The impact of diabetes in implant oral rehabilitations: A bibliometric study and literature review

Introduction: Diabetes represents a potential risk factor for bone healing and dental implant treatment predictability. The aim of the present investigation was to perform a bibliometric evaluation of articles on the topic of the impact of diabetes on implant oral rehabilitations. Material and methods: A Boolean keywords search was performed on Scopus database and recorded the list of articles, authors and affiliations. The journal impact factor was calculated by the Journal Citation Report Clarivate electronic database. The total papers, number of citations and journal impact factors were calculated. Results: a total of 476 papers and 162 authors were assessed. The mean authors total citations were 2880.11± 4070.24 and the mean impact factor value was 1.942±1.15 Conclusions: uncontrolled diabetes impacts on dental implant rehabilitation with an increased risk of implant failure and periimplant disease in long-term rehabilitation

In search of knowledge: text mining dedicated to technical translation

Articolo pubblicato su CD e commercializzato direttamente dall'ASLIB (http://shop.emeraldinsight.com/product_info.htm/cPath/56_59/products_id/431). Programma del convegno su http://aslib.co.uk/conferences/tc_2011/programme.htm

Global recession and higher education in eastern Asia: China, Mongolia and Vietnam

This paper presents a perspective on the capacity of colleges and universities during past and present economic shocks. The main argument is that the environment of the global recession-an Asia far more economically integrated than during past economic shocks, with more unified aspirations to be globally competitive and socially responsible-no longer delay reforms in higher education. In fact, the global recession has become an opportune time for higher education in Asia, specifically developing countries in eastern (East and Southeast) Asia, to continue reforming governance and administration, access and equity, internal and external efficiency, and regional collaboration. Economic shocks have accelerated reforms in higher education, especially those for promoting innovation in their economies, though more is needed in improving governance and access for underserved populations. This paper examines the cases of China, Mongolia, and Vietnam as examples of how the global recession and regional integration are growing forces in shaping their higher education reform and development. The paper also identifies a series of measures for increasing the resilience of higher education systems in serving poor and vulnerable populations during economic recessions. Responses to the global economic recession by nations in eastern Asia are likely to improve the global shift in economy and human capital. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

Neural networks for fatigue crack propagation predictions in real-time under uncertainty

Crack propagation analyses are fundamental for all mechanical structures for which safety must be guaranteed, e. g. as for the aviation and aerospace fields. The estimation of life for structures in presence of defects is a process inevitably affected by numerous and unavoidable uncertainty and variability sources, whose effects need to be quantified to avoid unexpected failures or excessive conservativism. In this work, residual fatigue life prediction models have been created through neural networks for the purpose of performing probabilistic life predictions of damaged structures in real-time and under stochastically varying input parameters. In detail, five different neural network architectures have been compared in terms of accuracy, computational runtimes and minimum number of samples needed for training, so to determine the ideal architecture with the strongest generalization power. The networks have been trained, validated and tested by using the fatigue life predictions computed by means of simulations developed with FEM and Monte Carlo methods. A real-world case study has been presented to show how the proposed approach can deliver accurate life predictions even when input data are uncertain and highly variable. Results demonstrated that the “H1-L1” neural network has been the best model, achieving an accuracy (Mean Square Error) of 4.8e-7 on the test dataset, and the best and the most stable results when decreasing the amount of data. Additionally, since requiring only very few parameters, its potential applicability for Structural Health Monitoring purposes in small cost-effective GPU devices resulted to be attractive

On the use of neural networks and statistical tools for nonlinear modeling and on-field diagnosis of solid oxide fuel cell stacks

Abstract The paper reports on the activities performed within the European funded project GENIUS to develop black-box models for modeling and diagnosis of solid oxide fuel cell (SOFC) stacks. Two modeling techniques were investigated, i.e. Neural Networks (NNs) and Statistical Tools (STs). The deployment of NNs was twofold: Recurrent Neural Networks (RNNs) and an NN classifier were developed to simulate transient operation of SOFCs and identify some specific faults that may occur in such devices, respectively. On the other hand, STs are based on a stepwise multiple regression. Data for model development were obtained from experiments specifically designed to reach maximal information content. The final aim was to obtain highly general models of SOFC stacks' operation in both transient and steady state. All the developed black-box models exhibited high accuracy and reliability on both training and test data-sets. Moreover, the black-box models were also proven effective in performing real-time monitoring and degradation analysis for different SOFC stack technologies

Profile of Trypanosoma cruzi Infection in a Tropical Medicine Reference Center, Northern Italy

Chagas disease (CD) is endemic in Central and South America, Mexico and even in some areas of the United States. However, cases have been increasingly recorded also in non-endemic countries. The estimated number of infected people in Europe is in a wide range of 14000 to 181000 subjects, mostly resident in Spain, Italy and the United Kingdom

Impact of COVID-19 pandemic lockdown on narcolepsy type 1 management

Study Objectives: Narcolepsy type 1 (NT1) is a chronic rare hypersomnia of central origin requiring a combination of behavioral and pharmacological treatments. During the coronavirus disease 2019 (COVID-19) pandemic, in Italy the population was forced into a lockdown. With this study, we aimed to describe the lockdown impact on NT1 symptom management, according to different patients' working schedule. Methods: In the period between 10 April and 15 May 2020, we performed routine follow-up visits by telephone (as recommended during the COVID-19 emergency) to 50 patients >18 years old (40% males) under stable long-term treatment. We divided patients into three groups: unchanged working schedule, forced working/studying at home, and those who lost their job (“lost occupation”). Current sleep–wake habit and symptom severity were compared with prelockdown assessment (six months before) in the three patient groups. Results: At assessment, 20, 22, and eight patients belonged to the unchanged, working/studying at home, and lost occupation groups, respectively. While in the lost occupation group, there were no significant differences compared with prepandemic assessment, the patients with unchanged schedules reported more nocturnal awakenings, and NT1 patients working/studying at home showed an extension of nocturnal sleep time, more frequent daytime napping, improvement of daytime sleepiness, and a significant increase in their body mass index. Sleep-related paralysis/hallucinations, automatic behaviors, cataplexy, and disturbed nocturnal sleep did not differ. Conclusions: Narcolepsy type 1 patients working/studying at home intensified behavioral interventions (increased nocturnal sleep time and daytime napping) and ameliorated daytime sleepiness despite presenting with a slight, but significant, increase of weight

A Genome-Wide Screening and SNPs-to-Genes Approach to Identify Novel Genetic Risk Factors Associated with Frontotemporal Dementia

Frontotemporal dementia (FTD) is the second most prevalent form of early onset dementia after Alzheimer’s disease (AD). We performed a case-control association study in an Italian FTD cohort (n = 530) followed by the novel SNPs-to-genes approach and functional annotation analysis. We identified two novel potential loci for FTD. Suggestive SNPs reached p-values ~10-7 and OR > 2.5 (2p16.3) and 1.5 (17q25.3). Suggestive alleles at 17q25.3 identified a disease-associated haplotype causing decreased expression of -cis genes such as RFNG and AATK involved in neuronal genesis and differentiation, and axon outgrowth, respectively. We replicated this locus through the SNPs-to-genes approach. Our functional annotation analysis indicated significant enrichment for functions of the brain (neuronal genesis, differentiation and maturation), the synapse (neurotransmission and synapse plasticity), and elements of the immune system, the latter supporting our recent international FTD-GWAS. This is the largest genome-wide study in Italian FTD to date. Although our results are not conclusive, we set the basis for future replication studies and identification of susceptible molecular mechanisms involved in FTD pathogenesis

The Urokinase/Urokinase Receptor System in Mast Cells: Effects of its Functional Interaction with fMLF Receptors.

Mast cell and basophils express the high affinity receptor for IgE (FcɛRI) and are primary effector cells of allergic disorders. The urokinase (uPA)-mediated plasminogen activation system is involved in physiological and pathological events based on cell migration and tissue remodelling, such as inflammation, wound healing, angiogenesis and metastasis. uPA is a serine protease that binds uPAR, a high affinity glycosyl-phosphatidyl-inositol (GPI)-anchored receptor. uPAR focuses uPA activity at the cell surface and activates intracellular signaling through lateral interactions with integrins, receptor tyrosine kinases and the G-protein-coupled family of fMLF chemotaxis receptors (FPRs). We investigated the expression of the uPA-uPAR system and its functional interaction with FPRs in human mast cells (MCs). Differently from basophils, MCs produced uPA that was able to induce their chemotaxis. Indeed, MCs also expressed uPAR, both in the intact and in a cleaved form (DII-DIII-uPAR) that can expose, at the N-terminus, the SRSRY sequence, able to interact with FPRs and to mediate cell chemotaxis. MCs also expressed mRNAs for FPRs that were functionally active; indeed, uPA and a soluble peptide (uPAR84-95), containing the SRSRY chemotactic sequence of uPAR and able to interact with FPRs, were able to induce MCs chemotaxis. Thus, uPA is a potent chemoattractant for MCs acting through the exposure of the chemotactic epitope of uPAR, that is an endogenous ligand for FPRs. The same mechanism could be involved in VEGF-A secretion by human MCs, also induced by uPA and uPAR84-95 stimulation