487 Left atrial strain/strain rate analysis in patients with dilated cardiomyopathy. correlation with clinical, electrocardiographic and echocardiographic findings

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Different carbohydrate sources affect swine performance and post-prandial glycaemic response

The type of starch and fibre in the diet affects several parameters, including glycaemic and insulin response, that are involved in pig growth performance. Four experimental diets for growing pigs differing for carbohydrates source (corn, barley, faba bean and pea) were tested. The diets were analysed in vitro to assess the carbohydrates characteristics, and they were administered to 56 crossbreed growing pigs (Landrace × Large White) randomly divided into four groups (mean age of 95 ± 6 days; body weight 80 kg ± 4 days). Clinical examination and average daily gain were performed before recruitment and after 40 days of experiment. The metabolic effects were investigated by blood count and serum biochemical parameters and by the glycaemic and insulin post-prandial response. The study revealed substantial differences among the diets, suggesting that alternative feedstuffs for swine affect several parameters, including glycaemic and insulin response, with no negative effects on growing performance. The Barley group showed the highest daily weight gain (p <.05) associated with the highest glycaemic (p <.05) and insulin response at 1 and 2 h post-prandial (p <.01), suggesting that the barley-based diet can support performance comparable to that of the corn-based diet in growing pig. By contrast, the lowest glycaemia was observed in the Faba bean group (p <.05), confirming the capacity of this legume to modulate post-prandial glucose levels. Moreover, the ability of some ingredients in lowering glucose and insulin response enriches the knowledge on functional nutrients for animal diets and to prevent the incidence of enteric diseases.Highlights The type of starch and fibre used in the diet highly affected some blood parameters, such as glycaemic and insulin responses. The Barley group showed the highest daily weight gain. Lower glycaemia levels were observed in the Faba bean group compared to the Corn one. Alternative protein sources for swine diets can limit the glycaemic and insulin response with no negative effects on growing performance

Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients

In this work, four different methods based on Physics-Informed Neural Networks (PINNs) for solving Differential Equations (DE) are compared: Classic-PINN that makes use of Deep Neural Networks (DNNs) to approximate the DE solution;Deep-TFC improves the efficiency of classic-PINN by employing the constrained expression from the Theory of Functional Connections (TFC) so to analytically satisfy the DE constraints;PIELM that improves the accuracy of classic-PINN by employing a single-layer NN trained via Extreme Learning Machine (ELM) algorithm;X-TFC, which makes use of both constrained expression and ELM. The last has been recently introduced to solve challenging problems affected by discontinuity, learning solutions in cases where the other three methods fail. The four methods are compared by solving the boundary value problem arising from the 1D Steady-State Advection–Diffusion Equation for different values of the diffusion coefficient. The solutions of the DEs exhibit steep gradients as the value of the diffusion coefficient decreases, increasing the challenge of the problem

Tailoring Micro-solar Systems to Heterogeneous Wireless Sensor Networks

Energetic needs of wireless sensor networks (WSNs) have been thoroughly studied. Among the most important results, clustering protocols are able to reduce significantly energy consumption in these networks. In the last few years though, focus has also been put on energy harvesting for WSNs. With energy harvesting researchers aim to reach energy neutrality, which means the network only runs on harvested energy. Many papers propose design options for energy harvested WSN, but they only focus on ad-hoc solutions, homogeneous WSNs, or pose other limitations. In this paper we propose a new approach. We study the energetic need of a heterogeneous WSN clustered with a known algorithm (REECHD) through simulation, in order to calculate the minimum and ideal energy to harvest for a given network. Given that, we design an appropriate micro-solar power system to achieve energy neutrality

An Italian prospective multicenter survey on patients suspected of having non-celiac gluten sensitivity.

BACKGROUND: Non-celiac gluten sensitivity (NCGS) is still an undefined syndrome with several unsettled issues despite the increasing awareness of its existence. We carried out a prospective survey on NCGS in Italian centers for the diagnosis of gluten-related disorders, with the aim of defining the clinical picture of this new syndrome and to establish roughly its prevalence compared with celiac disease. METHODS: From November 2012 to October 2013, 38 Italian centers (27 adult gastroenterology, 5 internal medicine, 4 pediatrics, and 2 allergy) participated in this prospective survey. A questionnaire was used in order to allow uniform and accurate collection of clinical, biochemical, and instrumental data. RESULTS: In total, 486 patients with suspected NCGS were identified in this 1-year period. The female/male ratio was 5.4 to 1, and the mean age was 38 years (range 3–81). The clinical picture was characterized by combined gastrointestinal (abdominal pain, bloating, diarrhea and/or constipation, nausea, epigastric pain, gastroesophageal reflux, aphthous stomatitis) and systemic manifestations (tiredness, headache, fibromyalgia-like joint/muscle pain, leg or arm numbness, 'foggy mind,' dermatitis or skin rash, depression, anxiety, and anemia). In the large majority of patients, the time lapse between gluten ingestion and the appearance of symptoms varied from a few hours to 1 day. The most frequent associated disorders were irritable bowel syndrome (47%), food intolerance (35%) and IgE-mediated allergy (22%). An associated autoimmune disease was detected in 14% of cases. Regarding family history, 18% of our patients had a relative with celiac disease, but no correlation was found between NCGS and positivity for HLA-DQ2/-DQ8. IgG anti-gliadin antibodies were detected in 25% of the patients tested. Only a proportion of patients underwent duodenal biopsy; for those that did, the biopsies showed normal intestinal mucosa (69%) or mild increase in intraepithelial lymphocytes (31%). The ratio between suspected NCGS and new CD diagnoses, assessed in 28 of the participating centers, was 1.15 to 1. CONCLUSIONS: This prospective survey shows that NCGS has a strong correlation with female gender and adult age. Based on our results, the prevalence of NCGS seems to be only slightly higher than that of celiac disease. Please see related article http://www.biomedcentral.com/1741-7015/12/86

Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease

Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies, but no morphological changes in the small bowel mucosa. A minority of patients (17%) showed clinical symptoms and need a gluten free diet at time of diagnosis, while the majority progress over several years (up to a decade) without any clinical problem neither a progression of the small intestine mucosal damage even when they continued to assume gluten in their diet. Recently we developed a traditional multivariate approach to predict the natural history, on the base of the information at enrolment (time 0) by a discriminant analysis model. Still, the traditional multivariate model requires stringent assumptions that may not be answered in the clinical setting. Starting from a follow-up dataset available for PCD, we propose the application of Machine Learning (ML) methodologies to extend the analysis on available clinical data and to detect most influent features predicting the outcome. These features, collected at time of diagnosis, should be capable to classify patients who will develop duodenal atrophy from those who will remain potential. Four ML methods were adopted to select features predictive of the outcome; the feature selection procedure was indeed capable to reduce the number of overall features from 85 to 19. ML methodologies (Random Forests, Extremely Randomized Trees, and Boosted Trees, Logistic Regression) were adopted, obtaining high values of accuracy: all report an accuracy above 75%. The specificity score was always more than 75% also, with two of the considered methods over 98%, while the best performance of sensitivity was 60%. The best model, optimized Boosted Trees, was able to classify PCD starting from the selected 19 features with an accuracy of 0.80, sensitivity of 0.58 and specificity of 0.84. Finally, with this work, we are able to categorize PCD patients that can more likely develop overt CD using ML. ML techniques appear to be an innovative approach to predict the outcome of PCD, since they provide a step forward in the direction of precision medicine aimed to customize healthcare, medical therapies, decisions, and practices tailoring the clinical management of PCD children

Improvement of Rumen Fermentation Efficiency Using Different Energy Sources: In Vitro Comparison between Buffalo and Cow

During haymaking and ensilage, a significant loss of sugars occurs. The addition of a total mixed ratio (TMR) with a liquid feed might provide promptly utilisable energy and recover the nutrients lost during the conservation. Interesting results were already obtained by including liquid feed in a TMR in a dairy cow. However, the possibility to also utilize them in Italian Mediterranean buffalo is not yet supported by data. This study aimed to evaluate the in vitro fermentation characteristics and kinetics of different types of liquid feed, utilising bovine and buffalo rumen liquor as inocula. TMR supplemented with 0.025 g of four different liquid feeds was incubated with the TMR as control with buffalo and bovine rumen fluid using in vitro gas production technique. Considering bovine inoculum, all the experimental diets showed lower organic matter degradability and higher volatile fatty acid production than control TMR, while with buffalo rumen liquor, significant differences were observed between experimental and control diets in terms of gas production and fermentation kinetics. The tested liquid feeds can have different fermentation patterns depending on their ingredients and compositions. Supplementing liquid feeds to a standard diet seems to provide a source of energy that improves fermentation. No negative effects were observed on the in vitro fermentation at the dosage utilised

In vitro fermentation and chemical characteristics of mediterranean by-products for swine nutrition

The purpose of the study is to determine the nutritional characteristics of some by-products derived from fruit juice and olive oil production to evaluate their use in pig nutrition. Five by-products of citrus fruit (three citrus fruit pulp and two molasses) and three by-products of olive oil (olive cake) obtained by different varieties are analysed for chemical composition. The fermentation characteristics are evaluated in vitro using the gas production technique with swine faecal inoculum. All the citrus by-products are highly fermentable, producing gas and a high amount of short-chain fatty acids. The fermentation kinetics vary when comparing pulps and molasses. Citrus fruit pulps show lower and slower fermentation rates than molasses. The olive oil by-products, compared to citrus fruits ones, are richer in NDF and ADL. These characteristics negatively affect all the fermentation parameters. Therefore, the high concentration of fiber and lipids represents a key aspect in the nutrition of fattening pigs. The preliminary results obtained in this study confirm that the use of by-products in pig nutrition could represent a valid opportunity the reduce the livestock economic cost and environmental impact

The human tumor suppressor ARF interacts with Spinophilin/Neurabin II, a type 1 protein-phosphatase-binding protein

The INK4a gene, one of the most often disrupted loci in human cancer, encodes two unrelated proteins, p16(INK4a) and p14(ARF) (ARF) both capable of inducing cell cycle arrest. Although it has been clearly demonstrated that ARF inhibits cell cycle via p53 stabilization, very little is known about the involvement of ARF in other cell cycle regulatory pathways, as well as on the mechanisms responsible for activating ARF following oncoproliferative stimuli. In search of factors that might associate with ARF to control its activity or its specificity, we performed a yeast two-hybrid screen. We report here that the human homologue of spinophilin/neurabin II, a regulatory subunit of protein phosphatase 1 catalytic subunit specifically interacts with ARF, both in yeast and in mammalian cells. We also show that ectopic expression of spinophilin/neurabin II inhibits the formation of G418-resistant colonies when transfected into human and mouse cell lines, regardless of p53 and ARF status. Moreover, spinophilin/ARF coexpression in Saos-2 cells, where ARF ectopic expression is ineffective, somehow results in a synergic effect. These data demonstrate a role for spinophilin in cell growth and suggest that ARF and spinophilin could act in partially overlapping pathway