Journal article (peer-reviewed)abstract
- In this study, we investigate the functional behaviour of the intensity in high-angle annular dark field scanning transmission electron micrograph images. The model material is a silica particle (20 nm) gel at 5 wt%. By assuming that the intensity response is monotonically increasing with increasing mass thickness of silica, an estimate of the functional form is calculated using a maximum likelihood approach. We conclude that a linear functional form of the intensity provides a fair estimate but that a power function is significantly better for estimating the amount of silica in the z-direction. The work adds to the development of quantifying material properties from electron micrographs, especially in the field of tomography methods and three-dimensional quantitative structural characterization from a scanning transmission electron micrograph. It also provides means for direct three-dimensional quantitative structural characterization from a scanning transmission electron micrograph.
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| 3. |
- Röding, Magnus, 1984, et al.
(author)
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The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers
- 2012
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In: Journal of Magnetic Resonance. - : Elsevier BV. - 1090-7807 .- 1096-0856. ; 222, s. 105-111
-
Journal article (peer-reviewed)abstract
- Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distribution of self-diffusion coefficients to more established models such as the single exponential, the stretched exponential, and the log-normal distribution model with regard to performance and consistency. Even though the gamma distribution is very similar to the log-normal distribution, its NMR signal attenuation can be written in a closed form and therefore opens up for increased computational speed. Estimates of the mean self-diffusion coefficient, the spread, and the polydispersity index that were obtained using the gamma model were in excellent agreement with estimates obtained using the log-normal model. Furthermore, we demonstrate that the gamma distribution is by far superior to the log-normal, and comparable to the two other models, in terms of computational speed. This effect is particularly striking for multi-component signal attenuation. Additionally, the gamma distribution as well as the log-normal distribution incorporates explicitly a physically plausible model for polydispersity and spread, in contrast to the single exponential and the stretched exponential. Therefore, the gamma distribution model should be preferred in many experimental situations.
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| 4. |
- Röding, Magnus, et al.
(author)
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The power of heterogeneity : Parameter relationships from distributions
- 2016
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In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 11:5
-
Journal article (peer-reviewed)abstract
- Complex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions of individual parameters and the relationships between them, such as in nuclear magnetic resonance and optical spectroscopy. However, when data originates from different measurements and comes in different forms, resolving parameter relationships is a matter of data analysis rather than experiment. We present a method for resolving relationships between parameters that are distributed individually and also correlated. In two case studies, we model the relationships between diameter and luminescence properties of quantum dots and the relationship between molecular weight and diffusion coefficient for polymers. Although it is expected that resolving complicated correlated relationships require inherently multi-dimensional measurements, our method constitutes a useful contribution to the modelling of quantitative relationships between correlated parameters and measurements. We emphasise the general applicability of the method in fields where heterogeneity and complex distributions of parameters are obstacles to scientific insight.
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| 5. |
- Steglich, Thomas, 1983, et al.
(author)
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Microstructure and water distribution of commercial pasta studied by microscopy and 3D magnetic resonance imaging
- 2014
-
In: Food Research International. - : Elsevier BV. - 0963-9969 .- 1873-7145. ; 62, s. 644-652
-
Journal article (peer-reviewed)abstract
- Manufacturing pasta is a rather well known process, but it is still challenging to tailor pasta products with new raw materials. In this study, we evaluated the effects of raw materials on the microstructure and water distribution in cooked pasta using H-1 magnetic resonance imaging (MRI) as well as bright field and polarized light microscopy. The MRI parameters initial intensity (I-0) and transverse dephasing time (T-2*) serve as indicators of the local water concentration and water-macromolecule interactions through chemical exchange, respectively. These parameters were mapped throughout the whole pasta volume with a spatial resolution of 78 mu m in all three dimensions. MRI was combined with light microscopy to link I-0 and T-2* to microstructure components such as fiber particles and the extent of starch gelatinization. Four commercial spaghetti samples were analyzed which were made of durum wheat flour, both plain and enriched with wheat fiber, as well as with wholegrain and soft wheat flour. Although all pasta samples showed similar macroscopic water absorption as measured by weight increase, the sample structures differed at the microscopic scale. Compared to durum wheat spaghetti, the presence of fiber particles decreased T-2*, while spaghetti enriched with soft wheat flour increased T-2*. In addition, light microscopy showed that large fiber particles partly acted as barriers against water migration and protected starch granules from swelling. Smaller wheat fiber particles did not affect local starch swelling. Thus, the combination of light microscopy and MRI is a powerful tool to study the microstructure and water distribution in pasta.
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| 6. |
- Williamson, Nathan H., et al.
(author)
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Obtaining T1-T2 distribution functions from 1-dimensional T1 and T2 measurements : The pseudo 2-D relaxation model
- 2016
-
In: Journal of magnetic resonance. - : Elsevier BV. - 1090-7807 .- 1096-0856. ; 269, s. 186-195
-
Journal article (peer-reviewed)abstract
- We present the pseudo 2-D relaxation model (P2DRM), a method to estimate multidimensional probability distributions of material parameters from independent 1-D measurements. We illustrate its use on 1-D T1 and T2 relaxation measurements of saturated rock and evaluate it on both simulated and experimental T1-T2 correlation measurement data sets. Results were in excellent agreement with the actual, known 2-D distribution in the case of the simulated data set. In both the simulated and experimental case, the functional relationships between T1 and T2 were in good agreement with the T1-T2 correlation maps from the 2-D inverse Laplace transform of the full 2-D data sets. When a 1-D CPMG experiment is combined with a rapid T1 measurement, the P2DRM provides a double-shot method for obtaining a T1-T2 relationship, with significantly decreased experimental time in comparison to the full T1-T2 correlation measurement.
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| 7. |
- Williamson, Nathan H., et al.
(author)
-
Scaling exponent and dispersity of polymers in solution by diffusion NMR
- 2017
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In: Journal of Colloid and Interface Science. - : Elsevier BV. - 0021-9797 .- 1095-7103. ; 493, s. 393-397
-
Journal article (peer-reviewed)abstract
- Molecular mass distribution measurements by pulsed gradient spin echo nuclear magnetic resonance (PGSE NMR) spectroscopy currently require prior knowledge of scaling parameters to convert from polymer self-diffusion coefficient to molecular mass. Reversing the problem, we utilize the scaling relation as prior knowledge to uncover the scaling exponent from within the PGSE data. Thus, the scaling exponent—a measure of polymer conformation and solvent quality—and the dispersity (Mw/Mn) are obtainable from one simple PGSE experiment. The method utilizes constraints and parametric distribution models in a two-step fitting routine involving first the mass-weighted signal and second the number-weighted signal. The method is developed using lognormal and gamma distribution models and tested on experimental PGSE attenuation of the terminal methylene signal and on the sum of all methylene signals of polyethylene glycol in D2O. Scaling exponent and dispersity estimates agree with known values in the majority of instances, leading to the potential application of the method to polymers for which characterization is not possible with alternative techniques.
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| 8. |
- Williamson, Nathan H., et al.
(author)
-
The lognormal and gamma distribution models for estimating molecular weight distributions of polymers using PGSE NMR
- 2016
-
In: Journal of magnetic resonance. - : Academic Press. - 1090-7807 .- 1096-0856. ; 267, s. 54-62
-
Journal article (peer-reviewed)abstract
- We present comprehensive derivations for the statistical models and methods for the use of pulsed gradient spin echo (PGSE) NMR to characterize the molecular weight distribution of polymers via the well-known scaling law relating diffusion coefficients and molecular weights. We cover the lognormal and gamma distribution models and linear combinations of these distributions. Although the focus is on methodology, we illustrate the use experimentally with three polystyrene samples, comparing the NMR results to gel permeation chromatography (GPC) measurements, test the accuracy and noise-sensitivity on simulated data, and provide code for implementation.
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| 9. |
- Williamson, Nathan H., et al.
(author)
-
The pseudo 2-D relaxation model for obtaining T1-T2 relationships from 1-D T1 and T2 measurements of fluid in porous media
- 2018
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In: Microporous and Mesoporous Materials. - : Elsevier BV. - 1387-1811 .- 1873-3093. ; 269, s. 191-194
-
Journal article (peer-reviewed)abstract
- 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.
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| 10. |
- Bernin, Diana, 1979, et al.
(author)
-
Multi-scale characterization of pasta during cooking using microscopy and real-time magnetic resonance imaging
- 2014
-
In: Food Research International. - : Elsevier BV. - 0963-9969 .- 1873-7145. ; 66, s. 132-139
-
Journal article (peer-reviewed)abstract
- Macroscopic properties of pasta, such as the texture, are formed during cooking by a complex interplay of water and heat with the structuring agents starch and gluten. The impact of the starch-to-gluten ratio on microstructure and water distribution in pasta was analyzed by a multi-scale approach combining magnetic resonance imaging (MRI) and light microscopy. The cooking process and thus the water distribution was monitored non-invasively using 1H MRI in real-time with a temporal resolution of 45s. Our MRI set-up allowed following the water ingress by imaging the reduction of the uncooked core. The water ingress rate was neither dependent on pasta composition nor on the presence of salt in the cooking media (0.7% NaCl). Starch-rich samples showed a more homogeneous water distribution in the gelatinized zone, which was mirrored in a more homogeneous microstructure. In contrast, gluten-rich samples showed both a heterogeneous water distribution and microstructure. Thus, the gluten content affected local water content in the gelatinized zone but not the water ingress. © 2014 Elsevier Ltd.
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| 11. |
- Bradley, Siobhan J., et al.
(author)
-
Heterogeneity in the fluorescence of graphene and graphene oxide quantum dots
- 2017
-
In: Microchimica Acta. - : Springer Science and Business Media LLC. - 0026-3672 .- 1436-5073. ; 184:3, s. 871-878
-
Journal article (peer-reviewed)abstract
- Heterogeneity is an inherent property of a wealth of real-world nanomaterials and yet rarely in the reporting of new properties is its effect sufficiently addressed. Graphene quantum dots (GQDs) – fluorescent, nanoscale fragments of graphene - are an extreme example of a heterogeneous nanomaterial. Here, top-down approaches – by far the most predominant – produce batches of particles with a distribution of sizes, shapes, extent of oxidation, chemical impurities and more. This makes characterization of these materials using bulk techniques particularly complex and comparisons of properties across different synthetic methods uninformative. In particular, it hinders the understanding of the structural origin of their fluorescence properties. We present a simple synthetic method, which produces graphene quantum dots with very low oxygen content that can be suspended in organic solvents, suggesting a very pristine material. We use this material to illustrate the limitations of interpreting complex data sets generated by heterogeneous materials and we highlight how misleading this “pristine” interpretation is by comparison with graphene oxide quantum dots synthesized using an established protocol. In addition, we report on the solvatochromic properties of these particles, discuss common characterization techniques and their limitations in attributing properties to heterogeneous materials.
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| 12. |
- Carmona, Pierre, 1995, et al.
(author)
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Controlling the structure of spin-coated multilayer ethylcellulose/ hydroxypropylcellulose films for drug release
- 2023
-
In: International Journal of Pharmaceutics. - 0378-5173 .- 1873-3476. ; 644
-
Journal article (peer-reviewed)abstract
- Porous phase-separated ethylcellulose/hydroxypropylcellulose (EC/HPC) films are used to control drug transport out of pharmaceutical pellets. Water-soluble HPC leaches out and forms a porous structure that controls the drug transport. Industrially, the pellets are coated using a fluidized bed spraying device, and a layered film exhibiting varying porosity and structure after leaching is obtained. A detailed understanding of the formation of the multilayered, phase-separated structure during production is lacking. Here, we have investigated multilayered EC/HPC films produced by sequential spin-coating, which was used to mimic the industrial process. The effects of EC/HPC ratio and spin speed on the multilayer film formation and structure were investigated using advanced microscopy techniques and image analysis. Cahn-Hilliard simulations were performed to analyze the mixing behavior. A gradient with larger structures close to the substrate surface and smaller structures close to the air surface was formed due to coarsening of the layers already coated during successive deposition cycles. The porosity of the multilayer film was found to vary with both EC/HPC ratio and spin speed. Simulation of the mixing behavior and in situ characterization of the structure evolution showed that the origin of the discontinuities and multilayer structure can be explained by the non-mixing of the layers.
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| 13. |
- Carmona, Pierre, 1995, et al.
(author)
-
Cross-sectional structure evolution of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films during solvent quenching
- 2022
-
In: RSC Advances. - : Royal Society of Chemistry. - 2046-2069. ; 12:40, s. 26078-26089
-
Journal article (peer-reviewed)abstract
- Porous phase-separated ethylcellulose/hydroxypropylcellulose (EC/HPC) films are used to control drug transport out of pharmaceutical pellets. The films are applied on the pellets using fluidized bed spraying. The drug transport rate is determined by the structure of the porous films that are formed as the water-soluble HPC leaches out. However, a detailed understanding of the evolution of the phase-separated structure during production is lacking. Here, we have investigated EC/HPC films produced by spin-coating, which mimics the industrial manufacturing process. This work aimed to understand the structure formation and film shrinkage during solvent evaporation. The cross-sectional structure evolution was characterized using confocal laser scanning microscopy (CLSM), profilometry and image analysis. The effect of the EC/HPC ratio on the cross-sectional structure evolution was investigated. During shrinkage of the film, the phase-separated structure undergoes a transition from 3D to nearly 2D structure evolution along the surface. This transition appears when the typical length scale of the phase-separated structure is on the order of the thickness of the film. This was particularly pronounced for the bicontinuous systems. The shrinkage rate was found to be independent of the EC/HPC ratio, while the initial and final film thickness increased with increasing HPC fraction. A new method to estimate part of the binodal curve in the ternary phase diagram for EC/HPC in ethanol has been developed. The findings of this work provide a good understanding of the mechanisms responsible for the morphology development and allow tailoring of thin EC/HPC films structure for controlled drug release.
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| 14. |
- Carmona, Pierre, 1995, et al.
(author)
-
Structure evolution during phase separation in spin-coated ethylcellulose/hydroxypropylcellulose films
- 2021
-
In: Soft Matter. - : Royal Society of Chemistry. - 1744-683X .- 1744-6848. ; 17:14, s. 3913-3922
-
Journal article (peer-reviewed)abstract
- Porous phase-separated films made of ethylcellulose (EC) and hydroxypropylcellulose (HPC) are commonly used for controlled drug release. The structure of these thin films is controlling the drug transport from the core to the surrounding liquids in the stomach or intestine. However, detailed understanding of the time evolution of these porous structures as they are formed remains elusive. In this work, spin-coating, a widely applied technique for making thin uniform polymer films, was used to mimic the industrial manufacturing process. The focus of this work was on understanding the structure evolution of phase-separated spin-coated EC/HPC films. The structure evolution was determined using confocal laser scanning microscopy (CLSM) and image analysis. In particular, we determined the influence of spin-coating parameters and EC : HPC ratio on the final phase-separated structure and the film thickness. The film thickness was determined by profilometry and it influences the ethanol solvent evaporation rate and thereby the phase separation kinetics. The spin speed was varied between 1000 and 10 000 rpm and the ratio of EC : HPC in the polymer blend was varied between 78 : 22 wt% and 40 : 60 wt%. The obtained CLSM micrographs showed phase separated structures, typical for the spinodal decomposition phase separation mechanism. By using confocal laser scanning microscopy combined with Fourier image analysis, we could extract the characteristic length scale of the phase-separated final structure. Varying spin speed and EC : HPC ratio gave us precise control over the characteristic length scale and the thickness of the film. The results showed that the characteristic length scale increases with decreasing spin speed and with increasing HPC ratio. The thickness of the spin-coated film decreases with increasing spin speed. It was found that the relation between film thickness and spin speed followed the Meyerhofer equation with an exponent close to 0.5. Furthermore, good correlations between thickness and spin speed were found for the compositions 22 wt% HPC, 30 wt% HPC and 45 wt% HPC. These findings give a good basis for understanding the mechanisms responsible for the morphology development and increase the possibilities to tailor thin EC/HPC film structures.
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| 15. |
- Carmona, Pierre, 1995, et al.
(author)
-
Structure formation and coarsening kinetics of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films
- 2022
-
In: Soft Matter. - : Royal Society of Chemistry. - 1744-683X .- 1744-6848. ; 18:16, s. 3206-3217
-
Journal article (peer-reviewed)abstract
- Porous phase-separated ethylcellulose/hydroxypropylcellulose (EC/HPC) films are used to control drug transport from pharmaceutical pellets. The drug transport rate is determined by the structure of the porous films that are formed as water-soluble HPC leaches out. However, a detailed understanding of the evolution of the phase-separated structure in the films is lacking. In this work, we have investigated EC/HPC films produced by spin-coating, mimicking the industrial fluidized bed spraying. The aim was to investigate film structure evolution and coarsening kinetics during solvent evaporation. The structure evolution was characterized using confocal laser scanning microscopy and image analysis. The effect of the EC:HPC ratio (15 to 85 wt% HPC) on the structure evolution was determined. Bicontinuous structures were found for 30 to 40 wt% HPC. The growth of the characteristic length scale followed a power law, L(t) ∼ t(n), with n ∼ 1 for bicontinuous structures, and n ∼ 0.45-0.75 for discontinuous structures. The characteristic length scale after kinetic trapping ranged between 3.0 and 6.0 μm for bicontinuous and between 0.6 and 1.6 μm for discontinuous structures. Two main coarsening mechanisms could be identified: interfacial tension-driven hydrodynamic growth for bicontinuous structures and diffusion-driven coalescence for discontinuous structures. The 2D in-plane interface curvature analysis showed that the mean curvature decreased as a function of time for bicontinuous structures, confirming that interfacial tension is driving the growth. The findings of this work provide a good understanding of the mechanisms responsible for morphology development and open for further tailoring of thin EC/HPC film structures for controlled drug release. © 2022 The Royal Society of Chemistry
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| 16. |
- Deschout, H., et al.
(author)
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Disposable microfluidic chip with integrated light sheet illumination enables diagnostics based on membrane vesicles
- 2014
-
In: 17th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2013; Freiburg; Germany; 27 October 2013 through 31 October 2013. - 9781632666246
-
Conference paper (peer-reviewed)abstract
- Cell-derived membrane vesicles that are released in body fluids are emerging as potential non-invasive biomarkers for diseases like cancer. Techniques capable of measuring the size and concentration of such membrane vesicles directly in body fluids are urgently needed. Here we report on a microfluidic chip with integrated light sheet illumination, and demonstrate accurate fluorescence Single Particle Tracking measurements of the size and concentration of membrane vesicles in cell culture medium and in interstitial fluid collected from primary human breast tumours.
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| 17. |
- Deschout, Hendrik, et al.
(author)
-
Disposable microfluidic chip with integrated light sheet illumination enables diagnostics based on membrane vesicles
- 2013
-
In: 17th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2013; Freiburg; Germany; 27 October 2013 through 31 October 2013. ; 3, s. 2010-2012
-
Conference paper (peer-reviewed)abstract
- Cell-derived membrane vesicles that are released in body fluids are emerging as potential non-invasive biomarkers for diseases like cancer. Techniques capable of measuring the size and concentration of such membrane vesicles directly in body fluids are urgently needed. Here we report on a microfluidic chip with integrated light sheet illumination, and demonstrate accurate fluorescence Single Particle Tracking measurements of the size and concentration of membrane vesicles in cell culture medium and in interstitial fluid collected from primary human breast tumours.
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| 18. |
- Deschout, H., et al.
(author)
-
On-chip light sheet illumination enables diagnostic size and concentration measurements of membrane vesicles in biofluids
- 2014
-
In: Nanoscale. - : Royal Society of Chemistry (RSC). - 2040-3364 .- 2040-3372. ; 6:3, s. 1741-1747
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Journal article (peer-reviewed)abstract
- Cell-derived membrane vesicles that are released in biofluids, like blood or saliva, are emerging as potential non-invasive biomarkers for diseases, such as cancer. Techniques capable of measuring the size and concentration of membrane vesicles directly in biofluids are urgently needed. Fluorescence single particle tracking microscopy has the potential of doing exactly that by labelling the membrane vesicles with a fluorescent label and analysing their Brownian motion in the biofluid. However, an unbound dye in the biofluid can cause high background intensity that strongly biases the fluorescence single particle tracking size and concentration measurements. While such background intensity can be avoided with light sheet illumination, current set-ups require specialty sample holders that are not compatible with high-throughput diagnostics. Here, a microfluidic chip with integrated light sheet illumination is reported, and accurate fluorescence single particle tracking size and concentration measurements of membrane vesicles in cell culture medium and in interstitial fluid collected from primary human breast tumours are demonstrated.
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| 19. |
- Eriksson Barman, Sandra, 1985, et al.
(author)
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New characterization measures of pore shape and connectivity applied to coatings used for controlled drug release
- 2021
-
In: Journal of Pharmaceutical Sciences. - : Elsevier BV. - 1520-6017 .- 0022-3549. ; 110:7, s. 2753-2764
-
Journal article (peer-reviewed)abstract
- Pore geometry characterization-methods are important tools for understanding how pore structure influences properties such as transport through a porous material. Bottlenecks can have a large influence on transport and related properties. However, existing methods only catch certain types of bottleneck effects caused by variations in pore size. We here introduce a new measure, geodesic channel strength, which captures a different type of bottleneck effect caused by many paths coinciding in the same pore. We further develop new variants of pore size measures and propose a new way of visualizing 3-D characterization results using layered images. The new measures together with existing measures were used to characterize and visualize properties of 3-D FIB-SEM images of three leached ethyl-cellulose/hydroxypropyl-cellulose films. All films were shown to be anisotropic, and the strongest anisotropy was found in the film with lowest porosity. This film had very tortuous paths and strong geodesic channel-bottlenecks, while the paths through the other two films were relatively straight with well-connected pore networks. The geodesic channel strength was shown to give important new visual and quantitative insights about connectivity, and the new pore size measures provided useful information about anisotropies and inhomogeneities in the pore structures. The methods have been implemented in the freely available software MIST.
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| 20. |
- Fager, Cecilia, 1990, et al.
(author)
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3D high spatial resolution visualisation and quantification of interconnectivity in polymer films
- 2020
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In: International Journal of Pharmaceutics. - : Elsevier B.V.. - 0378-5173 .- 1873-3476. ; 587
-
Journal article (peer-reviewed)abstract
- A porous network acts as transport paths for drugs through films for controlled drug release. The interconnectivity of the network strongly influences the transport properties. It is therefore important to quantify the interconnectivity and correlate it to transport properties for control and design of new films. This work presents a novel method for 3D visualisation and analysis of interconnectivity. High spatial resolution 3D data on porous polymer films for controlled drug release has been acquired using a focused ion beam (FIB) combined with a scanning electron microscope (SEM). The data analysis method enables visualisation of pore paths starting at a chosen inlet pore, dividing them into groups by length, enabling a more detailed quantification and visualisation. The method also enables identification of central features of the porous network by quantification of channels where pore paths coincide. The method was applied to FIB-SEM data of three leached ethyl cellulose (EC)/hydroxypropyl cellulose (HPC) films with different weight percentages. The results from the analysis were consistent with the experimentally measured release properties of the films. The interconnectivity and porosity increase with increasing amount of HPC. The bottleneck effect was strong in the leached film with lowest porosity.
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| 21. |
- Fager, Cecilia, 1990, et al.
(author)
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Correlating 3D porous structure in polymer films with mass transport properties using FIB-SEM tomography
- 2021
-
In: Chemical Engineering Science: X. - : Elsevier BV. - 2590-1400. ; 12
-
Journal article (peer-reviewed)abstract
- Porous polymer coatings are used to control drug release from pharmaceutical products. The coating covers a drug core and depending on the porous structure, different drug release rates are obtained. This work presents mass transport simulations performed on porous ethyl cellulose films with different porosities. The simulations were performed on high spatial resolution 3D data obtained using a focused ion beam scanning electron microscope. The effective diffusion coefficient of water was determined using a diffusion chamber. Lattice Boltzmann simulations were used to simulate water diffusion in the 3D data. The simulated coefficient was in good agreement with the measured coefficient. From the results it was concluded that the tortuosity and constrictivity of the porous network increase with decreasing amount of added hydroxypropyl cellulose, resulting in a sharp decrease in effective diffusion. This work shows that high spatial resolution 3D data is necessary, and that 2D data is insufficient, in order to predict diffusion through the porous structure with high accuracy.
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| 22. |
- Fager, Cecilia, 1990, et al.
(author)
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Optimization of FIB-SEM Tomography and Reconstruction for Soft, Porous, and Poorly Conducting Materials
- 2020
-
In: Microscopy and Microanalysis. - 1431-9276 .- 1435-8115. ; 26:4, s. 837-845
-
Journal article (peer-reviewed)abstract
- Tomography using a focused ion beam (FIB) combined with a scanning electron microscope (SEM) is well-established for a wide range of conducting materials. However, performing FIB-SEM tomography on ion- and electron-beam-sensitive materials as well as poorly conducting soft materials remains challenging. Some common challenges include cross-sectioning artifacts, shadowing effects, and charging. Fully dense materials provide a planar cross section, whereas pores also expose subsurface areas of the planar cross-section surface. The image intensity of the subsurface areas gives rise to overlap between the grayscale intensity levels of the solid and pore areas, which complicates image processing and segmentation for three-dimensional (3D) reconstruction. To avoid the introduction of artifacts, the goal is to examine porous and poorly conducting soft materials as close as possible to their original state. This work presents a protocol for the optimization of FIB-SEM tomography parameters for porous and poorly conducting soft materials. The protocol reduces cross-sectioning artifacts, charging, and eliminates shadowing effects. In addition, it handles the subsurface and grayscale intensity overlap problems in image segmentation. The protocol was evaluated on porous polymer films which have both poor conductivity and pores. 3D reconstructions, with automated data segmentation, from three films with different porosities were successfully obtained.
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| 23. |
- Hellström, Magnus, et al.
(author)
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A population-based 220,014- injury event cohort 1993-2014 Umeå, Sweden
-
Other publication (other academic/artistic)abstract
- Injury kills more people than AIDS, malaria, and tuberculosis—together. In rich countries fall injuries dominate quantitatively, while other mechanisms as traffic and occupational injuries decrease. This is a descriptive macro-perspective of the entire injury as a data repository and reference to further more comprehensive studies, e.g., socio-demography, comorbidity, drugs and trauma recidivism.A population-based registration of patients admitted to an emergency department was done 1993-2014.Of the 220,014 injury events, 43% were fall injuries, 12% transportation injuries; assault 4%; 18% were hospitalized; 0.2% were fatal. Young men and old women were at the highest risk for injury. There were 23% fractures in the entire material, increasing to 40% in senescence, whereof 40% hip fractures. With age, fracture locations changed from distal to proximal, and from upper to lower extremity. Fall injuries accounted for 80% of all trauma-related hospital days, mostly old people. The spatial distribution of the population is heavily skewed, spanning from urban core areas to rural peripheries.This is a description of a population-based injury panorama to further studies linking cause, mechanism and type of injury to available medical, sociologic and economic information. Age and sex affected the type, soft tissue injury/fracture and anatomic location, i.e., proximal/distal and upper/lower extremity. At the beginning and end of life, endogenic risk factors are more dominant than in adulthood where exogenic factors dominate. It therefore seems reasonable to believe that it should be possible to substantially prevent injuries by using multipronged analyses to design specific interventions. Injuries are not accidents.
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| 24. |
- Longfils, Marco, 1990, et al.
(author)
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Raster Image Correlation Spectroscopy Performance Evaluation
- 2019
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In: Biophysical Journal. - : Elsevier BV. - 0006-3495 .- 1542-0086. ; 117:10, s. 1900-1914
-
Journal article (peer-reviewed)abstract
- 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 mu m(2) s(-1), a typical value for intracellular measurements, similar to 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 x 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-mM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical leastsquares 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.
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| 25. |
- Longfils, Marco, 1990, et al.
(author)
-
Single particle raster image analysis of diffusion for particle mixtures
- 2018
-
In: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 269:3, s. 269-281
-
Journal article (peer-reviewed)abstract
- 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.
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| 26. |
- Naeye, B, et al.
(author)
-
Hemocompatibility of siRNA loaded dextran nanogels
- 2011
-
In: Biomaterials. - : Elsevier BV. - 0142-9612 .- 1878-5905. ; 32:34, s. 9120-9127
-
Journal article (peer-reviewed)abstract
- Although the behavior of nanoscopic delivery systems in blood is an important parameter when contemplating their intravenous injection, this aspect is often poorly investigated when advancing from in vitro to in vivo experiments. In this paper, the behavior of siRNA loaded dextran nanogels in human plasma and blood is examined using fluorescence fluctuation spectroscopy, platelet aggregometry, flow cytometry and single particle tracking. Our results show that, in contrast to their negatively charged counterparts, positively charged siRNA loaded dextran nanogels cause platelet aggregation and show increased binding to human blood cells. Although PEGylating the nanogels did not have a significant effect on their interaction with blood cells, single particle tracking revealed that it is necessary to prevent their aggregation in human plasma. We therefore conclude that PEGylated negatively charged dextran nanogels are the most suited for further in vivo studies as they do not aggregate in human plasma and exhibit minimal interactions with blood cells.
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| 27. |
- Normann, Anne, et al.
(author)
-
Influence of color, shape and damages on consumer preferences and perceived sensory attributes on sub-optimal apples
- 2018
-
Conference paper (other academic/artistic)abstract
- Sustainable food production and consumption are key elements today. About one third of food produced for human consumption is wasted. Consumers are responsible for the largest amount of food waste throughout the supply chain; part of this is indirect by e.g. discarding food products already in the store. The unwillingness to purchase and consume sub-optimal food products is thought to be an important cause of food waste; however, the reasons behind it are still insufficiently studied. Our research addresses the question of how combinations of color, shape and damage of apples influence consumer preferences and perceived sensory attributes.Based on a cubic design of visual appearance (color (red-to-green); shape (normal-to-odd); damage (none-to-damage) with a total of eight combinations ranging from optimal to suboptimal in all three dimensions, a total of 130 participants (68% women and 32% men), participated in a laboratory study where an image for each apple type from the design was presented in a blind tasting session (peeled and sliced apples). Sensory perception was evaluated by thirteen flavor and texture attributes on a 7-point scale. Liking was evaluated on a 7-point hedonic scale.The results showed a significant difference between the optimal apple and apples with shape and damage imperfections. Further, the optimal apple was perceived sweeter, crispier and less bitter than all other apples. The optimal apple had higher liking score, significantly different from the apples which all had a sub-optimal shape. This means that an odd shape had a negative effect on liking. A linear regression analysis showed that odd shaped apples were perceived as mainly earthy and bitter. Hence, visual sub-optimality, even presented to consumers in images, have an effect on how an apple is perceived and liked where an odd shape has larger negative impact than color and damage.
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| 28. |
- Normann, Anne, et al.
(author)
-
Influence of color, shape and damages on consumer preferences and perceived sensory attributes on sub-optimal apples
- 2018
-
Conference paper (other academic/artistic)abstract
- Sustainable food production and consumption are key elements today. About one third of food produced for human consumption is wasted. Consumers are responsible for the largest amount of food waste throughout the supply chain; part of this is indirect by e.g. discarding food products already in the store. The unwillingness to purchase and consume sub-optimal food products is thought to be an important cause of food waste; however, the reasons behind it are still insufficiently studied. Our research addresses the question of how combinations of color, shape and damage of apples influence consumer preferences and perceived sensory attributes. Based on a cubic design of visual appearance (color (red-to-green); shape (normal-to-odd); damage (none-to-damage) with a total of eight combinations ranging from optimal to suboptimal in all three dimensions, a total of 130 participants (68% women and 32% men), participated in a laboratory study where an image for each apple type from the design was presented in a blind tasting session (peeled and sliced apples). Sensory perception was evaluated by thirteen flavor and texture attributes on a 7-point scale. Liking was evaluated on a 7-point hedonic scale. The results showed a significant difference between the optimal apple and apples with shape and damage imperfections. Further, the optimal apple was perceived sweeter, crispier and less bitter than all other apples. The optimal apple had higher liking score, significantly different from the apples which all had a sub-optimal shape. This means that an odd shape had a negative effect on liking. A linear regression analysis showed that odd shaped apples were perceived as mainly earthy and bitter. Hence, visual sub-optimality, even presented to consumers in images, have an effect on how an apple is perceived and liked where an odd shape has larger negative impact than color and damage.
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| 29. |
- Normann, Anne, et al.
(author)
-
Sustainable fruit consumption : The influence of color, shape and damage on consumer sensory perception and liking of different apples
- 2019
-
In: Sustainability. - : MDPI AG. - 2071-1050. ; 11:17
-
Journal article (peer-reviewed)abstract
- 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..
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| 30. |
- Persson, Gustav, 1993, et al.
(author)
-
Visualisation of individual dopants in a conjugated polymer : sub-nanometre 3D spatial distribution and correlation with electrical properties
- 2022
-
In: Nanoscale. - : Royal Society of Chemistry. - 2040-3364 .- 2040-3372. ; 14, s. 15404-15413
-
Journal article (peer-reviewed)abstract
- While molecular doping is ubiquitous in all branches of organic electronics, little is known about the spatial distribution of dopants, especially at molecular length scales. Moreover, a homogeneous distribution is often assumed when simulating transport properties of these materials, even though the distribution is expected to be inhomogeneous. In this study, electron tomography is used to determine the position of individual molybdenum dithiolene complexes and their three-dimensional distribution in a semiconducting polymer at the sub-nanometre scale. A heterogeneous distribution is observed, the characteristics of which depend on the dopant concentration. At 5 mol% of the molybdenum dithiolene complex, the majority of the dopant species are present as isolated molecules or small clusters up to five molecules. At 20 mol% dopant concentration and higher, the dopant species form larger nanoclusters with elongated shapes. Even in case of these larger clusters, each individual dopant species is still in contact with the surrounding polymer. The electrical conductivity first strongly increases with dopant concentration and then slightly decreases for the most highly doped samples, even though no large aggregates can be observed. The decreased conductivity is instead attributed to the increased energetic disorder and lower probability of electron transfer that originates from the increased size and size variation in dopant clusters. This study highlights the importance of detailed information concerning the dopant spatial distribution at the sub-nanometre scale in three dimensions within the organic semiconductor host. The information acquired using electron tomography may facilitate more accurate simulations of charge transport in doped organic semiconductors.
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| 31. |
- Prifling, B., et al.
(author)
-
Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures
- 2021
-
In: Frontiers in Materials. - : Frontiers Media SA. - 2296-8016. ; 8
-
Journal article (peer-reviewed)abstract
- Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast database comprising 90,000 microstructures drawn from nine different stochastic models, and compute their effective diffusivity and permeability as well as various microstructural descriptors. To the best of our knowledge, this is the largest and most diverse dataset created for studying the influence of 3D microstructure on mass transport. In particular, we establish microstructure-property relationships using analytical prediction formulas, artificial (fully-connected) neural networks, and convolutional neural networks. Again, to the best of our knowledge, this is the first time that these three statistical learning approaches are quantitatively compared on the same dataset. The diversity of the dataset increases the generality of the determined relationships, and its size is vital for robust training of convolutional neural networks. We make the 3D microstructures, their structural descriptors and effective properties, as well as the code used to study the relationships between them available open access.
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| 32. |
- Röding, Fredrik, et al.
(author)
-
Geriatric falls. A Population-based study 27,402 injury events in people 65 years and older
-
Other publication (other academic/artistic)abstract
- Background: In rich countries falls are one of the commonest injuries, killing more people than all other injury mechanisms together, incapacitating orders of magnitude more, and are responsible for >70% of all trauma hospital beds.Materials: All injuries admitted to the emergency department, 1993-2014, Umeå university hospital, Sweden were registered, e.g., mechanism, injury, localization, type, severity score and treatment, 220,014 injury events. Here we look at 27,402 falls in people over 64.Results: Geriatric fall injuries were 12.5% of all admissions, responsible for 40.7% of all trauma-related hospital days. Fall was the only injury mechanism where women dominated. Between 65-69, falls were 64% of all injuries; for 90+ not less than 93%. With age, severity score increased: between 65 and 69, 10% had score ≥ 3; in 90+, 29% had. Hip fractures increased from 6.2% to 24.4% of all injuries. There was no apparent association between recorded fall height and severity score. Both fractures and soft tissue injuries became more common in the lower extremity, and also more proximal.Conclusions: The changing age/sex patterns in type and localization indicate that extraskeletal factors govern the injury localization/type, not only bone strength. The injury distribution and increasing severity with age, also indicate that not only fall tendency, but also deficient neuromuscular reflexes that distribute the kinetic energy matter; impact can be high even after a fall from standing or less. Therefore, secondary fracture prevention should involve all fall injuries, and also aim at all modifiable risk factors.
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| 33. |
- Röding, Magnus, et al.
(author)
-
A Highly Accurate Pixel-Based FRAP Model Based on Spectral-Domain Numerical Methods
- 2019
-
In: Biophysical Journal. - : Elsevier BV. - 0006-3495 .- 1542-0086. ; 116:7, s. 1348-1361
-
Journal article (peer-reviewed)abstract
- 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.
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| 34. |
- Röding, Magnus, et al.
(author)
-
Approximate Bayesian computation for estimating number concentrations of monodisperse nanoparticles in suspension by optical microscopy
- 2016
-
In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. - 1539-3755 .- 1550-2376. ; 93:6
-
Journal article (peer-reviewed)abstract
- We present an approximate Bayesian computation scheme for estimating number concentrations of monodisperse diffusing nanoparticles in suspension by optical particle tracking microscopy. The method is based on the probability distribution of the time spent by a particle inside a detection region. We validate the method on suspensions of well-controlled reference particles. We illustrate its usefulness with an application in gene therapy, applying the method to estimate number concentrations of plasmid DNA molecules and the average number of DNA molecules complexed with liposomal drug delivery particles.
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| 35. |
- Röding, Magnus, 1984, et al.
(author)
-
Automatic Particle Detection in Microscopy Using Temporal Correlations
- 2013
-
In: Microscopy Research and Technique. - : Wiley. - 1059-910X. ; 76:10, s. 997-1006
-
Journal article (peer-reviewed)abstract
- One of the fundamental problems in the analysis of single particle tracking data is the detection of individual particle positions from microscopy images. Distinguishing true particles from noise with a minimum of false positives and false negatives is an important step that will have substantial impact on all further analysis of the data. A common approach is to obtain a plausible set of particles from a larger set of candidate particles by filtering using manually selected threshold values for intensity, size, shape, and other parameters describing a particle. This introduces subjectivity into the analysis and hinders reproducibility. In this paper, we introduce a method for automatic selection of these threshold values based on maximizing temporal correlations in particle count time series. We use Markov Chain Monte Carlo to find the threshold values corresponding to the maximum correlation, and we study several experimental data sets to assess the performance of the method in practice by comparing manually selected threshold values from several independent experts with automatically selected threshold values. We conclude that the method produces useful results, reducing subjectivity and the need for manual intervention, a great benefit being its easy integratability into many already existing particle detection algorithms.
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| 36. |
- Röding, Magnus, 1984, et al.
(author)
-
Computational high-throughput screening of fluid permeability in heterogeneous fiber materials
- 2016
-
In: Soft Matter. - : Royal Society of Chemistry (RSC). - 1744-6848 .- 1744-683X. ; 12:29, s. 6293-6299
-
Journal article (peer-reviewed)abstract
- We explore computational high-throughput screening as a design strategy for heterogeneous, isotropic fiber materials. Fluid permeability, a key property in the design of soft porous materials, is systematically studied using a multi-scale lattice Boltzmann framework. After characterizing microscopic permeability as a function of solid volume fraction in the microstructure, we perform high-throughput computational screening of in excess of 35 000 macrostructures consisting of a continuous bulk interrupted by spherical/elliptical domains with either lower or higher microscopic permeability (hence with two distinct microscopic solid volume fractions and therefore two distinct microscopic permeabilities) to assess which parameters determine macroscopic permeability for a fixed average solid volume fraction. We conclude that the fractions of bulk and domains and the distribution of solid volume fraction between them are the primary determinants of macroscopic permeability, and that a substantial increase in permeability compared to the corresponding homogenous material is attainable.
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| 37. |
- Röding, Magnus, 1984, et al.
(author)
-
Computational Screening of Diffusive Transport in Nanoplatelet-Filled Composites: Use of Graphene to Enhance Polymer Barrier Properties
- 2018
-
In: ACS Applied Nano Materials. - : American Chemical Society (ACS). - 2574-0970. ; 1:1, s. 160-167
-
Journal article (peer-reviewed)abstract
- 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 4000 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.
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| 38. |
- Röding, Magnus, 1984
(author)
-
Concentration measurements in single particle microscopy
- 2011
-
Licentiate thesis (other academic/artistic)abstract
- The topic of this thesis is the introduction of two novel methods for using single particle microscopy as a tool for absolute number concentration measurements of Brownian particles. The key idea of both methods is that in order to estimate number concentration, the size of the (three-dimensional) particle detection region has to be estimated. Typically, this size has until now been estimated by means of a separate a priori calibration measurement. Thus, in many cases the influence of for example particle brightness and image analysis settings on the final result have been ignored. In the first paper, we use single particle tracking to estimate the size of the detection region. This is based on modeling the distribution of trajectory lengths within the detection region. The modeling is simplified by assuming that particles enter and exit the detection region only by means of axial diffusion, i.e. parallel to the optical axis and orthogonal to the focal plane. In the second paper, we study a time series of particle counts known as a Smoluchowski process. We approximate this non-Markov process by a Markov chain and demonstrate that this model can be used to estimate the size of the detection region. This implies that individual particles need not be tracked. We also introduce a method for automatic selection of a threshold for minimum contrast between particles and the image background, based on analyzing the correlations between particle counts in consecutive frames. In both cases, we perform experimental validation by estimation of the number concentration of different dilutions of a nanosphere water dispersion, and we find close agreement with validation measurements.
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| 39. |
- Röding, Magnus
(author)
-
Effective diffusivity in lattices of impermeable superballs
- 2018
-
In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. - 1063-651X .- 1095-3787. ; 98:5
-
Journal article (peer-reviewed)abstract
- 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
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| 40. |
- Röding, Magnus, et al.
(author)
-
Functional regression-based fluid permeability prediction in monodisperse sphere packings from isotropic two-point correlation functions
- 2017
-
In: Computational materials science. - : Elsevier BV. - 0927-0256 .- 1879-0801. ; 134, s. 126-131
-
Journal article (peer-reviewed)abstract
- 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.
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| 41. |
- Röding, Magnus, 1984, et al.
(author)
-
Identifying directional persistence in intracellular particle motion using Hidden Markov Models
- 2014
-
In: Mathematical Biosciences. - : Elsevier BV. - 0025-5564 .- 1879-3134. ; 248, s. 140-145
-
Journal article (peer-reviewed)abstract
- Particle tracking is a widely used and promising technique for elucidating complex dynamics of the living cell. The cytoplasm is an active material, in which the kinetics of intracellular structures are highly heterogeneous. Tracer particles typically undergo a combination of random motion and various types of directed motion caused by the activity of molecular motors and other non-equilibrium processes. Random switching between more and less directional persistence of motion generally occurs. We present a method for identifying states of motion with different directional persistence in individual particle trajectories. Our analysis is based on a multi-scale turning angle model to characterize motion locally, together with a Hidden Markov Model with two states representing different directional persistence. We define one of the states by the motion of particles in a reference data set where some active processes have been inhibited. We illustrate the usefulness of the method by studying transport of vesicles along microtubules and transport of nanospheres activated by myosin. We study the results using mean square displacements, durations, and particle speeds within each state. We conclude that the method provides accurate identification of states of motion with different directional persistence, with very good agreement in terms of mean-squared displacement between the reference data set and one of the states in the two-state model.
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| 42. |
- Röding, Magnus, et al.
(author)
-
Inverse design of anisotropic spinodoid materials with prescribed diffusivity
- 2022
-
In: Scientific Reports. - : Nature Research. - 2045-2322. ; 12:1
-
Journal article (peer-reviewed)abstract
- The three-dimensional microstructure of functional materials determines its effective properties, like the mass transport properties of a porous material. Hence, it is desirable to be able to tune the properties by tuning the microstructure accordingly. In this work, we study a class of spinodoid i.e. spinodal decomposition-like structures with tunable anisotropy, based on Gaussian random fields. These are realistic yet computationally efficient models for bicontinuous porous materials. We use a convolutional neural network for predicting effective diffusivity in all three directions. We demonstrate that by incorporating the predictions of the neural network in an approximate Bayesian computation framework for inverse problems, we can in a computationally efficient manner design microstructures with prescribed diffusivity in all three directions. © 2022, The Author(s).
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| 43. |
- Röding, Magnus, et al.
(author)
-
Machine learning-accelerated small-angle X-ray scattering analysis of disordered two- and three-phase materials
- 2022
-
In: Frontiers in Materials. - : Frontiers Media S.A.. - 2296-8016. ; 9
-
Journal article (peer-reviewed)abstract
- Small-angle X-ray scattering (SAXS) is a useful technique for nanoscale structural characterization of materials. In SAXS, structural and spatial information is indirectly obtained from the scattering intensity in the spectral domain, known as the reciprocal space. Therefore, characterizing the structure requires solving the inverse problem of finding a plausible structure model that corresponds to the measured scattering intensity. Both the choice of structure model and the computational workload of parameter estimation are bottlenecks in this process. In this work, we develop a framework for analysis of SAXS data from disordered materials. The materials are modeled using Gaussian Random Fields (GRFs). We study the case of two phases, pore and solid, and three phases, where a third phase is added at the interface between the two other phases. Further, we develop very fast GPU-accelerated, Fourier transform-based numerical methods for both structure generation and SAXS simulation. We demonstrate that length scales and volume fractions can be predicted with good accuracy using our machine learning-based framework. The parameter prediction executes virtually instantaneously and hence the computational burden of conventional model fitting can be avoided. Copyright © 2022 Röding, Tomaszewski, Yu, Borg and Rönnols.
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| 44. |
- Röding, Magnus, 1984, et al.
(author)
-
Massively parallel approximate Bayesian computation for estimating nanoparticle diffusion coefficients, sizes and concentrations using confocal laser scanning microscopy
- 2018
-
In: Journal of Microscopy. - : Wiley. - 1365-2818 .- 0022-2720. ; 271:2, s. 174-182
-
Journal article (peer-reviewed)abstract
- 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.
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| 45. |
- Röding, Magnus, 1984, et al.
(author)
-
Measuring absolute nanoparticle number concentrations from particle count time series
- 2013
-
In: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 251:1, s. 19-26
-
Journal article (peer-reviewed)abstract
- Single-particle microscopy is important for characterization of nanoparticulate matter for which accurate concentration measurements are crucial. We introduce a method for estimating absolute number concentrations in nanoparticle dispersions based on a fluctuating time series of particle counts, known as a Smoluchowski process. Thus, unambiguous tracking of particles is not required and identification of single particles is sufficient. However, the diffusion coefficient of the particles must be estimated separately. The proposed method does not require precalibration of the detection region volume, as this can be estimated directly from the observations. We evaluate the method in a simulation study and on experimental data from a series of dilutions of 0.2- and 0.5-m polymer nanospheres in water, obtaining very good agreement with reference values.
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| 46. |
- Röding, Magnus, 1984, et al.
(author)
-
Measuring absolute number concentrations of nanoparticles using single-particle tracking
- 2011
-
In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. - 1539-3755 .- 1550-2376. ; 84:3
-
Journal article (peer-reviewed)abstract
- Single-particle tracking (SPT) microscopy is increasingly used to characterize nanoparticulate systems. We introduce a concept for estimation of particle number concentration in Brownian particle dispersions using SPT based on a model for the trajectory length distribution of particles to estimate the detection region volume. The resulting method is independent of precalibration reference measurements, and robust with respect to image processing settings. Experimentally estimated concentrations of different dilutions of 0.19- and 0.52-mu m polymer nanospheres are in excellent agreement with estimates computed from the concentrations of the stock solutions.
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| 47. |
- Röding, Magnus, et al.
(author)
-
Microstructure of a granular amorphous silica ceramic synthesized by spark plasma sintering
- 2016
-
In: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 264:3, s. 298-303
-
Journal article (peer-reviewed)abstract
- We study the microstructure of a granular amorphous silica ceramic material synthesized by spark plasma sintering. Using monodisperse spherical silica particles as precursor, spark plasma sintering yields a dense granular material with distinct granule boundaries. We use selective etching to obtain nanoscopic pores along the granule borders. We interrogate this highly interesting material structure by combining scanning electron microscopy, X-ray computed nanotomography and simulations based on random close packed spherical particles. We determine the degree of anisotropy caused by the uni-axial force applied during sintering, and our analysis shows that our synthesis method provides a means to avoid significant granule growth and to fabricate a material with well-controlled microstructure.
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| 48. |
- Röding, Magnus, 1984, et al.
(author)
-
Predicting permeability via statistical learning on higher-order microstructural information
- 2020
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
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Journal article (peer-reviewed)abstract
- Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the geometry of the pore microstructure facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we study the predictability of different structural descriptors via both linear regressions and neural networks. A large data set of 30,000 virtual, porous microstructures of different types, including both granular and continuous solid phases, is created for this end. We compute permeabilities of these structures using the lattice Boltzmann method, and characterize the pore space geometry using one-point correlation functions (porosity, specific surface), two-point surface-surface, surface-void, and void-void correlation functions, as well as the geodesic tortuosity as an implicit descriptor. Then, we study the prediction of the permeability using different combinations of these descriptors. We obtain significant improvements of performance when compared to a Kozeny-Carman regression with only lowest-order descriptors (porosity and specific surface). We find that combining all three two-point correlation functions and tortuosity provides the best prediction of permeability, with the void-void correlation function being the most informative individual descriptor. Moreover, the combination of porosity, specific surface, and geodesic tortuosity provides very good predictive performance. This shows that higher-order correlation functions are extremely useful for forming a general model for predicting physical properties of complex materials. Additionally, our results suggest that artificial neural networks are superior to the more conventional regression methods for establishing quantitative structure-property relationships. We make the data and code used publicly available to facilitate further development of permeability prediction methods.
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| 49. |
- Röding, Magnus, 1984, et al.
(author)
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Self-calibrated concentration measurements of polydisperse nanoparticles
- 2013
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In: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 252:1, s. 79-88
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Journal article (peer-reviewed)abstract
- Summary Quantitative characterization of nanoparticles, e.g. accurate estimation of concentration distributions, is critical to many pharmaceutical and biological applications. We present a method that enables for the first time highly accurate size and absolute concentration measurements of polydisperse nanoparticles in solution, based on fluorescence single particle tracking, that are self-calibrated in the sense that the detection region volume is estimated based on the tracking data. The method is evaluated using simulations and experimental data of polystyrene nanospheres in water/sucrose solution. In addition, the method is used to quantify aggregation and clearance of different types of liposomes after intravenous injection in rats, where additional and more accurate information can be obtained that was previously unavailable, which can help elucidate their usefulness as drug carriers.
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| 50. |
- Röding, Magnus
(author)
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Shape-dependent effective diffusivity in packings of hard cubes and cuboids compared with spheres and ellipsoids
- 2017
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In: Soft Matter. - : Royal Society of Chemistry (RSC). - 1744-683X .- 1744-6848. ; 13:46, s. 8864-8870
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Journal article (peer-reviewed)abstract
- We performed computational screening of effective diffusivity in different configurations of cubes and cuboids compared with spheres and ellipsoids. In total, more than 1500 structures are generated and screened for effective diffusivity. We studied simple cubic and face-centered cubic lattices of spheres and cubes, random configurations of cubes and spheres as a function of volume fraction and polydispersity, and finally random configurations of ellipsoids and cuboids as a function of shape. We found some interesting shape-dependent differences in behavior, elucidating the impact of shape on the targeted design of granular materials.
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