Effect of Hypertension on Outcomes of High-Risk Patients After BCG-Treated Bladder Cancer

Immunotherapy with Bacillus Calmette Guerin (BCG) is the most efficacious treatment for high-risk bladder cancer (BC) (Ta/T1 or carcinoma in situ) to reduce the risk of recurrence. Our aim was to evaluate whether hypertension and diabetes influence the outcome of patients with noninvasive BC treated with BCG instillations. In order to collect homogeneous data, we considered as "hypertensive" only those patients who had previous diagnosed hypertension and a history of taking medical therapy with antihypertensive drugs (AHT), and as "diabetic" only those prescribed oral antidiabetics or insulin (ADT). We analyzed 343 high-risk BC patients undergoing BCG 1995 2010) with a median follow-up of 116 months (range 48-238). The distribution of various kinds of AHT and antidiabetic drugs was homogeneous, with no significant differences (p > 0.05). In both univariate and multivariate analyses, the only statistically significant parameter propostic for recurrence after BCG treatment was AHT. Recurrence-liee survival curves showed a significant correlation with AHT (p = 0.0168, hazards ratio [HR] 1.45, 95% confidence interval [CI] 1.0692-1.9619); there was no correlation ( p = 0.9040) with ADT (HR 0.9750, 95% CI 0.6457-1.4721). After stratification of AHT and A.DT according to drug(s) prescribed, there were no significant differences in the BC recurrence rate (p > 0.05). In this study with a very long-term follow-up, hypertension alone (evaluated by AHT) revealed the increased risk of BC recurrence after BCG treatment. Several hypotheses have been formulated to support these findings, but further prospective studies are needed to both evaluate the real influence of hypertension and identify a possible prognostic factor to be used in selecting poor-prognosis BC patients as early candidates for surgical treatment

LCA of virgin and recycled materials to assess the sustainability of paved surfaces in agricultural environment

The construction sector is currently characterized by high raw material consumption but also by the production of high volume of wastes, mostly constituted by construction and demolition wastes that could be valorized promoting the use of recycled aggregates in substitution of raw aggregates. A promising application for recycled aggregates is for the realization of rural roads and pavements. The agricultural context, characterized by particular type of traffic and need to balance performance and integration with the environment, is suited for the use of these materials for paved surfaces since it can promote, in several cases, the adoption of rural circular processes internal to the farm. However, if on one hand the adoption of recycled aggregates could increase the sustainability of the sector, on the other it could increment the environmental loads if the whole process is not properly organized. For instance, the negative effects of transportation operations can cancel the environmental benefits if high distances between the production and the destination sites are present. This work reports the results of the Life Cycle Assessment (LCA), from cradle-to-gate, of four different construction aggregate classes that can be used for the realization of rural roads, pavements and forecourts, and paved areas in agricultural environment. The first three materials are recycled aggregates produced by the recycling processes of construction and demolition waste and the fourth type refers to gravel aggregates produced from natural resources. The Life Cycle Assessment was realized using site-specific primary data from the local territorial context and paying particular attention to transportation-related impacts, land use, avoided landfill and preservation of non-renewable resources. The results of the work clearly show that the environmental impacts in both scenarios of recycled aggregates are lower than the virgin aggregate scenario. In fact, considering the midpoint categories, the recycled materials proved to be more virtuous in almost all the indicators, with the exception of except for the marine eutrophication. The most significant gap between virgin and recycled materials has been in global warming and marine and freshwater eco-toxicity

Microventilation system improves the ageing conditions in existent wine cellars

Background and Aims: The importance of indoor environmental conditions in a cellar is well known and continuously investigated. The process of wine ageing consists of several steps, during which temperature (T) and relative humidity (RH) play a fundamental role as the quality of the final product is strongly related to stable and suitable environmental conditions. Critical factors, such as mould growth or wine evaporation, have emerged when ventilation has proved to be insufficient or poorly designed. The limitation of stagnant areas and the homogeneity inT and RH provide for proper wine conservation; however, unwanted local conditions can occur in the zones with insufficient air exchange. Methods and Results: Considering these aspects, a controlled microventilation and monitoring system was installed in a case study cellar, and T and RH were monitored for 1 year. The data have been analysed to investigate criticalities of the environmental conditions. The ventilation was activated in specific critical conditions to increase the homogeneity of the T and RH in the critical zones. The results show that the microventilation system improves the homogeneity of both T and RH without affecting the average values. Conclusions: The study demonstrated the efficacy of the system and indicated possible modifications to improve system performance. Significance of the Study: The system proved to be a useful tool for both improving the environmental conditions and providing useful information to the winemakers about the ageing conditions

Simulations in agricultural buildings: a machine learning approach to forecast seasonal energy need

A fast and reliable estimation of building energy need is essential in agricultural building design, nonetheless, a large number of simulations is required to obtain better energy saving solutions. The aim of this work is to understand if machine learning can substitute numerical simulations and speed up the building design process and assess the incidence of specific architectural elements. Supervised regression models has been trained and tested in a data-set of thousands simulations performed on a case-study agricultural building. Among the algorithms, the tree-based Extreme Gradient Boosting showed the best performance. A study on model explainability has been carried out using SHAP and features importance, which is fundamental to help academics and professionals devise better design strategies for both new constructions and retrofitting interventions

Assessment of the INLA approach on gerarchic bayesian models for the spatial disease distribution: a real data application

The use of approximate methods as the INLA (Integrated Nested Laplace Approximation) approach is being widely used in Bayesian inference, especially in spatial risk model estimation where the Besag-York-Mollie (BYM) model ` has found a proper use. INLA appears time saving compared to Monte Carlo simulations based on Markov Chains (MCMC), but it produces some differences in estimates [1, 2]. Data from the Veneto Cancer Registry has been considered with the scope to compare cancer incidence estimates with INLA method and with two other procedures based on MCMC simulation, WinBUGS and CARBayes, under R environment. It is noteworthy that INLA returns estimates comparable to both MCMC procedures, but it appears sensitive to the a-priori distribution. INLA is fast and efficient in particular with samples of moderate-high size. However, care must to be paid to the choice of the parameter relating to the a-priori distribution

MytiBase: a knowledgebase of mussel (M. galloprovincialis) transcribed sequences

<p>Abstract</p> <p>Background</p> <p>Although Bivalves are among the most studied marine organisms due to their ecological role, economic importance and use in pollution biomonitoring, very little information is available on the genome sequences of mussels. This study reports the functional analysis of a large-scale Expressed Sequence Tag (EST) sequencing from different tissues of <it>Mytilus galloprovincialis </it>(the Mediterranean mussel) challenged with toxic pollutants, temperature and potentially pathogenic bacteria.</p> <p>Results</p> <p>We have constructed and sequenced seventeen cDNA libraries from different Mediterranean mussel tissues: gills, digestive gland, foot, anterior and posterior adductor muscle, mantle and haemocytes. A total of 24,939 clones were sequenced from these libraries generating 18,788 high-quality ESTs which were assembled into 2,446 overlapping clusters and 4,666 singletons resulting in a total of 7,112 non-redundant sequences. In particular, a high-quality normalized cDNA library (Nor01) was constructed as determined by the high rate of gene discovery (65.6%). Bioinformatic screening of the non-redundant <it>M. galloprovincialis </it>sequences identified 159 microsatellite-containing ESTs. Clusters, consensuses, related similarities and gene ontology searches have been organized in a dedicated, searchable database <url>http://mussel.cribi.unipd.it</url>.</p> <p>Conclusion</p> <p>We defined the first species-specific catalogue of <it>M. galloprovincialis </it>ESTs including 7,112 unique transcribed sequences. Putative microsatellite markers were identified. This annotated catalogue represents a valuable platform for expression studies, marker validation and genetic linkage analysis for investigations in the biology of Mediterranean mussels.</p

Lesson learned in big data for dairy cattle: advanced analytics for heat stress detection

This report provides an overview of the strategies for data management and data analysis developed within the EU project EIT Food DairySust “Big data and advanced analytics for sustainable management of the dairy cattle sector”. The main ambition of this project is to improve sustainability and animal welfare, besides productivity, in dairy farming, through advanced data analytics for every level of stakeholders. Good data management, in terms of acquisition, processing, harmonization and imputation, is required for good modelling for early diagnosis and for the identification of optimal prevention strategies, particularly in fields where monitoring can collect very heterogeneous data, and for which agreed protocols have not yet been standardized. The project investigated the “ecosystem” of data and application strategies for sharing computer resources and information in a secure and organic manner. This research first developed an optimal computational ecosystem based on the integration and harmonization of heterogeneous data types. Classical and advanced modelling strategies were used and compared. The results are suitable to provide the stakeholders with improved decision-making process about animal welfare and sustainability of the production. This report focuses on the implementation of a numerical model for the assessment of the impact of heat stress on milk production and provides a feedback on it

Hacia la adaptación de Scrum para incorporar calidad de datos en ámbito del desarrollo ágil

En la actualidad, la mayoría de las organizaciones utilizan Sistemas de Información (SI) para llevar adelante sus procesos de negocio y toma de decisiones. Los sistemas informáticos son parte de los SI, y uno de sus elementos principales son los datos. Estos comúnmente son utilizados en diferentes ámbitos, como por ejemplo, procesos de negocio, gestión del conocimiento, toma de decisiones, explotación de la información, analítica de datos, etc. Por este motivo, resulta lógico pensar que los datos deben tener un nivel de calidad adecuado, de manera que las organizaciones puedan cumplir sus objetivos estratégicos. En el ámbito del desarrollo ágil, no es común definir, especificar e implementar requisitos de calidad en relación a los datos, y la metodología ágil Scrum no es la excepción. El objetivo de esta línea de investigación consiste en realizar una propuesta de adaptación del Framework de Scrum, para que se considere la definición, especificación e implementación de requisitos de calidad de datos, usando como referencia la Norma ISO/IEC 25000. La principal contribución de esta investigación consiste en ayudar a garantizar la calidad de los datos en contexto del desarrollo ágil, particularmente cuando se usa Scrum.Red de Universidades con Carreras en Informátic