| 1. |
- Eliasson, Charlotte, 1973, et al.
(författare)
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Multivariate methodology for surface enhanced Raman chemical imaging of lymphocytes
- 2006
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 81:1, s. 13-20
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Tidskriftsartikel (refereegranskat)abstract
- Surface enhanced Raman spectroscopy (SERS) was used to study the uptake of rhodamine 6G in human lymphocytes. In total four Raman images of lymphocytes were used. The aim was to find a multivariate methodology capable of separating spectra with chemical information from those that mainly contained the surface enhanced background, in order to create chemical images. The standard PCA procedure was compared with PCA of standard normal variate (SNV) corrected spectra, spectra baseline corrected in the wavelet domain, and variable trimming before PCA, to isolate unique spectra. It was not straightforward to perform a standard PCA for overview, since the small background variation in many variables dominated over the Raman band variation that only occur in few variables. It was shown that wavelet filtering could remove background variations and that variable trimming followed by PCA modelling left the unique Raman spectra as outliers, which facilitated interpretation of the Raman score images.
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| 2. |
- Eliasson, Charlotte, 1973, et al.
(författare)
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Surface-enhanced Raman scattering imaging of single living lymphocytes with multivariate evaluation
- 2005
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Ingår i: Spectrochimica Acta Part A-Molecular and Biomolecular Spectroscopy. - : Elsevier BV. - 1386-1425. ; 61:4, s. 755-760
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Tidskriftsartikel (refereegranskat)abstract
- This paper is aimed to show the possibility to determine individual organic compounds introduced into single living cells with surface-enhanced Raman spectroscopy (SERS). Surface enhancement was achieved with gold colloids that were allowed to diffuse into lymphocytes. An introduced analyte, rhodamine 6G, could be imaged together with for example nucleotides and amino acids of the cell. Multivariate evaluation of surface-enhanced Raman images proved to be a powerful tool for the separation of spectral information of various intracellular components. The principal component analysis (PCA) enabled identification of spectra containing different chemical information and separation of the spectral contribution of rhodamine 6G from the complex cellular matrix.
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| 3. |
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| 4. |
- Engelbrektsson, Johan, 1976
(författare)
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Multivariate Measurements and Chemical Imaging of Organic Compounds
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Chemical imaging is an emerging analytical technique, based on the interplay between, most often, spectroscopic measurements and advanced evaluation methodology. With this we can study the distribution of chemical compounds in different compartments, such as individual cells and pharmaceutical tablets. Also, chemical imaging allows for studies of time dependent processes, such as uptake of drugs or dissolution.Surface enhanced Raman spectroscopy (SERS) was used to acquire data in complex matrices (lymphocytes), the spectra obtained varied significantly in background and intensity. Near-infrared spectroscopy (NIR) and atomic force microscopy (AFM) were used to characterise the texture of pharmaceutical tablets. Also, the dissolution of a tablet was monitored over time.The focus of this thesis is the data analysis, more specifically the multivariate handling of large data sets, comparisons of images, structure identification and textures. Three application areas have been more thoroughly investigated; normalisation of spectral data to obtain quantitative results during difficult statistical sampling conditions; extraction of relevant spectral and chemical information from complex matrices and measurements in noisy or high-background environments; detection of small changes in spatial features. A normalisation method for highly variable SERS measurements, based on an internal standard self assembled monolayer was developed and studied for use with multivariate regression. It was shown that the highly variable background in SERS imaging could be reduced with wavelet filtering and modelling of the background to extract chemically interesting spectra as outliers. Together with the concept of an internal standard applied as a self assembled monolayer, this points in the direction of a solution for quantitative SERS.The use of wavelet transformation in combination with principal components analysis, were shown to be successful in characterisation of spatial features without prior segmentation. Continuous wavelet transform (CWT) gave more consistent results in texture analysis than discrete wavelet transform (DWT), and dual-tree complex wavelet transform (DT-CWT).
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| 5. |
- Strömberg, Niklas, 1974, et al.
(författare)
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A high throughput optical system for imaging optodes
- 2009
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Ingår i: Sensors and Actuators B-Chemical. - : Elsevier BV. - 0925-4005. ; 140:2, s. 418-425
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this study was to design a high throughput macro imaging system for intensity ratio based optodes, which facilitate both extensive replication and large number of samples to fulfill the statistical requirements for understanding natural processes occurring over extended time. The suggested system accommodates up to 24 sample cells with a field of view of 35 mm or 12 sample cells and 12 calibration cells for a seamless replacement of the optodes to follow processes that last longer than the optode lifetime. The individual components such as sample turrets, LED light sources, filters and lens designs are tested and discussed in detail. Positioning and alignment of an adjacent cell is completed within 6 s with an accuracy of five pixels. The acceleration profile for the sample turret is software controlled, which makes it possible to study e.g. sediments with overlaying water without effects from re-suspension. Calibration is performed by simultaneous filling of all the flow-cells with calibration solution and thereafter a sample run is executed. Thus, the effort required for calibration is the same regardless of the number of sample cells used. The system is automated and controlled through Matlab (Mathworks Inc), which is also is used for post processing of the images. The system was designed for an environmental application where more than 2000 individual images were collected and calibrated to yield 360 sample images.
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| 6. |
- Svensson, Olof, et al.
(författare)
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An evaluation of 2D-wavelet filters for estimation of differences in textures of pharmaceutical tablets
- 2006
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 84:1-2, s. 3-8
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Tidskriftsartikel (refereegranskat)abstract
- In chemical imaging spectra are acquired over a surface with one spectrum for each pixel of the image. The obtained spectra usually carry a mixture of chemical and physical information. One may view the properties that vary over the image, the mean spectral magnitude from separate wavelength intervals, or better, PCA scores may be shown as images.In this way a multitude of images are compressed to a few images that in the PCA case are representative for the main variation in the sample images. These images may be viewed manually and deductions as to e.g. differences in homogeneity can be made. At an increased rate of samples, the observer will have difficulties coping with the repetitive work and different observers will most likely have slightly different interpretations. In order to automate the process of estimation of e.g. homogeneity and particle density, image filters can be used to calculate a small set of texture descriptors for each image. Calculations based on the 2D versions of the discrete wavelet transform (DWT) using Daubechies 14 and the dual tree complex wavelet transform (DT-CWT) using near-symmetric 13, 19 tap filters in combination with q-shift 14, 14 tap filters were evaluated for this purpose.The aim with this work is to evaluate texture descriptors based on a combination of 2D-wavelet filters and energy, i.e. l(1)-norm, calculations for each wavelet scale. These descriptors are then used as observations for overview in e.g. PCA. In this way the texture differences can be ranked by ordinary use of PCA or PLS.This method is tested on multivariate near infrared images of pharmaceutical tablets. Score images are selected to represent variations of the aggregate density and sizes in the compressed tablets. Images are shifted and rotated to compare shift and rotational independence of the texture descriptors.
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| 7. |
- Zielinski, Oliver, et al.
(författare)
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Detecting marine hazardous substances and organisms: sensors for pollutants, toxins, and pathogens
- 2009
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Ingår i: Ocean Science. - 1812-0784. ; 5:3, s. 329-349
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Forskningsöversikt (refereegranskat)abstract
- Marine environments are influenced by a wide diversity of anthropogenic and natural substances and organisms that may have adverse effects on human health and ecosystems. Real-time measurements of pollutants, toxins, and pathogens across a range of spatial scales are required to adequately monitor these hazards, manage the consequences, and to understand the processes governing their magnitude and distribution. Significant technological advancements have been made in recent years for the detection and analysis of such marine hazards. In particular, sensors deployed on a variety of mobile and fixed-point observing platforms provide a valuable means to assess hazards. In this review, we present state-of-the-art of sensor technology for the detection of harmful substances and organisms in the ocean. Sensors are classified by their adaptability to various platforms, addressing large, intermediate, or small areal scales. Current gaps and future demands are identified with an indication of the urgent need for new sensors to detect marine hazards at all scales in autonomous real-time mode. Progress in sensor technology is expected to depend on the development of small-scale sensor technologies with a high sensitivity and specificity towards target analytes or organisms. However, deployable systems must comply with platform requirements as these interconnect the three areal scales. Future developments will include the integration of existing methods into complex and operational sensing systems for a comprehensive strategy for long-term monitoring. The combination of sensor techniques on all scales will remain crucial for the demand of large spatial and temporal coverage.
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