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Carmona, P., Poulsen, J., Westergren, J., Nilsson Pingel, T., Röding, M., Lambrechts, E., . . . Loren, N. (2023). Controlling the structure of spin-coated multilayer ethylcellulose/hydroxypropylcellulose films for drug release.. International Journal of Pharmaceutics, 644, Article ID 123350.
Open this publication in new window or tab >>Controlling the structure of spin-coated multilayer ethylcellulose/hydroxypropylcellulose films for drug release.
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2023 (English)In: International Journal of Pharmaceutics, ISSN 0378-5173, E-ISSN 1873-3476, Vol. 644, article id 123350Article in journal (Refereed) Epub ahead of print
Abstract [en]

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.

Keywords
Cahn-Hilliard simulations, cellulose, confocal laser scanning microscope, electron microscopy, multilayer film, phase separation kinetics, phase separation mechanisms, porous film for controlled release
National Category
Food Science
Identifiers
urn:nbn:se:ri:diva-66152 (URN)10.1016/j.ijpharm.2023.123350 (DOI)37640089 (PubMedID)
Note

The Swedish Foundation for Strategic Research (SSF grant FID16-0013), the Swedish Research Council (VR grant 2018-03986), and the Swedish Research Council for Sustainable Development (grant 2019-01295) are gratefully acknowledged for the funding. AstraZeneca is acknowledged for the financial support and materials. Funding is acknowledged by the Fund for Scientific Research Flanders (grants I012020N & I000321N) and the Special Research Fund of Ghent University (grant BOF.COR.2022.0003.01). 

Available from: 2023-09-08 Created: 2023-09-08 Last updated: 2023-09-08Bibliographically approved
Niimi, J., Ahlinder, A., Nilsson Pingel, T., Niimi, C., Höglund, E., Öhgren, C., . . . Nielsen, T. (2023). Saltiness enhancement: Impact of acid added to bread with heterogeneously distributed sodium chloride. Lebensmittel-Wissenschaft + Technologie, 176, Article ID 114557.
Open this publication in new window or tab >>Saltiness enhancement: Impact of acid added to bread with heterogeneously distributed sodium chloride
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2023 (English)In: Lebensmittel-Wissenschaft + Technologie, ISSN 0023-6438, E-ISSN 1096-1127, Vol. 176, article id 114557Article in journal (Refereed) Published
Abstract [en]

The current global sodium consumption exceeds recommended daily intakes and there is a great need to reduce the sodium content in foods for a healthier society. The current study investigated the effect of combining sensory interaction principles and heterogeneous distribution of NaCl in bread on sensory properties, structure, and NaCl distribution. Breads were prepared in three different arrangements of NaCl distribution: homogenous, layered, and layered with lactic acid. Within each arrangement, four NaCl levels were tested. The breads were evaluated by a sensory panel for perceived saltiness, sourness, and qualitative texture, measured for stiffness, and the NaCl distribution was determined by X-ray fluorescence microscopy (XFM). Perceived saltiness was significantly enhanced in breads beyond heterogeneous NaCl distribution when lactic acid was added. Stiffness measurements were affected by layering of bread, the layers without NaCl were stiffer with an increase in overall salt concentration. The heterogeneous distribution of NaCl in layered breads could be visualised by XFM and textural consequences of layering bread are discussed. The current study demonstrates the potential of combining principles of pulsation of taste and sensory interactions together to enhance salt perception, and hence suggesting the approach as a possible further strategy for NaCl reduction in bread.

Place, publisher, year, edition, pages
Academic Press, 2023
Keywords
Heterogeneous salt distribution, Perception, Pulsation, Salt, Sensory interactions, Fluorescence microscopy, Food products, Lactic acid, Sensory perception, Stiffness, Textures, 'current, Heterogeneous distributions, Recommended daily intakes, Sensory panels, Sensory properties, Stiffness measurements, X-ray fluorescence microscopy, Sodium chloride
National Category
Food Science
Identifiers
urn:nbn:se:ri:diva-63980 (URN)10.1016/j.lwt.2023.114557 (DOI)2-s2.0-85147538587 (Scopus ID)
Note

Correspondence Address: Niimi J, RISE Research Institutes of Sweden, Sweden. Funding details: Västra Götalandsregionen, RUN 2020–00378; Funding details: VINNOVA, 2020–01824; Funding text 1: The measurements indicated only a little NaCl migration after baking, freezing, storage and thawing, since sharp changes in the chlorine signals were not observed, but rather a gradual transition between the layers (Fig. S6). Also, the signal did not drop to zero in the centre of the layers with no added NaCl. The amount of NaCl migration appeared to be so small that it is not expected to have a significant impact on the perceived saltiness of the breads. Additional measurements were performed using ICP-OES and IC to investigate if the migration of sodium is larger than the observed chlorine migration in the XFM measurements. The migration of sodium was similar or less to that of chlorine, which supported the conclusions drawn from the XFM results (for methodology and a summary of the ICP-OES/IC results see S2.0 and Table S2 in the supplementary material). Given that the ICP-OES/IC measurements showed that chlorine migrated in a similarly strong manner to sodium, it is reasonable to assume that the sodium distribution was adequately represented by chlorine. These measurements with XFM demonstrated its applicability in measuring chlorine ions in bread. Previous applications of XFM were on plant materials such as leaves, seedlings, barley grains, and rice kernels to measure distribution of ions such as zinc, calcium, potassium, and manganese among others. The results demonstrate that XFM can be a useful tool in confirming heterogenous distribution of chlorine ions of NaCl in processed food stuffs, such as breads.This study was performed under the project ReduSalt – Salt Reduction in Foods, a project funded by Sweden's Innovation Agency (Vinnova), grant number 2020–01824. The financial support by Region Västra Götaland, Sweden, grant number RUN 2020–00378, is also gratefully acknowledged.  Funding text 2: This study was performed under the project ReduSalt – Salt Reduction in Foods, a project funded by Sweden's Innovation Agency (Vinnova) , grant number 2020–01824 . The financial support by Region Västra Götaland, Sweden , grant number RUN 2020–00378 

Available from: 2023-02-22 Created: 2023-02-22 Last updated: 2023-06-08Bibliographically approved
Loren, N., Niimi, J., Höglund, E., Albin, R., Rytter, E., Bjerre, K. & Nielsen, T. (2023). Sodium reduction in foods: Challenges and strategies for technical solutions. Journal of Food Science, 88(3), 885
Open this publication in new window or tab >>Sodium reduction in foods: Challenges and strategies for technical solutions
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2023 (English)In: Journal of Food Science, ISSN 0022-1147, E-ISSN 1750-3841, Vol. 88, no 3, p. 885-Article in journal (Refereed) Published
Abstract [en]

In many parts of the world, sodium consumption is higher than recommended levels, representing one of the most important food-related health challenges and leading to considerable economical costs for society. Therefore, there is a need to find technical solutions for sodium reduction that can be implemented by food producers and within food services. The aims of this review are to discuss the barriers related to sodium reduction and to highlight a variety of technical solutions. The barriers relate to consumer perception, microbiology, processing, and physicochemistry. Existing technical solutions include inhomogeneous salt distribution, coated salt particles, changing particle sizes and forms, surface coating, multisensory combinations, sodium replacements, double emulsions, adapted serum release by microstructure design, and adapted brittleness by microstructure design. These solutions, their implementation and the associated challenges, and applicable product categories are described. Some of these solutions are ready for use or are in their early development stages. Many solutions are promising, but in most cases, some form of adaptation or optimization is needed before application in specific products, and care must always be taken to ensure food safety. For instance, further research and innovation are required in the dynamic evolution of saltiness perception, consumer acceptance, the binding and migration of sodium, juiciness, microbiological safety, and the timing of salt addition during processing. Once implemented, these solutions will undoubtedly support food producers and food services in reducing sodium content and extend the application of the solutions to different foods. © 2022 Research Institutes of Sweden, Swedish Food Federation and Lyckeby Culinar AB.

Place, publisher, year, edition, pages
John Wiley and Sons Inc, 2023
Keywords
food, inhomogeneous salt distribution, multisensory, safety, sodium reduction, technical solutions
National Category
Food Science
Identifiers
urn:nbn:se:ri:diva-63988 (URN)10.1111/1750-3841.16433 (DOI)2-s2.0-85147016942 (Scopus ID)
Note

 Correspondence Address: Lorén, N. RISE Agriculture and Food, Sweden; email: niklas.loren@ri.se;

Funding details: VINNOVA, 2020‐01824; Funding text 1: This review has been compiled within ReduSalt – Salt Reduction in Foods, a project funded by Sweden's Innovation Agency (Vinnova), grant number 2020‐01824.

Available from: 2023-02-15 Created: 2023-02-15 Last updated: 2023-07-03Bibliographically approved
Schott, F., Isaksson, S., Larsson, E., Marone, F., Öhgren, C., Röding, M., . . . Raaholt, B. (2023). Structural formation during bread baking in a combined microwave-convective oven determined by sub-second in-situ synchrotron X-ray microtomography. Food Research International, 173, Article ID 113283.
Open this publication in new window or tab >>Structural formation during bread baking in a combined microwave-convective oven determined by sub-second in-situ synchrotron X-ray microtomography
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2023 (English)In: Food Research International, ISSN 0963-9969, E-ISSN 1873-7145, Vol. 173, article id 113283Article in journal (Refereed) Published
Abstract [en]

A new concept has been developed for characterizing the real-time evolution of the three-dimensional pore and lamella microstructure of bread during baking using synchrotron X-ray microtomography (SRµCT). A commercial, combined microwave-convective oven was modified and installed at the TOMCAT synchrotron tomography beamline at the Swiss Light Source (SLS), to capture the 3D dough-to-bread structural development in-situ at the micrometer scale with an acquisition time of 400 ms. This allowed characterization and quantitative comparison of three baking technologies: (1) convective heating, (2) microwave heating, and (3) a combination of convective and microwave heating. A workflow for automatic batchwise image processing and analysis of 3D bread structures (1530 analyzed volumes in total) was established for porosity, individual pore volume, elongation, coordination number and local wall thickness, which allowed for evaluation of the impact of baking technology on the bread structure evolution. The results showed that the porosity, mean pore volume and mean coordination number increase with time and that the mean local cell wall thickness decreases with time. Small and more isolated pores are connecting with larger and already more connected pores as function of time. Clear dependencies are established during the whole baking process between the mean pore volume and porosity, and between the mean local wall thickness and the mean coordination number. This technique opens new opportunities for understanding the mechanisms governing the structural changes during baking and discern the parameters controlling the final bread quality. © 2023 The Author(s)

Place, publisher, year, edition, pages
Elsevier Ltd, 2023
Keywords
Baking, Bread, Convective, Image analysis, In-situ, Microwave, Oven, Synchrotron X-ray microtomography, Food products, Light sources, Microwave heating, Porosity, Quality control, Tomography, Baking technology, Convective heating, Image-analysis, Microwave-heating, Pore volume
National Category
Energy Engineering
Identifiers
urn:nbn:se:ri:diva-65961 (URN)10.1016/j.foodres.2023.113283 (DOI)2-s2.0-85166305869 (Scopus ID)
Note

This work was funded by VINNOVA (Swedeńs Innovation Agency)[2019–02572], and additional internal RISE co-financing from 2020. Florian and Rajmund were financed by the Swedish Research Council [2019–03742]. Niklas gratefully acknowledges funding from the Swedish Research Council [2018–06378]. The computations and data handling were carried out under the following QIM-related projects: SNIC 2022/6–157 and LU 2022/2–22, which were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at LUNARC at Lund University, partially funded by the Swedish Research Council through grant agreement [2018–05973].

Available from: 2023-08-24 Created: 2023-08-24 Last updated: 2023-08-24Bibliographically approved
Carmona, P., von Corswant, C., Röding, M., Särkkä, A., Olsson, E. & Loren, N. (2022). Cross-sectional structure evolution of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films during solvent quenching. RSC Advances, 12(40), 26078-26089
Open this publication in new window or tab >>Cross-sectional structure evolution of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films during solvent quenching
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2022 (English)In: RSC Advances, E-ISSN 2046-2069, Vol. 12, no 40, p. 26078-26089Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
Royal Society of Chemistry, 2022
Keywords
Controlled drug delivery, Morphology, Pelletizing, Separation, Shrinkage, Cross-sectional structures, Drug transport, Drug transport rates, Ethylcellulose, Hydroxypro-pylcellulose, Industrial manufacturing process, Phase-separated structures, Porous film, Structure evolution, Watersoluble, Fluidized beds
National Category
Chemical Sciences
Identifiers
urn:nbn:se:ri:diva-61216 (URN)10.1039/d2ra04178b (DOI)2-s2.0-85139943638 (Scopus ID)
Note

Funding details: 2019-01295; Funding details: Stiftelsen för Strategisk Forskning, SSF, FID16-0013; Funding details: Vetenskapsrådet, VR, 2018-03986; Funding text 1: The Swedish Foundation for Strategic Research (SSF grant FID16-0013), the Swedish Research Council (VR grant 2018-03986), and the Swedish Research Council for Sustainable Development (grant 2019-01295) are gratefully acknowledged for the funding. AstraZeneca is acknowledged for the financial support and materials.

Available from: 2022-12-02 Created: 2022-12-02 Last updated: 2023-05-26Bibliographically approved
Röding, M., Wåhlstrand Skärström, V. & Loren, N. (2022). Inverse design of anisotropic spinodoid materials with prescribed diffusivity. Scientific Reports, 12(1), Article ID 17413.
Open this publication in new window or tab >>Inverse design of anisotropic spinodoid materials with prescribed diffusivity
2022 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 12, no 1, article id 17413Article in journal (Refereed) Published
Abstract [en]

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).

Place, publisher, year, edition, pages
Nature Research, 2022
Keywords
anisotropy, article, convolutional neural network, decomposition, diffusivity, prediction, Bayes theorem, diffusion weighted imaging, normal distribution, porosity, Diffusion Magnetic Resonance Imaging
National Category
Physical Sciences
Identifiers
urn:nbn:se:ri:diva-61195 (URN)10.1038/s41598-022-21451-6 (DOI)2-s2.0-85140077785 (Scopus ID)
Note

 Funding details: 2019-01295; Funding details: Nvidia; Funding text 1: We acknowledge the financial support of the Swedish Research Council for Sustainable Development (Grant Number 2019-01295). A GPU used for part of this research was donated by the NVIDIA Corporation. The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC).; Funding text 2: We acknowledge the financial support of the Swedish Research Council for Sustainable Development (Grant Number 2019-01295). A GPU used for part of this research was donated by the NVIDIA Corporation. The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC).

Available from: 2022-12-06 Created: 2022-12-06 Last updated: 2023-05-26Bibliographically approved
Carmona, P., Röding, M., Särkkä, A., von Corswant, C., Olsson, E. & Loren, N. (2022). Structure formation and coarsening kinetics of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films. Soft Matter, 18(16), 3206-3217
Open this publication in new window or tab >>Structure formation and coarsening kinetics of phase-separated spin-coated ethylcellulose/hydroxypropylcellulose films
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2022 (English)In: Soft Matter, ISSN 1744-683X, E-ISSN 1744-6848, Vol. 18, no 16, p. 3206-3217Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
Royal Society of Chemistry, 2022
Keywords
Coarsening, Controlled drug delivery, Fluidized beds, Kinetics, Ostwald ripening, Bicontinuous structures, Characteristic length, Coarsening kinetics, Ethylcellulose, Film structure, Formation kinetics, Hydroxypro-pylcellulose, Length scale, Structure evolution, Structure formations, Separation, cellulose, hydroxypropylcellulose, solvent, water, chemistry, porosity, Solvents
National Category
Medical Materials
Identifiers
urn:nbn:se:ri:diva-59252 (URN)10.1039/d2sm00113f (DOI)2-s2.0-85128483936 (Scopus ID)
Note

Funding details: 2019-01295; Funding details: Stiftelsen för Strategisk Forskning, SSF, FID16-0013; Funding details: Vetenskapsrådet, VR, 2018-03986; Funding text 1: The Swedish Foundation for Strategic Research (SSF grant FID16-0013), the Swedish Research Council (VR grant 2018-03986), and the Swedish Research Council for Sustainable Development (grant 2019-01295) are gratefully acknowledged for the funding. AstraZeneca is acknowledged for the financial support and materials. Philip Townsend, RISE/Chalmers, is acknowledged for his contribution to the 2D-curvature estimation.

Available from: 2022-05-23 Created: 2022-05-23 Last updated: 2023-05-26Bibliographically approved
Skärberg, F., Fager, C., Mendoza-Lara, F., Josefson, M., Olsson, E., Loren, N. & Röding, M. (2021). Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release. Journal of Microscopy, 283(1), 51-63
Open this publication in new window or tab >>Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release
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2021 (English)In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 283, no 1, p. 51-63Article in journal (Refereed) Published
Abstract [en]

Phase-separated polymer films are commonly used as coatings around pharmaceutical oral dosage forms (tablets or pellets) to facilitate controlled drug release. A typical choice is to use ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. When an EC/HPC film is in contact with water, the leaching out of the water-soluble HPC phase produces an EC film with a porous network through which the drug is transported. The drug release can be tailored by controlling the structure of this porous network. Imaging and characterization of such EC porous films facilitates understanding of how to control and tailor film formation and ultimately drug release. Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography is a well-established technique for high-resolution imaging, and suitable for this application. However, for segmenting image data, in this case to correctly identify the porous network, FIB-SEM is a challenging technique to work with. In this work, we implement convolutional neural networks for segmentation of FIB-SEM image data. The data are acquired from three EC porous films where the HPC phases have been leached out. The three data sets have varying porosities in a range of interest for controlled drug release applications. We demonstrate very good agreement with manual segmentations. In particular, we demonstrate an improvement in comparison to previous work on the same data sets that utilized a random forest classifier trained on Gaussian scale-space features. Finally, we facilitate further development of FIB-SEM segmentation methods by making the data and software used open access. © 2021 The Authors.

Place, publisher, year, edition, pages
Blackwell Publishing Ltd, 2021
Keywords
controlled drug release, convolutional neural networks, deep learning, focused ion beam scanning electron microscopy, image analysis, machine learning, microstructure, polymer films, porous materials, semantic segmentation
National Category
Polymer Chemistry
Identifiers
urn:nbn:se:ri:diva-53031 (URN)10.1111/jmi.13007 (DOI)2-s2.0-85104456896 (Scopus ID)
Note

Funding details: 2019‐01295; Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: Vetenskapsrådet, VR, 2016‐03809; Funding text 1: We acknowledge Anna Olsson and Christian von Corswant at AstraZeneca Gothenburg for discussions and for providing the samples and Chalmers Material Analysis Laboratory for their support of microscopes. We acknowledge the financial support of the Swedish Research Council (Grant number 2016‐03809), the Swedish Research Council for Sustainable Development (Grant number 2019‐01295), the Swedish Foundation for Strategic Research (the project ‘Material structures seen through microscopes and statistics'), and Chalmers Area of Advance Materials Science. A GPU used for part of this research was donated by the NVIDIA Corporation. The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC)

Available from: 2021-05-25 Created: 2021-05-25 Last updated: 2023-05-26Bibliographically approved
Wåhlstrand Skärström, V., Krona, A., Loren, N. & Röding, M. (2021). DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks. Journal of Microscopy, 282(2), 146-161
Open this publication in new window or tab >>DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks
2021 (English)In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 282, no 2, p. 146-161Article in journal (Refereed) Published
Abstract [en]

Conventional analysis of fluorescence recovery after photobleaching (FRAP) data for diffusion coefficient estimation typically involves fitting an analytical or numerical FRAP model to the recovery curve data using non-linear least squares. Depending on the model, this can be time consuming, especially for batch analysis of large numbers of data sets and if multiple initial guesses for the parameter vector are used to ensure convergence. In this work, we develop a completely new approach, DeepFRAP, utilizing machine learning for parameter estimation in FRAP. From a numerical FRAP model developed in previous work, we generate a very large set of simulated recovery curve data with realistic noise levels. The data are used for training different deep neural network regression models for prediction of several parameters, most importantly the diffusion coefficient. The neural networks are extremely fast and can estimate the parameters orders of magnitude faster than least squares. The performance of the neural network estimation framework is compared to conventional least squares estimation on simulated data, and found to be strikingly similar. Also, a simple experimental validation is performed, demonstrating excellent agreement between the two methods. We make the data and code used publicly available to facilitate further development of machine learning-based estimation in FRAP. Lay description: Fluorescence recovery after photobleaching (FRAP) is one of the most frequently used methods for microscopy-based diffusion measurements and broadly used in materials science, pharmaceutics, food science and cell biology. In a FRAP experiment, a laser is used to photobleach fluorescent particles in a region. By analysing the recovery of the fluorescence intensity due to the diffusion of still fluorescent particles, the diffusion coefficient and other parameters can be estimated. Typically, a confocal laser scanning microscope (CLSM) is used to image the time evolution of the recovery, and a model is fit using least squares to obtain parameter estimates. In this work, we introduce a new, fast and accurate method for analysis of data from FRAP. The new method is based on using artificial neural networks to predict parameter values, such as the diffusion coefficient, effectively circumventing classical least squares fitting. This leads to a dramatic speed-up, especially noticeable when analysing large numbers of FRAP data sets, while still producing results in excellent agreement with least squares. Further, the neural network estimates can be used as very good initial guesses for least squares estimation in order to make the least squares optimization convergence much faster than it otherwise would. This provides for obtaining, for example, diffusion coefficients as soon as possible, spending minimal time on data analysis. In this fashion, the proposed method facilitates efficient use of the experimentalist's time which is the main motivation to our approach. The concept is demonstrated on pure diffusion. However, the concept can easily be extended to the diffusion and binding case. The concept is likely to be useful in all application areas of FRAP, including diffusion in cells, gels and solutions. © 2020 The Authors. 

Place, publisher, year, edition, pages
Blackwell Publishing Ltd, 2021
Keywords
confocal laser scanning microscopy, deep learning, deep neural network, diffusion, fluorescence recovery after photobleaching, machine learning, regression
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-52079 (URN)10.1111/jmi.12989 (DOI)2-s2.0-85099352468 (Scopus ID)
Note

Funding details: 2019‐01295; Funding details: Vetenskapsrådet, VR, 2016‐03809; Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding text 1: The financial support of the Swedish Research Council for Sustainable Development (grant number 2019‐01295), the Swedish Research Council (grant number 2016‐03809), and the Swedish Foundation for Strategic Research (the project ‘Material structures seen through microscopes and statistics') is acknowledged. The computations were in part performed on resources at Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC). A GPU used for part of this research was donated by the NVIDIA Corporation.

Available from: 2021-01-26 Created: 2021-01-26 Last updated: 2023-10-05Bibliographically approved
Barman, S., Fager, C., Röding, M., Loren, N., von Corswant, C., Olsson, E., . . . Rootzén, H. (2021). New characterization measures of pore shape and connectivity applied to coatings used for controlled drug release. Journal of Pharmaceutical Sciences, 110(7), 2753
Open this publication in new window or tab >>New characterization measures of pore shape and connectivity applied to coatings used for controlled drug release
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2021 (English)In: Journal of Pharmaceutical Sciences, ISSN 0022-3549, E-ISSN 1520-6017, Vol. 110, no 7, p. 2753-Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
Elsevier B.V., 2021
National Category
Paper, Pulp and Fiber Technology
Identifiers
urn:nbn:se:ri:diva-52835 (URN)10.1016/j.xphs.2021.02.024 (DOI)2-s2.0-85103101944 (Scopus ID)
Note

Funding details: Stiftelsen för Strategisk Forskning, SSF, AM13-0066; Funding details: VINNOVA; Funding details: Knut och Alice Wallenbergs Stiftelse, 20012.0067; Funding details: Vetenskapsrådet, VR, 2016-04187; Funding text 1: We thank Aila Särkkä and everyone involved in the SSF project for valuable feedback. We also appreciate the feedback given at workshops organized by the Chalmers center SuMo Biomaterials and within the project COSIMA, both funded by Vinnova. Funding: This work was supported by the Swedish Foundation for Strategic Research [grant number AM13-0066 ], the Knut and Alice Wallenberg foundation [grant number 20012.0067 ], and the Swedish Research Council [grant number 2016-04187 ].

Available from: 2021-04-23 Created: 2021-04-23 Last updated: 2023-05-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9979-5488

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