Screening of at-risk blood donors for Chagas disease in non-endemic countries: Lessons from a 2-year experience in Tuscany, Italy

Background: Chagas disease (CD) is caused by the protozoan parasite Trypanosoma cruzi and is transmitted by blood-sucking triatomine insects in endemic areas of Latin America. Transmission can also occur via blood transfusion and is a major cause of CD in non-endemic areas. Objectives: The aim of the study was to assess the prevalence of anti-T. cruzi antibodies in blood donors at risk of infection in Tuscany, Italy, following the introduction of blood safety Italian legislation. Material and methods: Donors (N = 1985) were tested in 2016 to 2018 for anti-T. cruzi IgG using an immunochromatographic test (ICT). Chemiluminescent immunoassay (CLIA) was performed on ICT-positive donors to exclude CD, whereas enzyme-linked immunosorbent assay and Western blot were performed in case of discordant results. All assays were performed on CD patients (N = 10) for validation. Results: Ten blood donors had a positive ICT result, with a resulting T. cruzi seroprevalence of 0.5% but demonstrates negative results to CLIA, as well as to the other serological assays. The comparison of serological assays suggested a lower relative sensitivity of ICT. Conclusion: The results of this study confirm the significance of serological testing in the screening strategy for TT CD. However, they provide evidence for discontinuing the use of ICT as a screening test and suggest that a sensitive, specific and multi-sample format assay should be used at the national level for uniformity of results

A deep attention based approach for predictive maintenance applications in IoT scenarios

Purpose: The recent innovations of Industry 4.0 have made it possible to easily collect data related to a production environment. In this context, information about industrial equipment – gathered by proper sensors – can be profitably used for supporting predictive maintenance (PdM) through the application of data-driven analytics based on artificial intelligence (AI) techniques. Although deep learning (DL) approaches have proven to be a quite effective solutions to the problem, one of the open research challenges remains – the design of PdM methods that are computationally efficient, and most importantly, applicable in real-world internet of things (IoT) scenarios, where they are required to be executable directly on the limited devices’ hardware. Design/methodology/approach: In this paper, the authors propose a DL approach for PdM task, which is based on a particular and very efficient architecture. The major novelty behind the proposed framework is to leverage a multi-head attention (MHA) mechanism to obtain both high results in terms of remaining useful life (RUL) estimation and low memory model storage requirements, providing the basis for a possible implementation directly on the equipment hardware. Findings: The achieved experimental results on the NASA dataset show how the authors’ approach outperforms in terms of effectiveness and efficiency the majority of the most diffused state-of-the-art techniques. Research limitations/implications: A comparison of the spatial and temporal complexity with a typical long-short term memory (LSTM) model and the state-of-the-art approaches was also done on the NASA dataset. Despite the authors’ approach achieving similar effectiveness results with respect to other approaches, it has a significantly smaller number of parameters, a smaller storage volume and lower training time. Practical implications: The proposed approach aims to find a compromise between effectiveness and efficiency, which is crucial in the industrial domain in which it is important to maximize the link between performance attained and resources allocated. The overall accuracy performances are also on par with the finest methods described in the literature. Originality/value: The proposed approach allows satisfying the requirements of modern embedded AI applications (reliability, low power consumption, etc.), finding a compromise between efficiency and effectiveness

Barium titanate nanoparticles and hypergravity stimulation improve differentiation of mesenchymal stem cells into osteoblasts.

BACKGROUND: Enhancement of the osteogenic potential of mesenchymal stem cells (MSCs) is highly desirable in the field of bone regeneration. This paper proposes a new approach for the improvement of osteogenesis combining hypergravity with osteoinductive nanoparticles (NPs). MATERIALS AND METHODS: In this study, we aimed to investigate the combined effects of hypergravity and barium titanate NPs (BTNPs) on the osteogenic differentiation of rat MSCs, and the hypergravity effects on NP internalization. To obtain the hypergravity condition, we used a large-diameter centrifuge in the presence of a BTNP-doped culture medium. We analyzed cell morphology and NP internalization with immunofluorescent staining and coherent anti-Stokes Raman scattering, respectively. Moreover, cell differentiation was evaluated both at the gene level with quantitative real-time reverse-transcription polymerase chain reaction and at the protein level with Western blotting. RESULTS: Following a 20 g treatment, we found alterations in cytoskeleton conformation, cellular shape and morphology, as well as a significant increment of expression of osteoblastic markers both at the gene and protein levels, jointly pointing to a substantial increment of NP uptake. Taken together, our findings suggest a synergistic effect of hypergravity and BTNPs in the enhancement of the osteogenic differentiation of MSCs. CONCLUSION: The obtained results could become useful in the design of new approaches in bone-tissue engineering, as well as for in vitro drug-delivery strategies where an increment of nanocarrier internalization could result in a higher drug uptake by cell and/or tissue constructs

A Framework for Recommending Multimedia Cultural Visiting Paths

In this work, we present a general framework for Cultural Heritage applications able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context- Aware recommendation services in order to generate dynamic multimedia visiting paths useful for the users during the exploration of different kinds of cultural sites. A specific application of our system within the cultural heritage domain is proposed together with some experimental results

Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models

A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particle Swarm Optimization (PSO), Adaptive Particle Swarm Optimization (APSO; the TRIBES strategy), and an existing hybrid optimization strategy (hPSO). All the strategies are tested on 2D, 5D and 10D Rosenbrock and Griewank polynomial test functions and a synthetic hydrogeologic application to identify the source of a contaminant plume in an aquifer. Tests are performed using a series of runs with random initial guesses for the estimated (function/model) parameters. Squads is observed to have the best performance when both robustness and efficiency are taken into consideration than the other strategies for all test functions and the hydrogeologic application

AI for Zero-Touch Management of Satellite Networks in B5G and 6G Infrastructures

Satellite Communication (SatCom) networks are become more and more integrated with the terrestrial telecommunication infrastructure. In this paper, we shows the current status of the still ongoing European Space Agency (ESA) project”Data-driven Network Controller Orchestration for Real time Network Management-ANChOR”. In particular, we propose a Long Short-Term Memory (LSTM)based methodology to drive the dynamic selection of the optimal satellite gateway station, which will be performed by combining different kinds of information (i.e. traffic profile, network and weather conditions). Some preliminary results on the real world dataset shows the effectiveness of the proposed approach

Interfacing polymeric scaffolds with primary pancreatic ductal adenocarcinoma cells to develop 3D cancer models

We analyzed the interactions between human primary cells from pancreatic ductal adenocarcinoma (PDAC) and polymeric scaffolds to develop 3D cancer models useful for mimicking the biology of this tumor. Three scaffold types based on two biocompatible polymeric formulations, such as poly(vinyl alcohol)/gelatin (PVA/G) mixture and poly(ethylene oxide terephthalate)/poly(butylene terephthalate) (PEOT/PBT) copolymer, were obtained via different techniques, namely, emulsion and freeze-drying, compression molding followed by salt leaching, and electrospinning. In this way, primary PDAC cells interfaced with different pore topographies, such as sponge-like pores of different shape and size or nanofiber interspaces. The aim of this study was to investigate the influence played by the scaffold architecture over cancerous cell growth and function. In all scaffolds, primary PDAC cells showed good viability and synthesized tumor-specific metalloproteinases (MMPs) such as MMP-2, and MMP-9. However, only sponge-like pores, obtained via emulsion-based and salt leaching-based techniques allowed for an organized cellular aggregation very similar to the native PDAC morphological structure. Differently, these cell clusters were not observed on PEOT/PBT electrospun scaffolds. MMP-2 and MMP-9, as active enzymes, resulted to be increased in PVA/G and PEOT/PBT sponges, respectively. These findings suggested that spongy scaffolds supported the generation of pancreatic tumor models with enhanced aggressiveness. In conclusion, primary PDAC cells showed diverse behaviors while interacting with different scaffold types that can be potentially exploited to create stage-specific pancreatic cancer models likely to provide new knowledge on the modulation and drug susceptibility of MMPs

Connexin Expression in Human Minor Salivary Glands: An Immunohistochemical Microscopy Study

Connexins (Cxs) are transmembrane proteins involved in the formation of hemichannels and gap junctions (GJs). GJs are involved in various physiological functions, including secretion in glandular tissue. It has been demonstrated that Cx26, Cx32, and Cx43 are mainly expressed in glands, but no data are available in human salivary glands to date. The aim of our study was to investigate the presence and the localization of Cxs in human minor labial salivary glands. Immunofluorescence and immunoelectron microscopy were employed to evaluate the Cx26, Cx32, and Cx43 protein in human labial salivary gland biopsies (hLSGBs). RT-PCR was also used to detect their mRNA expression. Cx expression was found at both the mRNA and protein levels in all hLSGBs analysed. Cxs were observed at the level of the duct and acinar cells, as well as in myoepithelial cells. The localization of the three Cx types was very similar, suggesting colocalization of these Cxs in the same connexons. These results demonstrated the presence of Cxs in human salivary glands for the first time. Moreover, the few samples with primary Sjogren's Syndrome analysed only by immunofluorescence showed an alteration of the Cx expression, indicating that these proteins could be involved in salivary gland dysfunctions