Desenvolvimento de um algoritmo para identificação e correção de spikes em espectroscopia Raman de imagem

Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.

Desenvolvimento de um algoritmo para identificação e correção de spikes em espectroscopia Raman de imagem

Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.

Surface-enhanced Raman scattering and micro-Raman imaging of Langmuir-Blodgett films of rhodium phthalocyanine

Rhodium phthalocyanine (RhPc) was synthesized and ultra thin Langmuir-Blodgett (LB) films of RhPc were successfully fabricated. The LB film characterization was carried out using both UV-vis absorption spectra and Raman scattering. The Raman spectroscopy was carried out using 633 and 780 nm laser lines. LB films were deposited onto Ag nanoparticles to achieve the surface-enhanced pre-resonance Raman scattering (pre-SERRS) and surface-enhanced Raman scattering (SERS) for both laser lines, respectively, which allowed the characterization of the RhPc ultra thin films. The morphology of the LB RhPc neat film is extracted from micro-Raman imaging. (C) 2003 Elsevier B.V. All rights reserved.

Properties of seawater and particulate matter from a WETLabs ALFA hyperspectral laser spectrofluorometer mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements made with an Aquatic Laser Fluorescence Analyzer (ALFA) (Chekalyuk et al., 2014), connected in-line to the TARA flow through system during 2013. The ALFA instrument provides dual-wavelength excitation (405 and 514 nm) of laser-stimulated emission (LSE) for spectral and temporal analysis. It offers in vivo fluorescence assessments of phytoplankton pigments, biomass, photosynthetic yield (Fv/Fm), phycobiliprotein (PBP)-containing phytoplankton groups, and chromophoric dissolved organic matter (CDOM) (Chekalyuk and Hafez, 2008; 2013A). Spectral deconvolution (SDC) is used to assess the overlapped spectral bands of aquatic fluorescence constituents and water Raman scattering (R). The Fv/Fm measurements are spectrally corrected for non-chlorophyll fluorescence background produced by CDOM and other constituents (Chekalyuk and Hafez, 2008). The sensor was cleaned weakly following the manufacturer recommended protocol.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour.

In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

Inside standard and hyperspectral low-dose CT variational imaging: parameter identification and material decomposition

The main contribution of this thesis is the proposal of novel strategies for the selection of parameters arising in variational models employed for the solution of inverse problems with data corrupted by Poisson noise. In light of the importance of using a significantly small dose of X-rays in Computed Tomography (CT), and its need of using advanced techniques to reconstruct the objects due to the high level of noise in the data, we will focus on parameter selection principles especially for low photon-counts, i.e. low dose Computed Tomography. For completeness, since such strategies can be adopted for various scenarios where the noise in the data typically follows a Poisson distribution, we will show their performance for other applications such as photography, astronomical and microscopy imaging. More specifically, in the first part of the thesis we will focus on low dose CT data corrupted only by Poisson noise by extending automatic selection strategies designed for Gaussian noise and improving the few existing ones for Poisson. The new approaches will show to outperform the state-of-the-art competitors especially in the low-counting regime. Moreover, we will propose to extend the best performing strategy to the hard task of multi-parameter selection showing promising results. Finally, in the last part of the thesis, we will introduce the problem of material decomposition for hyperspectral CT, which data encodes information of how different materials in the target attenuate X-rays in different ways according to the specific energy. We will conduct a preliminary comparative study to obtain accurate material decomposition starting from few noisy projection data.

Quorum sensing detected by atomic force microscopy imaging of corrals surrounding multicellular arrangement of bacteria

Connectivity of the glycocalyx covering of small communities of Acidithiobacillus ferrooxidans bacteria deposited on hydrophilic mica plates was imaged by atomic force microscopy. When part of the coverage was removed by water rinsing, an insoluble structure formed by corrals surrounding each individual bacterium was observed. A collective ring structure with clustered bacteria (>= 3) was observed, which indicates that the bacteria perceived the neighborhood in order to grow a protective structure that results in smaller production of exopolysaccharides material. The most surprising aspect of these collective corral structures was that they occur at a low bacterial cell density. The deposited layers were also analyzed by confocal Raman microscopy and shown to contain polysaccharides, protein, and glucoronic acid.

C-13-NMR, H-1-NMR, and FT-Raman study of radiation-induced modifications in radiation dosimetry polymer gels

H-1- and C-13-NMR spectroscopy and FT-Raman spectroscopy are used to investigate the properties of a polymer gel dosimeter post-irradiation. The polymer gel (PACT) is composed of acrylamide, N,N'-methylene-bisacrylamide, gelatin, and water. The formation of a polyacrylamide network within the gelatin matrix follows a dose dependence nonlinearly correlated to the disappearance of the double bonds from the dissolved monomers within the absorbed dose range of 0-50 Gy. The signal from the gelatin remains constant with irradiation. We show that the NMR spin-spin relaxation times (T-2) of PAGs irradiated to up to 50 Gy measured in a NMR spectrometer and a clinical magnetic resonance imaging scanner can be modeled using the spectroscopic intensity of the growing polymer network. More specifically, we show that the nonlinear T-2 dependence against dose can be understood in terms of the fraction of protons in three different proton pools. (C) 2000 John Wiley & Sons, Inc.

Magnetization transfer imaging for polymer gel dosimetry

Off-resonance RF pre-saturation was used to obtain contrast in MRI images of polymer gel dosimeters irradiated to doses up to 50 Gy. Two different polymer gel dosimeters composed of 2-hydroxyethyl-acryl ate or methacrylic acid monomers mixed with N, N'-methylene-bisacrylamide (BIS), dispersed in an aqueous gelatin matrix were evaluated. Radiation-induced polymerization of the co-monomers generates a fast-relaxing insoluble polymer. Saturation of the polymer using off-resonance Gaussian RF pulses prior to a spin-echo read-out with a short echo time leads to contrast that is dependent on the absorbed dose. This contrast is attributed to magnetization transfer (MT) between free water and the polymer, and direct saturation of water was found to be negligible under the prevailing experimental conditions. The usefulness of MT imaging was assessed by computing the dose resolution obtained with this technique. We found a low value of dose resolution over a wide range of doses could be obtained with a single experiment. This is an advantage over multiple spin echo (MSE) experiments using a single echo spacing where an optimal dose resolution is achieved over only very limited ranges of doses. The results suggest MT imaging protocols may be developed into a useful tool for polymer gel dosimetry.

Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery

This Letter evaluates several narrow-band indices from EO-1 Hyperion imagery in discriminating sugarcane areas affected by 'orange rust' ( Puccinia kuehnii ) disease. Forty spectral vegetation indices (SVIs), focusing on bands related to leaf pigments, leaf internal structure, and leaf water content, were generated from an image acquired over Mackay, Queensland, Australia. Discriminant function analysis was used to select an optimum set of indices based on their correlations with the discriminant function. The predictive ability of each index was also assessed based on the accuracy of classification. Results demonstrated that Hyperion imagery can be used to detect orange rust disease in sugarcane crops. While some indices that only used visible near-infrared (VNIR) bands (e.g. SIPI and R800/R680) offer separability, the combination of VNIR bands with the moisture-sensitive band (1660 nm) yielded increased separability of rust-affected areas. The newly formulated 'Disease-Water Stress Indices' (DWSI-1=R800/R1660; DSWI-2=R1660/R550; DWSI-5=(R800+R550)/(R1660+R680)) produced the largest correlations, indicating their superior ability to discriminate sugarcane areas affected by orange rust disease.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy.

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Détection de protéines par diffusion Raman exaltée par effet de pointe (TERS)

La concentration locale des messagers chimiques sécrétés par les cellules peut être mesurée afin de mieux comprendre les mécanismes moléculaires liés à diverses maladies, dont les métastases du cancer. De nouvelles techniques analytiques sont requises pour effectuer ces mesures locales de marqueurs biologiques à proximité des cellules. Ce mémoire présentera le développement d’une nouvelle technique basée sur la réponse plasmonique sur des leviers AFM, permettant d’étudier les réactions chimiques et biologiques à la surface des leviers grâce au phénomène de résonance des plasmons de surface (SPR), ainsi qu’à la diffusion Raman exaltée par effet de pointe (TERS). En effet, il est possible de localiser l’amplification du signal Raman à la pointe d’un levier AFM, tout comme le principe de la diffusion Raman exaltée par effet de surface (SERS) basée sur la diffusion de la lumière par des nanoparticules métalliques, et permettant une large amplification du signal Raman. La surface du levier est recouverte d’une nano-couche métallique d’or, suivi par des réactions biologiques pour l’immobilisation d’un récepteur moléculaire, créant ainsi un biocapteur sur la pointe du levier. Une détection secondaire utilisant des nanoparticules d’or conjuguées à un anticorps secondaire permet également une amplification du signal SPR et Raman lors de la détection d’antigène. Ce mémoire démontrera le développement et la validation de la détection de l’immunoglobuline G (IgG) sur la pointe du levier AFM.Dans des projets futurs, cette nouvelle technique d’instrumentation et d’imagerie sera optimisée grâce à la création d’un micro-détecteur protéique généralement adapté pour l’étude de la communication cellulaire. En intégrant le signal SPR à la microscopie AFM, il sera alors possible de développer des biocapteurs SPR couplés à une sonde à balayage, ce qui permettra d’effectuer une analyse topographique et de l’environnement chimique d’échantillons cellulaires en temps réel, pour la mesure des messagers moléculaires sécrétés dans la matrice extracellulaire, lors de la communication cellulaire.