| 1. |
- Andersson, Claes, 1987, et al.
(författare)
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A Bayesian hierarchical point process model for epidermal nerve fiber patterns
- 2019
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Ingår i: Mathematical Biosciences. - : Elsevier BV. - 1879-3134 .- 0025-5564. ; 313, s. 48-60
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Tidskriftsartikel (refereegranskat)abstract
- We introduce the Thomas process in a Bayesian hierarchical setting as a model for point pattern data with a nested structure. This model is applied to a nerve fiber data set which consists of several point patterns of nerve entry points from 47 subjects divided into 3 groups, where the grouping is based on the diagnosed severity of a certain nerve disorder. The modeling assumption is that each point pattern is a realization of a Thomas process, with parameter values specific to the subject. These parameter values are in turn assumed to come from distributions that depend on which group the subject belongs to. To fit the model, we construct an MCMC algorithm, which is evaluated in a simulation study. The results of the simulation study indicate that the group level mean of each parameter is well estimated, but that the estimation of the between subject variance is more challenging. When fitting the model to the nerve fiber data, we find that the structure within clusters appears to be the same in all groups, but that the number of clusters decreases with the progression of the nerve disorder.
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| 2. |
- Andersson, Claes, 1987, et al.
(författare)
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Discovering early diabetic neuropathy from epidermal nerve fiber patterns
- 2016
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Ingår i: Statistics in Medicine. - : Wiley. - 0277-6715 .- 1097-0258. ; 35:24, s. 4427-4442
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Tidskriftsartikel (refereegranskat)abstract
- Epidermal nerve fibre (ENF) density and morphology are used to study small fibre involvement in diabetic, HIV, chemotherapy induced and other neuropathies. ENF density and summed length of ENFs per epidermal surface area are reduced, and ENFs may appear more clustered within the epidermis in subjects with small fibre neuropathy than in healthy subjects. Therefore, it is important to understand the spatial structure of ENFs. In this paper, we compare the ENF patterns between healthy subjects and subjects suffering from mild diabetic neuropathy. The study is based on suction skin blister specimens from the right foot of 32 healthy subjects and eight subjects with mild diabetic neuropathy. We regard the ENF entry point (location where the trunks of a nerve enters the epidermis) and ENF end point (termination of the nerve fibres) patterns as realizations of spatial point processes, and develop tools that can be used in the analysis and modelling of ENF patterns. We use spatial summary statistics and shift plots and define a new tool, reactive territory, to study the spatial patterns and to compare the patterns of the two groups. We will also introduce a simple model for these data in order to understand the growth process of the nerve fibres.
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| 3. |
- Andersson, Claes, 1987, et al.
(författare)
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Hierarchical models for epidermal nerve fiber data
- 2018
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Ingår i: Statistics in Medicine. - : Wiley. - 0277-6715 .- 1097-0258. ; 37:3, s. 357-374
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Tidskriftsartikel (refereegranskat)abstract
- While epidermal nerve fiber (ENF) data have been used to study the effects of small fiber neuropathies through the density and the spatial patterns of the ENFs, little research has been focused on the effects on the individual nerve fibers. Studying the individual nerve fibers might give a better understanding of the effects of the neuropathy on the growth process of the individual ENFs. In this study, data from 32 healthy volunteers and 20 diabetic subjects, obtained from suction induced skin blister biopsies, are analyzed by comparing statistics for the nerve fibers as a whole and for the segments that a nerve fiber is composed of. Moreover, it is evaluated whether this type of data can be used to detect diabetic neuropathy, by using hierarchical models to perform unsupervised classification of the subjects. It is found that using the information about the individual nerve fibers in combination with the ENF counts yields a considerable improvement as compared to using the ENF counts only. Copyright © 2017 John Wiley & Sons, Ltd.
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| 4. |
- Bolin, David, 1983, et al.
(författare)
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Statistical Prediction of Global Sea Level From Global Temperature
- 2015
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Ingår i: Statistica Sinica. - : Statistica Sinica (Institute of Statistical Science). - 1017-0405. ; 25:1, s. 351-367
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Tidskriftsartikel (refereegranskat)abstract
- Sea level rise is a threat to many coastal communities, and projection of future sea level for different climate change scenarios is an important societal task In this paper, we first construct a time series regression model to predict global sea level from global temperature. The model is fitted to two sea level data sets (with and without corrections for reservoir storage of water) and three temperature data sets. The effect of smoothing before regression is also studied. Finally, we apply a novel methodology to develop confidence bands for the projected sea level, simultaneously for 2000-2100, under different scenarios, using temperature projections from the latest climate modeling experiment. The main finding is that different methods for sea level projection, which appear to disagree, have confidence intervals that overlap, when taking into account the different sources of variability in the analyses.
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| 5. |
- Häbel, Henrike, 1987, et al.
(författare)
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A three-dimensional anisotropic point process characterization for pharmaceutical coatings
- 2017
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Ingår i: Spatial Statistics. - : Elsevier BV. - 2211-6753. ; 22:2, s. 306-320
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Tidskriftsartikel (refereegranskat)abstract
- © 2017 Elsevier B.V. Spatial characterization and modeling of the structure of a material may provide valuable knowledge on its properties and function. Especially, for a drug formulation coated with a polymer film, understanding the relationship between pore structure and drug release properties is important to optimize the coating film design. Here, we use methods from image analysis and spatial statistics to characterize and model the pore structure in pharmaceutical coatings. More precisely, we use and develop point process theory to characterize the branching structure of a polymer blended film with data from confocal laser scanning microscopy. Point patterns, extracted by identifying branching points of pore channels, are both inhomogeneous and anisotropic. Therefore, we introduce a directional version of the inhomogeneous K-function to study the anisotropy and then suggest two alternative ways to model the anisotropic three-dimensional structure. First, we apply a linear transformation to the data such that it appears isotropic and subsequently fit isotropic inhomogeneous Strauss or Lennard-Jones models to the transformed pattern. Second, we include the anisotropy directly in a Lennard-Jones and a more flexible step-function model with anisotropic pair-potential functions. The methods presented will be useful for anisotropic inhomogeneous point patterns in general and for characterizing porous material in particular.
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| 6. |
- Häbel, Henrike, 1987, et al.
(författare)
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Characterization of pore structure of polymer blended films used for controlled drug release
- 2016
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Ingår i: Journal of Controlled Release. - : Elsevier BV. - 0168-3659 .- 1873-4995. ; 222, s. 151-158
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Tidskriftsartikel (refereegranskat)abstract
- The characterization of the pore structure in pharmaceutical coatings is crucial for understanding and controlling mass transport properties and function in controlled drug release. Since the drug release rate can be associated with the film permeability, the effect of the pore structure on the permeability is important to study. In this paper, a new approach for characterizing the pore structure in polymer blended films was developed based on an image processing procedure for given two-dimensional scanning electron microscopy images of film cross-sections. The focus was on different measures for characterizing the complexity of the shape of a pore. The pore characterization developed was applied to ethyl cellulose (EC) and hydroxypropyl cellulose (HPC) blended films, often used as pharmaceutical coatings, where HPC acts as the pore former. It was studied how two different HPC viscosity grades influence the pore structure and, hence, mass transport through the respective films. The film with higher HPC viscosity grade had been observed to be more permeable than the other in a previous study; however, experiments had failed to show a difference between their pore structures. By instead characterizing the pore structures using tools from image analysis, statistically significant differences in pore area fraction and pore shape were identified. More specifically, it was found that the more permeable film with higher HPC viscosity grade seemed to have more extended and complex pore shapes than the film with lower HPC viscosity grade. This result indicates a greater degree of connectivity in the film with higher permeability and statistically confirms hypotheses on permeability from related experimental studies.
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| 7. |
- Häbel, Henrike, 1987, et al.
(författare)
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Colloidal particle aggregation in three dimensions
- 2019
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Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 275:3, s. 149-158
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Tidskriftsartikel (refereegranskat)abstract
- Colloidal systems are of importance not only for everyday products, but also for the development of new advanced materials. In many applications, it is crucial to understand and control colloidal interaction. In this paper, we study colloidal particle aggregation of silica nanoparticles, where the data are given in a three-dimensional micrograph obtained by high-angle annular dark field scanning transmission electron microscopy tomography. We investigate whether dynamic models for particle aggregation, namely the diffusion limited cluster aggregation and the reaction limited cluster aggregation models, can be used to construct structures present in the scanning transmission electron microscopy data. We compare the experimentally obtained silica aggregate to the simulated postaggregated structures obtained by the dynamic models. In addition, we fit static Gibbs point process models, which are commonly used models for point patterns with interactions, to the silica data. We were able to simulate structures similar to the silica structures by using Gibbs point process models. By fitting Gibbs models to the simulated cluster aggregation patterns, we saw that a smaller probability of aggregation would be needed to construct structures similar to the observed silica particle structure.
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| 8. |
- Häbel, Henrike, 1987, et al.
(författare)
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From static micrographs to particle aggregation dynamics in three dimensions
- 2016
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Ingår i: Journal of Microscopy. - : Wiley. - 1365-2818 .- 0022-2720. ; 262:1, s. 102-111
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Tidskriftsartikel (refereegranskat)abstract
- Studies on colloidal aggregation have brought forth theories on stability of colloidal gels and models for aggregation dynamics. Still, a complete link between developed frameworks and obtained laboratory observations has to be found. In this work, aggregates of silica nanoparticles (20 nm) are studied using diffusion limited cluster aggregation (DLCA) and reaction limited cluster aggregation (RLCA) models. These processes are driven by the probability of particles to aggregate upon collision. This probability of aggregation is one in the DLCA and close to zero in the RLCA process. We show how to study the probability of aggregation from static micrographs on the example of a silica nanoparticle gel at 9 wt%. The analysis includes common summary functions from spatial statistics, namely the empty space function and Ripley's K-function, as well as two newly developed summary functions for cluster analysis based on graph theory. One of the new cluster analysis functions is related to the clustering coefficient in communication networks and the other to the size of a cluster. All four topological summary statistics are used to quantitatively compare in plots and in a least-square approach experimental data to cluster aggregation simulations with decreasing probabilities of aggregation. We study scanning transmission electron micrographs and utilize the intensity - mass thickness relation present in such images to create comparable micrographs from three-dimensional simulations. Finally, a characterization of colloidal silica aggregates and simulated structures is obtained, which allows for an evaluation of the cluster aggregation process for different aggregation scenarios. As a result, we find that the RLCA process fits the experimental data better than the DLCA process.
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| 9. |
- Lee, Adél, et al.
(författare)
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Characterizing cross-subject spatial interaction patterns in functional magnetic resonance imaging studies: A two-stage point-process model
- 2017
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Ingår i: Biometrical Journal. - : Wiley. - 0323-3847 .- 1521-4036. ; 59, s. 1352-1381
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Tidskriftsartikel (refereegranskat)abstract
- © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim We develop a two-stage spatial point process model that introduces new characterizations of activation patterns in multisubject functional Magnetic Resonance Imaging (fMRI) studies. Conventionally multisubject fMRI methods rely on combining information across subjects one voxel at a time in order to identify locations of peak activation in the brain. The two-stage model that we develop here addresses shortcomings of standard methods by explicitly modeling the spatial structure of functional signals and recognizing that corresponding cross-subject functional signals can be spatially misaligned. In our first stage analysis, we introduce a marked spatial point process model that captures the spatial features of the functional response and identifies a configuration of activation units for each subject. The locations of these activation units are used as input for the second stage model. The point process model of the second stage analysis is developed to characterize multisubject activation patterns by estimating the strength of cross-subject interactions at different spatial ranges. The model uses spatial neighborhoods to account for the cross-subject spatial misalignment in corresponding functional units. We applied our methods to an fMRI study of 21 individuals who performed an attention test. We identified four brain regions that are involved in the test and found that our model results agree well with our understanding of how these regions engage with the tasks performed during the attention test. Our results highlighted that cross-subject interactions are stronger in brain areas that have a more specific function in performing the experimental tasks than in other areas.
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| 10. |
- Longfils, Marco, 1990, et al.
(författare)
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Raster Image Correlation Spectroscopy Performance Evaluation
- 2019
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Ingår i: Biophysical Journal. - : Elsevier BV. - 0006-3495 .- 1542-0086. ; 117:10, s. 1900-1914
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Tidskriftsartikel (refereegranskat)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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