Application des techniques de Séparation de Sources a des spectres Raman issus de microorganismes

Nous présentons dans ce papier une application biomédicale des techniques de Séparation Aveugle de Sources (SAS) à la séparation et à l'identification de Spectres Raman (SR) issus de micro-organismes. Dans l'étude de micro-organismes par spectroscopie Raman, la principale difficulté est de dissocier le SR des bactéries de celui du milieu de culture, les bactéries ayant besoin d'un milieu de culture pour être étudiées. Les méthodes classiques effectuent une mesure préliminaire du SR du milieu de culture et soustraient cette mesure au SR des bactéries sur leur milieu de culture. L'avantage majeur des techniques de SAS est l'extraction du SR des bactéries sans mesure préalable du milieu de culture, ce qui rend le SR des bactéries indépendant des variations du milieu de culture

Diagnosis Of The Chronic Lymphocytic Leukemia (CLL) Using A Raman-Based Scanner Optimized For Blood Smear Analysis (M3s Project)

Introduction/ Background In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. Aims The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. Methods Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labeling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a microscope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted to immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). Results Currently, a total of 60 patients (CLL and healthy) were included in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (Random Forest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.

A study of Docetaxel-induced effects in MCF-7 cells by means of Raman microspectroscopy

Chemotherapies feature a low success rate of about 25%, and therefore, the choice of the most effective cytostatic drug for the individual patient and monitoring the efficiency of an ongoing chemotherapy are important steps towards personalized therapy. Thereby, an objective method able to differentiate between treated and untreated cancer cells would be essential. In this study, we provide molecular insights into Docetaxel-induced effects in MCF-7 cells, as a model system for adenocarcinoma, by means of Raman microspectroscopy combined with powerful chemometric methods. The analysis of the Raman data is divided into two steps. In the first part, the morphology of cell organelles, e.g. the cell nucleus has been visualized by analysing the Raman spectra with k-means cluster analysis and artificial neural networks and compared to the histopathologic gold standard method hematoxylin and eosin staining. This comparison showed that Raman microscopy is capable of displaying the cell morphology; however, this is in contrast to hematoxylin and eosin staining label free and can therefore be applied potentially in vivo. Because Docetaxel is a drug acting within the cell nucleus, Raman spectra originating from the cell nucleus region were further investigated in a next step. Thereby we were able to differentiate treated from untreated MCF-7 cells and to quantify the cell–drug response by utilizing linear discriminant analysis models

Industrial Applications of the Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy is now a well-established phenomenon, which has been thoroughly characterized in a variety of interfacial and colloidal environments. Although some quantitative aspects of the underlying enhancement mechanisms apparently remain unresolved, attention is now shifting towards application of SERS to explore phenomena of chemical, physical, biological and industrial significance. The goal of this review is to appreciate the industrial value of innovative SERS technique on the basis of our experience in development of new SERS-active substrates and in their biomedical and biotechnological applications. Examples of diverse SERS analytical applications as well as some very recent facilities, as SERS microprobe analysis, SERS fiber optics probes, FT-SERS spectroscopy, SERS detection for high-performance liquid chromatography, etc. , are also discussed

Investigation by confocal raman microspectroscopy of the molecular factors responsible for grain cohesion in the Triticum aestivum bread wheat. Role of the cell walls in the starchy endosperm

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