Université libre de Bruxelles

About: Université libre de Bruxelles is a education organization based out in Brussels, Belgium. It is known for research contribution in the topics: Population & Breast cancer. The organization has 24974 authors who have published 56969 publications receiving 2084303 citations. The organization is also known as: ULB.

The dysphonia severity index: an objective measure of vocal quality based on a multiparameter approach

Abstract: The vocal quality of a patient is modeled by means of a Dysphonia Severity Index (DSI), which is designed to establish an objective and quantitative correlate of the perceived vocal quality The DSI is based on the weighted combination of the following selected set of voice measurements: highest Frequency (F-0-High in Hz), lowest intensity (I-Low in dB), maximum phonation time (Mm in s), and jitter (%). The DSI is derived from a multivariate analysis of 387 subjects with the goal of describing, purely based on objective measures, the perceived voice quality It is constructed as DSI = 0.13 x MPT + 0.0053 x F-0-High - 0.26 x I-Low - 1.18 x Jitter (%)+ 12.4. The DSI For perceptually normal voices equals +5 and for severely dysphonic voices -5. The more negative the patient's index, the worse is his or her vocal quality As such, the DSI is especially useful to evaluate therapeutic evolution of dysphonic patients. Additionally, there is a high correlation between the DSI and the Voice Handicap Index score.

A model for circadian oscillations in the Drosophila period protein (PER).

Abstract: The mechanism of circadian oscillations in the period protein (PER) in Drosophila is investigated by means of a theoretical model. Taking into account recent experimental observations, the model for the circadian clock is based on multiple phosphorylation of PER and on the negative feedback exerted by PER on the transcription of the period (per) gene. This minimal biochemical model provides a molecular basis for circadian oscillations of the limit cycle type. During oscillations, the peak in per mRNA precedes by several hours the peak in total PER protein. The results support the view that multiple PER phosphorylation introduces times delays which strengthen the capability of negative feedback to produce oscillations. The analysis shows that the rhythm only occurs in a range bounded by two critical values of the maximum rate of PER degradation. A similar result is obtained with respect to the rate of PER transport into the nucleus. The results suggest a tentative explanation for the altered period of per mutants, in terms of variations in the rate of PER degradation.

Most random gene expression signatures are significantly associated with breast cancer outcome.

Abstract: Bridging the gap between animal or in vitro models and human disease is essential in medical research. Researchers often suggest that a biological mechanism is relevant to human cancer from the statistical association of a gene expression marker (a signature) of this mechanism, that was discovered in an experimental system, with disease outcome in humans. We examined this argument for breast cancer. Surprisingly, we found that gene expression signatures-unrelated to cancer-of the effect of postprandial laughter, of mice social defeat and of skin fibroblast localization were all significantly associated with breast cancer outcome. We next compared 47 published breast cancer outcome signatures to signatures made of random genes. Twenty-eight of them (60%) were not significantly better outcome predictors than random signatures of identical size and 11 (23%) were worst predictors than the median random signature. More than 90% of random signatures >100 genes were significant outcome predictors. We next derived a metagene, called meta-PCNA, by selecting the 1% genes most positively correlated with proliferation marker PCNA in a compendium of normal tissues expression. Adjusting breast cancer expression data for meta-PCNA abrogated almost entirely the outcome association of published and random signatures. We also found that, in the absence of adjustment, the hazard ratio of outcome association of a signature strongly correlated with meta-PCNA (R(2) = 0.9). This relation also applied to single-gene expression markers. Moreover, >50% of the breast cancer transcriptome was correlated with meta-PCNA. A corollary was that purging cell cycle genes out of a signature failed to rule out the confounding effect of proliferation. Hence, it is questionable to suggest that a mechanism is relevant to human breast cancer from the finding that a gene expression marker for this mechanism predicts human breast cancer outcome, because most markers do. The methods we present help to overcome this problem.