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.

Characterization of Type I and IV Collagens by Raman Microspectroscopy: Identification of Spectral Markers of the Dermo-Epidermal Junction

Abstract. Type I and IV collagens are important constituents of the skin. Type I collagen is found in all dermal layers in high proportion, while type IV collagen is localized in the basement membrane of the dermo-epidermal junction (DEJ). These proteins are strongly altered during aging or cancer progression. Although they possess amino acid compositions which, are close, they present also important structural differences inducing specific physicochemical properties. Raman spectroscopy is based on a nondestructive interaction of the light with the matter. This technique permits to probe the intrinsic molecular composition of the samples without staining or particular preparation. The aim of our research is to study the correlation between the molecular conformations of type I and IV collagens and their Raman features. We showed that signals specific of each protein can be revealed and that they translate structural differences between the two collagens. From this collagens spectral characterization, the analysis of skin sections also permitted to identify spectral markers of dermis, epidermis, and epidermis/dermis interface. These preliminary results represent basic data for further studies, particularly to probe skin molecular alterations induced by chronologic aging

Application Of Raman Microscopy For The Diagnosis Of The Chronic Lymphocytic Leukemia (Cll) : PS01.01 | ePoster Session I

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 labelling 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 micro- scope 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 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 in- cluded in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (RandomForest) 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

Involvement of corepressor complex subunit GPS2 in transcriptional pathways governing human bile acid biosynthesis

Coordinated regulation of bile acid biosynthesis, the predominant pathway for hepatic cholesterol catabolism, is mediated by few key nuclear receptors including the orphan receptors liver receptor homolog 1 (LRH-1), hepatocyte nuclear factor 4α (HNF4α), small heterodimer partner (SHP), and the bile acid receptor FXR (farnesoid X receptor). Activation of FXR initiates a feedback regulatory loop via induction of SHP, which suppresses LRH-1- and HNF4α-dependent expression of cholesterol 7α hydroxylase (CYP7A1) and sterol 12α hydroxylase (CYP8B1), the two major pathway enzymes. Here we dissect the transcriptional network governing bile acid biosynthesis in human liver by identifying GPS2, a stoichiometric subunit of a conserved corepressor complex, as a differential coregulator of CYP7A1 and CYP8B1 expression. Direct interactions of GPS2 with SHP, LRH-1, HNF4α, and FXR indicate alternative coregulator recruitment strategies to cause differential transcriptional outcomes. In addition, species-specific differences in the regulation of bile acid biosynthesis were uncovered by identifying human CYP8B1 as a direct FXR target gene, which has implications for therapeutic approaches in bile acid-related human disorders

Androgen receptor CAG polymorphism and the risk of benign prostatic hyperplasia in a Brazilian population

Benign prostatic hyperplasia (BPH) is a very frequent age-related proliferative abnormality in men. Polymorphic CAG repeat in the androgen receptor (AR) can alter transactivation of androgen-responsive genes and potentially influence BPH risk. We investigated the association between CAG repeat length and risk of BPH in a case-control study of a Brazilian population. We evaluated 214 patients; 126 with BPH and 88 healthy controls. DNA was extracted from peripheral leucocytes and the AR gene was analyzed using fragment analysis. Hazard ratio (HR) and 95% confidence interval were estimated using logistic regression models. Mean CAG length was not different between patients with BPH and controls. The CAG repeat length was examined as a categorical variable (CAG < 21 vs. CAG > 21 and CAG < 22 vs. CAG > 22) and did not differ between the control vs. the BPH group. We found no evidence for an association between AR CAG repeat length in BPH risk in a population-based sample of Brazilians