Lipid Composition of the Human Eye: Are Red Blood Cells a Good Mirror of Retinal and Optic Nerve Fatty Acids?

International audienceBACKGROUND: The assessment of blood lipids is very frequent in clinical research as it is assumed to reflect the lipid composition of peripheral tissues. Even well accepted such relationships have never been clearly established. This is particularly true in ophthalmology where the use of blood lipids has become very common following recent data linking lipid intake to ocular health and disease. In the present study, we wanted to determine in humans whether a lipidomic approach based on red blood cells could reveal associations between circulating and tissue lipid profiles. To check if the analytical sensitivity may be of importance in such analyses, we have used a double approach for lipidomics. METHODOLOGY AND PRINCIPAL FINDINGS: Red blood cells, retinas and optic nerves were collected from 9 human donors. The lipidomic analyses on tissues consisted in gas chromatography and liquid chromatography coupled to an electrospray ionization source-mass spectrometer (LC-ESI-MS). Gas chromatography did not reveal any relevant association between circulating and ocular fatty acids except for arachidonic acid whose circulating amounts were positively associated with its levels in the retina and in the optic nerve. In contrast, several significant associations emerged from LC-ESI-MS analyses. Particularly, lipid entities in red blood cells were positively or negatively associated with representative pools of retinal docosahexaenoic acid (DHA), retinal very-long chain polyunsaturated fatty acids (VLC-PUFA) or optic nerve plasmalogens. CONCLUSIONS AND SIGNIFICANCE: LC-ESI-MS is more appropriate than gas chromatography for lipidomics on red blood cells, and further extrapolation to ocular lipids. The several individual lipid species we have identified are good candidates to represent circulating biomarkers of ocular lipids. However, further investigation is needed before considering them as indexes of disease risk and before using them in clinical studies on optic nerve neuropathies or retinal diseases displaying photoreceptors degeneration

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Preservice Elementary Science Teachers' Argumentation Competence: Impact of a Training Programme

The recent literature has shown the importance of Preservice Elementary Science Teachers (PESTs) having a deep understanding of argumentation, as this factor may affect the nature of the class activities that are taught and what students learn. A lack of understanding of this factor may represent an obstacle in the development of science education programmes in line with the development of scientific competences. This paper presents the results of the design and implementation of a training programme of 6 sessions (12 hours of class participation plus 8 hours of personal homework) on argumentation. The programme was carried out by 57 Spanish PESTs from Malaga, Spain. The training programme incorporates the innovative use of certain strategies to improve competence in argumentation, such as teaching PESTs to identify the elements of arguments in order to design assessment rubrics or by including peer assessment during evaluation with and without rubrics. The results obtained on implementing the training programme were evaluated based on the development of PESTs’ argumentation competence using Toulmin’s argumentative model. Data collection methods involved two tasks carried out at the beginning and the end of the programme, i.e., pre-test and post-test, respectively. The conclusion of the study is that students made significant progress in their argumentation competence on completing the course. In addition, PESTs who followed the training programme achieved statistically better results at the end than those in the control group (n = 41), who followed a traditional teaching programme. A 6-month transfer task showed a slight improvement for the PESTs of the experimental group in relation to the control group in their ability to transfer argumentation to practice, especially to the extent to which they mentioned argumentation in their practice portfolios.This work is part of the “I+D Excelencia” project “Development and evaluation of scientific competences through context based and modelling teaching approaches” case studies (EDU2013-41952-P), funded by the Spanish Ministry of Economy and Finance through its 2013 research call

Modelling heavy tails and skewness in film returns

The average of box-office revenue is dominated by extreme outcomes, with most films earning little and most revenues flowing to a few blockbusters. In this paper the skewness and heavy tails of film returns are formally modelled using skew-Normal and skew-t distributions. Logarithmic skew-Normal and skew-t models of the distribution of box-office revenue are fitted conditional on star actors and directors, budget, release pattern, genre, rating, and year of release. The estimates show significantly more skewness and heavier tails than the log-Normal distribution. It is also found that a wide theatrical release has a much smaller impact on box-office revenue when heavy tails and skewness are explicitly modelled.

Explaining successful docker images using pattern mining analysis

Docker is on the rise in today’s enterprise IT. It permits shipping applications inside portable containers, which run from so-called Docker images. Docker images are distributed in public registries, which also monitor their popularity. The popularity of an image directly impacts on its usage, and hence on the potential revenues of its developers. In this paper, we present a frequent pattern mining-based approach for understanding how to improve an image to increase its popularity. The results in this work can provide valuable insights to Docker image providers, helping them to design more competitive software products

Screen wars, star wars, and sequels

Motion-picture profit, Nonparametric regression, Hollywood economics, L82, C14,