by Keyword: MCR-ALS
Mas, S., Torro, A., Bec, N., Fernández, L., Erschov, G., Gongora, C., Larroque, C., Martineau, P., de Juan, A., Marco, S., (2019). Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues Analytica Chimica Acta 1074, 69-79
The characterization of cancer tissues by matrix-assisted laser desorption ionization-mass spectrometry images (MALDI-MSI) is of great interest because of the power of MALDI-MS to understand the composition of biological samples and the imaging side that allows for setting spatial boundaries among tissues of different nature based on their compositional differences. In tissue-based cancer research, information on the spatial location of necrotic/tumoral cell populations can be approximately known from grayscale images of the scanned tissue slices. This study proposes as a major novelty the introduction of this physiologically-based information to help in the performance of unmixing methods, oriented to extract the MS signatures and distribution maps of the different tissues present in biological samples. Specifically, the information gathered from grayscale images will be used as a local rank constraint in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) for the analysis of MALDI-MSI of cancer tissues. The use of this constraint, setting absence of certain kind of tissues only in clear zones of the image, will help to improve the performance of MCR-ALS and to provide a more reliable definition of the chemical MS fingerprint and location of the tissues of interest. The general strategy to address the analysis of MALDI-MSI of cancer tissues will involve the study of the MCR-ALS results and the posterior use of MCR-ALS scores as dimensionality reduction for image segmentation based on K-means clustering. The resolution method will provide the MS signatures and their distribution maps for each tissue in the sample. Then, the resolved distribution maps for each biological component (MCR scores) will be submitted as initial information to K-means clustering for image segmentation to obtain information on the boundaries of the different tissular regions in the samples studied. MCR-ALS prior to K-means not only provides the desired dimensionality reduction, but additionally resolved non-biological signal contributions are not used and the weight given to the different biological components in the segmentation process can be modulated by suitable preprocessing methods.
JTD Keywords: MCR-ALS, K-means, Local rank constraints, MALDI-MSI, Grayscale images
Montoliu, I., Tauler, R., Padilla, M., Pardo, A., Marco, S., (2010). Multivariate curve resolution applied to temperature modulated metal oxide gas sensors Sensors and Actuators B: Chemical 145, (1), 464-473
Metal oxide (MOX) gas sensors have been widely used for years. Temperature modulation of gas sensors is as an alternative to increase their sensitivity and selectivity to different gas species. In order to enhance the extraction of useful information from this kind of signals, data processing techniques are needed. In this work, the use of self-modelling curve resolution techniques, in particular multivariate curve resolution-alternating least squares (MCR-ALS), is presented for the analysis of these signals. First, the performance of MCR in a synthetic dataset generated from temperature-modulated gas sensor response models has been evaluated, showing good results both in the resolution of gas mixtures and in the determination of concentration/sensitivity profiles. Secondly, experimental confirmation of previously obtained conclusions is attempted using temperature-modulated MOX sensors together with MCR-ALS for the analysis of carbon monoxide (CO) and methane (CH4) gas mixtures in dry air. Results allow confirming the possibility of using the proposed approach as a quantitative technique for gas mixtures analysis, and also reveal some limitations.
JTD Keywords: Temperature modulation, Multivariate curve resolution, MCR-ALS, Metal oxide sensors
Montoliu, I., Pomareda, V., Kalms, A., Pardo, A., Gobel, J., Kessler, M., Muller, G., Marco, S., (2009). Resolution of ion mobility spectra for the detection of hazardous substances in real sampling conditions Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 
13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 576-578
This work presents the possibilities offered by a blind source separation method such Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) in the analysis of Ion Mobility Spectra (IMS). Two security applications are analyzed in this context: the detection of TNT both in synthetic and real samples. Results obtained show the possibilities offered by the direct analysis of the drift time spectra when an appropriate resolution method is used.
JTD Keywords: Ion Mobility Spectrometry, Multivariate Curve Resolution, Security, LIMS, MCR-ALS
