Extensive Placental Methylation Profiling in Normal Pregnancies

The placental methylation pattern is crucial for the regulation of genes involved in trophoblast invasion and placental development, both key events for fetal growth. We investigated LINE-1 methylation and methylome profiling using a methylation EPIC array and the targeted methylation sequencing of 154 normal, full-term pregnancies, stratified by birth weight percentiles. LINE-1 methylation showed evidence of a more pronounced hypomethylation in small neonates compared with normal and large for gestational age. Genome-wide methylation, performed in two subsets of pregnancies, showed very similar methylation profiles among cord blood samples while placentae from different pregnancies appeared very variable. A unique methylation profile emerged in each placenta, which could represent the sum of adjustments that the placenta made during the pregnancy to preserve the epigenetic homeostasis of the fetus. Investigations into the 1000 most variable sites between cord blood and the placenta showed that promoters and gene bodies that are hypermethylated in the placenta are associated with blood-specific functions, whereas those that are hypomethylated belong mainly to pathways involved in cancer. These features support the functional analogies between a placenta and cancer. Our results, which provide a comprehensive analysis of DNA methylation profiling in the human placenta, suggest that its peculiar dynamicity can be relevant for understanding placental plasticity in response to the environment.     

Clinical and Molecular Diagnosis of Beckwith-Wiedemann Syndrome with Single- or Multi-Locus Imprinting Disturbance

Beckwith-Wiedemann syndrome (BWS) is a clinically and genetically heterogeneous overgrowth disease. BWS is caused by (epi)genetic defects at the 11p15 chromosomal region, which harbors two clusters of imprinted genes, IGF2/H19 and CDKN1C/KCNQ1OT1, regulated by differential methylation of imprinting control regions, H19/IGF2:IG DMR and KCNQ1OT1:TSS DMR, respectively. A subset of BWS patients show multi-locus imprinting disturbances (MLID), with methylation defects extended to other imprinted genes in addition to the disease-specific locus. Specific (epi)genotype-phenotype correlations have been defined in order to help clinicians in the classification of patients and referring them to a timely diagnosis and a tailored follow-up. However, specific phenotypic correlations have not been identified among MLID patients, thus causing a debate on the usefulness of multi-locus testing in clinical diagnosis. Finally, the high incidence of BWS monozygotic twins with discordant phenotypes, the high frequency of BWS among babies conceived by assisted reproductive technologies, and the female prevalence among BWS-MLID cases provide new insights into the timing of imprint establishment during embryo development. In this review, we provide an overview on the clinical and molecular diagnosis of single- and multi-locus BWS in pre- and post-natal settings, and a comprehensive analysis of the literature in order to define possible (epi)genotype-phenotype correlations in MLID patients.     

A mathematical model for the prediction of water vapour transmission rate at different temperature and relative humidity combinations

A simple mathematical procedure for the estimation of water vapour transmission rate under different conditions is presented and discussed. The ASTM dynamic and gravimetric methods were used for measuring the water vapour transmission rate of four thin plastic films (PET 19 μm, PVC 16 μm, EVA 15 μm and LDPE 23 μm) under 38 different conditions of temperature and relative humidity and the corresponding permeance values were drawn. On the basis of the Clausius Clapeyron's relationship between temperature and water vapour pressure, a simple equation was derived for a rapid transformation of water vapour transmission rate data. The mathematical procedure was applied to the data collected for the four thin films and good agreement was found between observed and predicted values for the PET and LDPE films, while for the PVC and EVA films the equation developed led to an overestimate of water vapour transmission at the lower temperatures.     

Daily Dialysis: Toward a New Standard in Well‐Being

Daily hemodialysis (DHD) is a promising option; however, logistic obstacles and clinical perplexities limit its dissemination. Understanding the mechanisms of, and the time until, the onset of improved well‐being may help to quantify clinical advantages and to define the minimum length of a “trial” of daily dialysis. By following 30 patients treated in 4 centers, this study aimed to determine how long a period of time is needed until a patient experiences subjective improvement. From November 1998 to November 2000, 30 patients tried at least 2 weeks of short daily dialysis in four Northern Italian centers of Piemonte and Valle d'Aosta. The DHD (2 – 3 hours; blood flow 270 – 350 mL/min; individual HCO₃, Na, K) was performed at home or in a center. Motivations to try DHD, fears and concerns regarding DHD, and changes in perceived well‐being were assessed by semi‐structured interview. The main clinical indications for a trial of DHD were poor tolerance of conventional treatment, cardiovascular disease, and hypertension or hypotension; only 6 patients had no comorbidity at start. The patients' main reasons for choosing DHD were related to job problems and the search for a better treatment. Most of the patients continued DHD because of improved well‐being; logistic reasons accounted for the drop‐outs (5 patients). The main fears were related to logistic aspects, vascular access problems, and excessive involvement of the partner on home dialysis. Improved well‐being was reported by 28 of 30 patients; 2 patients reported no difference. Subjective improvement was perceived within 2 weeks in 22 of 30 patients, and within 1 month in 28 of 30 patients. An offer of a 2 – 4 week trial of DHD may help patients and caregivers to determine whether subjective and objective benefits outweigh logistic problems and whether a permanent transfer to DHD is worthwhile.     

Evaluating a modified Google user interface via screen reader

This paper describes the progress of a research project aimed at improving the usability of web search tools for blind users who interact via screen readers and voice synthesizers. In the first stage of research, specific guidelines were proposed for simplifying the interaction with search engines for the blind. To evaluate these criteria, they were applied to Google user interfaces, by re-implementing the search form as well as the results page. Finally, the redesigned interfaces were evaluated through remote testing with 12 totally blind users. The results highlighted how Google, although already accessible, may be further improved in order to simplify interaction for people with impaired vision.

Grid and Databases: BaSTI as a Practical Integration Example

Stellar Astrophysics and in particular stellar evolutionary computations are extremely important to face a wealth of astrophysical problems, but they are also extremely demanding in terms of computing power and data storage. The Bag of Stellar Tracks and Isochrones (BaSTI) database is a theoretical astrophysical catalogue that collects fundamental data sets involving stars formation and evolution. To create this database it is necessary to run a large number of stellar evolutionary computations. The Grid technology seems to be a promising answer to data storage and processing needs of the BaSTI catalogue. In the framework of the EGEE Grid infrastructure, we managed to run a number of experiments aimed at designing and defining an application specific environment for the stellar simulation software and its interaction with the BaSTI database. Our successful implementation demonstrates that the “gridification” of stellar evolution code is not only possible but also even extremely convenient in terms of data processing speed and data sharing, and it can be a valuable instrument to support Astrophysical research.     

The proteomics of cancer stem cells: potential clinical applications for innovative research in oncology

Cancer stem cells (CSCs) or tumour-maintaining cells are becoming an important new reality in oncology. The intriguing molecular pathophysiology of CSCs may justify some of the obscure pathogenetic, diagnostic, prognostic, and above all, therapeutic aspects of cancer and, eventually, lead to new solutions in oncology. CSC is a cell within the tumour that possesses the capacity to self-renew and, in doing so, gives rise to the heterogeneous lineages that comprise the tumour. The precise identification of this peculiar subpopulation of cancer cells, which has some intriguing similarities to normal stem cells, is becoming an important and urgent topic in oncology. In fact, some debated CSC markers have been already adopted by pharmacological research as targets of new and/or old anticancer drugs, showing an intriguing therapeutic index. These discussed identification markers include cell surface proteins, different activated signalling pathways, several molecules of the stem cell niche, various drug resistance mechanisms (ABCG2 and ALDH), telomerase, oncogenes and oncosuppressors (p16INK4 - Rb) and lastly, various microRNAs. In this new promising area of cancer research, proteomics, in general, and oncoproteomics, in particular, can and must play a significant role if the methodological approaches and the experimental protocols are correctly designed and interpreted.     

Revisiting the Warburg effect in cancer cells with proteomics. The emergence of new approaches to diagnosis, prognosis and therapy

Most cancer cells exhibit elevated levels of glycolysis and this metabolic pathway seems to be related to a greater glucose uptake. This phenomenon, known as the Warburg effect, is considered one of the most fundamental metabolic alterations during malignant transformation. Originally, Warburg hypothesised that the aerobic glycolysis of cancer cells could be just an aspect of a more complex metabolic adaptation. However, this intriguing discovery was partially misinterpreted and disregarded over time. In recent years, the peculiarities of cancer cell metabolism have been re-evaluated in light of new metabolic data that seem to confirm and to widen the original concept of the Warburg effect. In fact, biochemical, molecular, and, above all, proteomic studies on the multifaceted roles of glycolytic enzymes in cancer cells in general, and in cancer stem cells in particular, seem to suggest more complex functional adaptations. These adaptations result in significantly altered protein expression patterns, and they have fundamental implications for diagnosis, prognosis and therapy. Revisiting the Warburg effect in cancer cells with a proteomic approach could deepen our knowledge of cancer cell metabolism and of cancer cell biology in general. Moreover, by identifying useful diagnostic, prognostic and therapeutic targets, it could significantly impact clinical practice.     

Exploration of distributional models for a novel intensity-dependent normalization procedure in censored gene expression data

Current gene intensity-dependent normalization methods, based on regression smoothing techniques, usually approach the two problems of reducing location bias and data rescaling without taking into account the censoring that is characteristic of certain gene expressions, produced by experimental measurement constraints or by previous normalization steps. Moreover, control of normalization procedures for balancing bias versus variance is often left to the user’s experience. An approximate maximum likelihood procedure for fitting a model smoothing the dependences of log-fold gene expression differences on average gene intensities is presented. Central tendency and scaling factor are modeled by means of the B-spline smoothing technique. As an alternative to the outlier theory and robust methods, the approach presented looks for suitable distributional models, possibly generalizing the classical Gaussian and Laplacian assumptions, controlling for different types of censoring. The Bayesian information criterion is adopted for model selection. Distributional assumptions are tested using goodness-of-fit statistics and Monte Carlo evaluation. Randomization quantiles are proposed to produce normally distributed adjusted data. Three publicly available data sets are analyzed for demonstration purposes. Student’s t error models reveal best performances in all of the data sets considered. More validating evidence is needed to evaluate the Asymmetric Laplace distribution, which showed interesting results in one data set.     

A semantic framework for metamodel-based languages

In the model-based development context, metamodel-based languages are increasingly being defined and adopted either for general purposes or for specific domains of interest. However, meta-languages such as the MOF (Meta Object Facility)—combined with the OCL (Object Constraint Language) for expressing constraints—used to specify metamodels focus on structural and static semantics but have no built-in support for specifying behavioral semantics. This paper introduces a formal semantic framework for the definition of the semantics of metamodel-based languages. Using metamodelling principles, we propose several techniques, some based on the translational approach while others based on the weaving approach, all showing how the Abstract State Machine formal method can be integrated with current metamodel engineering environments to endow language metamodels with precise and executable semantics. We exemplify the use of our semantic framework by applying the proposed techniques to the OMG metamodelling framework for the behaviour specification of the Finite State Machines provided in terms of a metamodel.