Environmental epigenomics: Current approaches to assess epigenetic effects of endocrine disrupting compounds (EDC's) on human health

Environmental Epigenomics is a developing field to study the epigenetic effect on human health from exposure to environmental factors. Endocrine disrupting chemicals have been detected primarily in pharmaceutical drugs, personal care products, food additives, and food containers. Exposure to endocrine-disrupting chemicals (EDCs) has been associated with a high incidence and prevalence of many endocrine-related disorders in humans. Nevertheless, further evidence is needed to establish a correlation between exposure to EDC and human disorders. Conventional detection of EDCs is based on chemical structure and concentration sample analysis. However, substantial evidence has emerged, suggesting that cell exposure to EDCs leads to epigenetic changes, independently of its chemical structure with non-monotonic low-dose responses. Consequently, a paradigm shift in toxicology assessment of EDCs is proposed based on a comprehensive review of analytical techniques used to evaluate the epigenetic effects. Fundamental insights reported elsewhere are compared in order to establish DNA methylation analysis as a viable method for assessing endocrine disruptors beyond the conventional study approach of chemical structure and concentration analysis

Src Dependent Pancreatic Acinar Injury Can Be Initiated Independent of an Increase in Cytosolic Calcium

Several deleterious intra-acinar phenomena are simultaneously triggered on initiating acute pancreatitis. These culminate in acinar injury or inflammatory mediator generation in vitro and parenchymal damage in vivo. Supraphysiologic caerulein is one such initiator which simultaneously activates numerous signaling pathways including non-receptor tyrosine kinases such as of the Src family. It also causes a sustained increase in cytosolic calcium- a player thought to be crucial in regulating deleterious phenomena. We have shown Src to be involved in caerulein induced actin remodeling, and caerulein induced changes in the Golgi and post-Golgi trafficking to be involved in trypsinogen activation, which initiates acinar cell injury. However, it remains unclear whether an increase in cytosolic calcium is necessary to initiate acinar injury or if injury can be initiated at basal cytosolic calcium levels by an alternate pathway. To study the interplay between tyrosine kinase signaling and calcium, we treated mouse pancreatic acinar cells with the tyrosine phosphatase inhibitor pervanadate. We studied the effect of the clinically used Src inhibitor Dasatinib (BMS-354825) on pervanadate or caerulein induced changes in Src activation, trypsinogen activation, cell injury, upstream cytosolic calcium, actin and Golgi morphology. Pervanadate, like supraphysiologic caerulein, induced Src activation, redistribution of the F-actin from its normal location in the sub-apical area to the basolateral areas, and caused antegrade fragmentation of the Golgi. These changes, like those induced by supraphysiologic caerulein, were associated with trypsinogen activation and acinar injury, all of which were prevented by Dasatinib. Interestingly, however, pervanadate did not cause an increase in cytosolic calcium, and the caerulein induced increase in cytosolic calcium was not affected by Dasatinib. These findings suggest that intra-acinar deleterious phenomena may be initiated independent of an increase in cytosolic calcium. Other players resulting in acinar injury along with the Src family of tyrosine kinases remain to be explored. © 2013 Mishra et al

An Ecological Study of the Determinants of Differences in 2009 Pandemic Influenza Mortality Rates between Countries in Europe

Pandemic A (H1N1) 2009 mortality rates varied widely from one country to another. Our aim was to identify potential socioeconomic determinants of pandemic mortality and explain between-country variation.Based on data from a total of 30 European countries, we applied random-effects Poisson regression models to study the relationship between pandemic mortality rates (May 2009 to May 2010) and a set of representative environmental, health care-associated, economic and demographic country-level parameters. The study was completed by June 2010.Most regression approaches indicated a consistent, statistically significant inverse association between pandemic influenza-related mortality and per capita government expenditure on health. The findings were similar in univariable [coefficient: -0.00028, 95% Confidence Interval (CI): -0.00046, -0.00010, p = 0.002] and multivariable analyses (including all covariates, coefficient: -0.00107, 95% CI: -0.00196, -0.00018, p = 0.018). The estimate was barely insignificant when the multivariable model included only significant covariates from the univariate step (coefficient: -0.00046, 95% CI: -0.00095, 0.00003, p = 0.063).Our findings imply a significant inverse association between public spending on health and pandemic influenza mortality. In an attempt to interpret the estimated coefficient (-0.00028) for the per capita government expenditure on health, we observed that a rise of 100 international dollars was associated with a reduction in the pandemic influenza mortality rate by approximately 2.8%. However, further work needs to be done to unravel the mechanisms by which reduced government spending on health may have affected the 2009 pandemic influenza mortality

Proposing to use artificial neural Networks for NoSQL attack detection

[EN] Relationships databases have enjoyed a certain boom in software worlds until now. These days, with the rise of modern applications, unstructured data production, traditional databases do not completely meet the needs of all systems. Regarding these issues, NOSQL databases have been developed and are a good alternative. But security aspects stay behind. Injection attacks are the most serious class of web attacks that are not taken seriously in NoSQL. This paper presents a Neural Network model approach for NoSQL injection. This method attempts to use the best and most effective features to identify an injection. The features used are divided into two categories, the first one based on the content of the request, and the second one independent of the request meta parameters. In order to detect attack payloads features, we work on character level analysis to obtain malicious rate of user inputs. The results demonstrate that our model has detected more attack payloads compare with models that work black list approach in keyword level

Nitrogen uptake and internal recycling in Zostera marina exposed to oyster farming: eelgrass potential as a natural biofilter

Oyster farming in estuaries and coastal lagoons frequently overlaps with the distribution of seagrass meadows, yet there are few studies on how this aquaculture practice affects seagrass physiology. We compared in situ nitrogen uptake and the productivity of Zostera marina shoots growing near off-bottom longlines and at a site not affected by oyster farming in San Quintin Bay, a coastal lagoon in Baja California, Mexico. We used benthic chambers to measure leaf NH4 (+) uptake capacities by pulse labeling with (NH4)-N-15 (+) and plant photosynthesis and respiration. The internal N-15 resorption/recycling was measured in shoots 2 weeks after incubations. The natural isotopic composition of eelgrass tissues and vegetative descriptors were also examined. Plants growing at the oyster farming site showed a higher leaf NH4 (+) uptake rate (33.1 mmol NH4 (+) m(-2) day(-1)) relative to those not exposed to oyster cultures (25.6 mmol NH4 (+) m(-2) day(-1)). We calculated that an eelgrass meadow of 15-16 ha (which represents only about 3-4 % of the subtidal eelgrass meadow cover in the western arm of the lagoon) can potentially incorporate the total amount of NH4 (+) excreted by oysters (similar to 5.2 x 10(6) mmol NH4 (+) day(-1)). This highlights the potential of eelgrass to act as a natural biofilter for the NH4 (+) produced by oyster farming. Shoots exposed to oysters were more efficient in re-utilizing the internal N-15 into the growth of new leaf tissues or to translocate it to belowground tissues. Photosynthetic rates were greater in shoots exposed to oysters, which is consistent with higher NH4 (+) uptake and less negative delta C-13 values. Vegetative production (shoot size, leaf growth) was also higher in these shoots. Aboveground/belowground biomass ratio was lower in eelgrass beds not directly influenced by oyster farms, likely related to the higher investment in belowground biomass to incorporate sedimentary nutrients

Smc5/6 coordinates formation and resolution of joint molecules with chromosome morphology to ensure meiotic divisions

During meiosis, Structural Maintenance of Chromosome (SMC) complexes underpin two fundamental features of meiosis: homologous recombination and chromosome segregation. While meiotic functions of the cohesin and condensin complexes have been delineated, the role of the third SMC complex, Smc5/6, remains enigmatic. Here we identify specific, essential meiotic functions for the Smc5/6 complex in homologous recombination and the regulation of cohesin. We show that Smc5/6 is enriched at centromeres and cohesin-association sites where it regulates sister-chromatid cohesion and the timely removal of cohesin from chromosomal arms, respectively. Smc5/6 also localizes to recombination hotspots, where it promotes normal formation and resolution of a subset of joint-molecule intermediates. In this regard, Smc5/6 functions independently of the major crossover pathway defined by the MutLγ complex. Furthermore, we show that Smc5/6 is required for stable chromosomal localization of the XPF-family endonuclease, Mus81-Mms4Eme1. Our data suggest that the Smc5/6 complex is required for specific recombination and chromosomal processes throughout meiosis and that in its absence, attempts at cell division with unresolved joint molecules and residual cohesin lead to severe recombination-induced meiotic catastroph

A hydraulically driven colonoscope

BACKGROUND: Conventional colonoscopy requires a high degree of operator skill and is often painful for the patient. We present a preliminary feasibility study of an alternative approach where a self-propelled colonoscope is hydraulically driven through the colon. METHODS: A hydraulic colonoscope which could be controlled manually or automatically was developed and assessed in a test bed modelled on the anatomy of the human colon. A conventional colonoscope was used by an experienced colonoscopist in the same test bed for comparison. Pressures and forces on the colon were measured during the test. RESULTS: The hydraulic colonoscope was able to successfully advance through the test bed in a comparable time to the conventional colonoscope. The hydraulic colonoscope reduces measured loads on artificial mesenteries, but increases intraluminal pressure compared to the colonoscope. Both manual and automatically controlled modes were able to successfully advance the hydraulic colonoscope through the colon. However, the automatic controller mode required lower pressures than manual control, but took longer to reach the caecum. CONCLUSIONS: The hydraulic colonoscope appears to be a viable device for further development as forces and pressures observed during use are comparable to those used in current clinical practice

A review of k-NN algorithm based on classical and Quantum Machine Learning

[EN] Artificial intelligence algorithms, developed for traditional computing, based on Von Neumann’s architecture, are slow and expen- sive in terms of computational resources. Quantum mechanics has opened up a new world of possibilities within this field, since, thanks to the basic properties of a quantum computer, a great degree of parallelism can be achieved in the execution of the quantum version of machine learning algorithms. In this paper, a study has been carried out on these proper- ties and on the design of their quantum computing versions. More specif- ically, the study has been focused on the quantum version of the k-NN algorithm that allows to understand the fundamentals when transcribing classical machine learning algorithms into its quantum versions

The impact of the Great Recession on mental health and its inequalities: the case of a Southern European region, 1997–2013

Background: Numerous studies have shown that macroeconomic changes have a great influence on health, prompting different concerns in recent literature about the effects of the current recession. The objetive of the study was to assess the changes in the mental health of the working-age population in the Basque Country (Spain) and its social inequalities following the onset of the 2008 recession, with special focus on the role of unemployment. Methods: Repeated cross-sectional study on the population aged 16-64, using four Basque Health Surveys (1997-2013). Age-adjusted prevalences of poor mental health and incremental prevalence ratios (working status and social class adjusted) between years were calculated. Absolute/relative measures of social inequalities were also calculated. Results: From 2008, there was a clear deterioration in the mental health, especially among men. Neither changes in employment status nor social class accounted for these changes. In men, the deterioration affected all working status categories, except the retired but significant changes occurred only among the employed. In women, poor mental health significantly increased among the unemployed. Students were also especially affected. Relative inequalities increased only in men. Conclusions: The Great Recession is being accompanied by adverse effects on mental health, which cannot be fully explained by the increase of unemployment. Public healtThis work was partially supported by the Ministry of Economy and Competitiveness (State Programme for Promotion of Scientific and Technical Research Challenges (CSO2013-44886-R))