A novel gene expression signature in peripheral blood mononuclear cells for early detection of colorectal cancer.

BACKGROUND: Early detection and treatment of colorectal adenomatous polyps (AP) and colorectal cancer (CRC) is associated with decreased mortality for CRC. However, accurate, non-invasive and compliant tests to screen for AP and early stages of CRC are not yet available. A blood-based screening test is highly attractive due to limited invasiveness and high acceptance rate among patients. AIM: To demonstrate whether gene expression signatures in the peripheral blood mononuclear cells (PBMC) were able to detect the presence of AP and early stages CRC. METHODS: A total of 85 PBMC samples derived from colonoscopy-verified subjects without lesion (controls) (n = 41), with AP (n = 21) or with CRC (n = 23) were used as training sets. A 42-gene panel for CRC and AP discrimination, including genes identified by Digital Gene Expression-tag profiling of PBMC, and genes previously characterised and reported in the literature, was validated on the training set by qPCR. Logistic regression analysis followed by bootstrap validation determined CRC- and AP-specific classifiers, which discriminate patients with CRC and AP from controls. RESULTS: The CRC and AP classifiers were able to detect CRC with a sensitivity of 78% and AP with a sensitivity of 46% respectively. Both classifiers had a specificity of 92% with very low false-positive detection when applied on subjects with inflammatory bowel disease (n = 23) or tumours other than CRC (n = 14). CONCLUSION: This pilot study demonstrates the potential of developing a minimally invasive, accurate test to screen patients at average risk for colorectal cancer, based on gene expression analysis of peripheral blood mononuclear cells obtained from a simple blood sample.

The Discrimination of Colored Acrylic, Cotton, and Wool Textile Fibers Using Micro-Raman Spectroscopy. Part 1 : In Situ Detection and Characterization of Dyes

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

Perceived behavioral changes in early multiple sclerosis.

Acquired behavioral changes have essentially been described in advanced multiple sclerosis (MS). The present study was designed to determine whether behavioral modifications specifically related to the MS pathological process could be identified in the initial phase of the disease, as compared to control patients with chronic, relapsing and progressive inflammatory disorders not involving the central nervous system (CNS). Eighty-eight early MS patients (Expanded Disability Status Scale score <or= 2.5) and 48 controls were tested. Perceived changes by informants in behavioral control, goal-directed behavior, decision making, emotional expression, insight and interpersonal relationships were assessed using the Iowa Scale of Personality Change (ISPC). Executive behavioral disturbances were screened using the Dysexecutive Questionnaire (DEX). The mean change between the premorbid and postmorbid ISPC ratings was similar in the MS [12.2 (SD 15.6)] and in the control [11.5 (SD 15.1)] group. The perceived behavioral changes (PBCs) most frequently reported in both groups were lack of stamina, lability/moodiness, anxiety, vulnerability to stress and irritability. Pathological scores in the DEX were also similar in both groups. Correlations between PBCs and DEX scores were different in MS and control groups. MS patients with cognitive impairment had a marginally higher number of PBCs than control patients (p=0.056) and a significantly higher DEXp score (p=0.04). These results suggest that (1) PBCs occurring in early MS patients were not different from those induced by comparable chronic non-CNS disorders, (2) qualitative differences in the relationship between behavioral symptoms and executive-behavioral changes may exist between MS and control groups, and (3) behavioral symptoms seem associated with cognitive deficits in MS. We further plan to assess these observations longitudinally.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Epidémiologie des cancers épithéliaux de la peau [Epidemiology of epithelial skin cancers]

With no less than 15,000 estimated new cases diagnosed per year, non melanomatous carcinomas are the commonest cutaneous cancers in the Swiss population. About 1 in 3 new cancer case is a basal (BCC) or a squamous cell carcinoma (SCC). Incidence rates are steadily increasing, faster for BCC than SCC. Rates are higher for men than women and increase exponentially with age. Systematic population-based registration of non melanomatous skin cancers faces many challenges that few cancer registries can meet. Rates of these cancers in Switzerland are among the highest in Europe. Primary and secondary nationwide prevention campaigns have been carried out for nearly 20 years with a focus on the deadliest cutaneous cancer: melanoma. However, detection of non melanomatous skin cancers benefits from these campaigns since prevention messages and means of early detection are similar for melanomas and other skin cancers.