Ex-vivo recruitment and x-ray assessment of donor lungs in a challenging retrieval from a donor supported by lvad using the portable normothermic perfusion system: A case report

Lung transplantation (LTx) is limited by the shortage of suitable donors. To overcome this problem, many programs have begun to use donors with extended criteria (marginal donors). However, brain-dead patients with implanted mechanical circulatory support system have rarely been considered as potential lung donors. This case demonstrates the feasibility of lung transplantations from organ donors supported by a mechanical circulatory support system despite the possible difficulties of lung retrieval. CASE PRESENTATION: Our case presents a successful procurement and bilateral lung transplantation from a donor supported by a left ventricular assist device (LVAD) who experienced an intraoperatively haemodynamic complication. The use of portable normothermic perfusion device let us to reduce ischemic injury and assess these marginal donor lungs helping us to determine the clinical suitability for transplantation. Given our extensive experience with the device instrumentation and management, the EVLP process was uneventful with excellent post-transplant course. CONCLUSIONS: This case report demonstrates the feasibility of lung transplantations from organ donors supported by a mechanical circulatory support system using the portable normothermic perfusion platform to assess and preserve these donor lungs

Creativity and Autism Spectrum Conditions: a Hypothesis on Lewis Carroll

The hypothesis formulated by Simon Baron-Cohen and his collaborators on the onset of autistic syndromes and their link with an excess of the so-called S brain is reflected in the work of Lewis Carroll, a formal logic and mathematics professor deeply inclined to visual and spatial descriptions, interested in affordances and systemic circuits, and devoid of empathic tendencies in creating his characters. In the future, this finding may serve as a test for predicting autism spectrum disorders and support the elaboration of narrative artefact for therapeutic purposes in relation to people with autism

Creativity and Autism Spectrum Conditions: a Hypothesis on Lewis Carroll

The hypothesis formulated by Simon Baron-Cohen and his collaborators on the onset of autistic syndromes and their link with an excess of the so-called S brain is reflected in the work of Lewis Carroll, a formal logic and mathematics professor deeply inclined to visual and spatial descriptions, interested in affordances and systemic circuits, and devoid of empathic tendencies in creating his characters. In the future, this finding may serve as a test for predicting autism spectrum disorders and support the elaboration of narrative artefact for therapeutic purposes in relation to people with autism

Ultrasound of the Small Bowel in Crohn's Disease

Several radiological and endoscopic techniques are now available for the study of inflammatory bowel diseases. In everyday practice, the choice of the technique to be used depends upon its availability and a careful evaluation of diagnostic accuracy, clinical usefulness, safety, and cost. The recent development of innovative and noninvasive imaging techniques has led to a new and exciting area in the exploration of the gastrointestinal tract, especially in Crohn's disease patients by using ultrasound with oral or intravenous contrast

A cross‐sectorial review of industrial best practices and case histories on Industry 4.0 technologies

Industry 4.0 (I4.0) was introduced in 2011, and its advanced enablers strongly affect industrial practices. In the current literature, while several papers offer general reviews on the topic, contributions exploring the evidences coming from the implementation of I4.0 in multi-sector Small and Medium Enterprises (SMEs) and large enterprises are few and expected. To address this gap, a comprehensive review of the main I4.0 enabling technologies is conducted, focusing on implementation experiences in companies belonging to different sectors. Forty (40) real case studies are analyzed and compared. The results show that 63% of the identified applications involve large enterprises in the transport sector, that is, automotive, aeronautics, and railway, adopting a structured set of enabling technologies. SMEs engaged in I4.0 projects primarily belong to the mechanical engineering sector, and 37% of such projects deals with the preliminary feasibility analysis of introducing a single enabling technology. Conclusions and trends guide researchers and practitioners in understanding the implementation level of I4.0 technologies

Integrating Machine Learning Paradigms for Predictive Maintenance in the Fourth Industrial Revolution era

In the last decade, manufacturing companies have been facing two significant challenges. First, digitalization imposes adopting Industry 4.0 technologies and allows creating smart, connected, self-aware, and self-predictive factories. Second, the attention on sustainability imposes to evaluate and reduce the impact of the implemented solutions from economic and social points of view. In manufacturing companies, the maintenance of physical assets assumes a critical role. Increasing the reliability and the availability of production systems leads to the minimization of systems’ downtimes; In addition, the proper system functioning avoids production wastes and potentially catastrophic accidents. Digitalization and new ICT technologies have assumed a relevant role in maintenance strategies. They allow assessing the health condition of machinery at any point in time. Moreover, they allow predicting the future behavior of machinery so that maintenance interventions can be planned, and the useful life of components can be exploited until the time instant before their fault. This dissertation provides insights on Predictive Maintenance goals and tools in Industry 4.0 and proposes a novel data acquisition, processing, sharing, and storage framework that addresses typical issues machine producers and users encounter. The research elaborates on two research questions that narrow down the potential approaches to data acquisition, processing, and analysis for fault diagnostics in evolving environments. The research activity is developed according to a research framework, where the research questions are addressed by research levers that are explored according to research topics. Each topic requires a specific set of methods and approaches; however, the overarching methodological approach presented in this dissertation includes three fundamental aspects: the maximization of the quality level of input data, the use of Machine Learning methods for data analysis, and the use of case studies deriving from both controlled environments (laboratory) and real-world instances

prognostic health management of production systems new proposed approach and experimental evidences

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Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success

open5AIM To develop a survey to help define the main problems in radiological clinical trials. METHODS Since 2006, we have managed seven different radio-logical clinical trials recruiting patients in academic and non-academic centres. We developed a preliminary questionnaire using a four-round Delphi approach to identify problems occurring in radiological clinical trials run at our centre. We investigated the recruitment experience, involvement of all multi-disciplinary team members and main obstacles to completing the projects. A final round of Delphi processes elucidated solutions to the identified problems.openValdora, Francesca; Bignotti, Bianca; Calabrese, Massimo; Houssami, Nehmat; Tagliafico, AlbertoValdora, Francesca; Bignotti, Bianca; Calabrese, Massimo; Houssami, Nehmat; Tagliafico, Albert