| 1. |
- Ahlinder, Linnea, et al.
(författare)
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Graphene oxide nanoparticle attachment and its toxicity on living lung epithelial cells
- 2015
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Ingår i: RSC Advances. - : Royal Society of Chemistry. - 2046-2069. ; 5:73, s. 59447-59457
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Tidskriftsartikel (refereegranskat)abstract
- Since its discovery, graphene and its oxidized form, graphene oxide (GO), have attracted interest in a wide range of technical applications. Concerns about their potential toxicity calls for scrutinized studies, but hitherto conflicting results have been reported which partly may be due to variations of synthesis and exposure procedures. Here we report on the attachment and toxicity of contamination-free graphene oxide nanoparticles (GONP) in living lung epithelial cells. The synthesis of chemically pure GONP was made by an improvement of the Hummer's method based on graphene exfoliated from graphite using high-intensity ultrasonication, resulting in two dimensional sheets with a lateral dimension in the range 200 nm to 3 mu m and thickness of 0.9 nm. Confocal Raman spectroscopy combined with multivariate analysis was used to study the interaction of GONP and living cells. It is shown that overlapping Raman bands due to GONPs and biomolecules in the cells can clearly be separated with this approach. Orthogonal partial least squares discriminant analysis was used to compare spectral data collected from cells exposed to GONP with spectral data collected from non-exposed control cells, and spectral data from cells exposed to a surfactant known to induce apoptosis. Our analyses show that GONP readily attach to the cells, forming sheets which cover a large fraction of the cell surfaces, and induce small chemical changes. In particular, chemical modifications of proteins and lipids in lung epithelial cells are inferred. GONPs do not, however, decrease cell viability. In contrast, enhanced cell proliferation is observed. Our results shed new light on the interactions of GO, and in contrast to some previous reports, suggest that GO is not toxic. The hyperspectral Raman spectroscopy analysis employed here should be applicable for other fields in nanomedicine as a label-free non-perturbing analytical method.
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| 2. |
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| 3. |
- Ahlinder, Linnea, et al.
(författare)
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Large Uptake of Titania and Iron Oxide Nanoparticles in the Nucleus of Lung Epithelial Cells as Measured by Raman Imaging and Multivariate Classification
- 2013
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Ingår i: Biophysical Journal. - : Elsevier BV. - 0006-3495 .- 1542-0086. ; 105:2, s. 310-319
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Tidskriftsartikel (refereegranskat)abstract
- It is a challenging task to characterize the biodistribution of nanoparticles in cells and tissue on a subcellular level. Conventional methods to study the interaction of nanoparticles with living cells rely on labeling techniques that either selectively stain the particles or selectively tag them with tracer molecules. In this work, Raman imaging, a label-free technique that requires no extensive sample preparation, was combined with multivariate classification to quantify the spatial distribution of oxide nanoparticles inside living lung epithelial cells (A549). Cells were exposed to TiO2 (titania) and/or alpha-FeO(OH) (goethite) nanoparticles at various incubation times (4 or 48 h). Using multivariate classification of hyperspectral Raman data with partial least-squares discriminant analysis, we show that a surprisingly large fraction of spectra, classified as belonging to the cell nucleus, show Raman bands associated with nanoparticles. Up to 40% of spectra from the cell nucleus show Raman bands associated with nanoparticles. Complementary transmission electron microscopy data for thin cell sections qualitatively support the conclusions.
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| 4. |
- Ahlinder, Linnea, et al.
(författare)
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Noise Removal with Maintained Spatial Resolution in Raman Images of Cells Exposed to Submicron Polystyrene Particles
- 2016
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Ingår i: Nanomaterials. - : MDPI AG. - 2079-4991. ; 6:5
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Tidskriftsartikel (refereegranskat)abstract
- The biodistribution of 300 nm polystyrene particles in A549 lung epithelial cells has been studied with confocal Raman spectroscopy. This is a label-free method in which particles and cells can be imaged without using dyes or fluorescent labels. The main drawback with Raman imaging is the comparatively low spatial resolution, which is aggravated in heterogeneous systems such as biological samples, which in addition often require long measurement times because of their weak Raman signal. Long measurement times may however induce laser-induced damage. In this study we use a super-resolution algorithm with Tikhonov regularization, intended to improve the image quality without demanding an increased number of collected pixels. Images of cells exposed to polystyrene particles have been acquired with two different step lengths, i.e., the distance between pixels, and compared to each other and to corresponding images treated with the super-resolution algorithm. It is shown that the resolution after application of super-resolution algorithms is not significantly improved compared to the theoretical limit for optical microscopy. However, to reduce noise and artefacts in the hyperspectral Raman images while maintaining the spatial resolution, we show that it is advantageous to use short mapping step lengths and super-resolution algorithms with appropriate regularization. The proposed methodology should be generally applicable for Raman imaging of biological samples and other photo-sensitive samples.
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| 5. |
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| 6. |
- Ahlinder, Linnea, 1987-
(författare)
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Raman Spectroscopy and Hyperspectral Analysis of Living Cells Exposed to Nanoparticles
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Nanoparticles, i.e. particles with at least one dimension smaller than 100 nm, are present in large quantities in ambient air and can also be found in an increasing amount of consumer products. It is known that many nanomaterials have physicochemical properties that differ from physicochemical properties of the same material in bulk size. It is therefore important to characterize nanoparticles and to evaluate their toxicity. To understand mechanisms behind nanotoxicity, it is important to study the uptake of nanoparticles, and how they are accumulated. For these purposes model studies of cellular uptake are useful. In this thesis metal oxide and carbon-based nanoparticles have been studied in living cells using Raman spectroscopy. Raman spectroscopy is a method that facilitates a non-destructive analysis without using any fluorescent labels, or any other specific sample preparation. It is possible to collect Raman images, i.e. images where each pixel corresponds to a Raman spectrum, and to use the spectral information to detect nanoparticles, and to identify organelles in cells. In this thesis the question whether or not nanoparticles can enter the cell nucleus of lung epithelial cells has been addressed using hyperspectral analysis. It is shown that titanium dioxide nanoparticles and iron oxide nanoparticles are taken up by cells, and also in the cell nucleus. In contrast, graphene oxide nanoparticles are mainly found attached on the outside of the cell membrane and very few nanoparticles are found in the cell, and none have been detected in the nucleus. It is concluded that graphene oxide nanoparticles are not cytotoxic. However, a comparison of Raman spectra of biomolecules in cells exposed to graphene oxide, unexposed cells and apoptotic cells, shows that the graphene oxide nanoparticles do affect lipid and protein structures. In this thesis, several multivariate data analysis methods have been used to analyze Raman spectra and Raman images. In addition, super-resolution algorithms, which originally have been developed to improve the resolution in photographic images, were optimized and applied to Raman images of cells exposed to submicron polystyrene particles in living cells.
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| 7. |
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| 8. |
- Andersson, Per Ola, et al.
(författare)
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Polymorph and size dependent uptake and toxicity of TiO2 nanoparticles in living lung epithelial cells
- 2011
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Ingår i: Small. - : Wiley. - 1613-6810 .- 1613-6829. ; 7:4, s. 514-523
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Tidskriftsartikel (refereegranskat)abstract
- The cellular uptake and distribution of five types of well-characterized anatase and rutile TiO(2) nanoparticles (NPs) in A549 lung epithelial cells is reported. Static light scattering (SLS), in-vitro Raman microspectroscopy (mu-Raman) and transmission electron spectroscopy (TEM) reveal an intimate correlation between the intrinsic physicochemical properties of the NPs, particle agglomeration, and cellular NP uptake. It is shown that mu-Raman facilitates chemical-, polymorph-, and size-specific discrimination of endosomal-particle cell uptake and the retention of particles in the vicinity of organelles, including the cell nucleus, which quantitatively correlates with TEM and SLS data. Depth-profiling mu-Raman coupled with hyperspectral data analysis confirms the location of the NPs in the cells and shows that the NPs induce modifications of the biological matrix. NP uptake is found to be kinetically activated and strongly dependent on the hard agglomeration size-not the primary particle size-which quantitatively agrees with the measured intracellular oxidative stress. Pro-inflammatory responses are also found to be sensitive to primary particle size.
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| 9. |
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| 10. |
- Höjer Holmgren, Karin, et al.
(författare)
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Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening
- 2021
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Ingår i: Analytical Chemistry. - : American Chemical Society. - 0003-2700 .- 1520-6882. ; 93:11, s. 4850-4858
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Tidskriftsartikel (refereegranskat)abstract
- Route determination of sulfur mustard was accomplished through comprehensive nontargeted screening of chemical attribution signatures. Sulfur mustard samples prepared via 11 different synthetic routes were analyzed using gas chromatography/high-resolution mass spectrometry. A large number of compounds were detected, and multivariate data analysis of the mass spectrometric results enabled the discovery of route-specific signature profiles. The performance of two supervised machine learning algorithms for retrospective synthetic route attribution, orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF), were compared using external test sets. Complete classification accuracy was achieved for test set samples (2/2 and 9/9) by using classification models to resolve the one-step routes starting from ethylene and the thiodiglycol chlorination methods used in the two-step routes. Retrospective determination of initial thiodiglycol synthesis methods in sulfur mustard samples, following chlorination, was more difficult. Nevertheless, the large number of markers detected using the nontargeted methodology enabled correct assignment of 5/9 test set samples using OPLS-DA and 8/9 using RF. RF was also used to construct an 11-class model with a total classification accuracy of 10/11. The developed methods were further evaluated by classifying sulfur mustard spiked into soil and textile matrix samples. Due to matrix effects and the low spiking level (0.05% w/w), route determination was more challenging in these cases. Nevertheless, acceptable classification performance was achieved during external test set validation: chlorination methods were correctly classified for 12/18 and 11/15 in spiked soil and textile samples, respectively.
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