Background and objectivesː Physical examination is the predominant method for evaluating pelvic floor defects. Magnetic Resonance Imaging (MRI) is a radiological technique useful to identify the underlying defects of pelvic floor structures that require surgery. The primary aim was to find correspondence between the clinical and radiological staging of pelvic organ prolapse (POP) before and after vaginal surgery. A secondary endpoint was to investigate, through clinical and MRI findings if surgery influences continence mechanisms. Finally, we reported changes in the quality of life in women who underwent surgery for prolapse. Materials and methodsː Twenty-five women with prolapse stage ≥ 2 POP-Q were recruited in this prospective study. They underwent preoperative clinical examination, MRI at rest and under the Valsalva maneuver, and quality of life questionnaires. Three months after vaginal surgery they repeated clinical and radiological evaluation. Resultsː Twenty women completed the study. Both clinical and MRI evaluations showed an improvement in prolapse and symptoms after surgery. There were some discrepancies between clinical and radiological staging. MRI parameters did not show differences between pre and postoperative at rest; under the Valsalva maneuver instead, the measurements changed after surgery. Continence was not worsening by the widening of the vesicourethral angle. Patients reported improvement in quality of life. Conclusionsː MRI is an accurate and objective method to define the stage of prolapse but the clinical evaluation alone is sufficient to stage prolapse before surgery and evaluate the result at follow-up. It is an accurate method to visualize some pelvic structures that can be compromised because of pelvic organ prolapse. MRI showed that vaginal surgery doesn’t affect continence mechanisms.

Optical forces are used to aggregate plasmonic nanoparticles and create SERS-active hot spots in liquid. When biomolecules are added to the nanoparticles, high sensitivity SERS detection is accomplished. Here we tailor this methodology to detect catalase and hemoglobin, two Raman resonant biomolecules, at concentrations down to 10 nM and 1 pM. Subsequently, we study the SERS signal in Bovine Serum Albumin as a function of the concentration, finding a monotonic dependence that suggests the possibility of quantitative detection. Finally, by exploiting nanoparticles functionalized with specific aptamers, we obtain first results on the SERS detection of Ochratoxin A, a fungal toxin found in food commodities and wine. This represents a first step towards the addition of molecular specificity to this novel biosensor strategy.

This study examines change detection techniques in dense point clouds for the purpose of Cultural Heritage preservation, with a particular focus on the San Pietro Barisano Bell Tower in Matera, Italy. Dense point clouds, obtained via advanced laser scanning, offer detailed 3D representations of heritage structures, facilitating the precise monitoring changes over time. The investigation uses a variety of change detection algorithms, including the Iterative Closest Point (ICP) algorithm, which is renowned for its robust registration capabilities in aligning point clouds with high accuracy. The combination of ICP with deviation analysis and feature-based methods allows for the effective identification of alterations, including deformations, material loss, and surface degradation. This methodology establishes a comprehensive framework for the monitoring of Cultural Heritage, thereby enabling timely and targeted preservation efforts. The results emphasise the substantial contribution of dense point cloud analysis to the enhancement of heritage management and the safeguarding of vulnerable architectural sites.

We analyze the information that can be retrieved from the tracking parameters produced by an innovative wearable eye tracker. The latter is based on a permanent-magnet marked corneal lens and by an array of magnetoresistive detectors that measure the magnetostatic field in several positions in the eye proximity. We demonstrate that, despite missing information due to the axial symmetry of the measured field, physiological constraints or measurement conditions make possible to infer complete eye-pose data. Angular precision and accuracy achieved with the current prototypical device are also assessed and briefly discussed. The results show that the instrumentation considered is suitable as a new, moderately invasive medical diagnostics for the characterization of ocular movements and associated disorders.

This paper provides an exhaustive narrative review of third-generation antipsychotics (TGAs), focusing on aripiprazole, cariprazine, brexpiprazole, and lurasidone for managing substance-induced psychosis. It includes a comprehensive literature review to evaluate the efficacy and tolerability of these medications. The paper emphasizes the distinct challenges in treating substance-induced psychosis, which is a psychiatric condition triggered by the misuse or withdrawal of various substances, leading to symptoms like hallucinations and delusions, and is distinct from primary psychotic disorders. It underscores the potential of TGAs in addressing both psychotic symptoms and substance-related issues, while highlighting the need for more research on long-term effects and advocating for an integrated approach combining pharmacological and psychological interventions

Power disaggregation aims at determining the appliance-by-appliance electricity consumption leveraging upon a single meter only, which measures the entire power demand. Data-driven procedures based on Factorial Hidden Markov Models have been proven remarkable results on energy disaggregation. Nevertheless, those procedures have various weaknesses: there is a scalability problem as the number of devices to observe raises and the algorithmic complexity of the inference step is severe. DNN architectures, such as Convolutional Neural Networks, have demonstrated to be a viable solution to deal with FHMMs shortcomings. Nonetheless, there are two significant limitations: a complicated and time-consuming training system based on back-propagation has to be employed to estimates the neural architecture parameters, and large amounts of training data covering as many operation conditions as possible need to be collected to attain top performances. In this work, we aim to overcome those limitations by leveraging upon the unique and useful characteristics of the extreme learning machine technique, which is based on a collection of randomly chosen hidden units and analytically defined output weights. Experiment evaluation has been conducted using the UK-DALE corpus. We find that the suggested approach achieves similar performances to recently proposed ANN-based methods and outperforms FHMMs. Besides, our solution generalises well to unseen houses.

Silicon-based thin-films and nanostructures are of paramount importance in a wide range of applications, including microelectronics, photovoltaics, large area sensors, as well as biomedicine. The wide accessibility of silicon and its relatively low cost have driven a continuous improvement of the technology based on this element. Plasma technology has been widely used for the synthesis of coatings and nanostructures based on silicon. Moreover, it has given a fundamental contribution for continuously improving the control of the physicochemical properties of silicon-based materials, and for allowing the synthesis of nanometric structures with well-defined shape and morphology. In this work, we have reviewed the most interesting developments of plasma-assisted processed for the synthesis of Si-based materials, both inorganic and organic, in the last five years. A special attention has been given to the new techniques, or modifications of already existing ones, that open new possibilities for the synthesis of materials with new properties, as well as nanostructures with novel characteristics.

Ecological information of invasive alien species are crucial for their effective management. How-ever, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore where the species is present since 1990 but no scientific infor-mation are available on its ecology. To start filling this knowledge gap, 236 catfish (67 cm to 150 cm of total length) were collected, measured, and dissected for stomach content analyses from three localities and in two habitats (littoral vs. pelagic) in late autumn/early winter. NPUE and BPUE (individuals and biomass (g) per unit effort (m2)) of catfish was generally higher in littoral (NPUE > 0.01; BPUE > 96) than pelagic habitats (NPUE < 0.009; BPUE < 114) but catfish had, on average, larger sizes in pelagic habitats. Overall, 581 individual prey items were recorded belonging to12 taxa. Pelagic catfish specialized their diet exclusively on three prey fish (coregonids, shad and roach) whilst the diet of littoral catfish was more variable, and was dominated by crayfish, perch, and roach. These results highlighted for the first time the interaction of larger catfish with the lake’s pelagic food web, and thus possible consequences are discussed, including the potential contrasting role S. glanis may have for the lake’s fishery.

In Mexico there is a deficit in the production of pine resin, because it depends on natural forests. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation of resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94 % rosin, 7.7 % turpentine and 11.49 % water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g_1, respectively. All variables showed differences (p≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71 % to the total variance, the error contributed between 88.29 and 93.56 %. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

The rapid and accurate detection of viruses and the discovery of single nucleotide polymorphisms (SNPs) are crucial for disease management and understanding viral evolution. In this study, a pipeline for virus detection, validation, and SNP discovery from next-generation sequencing (NGS) data is presented. By integrating state-of-the-art bioinformatics tools with artificial intelligence, the pipeline processes raw sequencing data to identify viral sequences with high accuracy and sensitivity. Before aligning the reads to the reference genomes, quality control measures and adapter trimming are performed to ensure the integrity of the data. Unmapped reads are subjected to de novo assembly to reveal novel viral sequences and genetic elements. The effectiveness of the pipeline is demonstrated by the identification of virus sequences, illustrating its potential for the detection of known and emerging pathogens. SNP discovery is performed using a custom Python script that compares the entire population of sequenced viral reads to a reference genome. This approach provides a comprehensive overview of viral genetic diversity and identifies dominant variants and a spectrum of genetic variations. The robustness of the pipeline is confirmed by the recovery of complete viral sequences, which improves our understanding of viral genomics. This study highlights the synergy between traditional bioinformatics techniques and modern approaches, providing a robust tool for analyzing viral genomes and contributing to the broader field of viral genomics.

Tumid Lupus Erythematosus has been the subject of heated debate as to its correct nosographic classification. In particular, its definition has changed over time, depending on the different studies performed. In this review we address the initial definition of TLE, the changes that have taken place in the understanding and placement within the classification of Lupus Erythematosus (LE), and focus on clinical, histopathological, immunophenotypical and differential diagnosis aspects.

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open source energy system models, it has emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system that is used to reproduce and understand its behaviour under given conditions, without seeking an optimal solution. Given the lack of simulation models that are also fully open source, in this paper a new open source energy system model is presented. The developed tool, called Multi Energy Systems Simulator (MESS), is a modular, multi-node model that allows to investigate non optimal solutions by simulating the energy system. The model has been built having in mind urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be be represented as well. MESS is capable of performing analysis on systems composed by multiple energy carriers (e.g. electricity, heat, fuels). In this work, the tool’s features will be presented by a comparison between MESS itself and an optimization model, in order to analyze and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development.

Adipose tissue-derived stem cells (ADSCs) represent a subset of mesenchymal stem cells in every adipose compartment throughout the body. ADSCs can differentiate into various cell types, including chondrocytes, osteocytes, myocytes, and adipocytes. Moreover, they exhibit a notable potential to differentiate in vitro into cells from other germinal lineages, including endothelial cells and neurons. ADSCs have a wide range of clinical applications, from breast surgery to chronic wounds. Furthermore, they are a promising cell population for future tissue-engineering uses. Accumulating evidence indicates decreased proliferation and differentiation potential of ADSCs with increasing age, body mass index, diabetes mellitus, metabolic syndrome, or exposure to radiotherapy. Therefore, recent literature thoroughly investigates this cell population's senescence mechanisms and how they can hinder their possible therapeutic applications. This review will discuss the biological mechanisms and the physio-pathological causes behind ADSC senescence and how they can impact cellular functionality. Moreover, we will examine the possible strategies to invert these processes, re-establishing the full regenerative potential of this progenitor population.

Lichen Amyloidosis (LA) is a type of cutaneous amyloidosis characterized by brownish hyperkeratotic and itchy papules on the lower leg, back, forearm or thigh. It is associated with itching and Atopic Dermatitis (AD) according to an etiopathogenetic mechanism that has not yet been fully elucidated. Currently, available therapies for this condition include oral antihistamines, laser, cyclosporine, topical corticosteroids and phototherapy, but in light of the overlap with AD, Dupilumab may also be indicated. We report the case of a female, 52 years old, suffering from AD and LA for about 27 years. She had lesions attributable to both diseases on the trunk and lower limbs associated with severe itching and had proved resistant to cyclosporine therapy. It was decided to opt for Dupilumab with induction of 2 fl of 300 mg and maintenance with 1 fl every other week. The therapy proved effective, returning a total resolution of both diseases one year after the beginning of the treatment. Dupilumab demonstrated efficacy and safety in LA related to AD and led to clinical and quality of life improvement in this patient. Therefore, Dupilumab should be considered when treating LA. Further studies should be conducted focusing on the efficacy of the drug on LA (whether or not related to AD), changes in skin lesions after discontinuation, and the safety of long-term application.

The dynamic response of a Bell-and-Bloom magnetometer to a parallel (to the bias field) time-dependent field is modelled beyond the commonly assumed quasi-static regime. The results unveil features that are related to the parametric nature of the considered system. It is shown that a for low-amplitude time-dependent field different operating conditions are possible and that, beside the commonly reported low-pass-filter behaviour, a band-pass response emerges. Moreover, we numerically show that for larger field amplitude the system, due to its parametric nature, has a kind of ``non-linear'' response.

Sequential reactions of aminoalkynes represent a powerful tool to easily assembly biologically important polyfunctionalized nitrogen heterocyclic scaffolds. Metal catalysis often plays a key role in terms of selectivity, efficiency, atom economy and green chemistry of these sequential approaches. This review examines the existing literature on the applications of reactions of aminoalkynes with carbonyls which are emerging for their synthetic potential. Aspect concerning the features of the starting reagents, the catalytic systems, alternative reaction conditions and the pathways as well as the possible intermediates are provided.

Abdominal aortic aneurysm (AAA) represents an important public health problem with a prevalence between 1.3% and 12.5%. Several population-based randomized trials have evaluated ultrasound screening for AAA providing evidence of a reduction in aneurysm-related mortality in the screened population. The aim of our study was to perform a systematic review and meta-analysis of the risk factors for AAA. We conducted a systematic review of observational studies and we performed a meta-analysis that evaluated the following risk factors: gender, smoking habits, hypertension, diabetes mellitus, Coronary Artery Disease and family history of AAA. Abdominal aortic aneurysm prevalence is higher in smokers and in males. It is important to underline that all countries, where AAA screening was set up, had high income level and the majority belong to Western Europe (United Kingdom, Sweden, Italy, Poland, Spain and Belgium). Abdominal aortic aneurysm screening is fundamental for public health. It would avoid deaths, ruptures, and emergency surgical interventions if abdominal aortic aneurysm was diagnosed early in the population target for screening.

Mini-drones can be used for a variety of tasks, such as weather monitoring, package delivery, search and rescue, and recreation. Their uses are mostly restricted to outside locations with access to the Global Positioning System (GPS) and/or similar systems since their usefulness, safety, and performance substantially rely on ubiquitously accurate positioning and navigation. Indoor localization is getting better, thanks to technologies like Visual Simultaneous Localization and Mapping (V-SLAM). However, more advancements are still required for mini-drone navigation applications with greater safety standards. In this research, a novel method for enhancing indoor mini-drone localization performance is proposed. By merging Oriented Rotated Brief SLAM (ORB-SLAM2), Semi-Direct Monocular Visual Odometry (SVO), and an Adaptive Complementary Filter, the suggested strategy improves V-SLAM approaches (ACF). The findings demonstrate that, when compared to other widely-used indoor localization algorithms, the suggested methodology performs better at estimating location under various situations (low light, low texture, and dynamic environments).

Graphs are largely used in computer science to model relations, or associations, among entities the compose complex systems. More recently, they found a broad field of application in bioinformatics and medical informatics supporting modelling, analysis of many systems. The applications span from representing interactions among molecules within cells, to model the functions of the brains. In order to support research, algorithms from graph theory that are able to extract knowledge from network should be coupled to efficient visualisation techniques. Although the importance of such topic, we retain that many challenges should be faced in the futures, such as automated pathway and network layout to better match biologists’ needs, the developing of a standard able to give more and better choices to represent nodes, edges finally, the developing of automated mechanism able to improve the network navigation methods that help users manage large and complex networks with the goal to improve the usability.

Fish Aggregating Devices (FADs) are anchored floating structures often made with cheap scrapped materials and used to aggregate pelagic fish under their artificial shadow. Globally, the dangerous impact of FADs has well known. They pose a severe threat due to known and unknown levels of bycatch, the danger to navigation, and their high potential to become marine litter. Entanglement and consequent mortality in FADs of protected species and species of conservation concern (e.g., sharks, sea turtles, and cetaceans) are a serious concern for several international inter-governmental bodies (e.g., EU, GFCM, and IWC). This work describes the first case of a cetacean, a striped dolphin (Stenella coeruleoalba), killed by a FAD in the Mediterranean Sea. This dolphin was found stranded along the coast of the central Tyrrhenian Sea. The evidence suggests that this specimen suffered a painful death. Although this is the first confirmed case of a cetacean killed by a FAD in Italian waters, given the extent of the deployment of FADs, the scale of this type of interaction with protected species might be seriously underestimated. Therefore, actions and monitoring need to be implemented urgently to effectively protect and conserve marine biodiversity.

In this study, the external magnetic field emitted by a wireless power transfer (WPT) system and the internal electric field induced into human body models during recharging operations of a compact electric vehicle (EV) are evaluated. To this aim an ad-hoc formulation for the source modeling is coupled with a commercial software that performs numerical dosimetry. Specifically, two realistic anatomical models both in a driving position and in a standing posture are considered, and the chassis of the EV is modeled either as a currently employed aluminum alloys and as a futuristic carbon fiber composite panel. Aligned and misaligned coil configurations of the WPT system are considered as well. The analysis of the obtained results shows that the ICNIRP reference levels are exceeded in the driving position, especially for the carbon fiber chassis, whereas no exceedance is observed in terms of basic restrictions, at least for the considered scenarios.

This study aimed to evaluate the hazards posed by foodborne bacteria of the Listeria genus by analyzing prevalence, diversity and virulence of Listeria spp. in food and food manufacturing plants. Seventy five isolates obtained from the routine analysis of 653 samples by three diagnostic laboratories in Northern Italy were genotipically differentiated by Repetitive Extragenic Palindrome (rep) PCR with the GTG5 primer, identified by sequencing the 16S rRNA gene and examined by specific PCR tests for the presence of L. monocytogenes virulence determinants occasionally found to occur in other species of the genus. The identity of the amplification products was confirmed by sequencing. Fifty seven isolates were identified as L. innocua, 12 as L. monocytogenes, 5 as L. welshimeri and one as L. seeligeri. All L. monocytogenes isolates belonged to the serotype 1/2a and were predicted to be virulent for the presence of the inlJ internalin gene. Potentially virulent strains of L. innocua, L. seeligeri and L. welshimeri, carrying the L. monocytogenes inlA gene and/or hly gene, were identified, and most isolates were found to possess the toxin-antitoxin system mazEF for efficient adaptation to heat shock. Results indicated the need to reinforce food contamination prevention measures against all Listeria species by efficiently defining their environmental distribution.

Neural or mental simulation of actions is a powerful tool for allowing cognitive agents to develop Prospection Capabilities that are crucial for learning and memorizing key aspects for challenging skills. In previous studies we developed an approach based on the animation of the redundant human Body Schema based on the Passive Motion Paradigm (PMP). In this paper we show that this approach can be easily extended to hyper-redundant serpentine robots as well as to hybrid configurations where the serpentine robot is functionally integrated with a traditional skeletal infrastructure. A simulation model is analyzed in detail showing that it incorporates spatio-temporal features discovered in the biomechanical studies of biological hydrostats like the elephant trunk or the octopus tentacles. It is proposed that such generative internal model can be the basis for a cognitive architecture appropriate for serpentine robots, independent of the underlying design and control technologies. Although robotic hydrostats have received a lot of attention in the last decades, the great majority of research activities have been focused on the actuation/sensorial/material technologies that can support the design of hyperredundant soft robots as well as the related control methodologies. The cognitive level of analysis has been limited to motion planning, without addressing synergy formation and metal time travel. This is where the contribution of the paper is focused on.

This paper provides a comprehensive overview of the potential applications of dual energy CT (DECT) in improving image quality and diagnostic capabilities of CT arthrography (CTA) in clinical practice. The paper covers the use of virtual non contrast (VNC) images, in which the injected contrast medium is reduced from the articular cavity, in order to better analyze 2D and 3D images of the bone. Moreover , virtual monoenergetic imaging (VMI) applications and their potential use for the reduction of metal artifacts and improving image contrast are reviewed. The role of virtual non calcium (VNCa) in detecting bone marrow edema surrounding the imaged joint will be discussed. Furthermore , the role of iodine map to enhance the contrast between soft tissues, optimizing the visualization of contrast material, and to distinguish contrast material from calcifications is described. Finally, a case series including different joints is provided to underline the additional advantages of high spatial resolution dual energy CT reconstructed images.

The Italian Stone Pine (Pinus pinea L.) is one of the most employed ornamental trees in towns with Mediterranean climates. For example, in the city of Rome, Pinus is the most common genus, with more than 51,000 trees. This study investigates technical and economic features of maintenance operations of Stone Pines and evaluates the productivity and costs of the observed yards. Pruning and felling are the most frequent management operations of trees in towns and this study analyzes the features of these operations carried out in 14 work sites. The operations were carried out either with aerial platforms (19 trees) or ascending the crown by tree-climbing (6 trees). The operations were sampled with time studies (12 trees for pruning and 13 for felling). Work time was measured from the beginning of operations to the transport of the residual biomass to the collection and loading point, using centesimal stopwatches and video recording. The total residual biomass was weighed or assessed. Total observation time amounted to 63.1 hours. The evaluation of the costs of each work site considered the fixed and the variable costs and the costs for the labor force. A Multiple Linear Regression model (statistics: determination coefficient R2: 0.74, adjusted R2: 0.67, p-value < 0.001) which utilizes four regressors easily evaluable before the work, was adopted to predict the gross time of the operations. This paper can contribute to optimize trees maintenance methods in urban sites and to assess the potential residual wood biomass attainable from urban forestry maintenance in the city of Rome.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

The COVID-19 appears as a catastrophic health risk with psychological, emotional, social and relational implications. From the early stages of the virus spread, the elderly population was identified as the most vulnerable and the health authorities have rightly focused on such frailest population. Conversely, less attention was paid to emotional and psychological dimension of children and adolescents. Actually, they were less at risk quoad vitam or quoad valetudinem, nevertheless they had to face a reality of anxiety, fears and uncertainties. The current study investigated state anxiety and emotion awareness in a healthy sample of older adolescents, 84 females and 64 males, aged 17 to 19, during the pandemic lockdown, using Self-rating Anxiety Scale and the Italian Emotion Awareness Questionnaire. An unexpected anxious phenomenology, impacting the anxiety ideo-affective domain, was found, while the somatic symptomatology appeared to be less severe. The highest anxiety symptom were the breathing difficulties. These findings supported the hypothesis that the COVID-19 pandemic may be a risk condition for an increased state anxiety in older adolescents and suggest the need to provide 1. an effective, empathic communication system with the direct participation of older adolescents, 2. a psychological counseling service for stress management of adolescents.

Idiopathic acute pancreatitis (IAP) presents a diagnostic challenge and refers to cases where the cause of acute pancreatitis remains uncertain despite a comprehensive diagnostic evalua-tion. Endoscopic ultrasound (EUS) has emerged as a valuable tool in the diagnostic workup of IAP. This review explores the pivotal role of EUS in detecting the actual cause of IAP, as-sessing its accuracy, timing, safety, and future technological improvement. Following PRISMA guidelines, 60 pertinent studies were selected and analysed. EUS emerges as a cru-cial diagnostic tool, particularly when conventional imaging fails. It can offer intricate visu-alization of the pancreas, biliary system, and adjacent structures. High accuracy of EUS is evident in detecting the actual causes of IAP such as microlithiasis, small bile duct stones, pancreas divisum, and small pancreatic tumors. Optimal timing for EUS is post-resolution of the acute phase of the disease. EUS, when conducted by experienced endoscopists, it boasts minimal safety concerns, and is crucial to prevent complications. EUS-guided interventions, including fine-needle aspiration, collection drainage, and biopsies, aid in cytological analy-sis. With high diagnostic accuracy, safety, and therapeutic potential, EUS is able to improve patient outcomes when managing IAP. Further refinement of EUS techniques and cost-effectiveness assessment of EUS-guided approaches need to be explored in multicenter prospective studies. This review underscores EUS as a transformative tool in unraveling IAP's enigma and advancing diagnostic and therapeutic strategies.

During embryonic development stem cells undergo the differentiation process so that they can specialise for different functions within the organism. Complex programs of gene transcription are crucial for this process to happen. Epigenetic modifications and the architecture of chromatin in the nucleus, by the formation of specific regions of active as well as inactive chromatin, allow the coordinated regulation of the genes for each cell fate. In this mini review, we discuss the current knowledge regarding the regulation of three-dimensional chromatin structure during neuronal differentiation. We also focus on the role played in neurogenesis by the nuclear lamina that ensures the tethering of the chromatin to the nuclear envelope.

Recently, many independent research project focus on the study of the molecular basis of aging processes. I parallel, the different progression of many diseaes between sex is a hot topic research area. These studies require many data, models and tools for inferring aging and sex specific molecular machinaries. Among the others, the Genotype-Tissue Expression (GTEx) database is one of the preminent resources for the analysis of expression data related to tissues, sex and age. The current version of the database has a lot of querying interface that enable many analysis centered on the expression of genes on tissues. Despite this the database lacks on the analysis at sex/age level, thus the researcher has to download data and then write queries by hand. Nevertheless it lacks on the integration with existing protein interaction data. Therefore, the need for the introduction of tools enabling easy access and powerful analysis capabilities (i.e. state of the art network based analysis and integration), arises. We here present NOMA-DB a framework for the analysis of age related genes based on the GTEx database that enable easy querying at sex/age level, network based analysis. The framework is based on wrapping the GTEx database and on building an application logic level on top of existing data. The current version enables the analysis of genes by tissue, gene and age, thus it may be used in potentially future directions of analysis towards better comprehension of aging/sex-related molecular machineries based on the analysis of expression dat

There is an increasing pressure by community and customers forcing companies to insert environmental concerns in their practices. To help companies initiatives, the green bonds market was incepted. Our research question is how to select bonds in a growing billion-dollar market. This paper presents a multi-criteria decision analysis (MCDA) model to enable investors identify opportunities based not only in opinions, but grounded on objective facts. Analytic Hierarchy Process (AHP) and Complex Proportional Assessment (COPRAS) are two MCDA methods applied in this paper. Top-fifteen green bonds ranked by specialized media were assessed with the proposed MCDA model. Criteria included the Environmental Performance Index (EPI) proposed by Yale University, and common financial indicators as assets, risks (β), and dividends. The new AHP–COPRAS rank is compared with another published by specialized media.

In the paper, the authors express the Fuss–Catalan numbers as several forms in terms of the Catalan–Qi function, find some analytic properties, including the monotonicity, logarithmic convexity, complete monotonicity, and minimality, of the Fuss–Catalan numbers, and derive a double inequality for bounding the Fuss–Catalan numbers.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

Sorption of pure CO2 and CH4 and CO2/CH4 binary gas mixtures in amorphous glassy Poly(2,6-dimethyl-1,4-phenylene) oxide (PPO) at 35°C up to 1000 Torr is investigated. Sorption experiments were carried out using an approach that combines barometry with FTIR spectroscopy in the transmission mode to quantify the sorption of pure and mixed gases in polymers. The pressure range is chosen to prevent any variation of the glassy polymer density. The solubility within the polymer of the CO2 present in the gaseous binary mixtures is practically coincident with the solubility of pure gaseous CO2, up to a total pressure of the gaseous mixtures equal to 1000 Torr and for CO2 mole fraction of ~0.5 mol mol-1 and ~0.3 mol mol-1. The Non-Equilibrium Thermodynamics for Glassy Polymers (NET-GP) modelling approach has been applied to the Non-Random Hydrogen Bonding (NRHB) lattice fluid model to fit the solubility data of pure gases. We have assumed here that no specific interactions are occurring between the matrix and the absorbed gas. The same thermodynamic approach has been then used to predict the solubility of CO2/CH4 mixed gases in PPO resulting in a deviation lower than 9.5% from the experimental results for CO2 solubility.

Dyslipidemia (Dys) is a disease characterised by abnormally high levels of lipids in the 1 blood. It causes the deposits of lipids on the arterial wall, leading to the insurgence of atherosclerosis, 2 i.e. the increased thickness of arterial walls, which finally increases the risk of cardiovascular diseases. 3 Dyslipidemia is as comorbidity of Type 2 Diabetes Mellitus (T2DM). A set of genes has been associated 4 with dyslipidemia, but examining the regulation of such genes in age and sex is still an open research 5 field. In this study, starting from publicly available databases, we select genes associated with 6 dyslipidemia and we analyse their basal level changes by means of age and sex. Also studying the 7 networks associated to the genes, we identify the rewiring changes showing that there exists a set of 8 genes whose expression changes with age in: artery tibial, artery aorta and blood. Finally, we report 9 about changes associated to gender atributes in the extracted data

During the last 150 years, the trout-culture industry focused on enhancing trout populations by stocking, in response to the growing anglers’ demand and the habitat degradation associated to the rapid urbanization and hydropower development. The industrialized north of Italy, home to the Italian Alpine and subalpine trout populations, is the source of most of the revenues of the national trout-culture industry. Its rapid growth and the massive introduction of non-native interfertile trouts eroded the genetic diversity of native lineages, leading to harsh confrontations between scientists, institutions, and sportfishing associations. We review here the state of art of the taxonomy and distribution of the northern Italian native trouts, presenting both scientific results and historical documentation. We think the only native trouts in this region are Salmo marmoratus, widespread in this region, plus small and fragmented populations of S. ghigii, present only in the Southwestern Alps. We strongly recommend the interruption of stocking of domesticated interfertile non-native trouts in this area, and recommend the adoption of Evolutionary Significant Units for salmonid fishery management. We further propose future research directions for a sustainable approach to the conservation and ecosystem management of the fishery resources and inland waters of northern Italy.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

Entrepreneurship education has become increasingly relevant. For some years now, the business environment for starting a new company in the Dominican Republic has been considered very propitious. This has generated that many universities have incorporated training in entrepreneurship in their study plans. This study aims to analyse whether the cognitive and affective components, the country's business environment, university training in entrepreneurship and attitudes towards entrepreneurship are antecedents of the entrepreneurial intention of university students. It also seeks to investigate the relationship between entrepreneurial intention and entrepreneurial behaviour of students. Data were collected through a structured questionnaire from a sample of 523 students who had taken courses on entrepreneurship. The data have been analysed through the SPSS and Smart-PLS programs. The results of this research highlight the importance of the affective component and attitudes towards entrepreneurship in the formation of students' entrepreneurial intentions. This reinforces the importance of cultivating positive attitudes through educational interventions. These results contribute to the understanding of the factors that drive entrepreneurial intentions among university students and provide a foundation for future research.

The EU has planned the phase-out of new vehicles based on internal combustion engines in favour of high efficiency electric cars by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each Country of the Union in terms of CO2 emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to the electricity production were calculated considering both the Italian electricity mix production at 2021 and those at 2035, envisaged considering two scenarios based on different introductions of renewable sources (RES). Afterwards, the values obtained were adopted for determining the CO2 emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analysis related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C and M car segments for Mild Hybrid, Full Hybrid and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO2 emissions were calculated for the same vehicles for a defined mileage, so to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative powertrain technologies (plug-in), if fed with low carbon fuels.

Dementia is a major issue for healthcare systems worldwide, necessitating the development of creative and effective strategies for its management. This paper examines the use of Artificial Intelligence (AI) technologies in caring for and managing people with dementia. AI-driven solutions can improve diagnosis, personalize care, optimize medication management, and reduce the burden on caregivers. This paper discusses the implementation of an AI-based framework for creating videos related to people’s memories to support train-therapy or travel- therapy, a non-pharmacological intervention for Alzheimer’s disease patients

Bamboo is the building material of the past and future. It offers numerous properties that make it versatile for various applications, including construction. Its impressive strength-to-weight ratio enables it to bear substantial loads and stresses, while its good elasticity allows efficient energy absorption. However, its mechanical properties can vary based on factors such as species, age, locations, methods, and treatment. Treating bamboo is essential to enhance its properties and durability. The literature provides various natural and chemical treatments which enhanced some of the properties but also reported a drawbacks on higher temperature, content and duration. This paper reviewed 57 articles from Scopus database, specifically focusing on article-document type publications from the years 2003 to 2023. Additional references were also incorporated to address concerns in properties, treatment and standards to provide systematic understanding. MATLAB was utilized for data text analytics. With extensive assessment on the articles, the following gaps and concerns were observed and recommends for further study and assessment such as for bamboo properties, the development of centralized guidelines and procedures for the preparation and processing; exploration of alternative materials to reinforce bamboo without compromising its ductility; development of joint connections, and testing of mechanical properties considering seismic, wind and vibration. For treatment methods, the standardization of procedures using natural, chemical or combination. Lastly, for bamboo codes and standards, assessment of existing codes and standards for testing the mechanical properties of bamboo highlighting the potential limitations and areas, uniformity, differences with all existing similar standards. By filling these gaps, it can support the reliability and robustness of bamboo as a sustainable material, fostering its promotion and adoption in construction industry.

Introduction. Anesthesia is widely used in various fields of dentistry to reduce patient discomfort when the treatment would be painful. The dentist may need to infiltrate the anesthetic into multiple locations and this is usually done with the same needle which passes through the soft tissues several times to distribute the anesthetic solution over a larger area. The present study aims to evaluate, through a morphological analysis under a scanning electron microscope (SEM), how the beveled tip of a 30G needle, used to inject anesthetic several times into different areas of the vestibular mucosa, changes. Materials and methods. 30G needles with two different brands were tested, in vivo used for a variable number of sequential injections from 1 to 6 on 192 patients. The specimens were analyzed under SEM observation to evaluate any deformations induced by contact with the vestibular soft tissues. Results. The amount of deformation, measured along the axis parallel to the needle, was proportional to the number of injections. The protrusion of deformations, measured on an axis perpendicular to the needle, were maximum on the needles used 3 times. For the needles used 4,5 and 6 injections, no further increase in deformations was noted. Conclusion. From the data it seems that the tested needles are not produced to withstand multiple injections consequently after the first injection on soft tissues, they undergo a deformation which could increase the risk of injury to the mucosa itself or to nerves and vessels with which they come into contact. It would be advisable to use the single needle for a reduced number of injections.

Education for Sustainable Development (ESD) is crucial in higher education, providing students with the knowledge, skills, and values necessary for a sustainable future. ESD seeks a holistic understanding of sustainability and promotes critical thinking and innovative approaches. Specifically, ESD is very important to address in engineering careers, as engineers will need to establish sustainable solutions in the future. For this reason, the integration of sustainability into university curricula has been studied for some time. In this way, this research analyses the perceptions (attitudes towards teachers; knowledge about sustainable development; environmental, economic and social attitudes; sustainable behaviours) that engineering students in the Dominican Republic have towards sustainable development. 626 questionnaires completed by engineering students were obtained. Subsequently, the data was analysed in SPSS and PLS-SEM. The results showed that attitudes towards teachers have an impact on engineering students' knowledge of sustainable development. In turn, the results also showed that knowledge about sustainable development influences both attitudes (economic, social and environmental) and sustainable behaviours of engineering students. Contrary to other research, this study suggested that economic attitudes are not identified as an antecedent of sustainable behaviours among engineering students. From these results, implications and future lines of research are generated.

Listeria ivanovii and L. monocytogenes, are the only pathogenic species of the genus Listeria and share many virulence factors and mechanisms of pathogenicity. L. ivanovii shows host tropism towards small ruminants and rodents and much lower virulence for humans compared to L. monocytogenes. However, severe infections caused by L. ivanovii, resulting in bacteremia, abortion and stillbirth, occasionally occurred in immunocompromised persons and in pregnant women, while in immunocompetent hosts L. ivanovii can cause gastroenteritis. In this review the updated knowledge on virulence aspects and distribution of L. ivanovii in the environment and in food are summarized. Recent research on its virulence characters at genome level gave indications on how pathogenicity evolved in this bacterial species. As for L. monocytogenes, L. ivanovii infections occur after the ingestion of contaminated food, so an overview of reports regarding its distribution in the food products was carried out to obtain indications on the categories of foods exposed to contamination by L. ivanovii. It was found that a wide variety of food products can be a source of this microorganism and that, like L. monocytogenes, L. ivanovii is able to persist in the food production environment. Studies on its ability to grow in enrichment and isolation media suggested that its occurrence in nature might be underestimated. Moreover, virulence varies among strains for differences in virulence character regulation, presence/absence of genetic regions and the possible instability of a Listeria pathogenicity genomic island, LIPI-2, which is unique to L. ivanovii. We can conclude that L. ivanovii, as a possible pathogen for animals and humans, requires more focused investigations regarding its occurrence in the environment and in food and on intra-species variability of pathogenic potential.

Prediction markets are heralded as powerful forecasting tools, but models to describe them often fail to capture the full complexity of the underlying mechanisms that drive price dynamics. To address this issue, we propose a model in which agents belong in a social network, have an opinion about the probability of a particular event to occur, and bet on the prediction market accordingly. Agents update their opinions about the event by interacting with their neighbours in the network, following the Deffuant model of opinion dynamics. Our results suggest that a simple market model that takes into account opinion formation dynamics is capable to replicate the empirical properties of historical prediction market time series, including volatility clustering and fat-tailed distribution of returns. Interestingly, the best results are obtained when there is the right level of variance in the opinions of the agents. Moreover, this paper provides a new way to indirectly validate opinion dynamics models against real data by using historical data obtained from PredictIt, an exchange platform whose data has never been used before to validate models of opinion diffusion.

In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters, and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.

Rare earth rich magnesium alloys are used in aerospace and automotive fields because of their high specific strength and good castability. However, due to their low corrosion resistance, protective surface treatments, such as conversion coating or electroless plating are necessary, when they have to be used in humid or corrosive environments. The present study was aimed to evaluate the effect of Plasma Electrolytic Oxidation (PEO) and different surface roughness (Ra≈0.8 μm and Ra≈0.3 μm) on the rotating bending fatigue of an innovative Mg alloy, with a high content of Nd (up to 3.1 wt%) and Gd (up to 1.7 wt %). Fatigue tests revealed a 15% decrease in the fatigue strength of the PEO treated alloy (fatigue strength = 88 MPa) with respect to the bare alloy (fatigue strength = 103 MPa). The reduction of fatigue strength was mainly due to the residual tensile stresses induced by the PEO treatment. The effect of surface roughness on the bare alloy was, instead, negligible. The mechanisms of crack initiation were similar in the untreated and PEO treated alloy, with crack nucleation sites located in correspondence of large facets of the cleavage planes.

Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemi-ological study was designed to assess the role of contagious pathogens (S. aureus and S.agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that have more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk components delivered to the dairy plant, and on the level of welfare. Whereas, the presence of S.agalactiae did not show any significant association. The major risk factors associated with the presence of S.aureus were also identified to help prioritise control programs. These results support the “One Sustainability” approach im-plying that an increase of animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.

The secondary structures of Scherer commonly known as perineuronal and perivascular satellitosis have been identified as a histopathological hallmark of diffuse, invasive, high-grade gliomas. They are recognized as perineuronal satellitosis when clusters of neoplastic glial cells surround neurons cell bodies and perivascular satellitosis when such tumour cells surround blood vessels infiltrating Virchow-Robin spaces. In this review, we provide an overview of emerging knowledge regarding how interactions between neurons and glioma cells can modulate tumour evolution and how neurons play a key role in glioma growth and progression, as well as the role of perivascular satellitosis into mechanisms of glioma cells spread. At the same time, we review the current knowledge about the role of perineuronal satellitosis and perivascular satellitosis within the tumour microenvironment (TME), in order to highlight critical knowledge gaps in research space.

Acquired immunodeficiency syndrome (AIDS) has transitioned from a progressive, fatal disease to a chronic, manageable disease thanks to better defining of antiretroviral therapy, hence contributing to increased life expectancy. In parallel, a growing number of subjects without overt clinical signs of disease but living with chronic HIV infection (people living with HIV, PLWH) are experiencing early cardiovascular disease worldwide. However, a progressive increase in the prevalence of multiple comorbid diseases has been reported as these patients age, including cardiovascular disease (CVD). Cardiovascular mortality can be either directly related to the viral infection, a progressive reduction of response to the antiretroviral therapy, chronic inflammation or lifestyle-related. Cardiovascular ageing represents a relevant issue in the management of HIV-infected patients. Although the exact pathophysiological mechanism that leads PLWH to develop cardiovascular disease is not entirely understood, there is substantial evidence that they accumulate age-related conditions earlier than the general population. Furthermore, since the proportion of PLWH growing older than 50 years has progressively increased, this results in a complex interaction between disease-related pathophysiology and the exposition of a growing burden of cardiovascular risk factors. For this reason, we performed a systematic review of the genes most frequently associated with ageing in HIV-infected subjects, followed by a bioinformatic analysis to explore the biological impact of the genes related to ageing.

The Water-Cooled Lead Lithium (WCLL) Breeding Blanket (BB) is one of the two BB concepts candidate to be selected as driver blanket for the EU-DEMO fusion reactor. In this regards, the development of a sound architecture of the WCLL Central Outboard Blanket (COB) Segment, ensuring the fulfilment of the thermal and structural design requirements, is one of the main goals of the EUROfusion consortium. To this purpose, an exploratory research campaign has been launched to preliminarily investigate the thermo-mechanical performances of the Bottom Cap (BC) region of the WCLL COB segment, because of its peculiarities making its design different from the other regions. The assessment has been carried out considering the nominal BB operating conditions, the Normal Operation (NO) scenario, as well as a steady-state scenario derived from the in-box LOCA accident, the Over-Pressurization (OP) scenario. Starting from the reference geometric layout of the WCLL COB BC region, a first set of analysis has been launched in order to evaluate its structural performances under a previously calculated thermal field and to select potential geometric improvements. Then, the analysis of a more complete BC region has been conducted from both the thermal and structural standpoints, evaluating its structural behaviour in compliance with the RCC-MRx code. Finally, after some iterations and geometric updates, a promising geometric layout of the BC region has been obtained even though some criticalities still persist in the internal Stiffening Plates and First Wall. However, the obtained results clearly showed that the proposed layout is worthy to be further assessed to achieve a robust enough configuration. The work has been performed following a theoretical-numerical approach based on the Finite Element Method (FEM) and adopting the quoted Ansys commercial FEM code.

The ovary is the major determinant of female reproductive health. Ovarian functions are mainly related to the primordial follicle pool, which is gradually loss with aging. Ovarian aging and reproductive dysfunctions share oxidative stress as common underlying mechanism. ROS signaling is essential for normal ovarian processes yet can contribute to various ovarian disorders when disrupted. Therefore, balance in the redox system is crucial for proper ovarian functions. In the present study, by focusing on mRNAs and ncRNAs described in the ovary and taking into account only validated ncRNA interactions, we built up an ovarian antioxidant ceRNA network, namely OvAnOx ceRNA, composed of 5 mRNAs (SOD1, SOD2, CAT, PRDX3, GR), 10 miRNAs and 5 lncRNAs (XIST, FGD5-AS1, MALAT1, NEAT1, SNHG1). Our bioinformatic analysis indicated that the components of the OvAnOx ceRNA not only contribute to antioxidant defence, but are also involved in other ovarian functions. Indeed, antioxidant enzymes encoded by mRNA of OvAnOx ceRNA operate within a regulatory network that impacts ovarian reserve, follicle dynamics, and oocyte maturation in normal and pathological conditions. The OvAnOx ceRNA represents a promising tool to unravel the complex dialogue between redox potential and ovarian signalling pathways involved in reproductive health, aging and diseases.

We present the hardware of a cheap multi-sensor magnetometric setup, where a relatively large set of magnetic field components is measured in several positions by calibrated magnetoresistive detectors. The setup is developed to map the (inhomogeneous) field generated by a known magnetic source, which is measured and then discerned from the background (homogeneous) geomagnetic field. The data output from this hardware can be successfully and reliably used to retrieve the position and orientation of the magnetic source with respect to the sensor frame, together with the orientation of the frame with respect to the environmental field. Possible applications of the setup are briefly discussed, and a synthetic description of the methods of data elaboration and analysis is provided.

Participatory landscape conservation is an innovative approach that weaves theory and practice to bridge the gap between theoretical models and practical applications. Intertropical regions as the case of Mexico face challenges to conciliate regional governability, social justice, and nature conservation. The State of Michoacan is one of these regions where the challenges exacerbate since nature conservation is last due to its ongoing territorial disputes. We implemented the participatory landscape conservation approach by creating a complementary form of protected areas with ongoing conflicts, drought conditions, and extreme poverty. We conducted participatory mapping and land cover/use analyses as main methodological tools to reach consensus among stakeholders. We integrated, macro, micro and social scales to provide sound arguments to integrate local, scholar and policy makers perceptions. The outcomes of the participatory mapping analyses were assessed. The present papers provide evidence of the positive outcome of using a Participatory Landscape Conservation to establish a Biosphere Reserve, safeguarding one of the most biologically diverse and delicate ecosystems consisting of seasonally dry tropical forests within a rather disputed region. We discussed the relevance of our findings and compared them to ongoing regional and global trends in the light of other forms of establishing protected areas.

Background/Objectives: Pityriasis rosea (PR) is a self-limiting exanthematous disease associated with the endogenous reactivation of human herpesvirus (HHV)-6 and HHV-7. Classically, the lesions gradually resolve leaving no sequelae. Therefore, the best treatment is reassuring the patient and suggesting a resting period. However, atypical PR cases characterized by extensive, persistent lesions and systemic symptoms may impact the patient’s quality of life, and, therefore, a treatment can be prescribed. There is limited evidence on the comparative effectiveness of pharmacological treatments for PR, therefore we performed a network meta-analysis to compare these interventions. Methods: Overall, 12 randomized control trials (RCTs) were identified. The outcomes were itch resolution and rash improvement. Results were expressed as risk ratio (RR) and 95% confidence interval (CI). We also calculated the relative ranking of the interventions for achieving the aforementioned outcomes as their surface under the cumulative ranking (SUCRA). Results: On network meta-analysis, only oral steroids and the combination of oral steroids+antihistamine resulted significantly superior to the placebo in terms of itch resolution (RR 0.44, CI 0.27-0.72 and RR 0.47, CI 0.22-0.99). Oral steroids resulted as the best treatment (SUCRA 0.90) for itch resolution. In terms of rash improvement, only acyclovir and erythromycin resulted significantly superior to placebo (RR 2.55, CI 1.81-3.58 and RR 1.69, CI 1.23-2.33), and acyclovir outperformed all the other tested interventions. Consequently, acyclovir ranked as the best intervention (SUCRA score 0.92). Conclusions: Acyclovir represents the best option in PR patients with extensive, persistent lesions or systemic symptoms. Steroids and antihistamines seemed the best treatment for itch resolution.

This article examines the evolution of bariatric surgery, with a focus on emerging technologies such as robotics and laparoscopy. In the case of gastric bypass, no significant differences have emerged between the two techniques in terms of hospitalization duration, weight loss, weight regain, or 30-day mortality. Robotic surgery, while requiring more time in the operating room, has been associated with lower rates of bleeding, mortality, transfusions, and infections. In revisional bariatric surgery, the robotic approach has shown fewer complications, shorter hospital stays, and a reduced need for conversion to open surgery. In the case of sleeve gastrectomy, robotic procedures have required more time and longer post-operative stays but have recorded lower rates of transfusions and bleeding compared to laparoscopy. However, robotic surgeries have proven to be more costly and potentially more complex in terms of post-operative complications. The review has also addressed the topic of the single anastomosis duodeno-ileal switch (SADIS), finding comparable results between robotic and laparoscopic techniques, although robotic procedures have required more time in the operating room. Robotic technology has proven to be safe and effective, albeit with slightly longer operating times in some cases.

In this work, we experimentally investigate mass and heat transport phenomena in a modular device while converting a solution salinity difference into a temperature difference. Operations occur under fixed total ambient pressure and without mechanical moving parts, thus realizing a fully static conversion. Provided that a constant salinity gradient can be imposed, the proposed device is able to generate a steady cooling capacity. Here, we purposely operate with environmentally benign and easily accessible sodium chloride water solutions only. A numerical model is finally elaborated, validated and used to explore a wider range of possible device configurations and operating conditions.

Smart living, a concept that has gained increasing attention in recent years, revolves around integrating advanced technologies in homes and cities to enhance the quality of life for citizens. Sensing and human action recognition are crucial aspects of this concept. Smart living applications span various domains, such as energy consumption, healthcare, transportation, and education, which greatly benefit from effective human action recognition. This field, originating from computer vision, seeks to recognize human actions and activities using not only visual data but also many other sensor modalities. This paper comprehensively reviews the literature on human action recognition in smart living environments, synthesizing the main contributions, challenges, and future research directions. This review selects five key domains: Sensing Technology, Multimodality, Real-time Processing, Interoperability, and Resource-Constrained Processing, as they encompass the critical aspects required for successfully deploying human action recognition in smart living. These domains highlight the essential role that sensing and human action recognition play in successfully developing and implementing smart living solutions. This paper serves as a valuable resource for researchers and practitioners seeking to explore further and advance the field of human action recognition in smart living.

Bisphenol A analogs (BPA analogs) are emerging contaminants with a rising production caused by the replacement of BPA with these compounds. The increased production of BPA analogs is leading to an increased release into various ecosystems, including sea. The aim of this study was to evaluate the biological effects of BPA analogs on a primary producer, the diatom Phaeodactylum tricornutum Bohlin. Three different BPA analogs (BPAF, BPF, and BPS) and their mixture were tested at the environmental relevant concentration of 300 ng/L. Growth curve, cell size and several biomarkers of oxidative stress and oxidative damage were measured. Our results indicated that the tested compounds caused alteration of the growth and induced oxidative stress altering many antioxidant enzymes. However, no oxidative damages were observed.

Historically, admission of hematological patients in the ICU shortly after the start of a critical illness is associated with better survival rates. Early intensive interventions administered by MET could have a role in the management of hematological critically ill patients, eventually reducing ICU admission rate. In this retrospective and monocentric study, we evaluate the safety and effectiveness of intensive treatments administered by the MET in a medical ward frame. The administered interventions were mainly helmet CPAP and pharmacological cardiovascular support. Frequent reassessment by the MET at least every 8 to 12 hours was guaranteed. We analyze data from 133 hematological patients that required MET intervention. In hospital mortality was 38%; mortality doesn’t increase in patients not immediately transferred to the ICU. Only 3 patients died without a former admission in ICU; in these cases, mortality was not related to the acute illness. Moreover, 37% of patients overcame the critical episode in the hematological ward. Higher SOFA and MEWS scores were associated with a worst survival rate, while neutropenia and pharmacological immunosuppression were not. The MET approach seems to be safe and effective. SOFA and MEWS confirmed to be effective tools for prognostication.

Non-alcoholic fatty liver disease (NAFLD) affects up to a quarter of the adult population in many developed and developing countries. This spectrum of liver disease ranges from simple steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. The incidence of NASH is projected to increase by up to 56% over the next 10 years. There is growing epidemiological evidence that NAFLD has become the fastest growing cause of hepatocellular carcinoma (HCC) in industrialized countries. The annual incidence of HCC varies between patients with NASH cirrhosis and patients with noncirrhotic NAFLD. In this review, NAFLD/NASH-associated HCC will be described, including its epidemiology, risk factors promoting hepatocarcinogenesis, and management of HCC in patients with obesity and associated metabolic comorbidities, including preventive strategies and therapeutic approaches to address this growing problem.

Biological nitrogen fixation (BNF) by symbiotic bacteria plays a vital role in sustainable agriculture. However, current quantification methods are often expensive and impractical. This study explores the potential of Raman spectroscopy, a non-invasive technique, for rapid assessment of BNF activity in soybeans. Raman spectra were obtained from soybean plants grown with and without rhizobia bacteria to identify spectral signatures associated with BNF. δN15 isotope ratio mass spectrometry (IRMS) was used to determine actual BNF percentages. Partial least squares regression (PLSR) was employed to develop a model for BNF quantification based on Raman spectra. The model explained 80% of the variation in BNF activity. To enhance the model's specificity for BNF detection regardless of nitrogen availability, a subsequent elastic net (Enet) regularization strategy was implemented. This approach provided insights into key wavenumbers and biochemicals associated with BNF in soybeans.

The outbreak of coronavirus disease-19 (COVID-19) has infected more than 11 million people and has claimed more than 530.000 deaths world-wide. In July 2020, still, there is no specific treatment for disease caused by the novel coronavirus. In the search to curb the global pandemic COVID-19, some eastern and developing countries have approved various treatment with controversial efficacy, among that the use of the antimalarial Hydroxychloroquine (HCQ), so far with inconclusive clinical evidence of effectiveness. On the other hand, computer-based screening suggest that HCQs analog are promising molecules, to impair viral replication in vitro[1]. Therefore, what is emerging from this complex background, is the need to understand molecular mechanism beyond drugs that can be helpful against viral infection for this and future pandemic. The intent of this Brief Report is to highlight: i) the involvement of the Mitogen Activated Protein Kinase (MAPK) cascade in viral infection and ii) the urgent need to have molecular data on the effectiveness of the combination of MAPK inhibitors together with HCQ and HCQs analogs in curbing viral infection. We are convinced that a better understanding of the patterns of elicited molecular mechanisms will be critical for new molecular approaches to this severe disease

Dyslipidemia (Dys) is a disease characterised by abnormally high levels of lipids in the blood. It causes the deposits of lipids on the arterial wall leading to the insurgence of atherosclerosis, i.e. the increased thickness of arterial walls, which finally increases the risk of cardiovascular diseases. Dyslipidemia is a comorbidity of Type 2 Diabetes Mellitus (T2DM). A set of genes has been associated with dyslipidemia, but examining the regulation of such genes in age and sex is still an open research field. In this study, we select from publicly available databases the genes associated with dyslipidemia and analyse changes in the basal level of such genes by age and sex. Moreover, we also distinct differential rewiring of the related gene association network in males and females. Our results show that there exist a set of genes whose expression changes with age in artery tibial, artery aorta and blood. Moreover, there exist significant differences between sex.

Although hundreds of keV in energy gain have already been demonstrated in dielectric laser accelerators (DLAs), there remains challenge in creating structures that can confine electrons for multiple millimeters. We focus here on dual gratings with single sided drive, which have experimentally demonstrated energy modulation numerous times. Using a FTDT simulation to find the fields within various DLA structures and correlating these results with particle tracking simulation, we look at the impact of teeth height and width, as well as gap and offset, on the performance of these structures. We find a tradeoff between electron throughput and acceleration, but that for any given grating geometry there is a gap and offset that will allow some charge acceleration. For our 780 nm laser wavelength, this results in a 1200 nm optimal gap size for most gratings.

Due to the high computational burden and the high nonlinearity of the responses, crashworthiness optimizations are notoriously hard-to-solve challenges. Among various approaches, methods like the Successive Response Surface Method (SRSM) have stood out for their efficiency in enhancing baseline designs within a few iterations. However, these methods have limitations that restrict their application. Their minimum iterative resampling required is often computationally prohibitive. Furthermore, surrogate models are conventionally constructed using Polynomial Response Surface (PRS), a method that is poorly versatile, prone to overfitting, and incapable of quantifying uncertainty. Furthermore, the lack of continuity between successive response surfaces results in suboptimal predictions. This paper introduces the Multi-Fidelity Successive Response Surface (MF-SRS), a Gaussian process-based method, which leverages a nonlinear multi-fidelity approach for more accurate and efficient predictions compared to SRSM. After initial testing on synthetic problems, this method is applied to a real-world crashworthiness task: optimizing a bumper crossmember and crash box system. Results, benchmarked against SRSM and the Gaussian Process Successive Response Surface (GP-SRS) – a single-fidelity Gaussian process-driven extension of SRSM, show that MF-SRS offers distinct advantages. Specifically, it improves upon the specific energy absorbed optimum value achieved by SRSM by 14.1 %, revealing its potential for future applications.

Predicting change from multivariate time series has relevant applications ranging from medical to engineering fields. Multisensory stimulation therapy in patients with dementia aims to change the patient’s behavioral state. For example, patients who exhibit a baseline of agitation may be paced to change their behavioral state to relaxed. This study aims to predict changes in behavioral state from the analysis of the physiological and neurovegetative parameters to support the therapist during the stimulation session. In order to extract valuable indicators for predicting changes, both handcrafted and learned features were evaluated and compared. The handcrafted features were defined starting from the CATCH22 feature collection, while the learned ones were extracted using a Temporal Convolutional Network, and the behavioral state was predicted through Bidirectional Long Short-Term Memory Auto-Encoder, operating jointly. From the comparison with the state-of-the-art, the learned features-based approach exhibits superior performance with accuracy rates of up to 99.42% with a time window of 70 seconds and up to 98.44% with a time window of 10 seconds.

In the current industrial landscape, increasingly pervaded by technological innovations, the adoption of optimized strategies for asset management is becoming a critical key success factor. Among the various strategies available, the “Prognostics and Health Management” strategy is able to support maintenance management decisions more accurately, through continuous monitoring of equipment health and “Remaining Useful Life” forecasting. In the present study, Convolutional Neural Network-based Deep Neural Network techniques are investigated for the Remaining Useful Life prediction of a punch tool, whose degradation is caused by working surface deformations during the machining process. Surface deformation is determined using a 3D scanning sensor capable of returning point clouds with micrometric accuracy during the operation of the punching machine, avoiding both downtime and human intervention. The 3D point clouds thus obtained are transformed into bidimensional image-type maps, i.e., maps of depths and normal vectors, to fully exploit the potential of convolutional neural networks for extracting features. Such maps are then processed by comparing 15 genetically optimized architectures with the transfer learning of 19 pre-trained models, using a classic machine learning approach, i.e., Support Vector Regression, as a benchmark. The achieved results clearly show that, in this specific case, optimized architectures provide performance far superior (MAPE=0.058) to that of transfer learning which, instead, remains at a lower or slightly higher level (MAPE=0.416) than Support Vector Regression (MAPE=0.857).

Continuous in-home monitoring of older adults living alone aims to improve their quality of life and independence, by detecting early signs of illness and functional decline or emergency conditions. To meet requirements for technology acceptance by seniors (unobtrusiveness, non-intrusiveness, privacy-preservation), this study presents and discusses a new smart sensor system for the detection of abnormalities during daily activities, based on ultra-wideband radar providing rich, not privacy-sensitive, information useful for sensing both cardiorespiratory and body movements, regardless of ambient lighting conditions and physical obstructions (through-wall sensing). The radar sensing is a very promising technology, enabling the measurement of vital signs and body movements at a distance, and thus meeting both requirements of unobtrusiveness and accuracy. In particular, impulse-radio ultra-wideband radar has attracted considerable attention in recent years thanks to many properties that make it useful for assisted living purposes. The proposed sensing system, evaluated in meaningful assisted living scenarios by involving 30 participants, exhibited the ability to detect vital signs, to discriminate among dangerous situations and activities of daily living, and to accommodate individual physical characteristics and habits. The reported results show that vital signs can be detected also while carrying out daily activities or after a fall event (post-fall phase), with accuracy varying according to the level of movements, reaching up to 95% and 91% in detecting respiration and heart rates, respectively. Similarly, good results were achieved in fall detection by using the micro-motion signature and unsupervised learning, with sensitivity and specificity greater than 97% and 90%, respectively.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

The paper proposes a human explainable artificial intelligence approach for mapping the status of environmental phenomena from multisource geo data. It is both knowledge and data driven: it exploits remote sensing expert’s knowledge to define the contributing factors from which partial evidence of the environmental status can be computed. Furthermore, it aggregates the partial evidences to compute a map of the environmental status by adapting to a region of interest through a learning mechanism exploiting Volunteered Geographic Information (VGI), both from in situ observations and photointerpretation. The approach is capable to capture the specificities of local context as well as to cope with the subjectivity and incompleteness of expert’s knowledge. The proposal is exemplified to map the status of standing water areas (i.e. water bodies and river, human driven or natural hazard flooding) by considering satellite data and geotagged observations. Results of the validation experiments were performed in three areas of Northern Italy, characterized by distinct ecosystems. Results of the proposed methodological framework showed better performances than traditional approaches based on single spectral indexes thresholding. The use of expert’s knowledge, possibly imprecise/uncertain and incomplete, the need of few ground truth data for learning, and finally the explainability of learned rules are the distinguishing characteristics of the proposal with respect to traditional machine learning methods.

Wolfram syndrome 1 (WS1) is an uncommon autosomal recessive neurological disorder that is characterized by diabetes insipidus, early-onset non-autoimmune diabetes mellitus, optic atrophy, and deafness (DIDMOAD). Other clinical manifestations are neuropsychiatric symptoms, urinary tract alterations, and endocrinological disorders. The rapid clinical course of WS1 results in death by the age of 30. Severe brain atrophy leads to central respiratory failure, which is the main cause of death in WS1 patients. Mutations in the WFS1 gene, located on chromosome 4p16, account for approximately 90% of WS1 cases. The gene produces wolframin, a transmembrane glycoprotein widely distributed and highly expressed in retinal, neural, and muscular tissues. Wolframin plays a crucial role in the regulation of apoptosis, insulin signaling, and ER calcium homeostasis, as well as the ER stress response. WS1 has been designated as a neurodegenerative and neurodevelopmental disorder due to the numerous abnormalities in the ER stress-mediated system. WS1 is a devastating neurodegenerative disease that affects patients and their families. Early diagnosis and recognition of the initial clinical signs may slow the disease's progression and improve symptomatology. Moreover, it is critical to provide genetic counseling to the patient's relatives in order to reduce the risk of transmitting WS1. Regrettably, there are currently no specific drugs for the therapy of this fatal disease. A better understanding of the etiology of WS1 will make possible the development of new therapeutic approaches that may enhance the life expectancy of patients. This review will examine the pathogenetic mechanisms, development, and progression of neuropsychiatric diseases commonly associated with WS1. A thorough understanding of WS1's neurophysiopathology is critical for achieving the goal of improving patients' quality of life and life expectancy.

(1) Background: Usually, the majority of patients suffering from vertigo and dizziness can be identified in four major categories: acute spontaneous vertigo, episodic (recurrent) vertigo, recurrent positional vertigo, chronic imbalance. Our purpose is to retrospectively evaluate the main causes of episodic vertigo and to find indications for a reliable clinical suspicion useful for a definitive diagnosis, comparing patients affected by different presenting symptomatology (acute vertigo, recurrent episodic vertigo, and imbalance) (2) Methods: we retrospectively evaluated the clinical records in a population of 249 consecutive patients observed for vertigo in our tertiary referral center in the period 1 January 2019 – 31 January 2020. On the basis of the reported clinical history, patients were divided into three groups: patients with first ever attack of vertigo, patients with recurrent vertigo and dizziness; patients with chronic imbalance. (3) Results: On the basis of the results of the instrumental examination, we arbitrary divided (for each type of symptoms) the patients in a group with a normal vestibular instrumental examination and a group of patients in which the clinical-instrumental evaluation showed some pathological results; a highly significant difference (p: 0.157) was found between recurrent and acute vertigo and between recurrent vertigo and imbalance. (4) Conclusions: patients with recurrent vertigo more frequently exhibit a negative otoneurological examination since they are often examined in the intercritical phase. A precise and in-depth research of the patient's clinical history is the key to suspect or make a diagnosis together with the search for some instrumental or clinical hallmark, especially in cases where the clinical picture does not fully meet the international diagnostic criteria.

Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS), Genome-Wide Association Studies (GWAS), Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. For example, by using genotyping microarrays (e.g. collections of Single Nucleotide Polymorphism - SNP) it is possible to uncover the reasons (i.e. mutation in genes) because a treatment works properly in some patients (for example absence of mutated genes), but it does not work (presence of mutated genes) in others. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g. high execution time and required memory) to bioinformatic software. Thus a main requirement of modern bioinformatic software is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. Thus, to exploit all the potential of this massive amount of data in the short possible time (before that data becomes obsolete), the necessity to develop parallel software tools for efficient data collection and analysis arise. Moreover, due to the heterogeneity of the data produced by the different kinds of experimental platforms, it is necessary to automatize in a comprehensive software pipeline, the various steps that compose a bioinformatic analysis, such as: the preprocessing of raw data to remove noise or corrupted data; the annotation of data with external knowledge (e.g. Gene Ontology), and the integration of molecular data with clinical data. It should be noted that such steps are necessary to make statistical or data mining analysis more effective. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based SNP genotyping data. A case study in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data.

A growing area in neurosciences is focused on the modeling and analysis the complex system of connections in neural systems, i.e. the connectome. Here we focus on the representation of connectomes by using graph theory formalisms. The human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. Recently, it has been proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space to define network nodes of individual brain networks. In the network domain, the question of comparison of the structure of networks arises. Such question is tackled by modeling the comparison of brain network as a network alignment (NA) problem. In this paper, we first defined the NA problem formally, then we applied three existing state of the art of multiple alignment algorithms (MNA) on diffusion MRI-derived brain networks and we compared the performances. The results confirm that MNA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes.

Soil texture is a key property influencing most soil physical, chemical, and biological processes and its catchment-scale spatial variation may yields insights for soil management. Texture data are generally available only at a few locations, since sampling and laboratory analyses are time consuming. Therefore, it is essential to predict soil size particles texture variability using appropriate methods. Moreover, soil texture distribution across a catchment is influenced by erosion and sedimentation processes controlled by hillslope morphology, which can be quantified through some topographic attributes. The study was aimed to evaluate the ability of a multivariate approach based on non-stationary geostatistics to merge remotely sensed high-resolution LiDAR-derived topographic attributes with Vis-NIR diffuse reflectance spectroscopy and laboratory analysis to produce high-resolution maps of soil sand content and estimation uncertainty in a forested catchment in southern Italy. Moreover, the proposed approach was compared with the commonly used univariate approach of ordinary kriging. Soil samples were collected at 135 locations within a 139 ha-forest catchment with granitic parent material and subordinately alluvial deposits, where soils classified as Typic Xerumbrepts and Ultic Haploxeralf crop out. A number of linear trend models coupled with different auxiliary variables were compared and the best one resulted the model using clay content as auxiliary variable. The improvement of estimation from using only LiDAR data (elevation) compared to the univariate (no trend) model was rather marginal.

In addition to CD4+ T lymphocytes, myeloid cells, and, particularly, differentiated macrophages, are targets of the human immunodeficiency virus type-1 (HIV-1) infection via interaction of gp120Env with CD4 and CCR5 or CXCR4. Both T cells and macrophages support virus replication although with substantial differences. In contrast to activated CD4+ T lymphocytes, HIV-1 replication in macrophages occurs in nondividing cells and it is characterized by virtual absence of cytopathicity both in vitro and in vivo. These general features should be considered in evaluating the role of cell-associated restriction factors aiming at preventing of curtailing virus replication in macrophages and T cells particularly in the context of designing strategies to tackle the viral reservoir in infected individuals receiving combination antiretroviral therapy. In this regard, we will here also discuss a model of reversible HIV-1 latency in primary human macrophages and the role of host factor determining restriction or reactivation of virus replication in myeloid cells.

Comprehensive understanding of tree characteristics and conditions holds paramount importance for the precise management of hazelnut orchards. It facilitates the determination of tree vigor, pruning requirements, phytosanitary interventions, and plant water consumption. The primary objective of this study was to explore, for the first time on a fruit tree with a bushy structure and across trees of four Italian distinct hazelnut cultivars, the efficacy of multispectral and thermal UAV (Unmanned Aerial Vehicle) technologies in assessing canopy attributes, vegetative growth, and predicting abiotic stresses. These technologies serve as tools for precision agriculture, enabling the computation of various indices such as the Normalized Difference Vegetation Index (NDVI) and crop water stress index (CWSI). The study of water content is of particular importance at this time, especially considering the increasing water stress levels in Europe as well as globally. While Red Green Blue (RGB) and thermal imagery collectively demonstrated superior performance in model reconstruction, the multispectral UAV remained more adept at characterizing size traits of hazelnut plants. Thermal images alone proved inadequate for accurately reconstructing hazelnut biometric characteristics. Furthermore, all indices were found to be cultivar-specific, underscoring the importance of conducting studies across different cultivars. The utilization of two UAVs, namely multispectral and thermal, facilitated the examination of the relationship between NDVI and CWSI across tree species.

We characterize the performance of a system based on a magnetoresistor array. This instrument is developed to map the magnetic field, and to track a dipolar magnetic source in the presence of a static homogeneous field. The position and orientation of the magnetic source with respect to the sensor frame is retrieved together with the orientation of the frame with respect to the environmental field. A nonlinear best-fit procedure is used, and its precision, time performance, and reliability are analyzed. This analysis is performed in view of the practical application for which the system is designed that is an eye-tracking diagnostics and rehabilitative tool for medical purposes, which require high speed ($\ge 100$~Sa/s) and sub-millimetric spatial resolution. A throughout investigation on the results makes it possible to list several observations, suggestions, and hints, which will be useful in the design of similar setups.

Qualtra, an innovative 10 MW geothermal power plant proposal, employs a closed-loop design to mitigate emissions, ensuring no direct release into the atmosphere. A thorough assessment utilizing energy and exergy analysis, Life Cycle Assessment (LCA), Exergo-economic and Exergo Environmental Analysis (EevA) was conducted. The LCA results, utilizing the ReCiPe 2016 midpoint methodology, encompass all the spectrum of environmental indicators provided. The technology implemented makes it possible to totally avoid direct atmospheric emissions from the Qualtra plant, so the environmental impact is mainly due to indirect emissions over the life cycle. The results obtained for the Global Warming Potential indicator is about 6.6 g CO2/kWh, notably lower compared to other conventional systems. Contribution analysis reveals that the construction phase dominates, accounting for over 90% of the impact in all LCA MidPoint categories. At the component level, a single score calculation incorporating normalization and weighting was executed. The resulting single score is then used into Exergo-Environmental Analysis (EEvA), highlighting the well system as the most impactful contributor, constituting approximately 45% of the total impact. Other substantial contributions to the environmental impact include the condenser (21%), the turbine (17%), and the HEGeo (14%). The Exergo-Economic analysis assesses cost distribution across major plant components, projecting an electricity cost of about 8.3 c€/kWh.

With the outbreak of the COVID-19 disease, the research community is producing unprecedented efforts dedicated to better understand and mitigate the affects of the pandemic. In this context, we review the data integration efforts required for accessing and searching genome sequences and metadata of SARS-CoV2, the virus responsible for the COVID-19 disease, which have been deposited into the most important repositories of viral sequences. Organizations that were already present in the virus domain are now dedicating special interest to the emergence of COVID-19 pandemics, by emphasizing specific SARS-CoV2 data and services. At the same time, novel organizations and resources were born in this critical period to serve specifically the purposes of COVID-19 mitigation, while setting the research ground for contrasting possible future pandemics. Accessibility and integration of viral sequence data, possibly in conjunction with the human host genotype and clinical data, are paramount to better understand the COVID-19 disease and mitigate its effects.

The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity then becomes crucial for tourist-oriented cities. This study focused on Baguio City, the "Summer Capital of the Philippines," attracting large crowds on holidays and actively promoting various events on non-holidays, thereby having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, load number (LN) changes for different temporal contexts are calculated based on spatial indicators grouped into air, traffic, economy, and waste. The city experiences the worst pressures on air quality during holidays with $99.23\%$ districts under very high to critical levels followed by regular and days with events. However, the total LN is balanced by favorable economic conditions with only $9.23\%$ at critical. EUCCLN effectively pinpoints areas experiencing critical states at any time, advocating targeted government monitoring. We demonstrate that Night Time Light, for places with no economic data available, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that EUCCLN monitoring urban pressures can easily be expanded to nowcasting with real-time data.

In a Water-Cooled Lithium-Lead (WCLL) Breeding Blanket (BB), the heat generated by the plasma thermal radiation and nuclear reactions is removed mainly by two components; namely, the First Wall (FW) and the Breeding Zone (BZ). The FW faces the neutrons and charged particles fluxes generated by the fusion reactions and the thermal radiation coming from the plasma. The present work takes into account the FW cooling system inspired by the WCLL BB 2018 design of DEMO 2017 baseline. Unlike the baseline where a Pressurized-Water Reactor (PWR) setup is used for the coolant, various setup between the Boiling Water Reactor (BWR) and the High-Pressure (HP) BWR are studied in the present work operating in the Two-Phase Flow (TPF) regime. The 3D model of the FW in the WCLL BB 2018 design is simplified into a 1D model and a steady state analysis is carried out to optimize the mass flow rate of the water and the number of parallel channels at the BB cells at different poloidal locations of the reactor, which helps not only in reducing the used coolant but also in improving the Tritium Breeding Ratio (TBR). The present work takes into account forced convection in the liquid only region, the subcooled boiling region, and the saturated boiling region using suitable empirical or semi-empirical models from the literature. The results are validated against the existing results in the literature. In the end, related conclusions are made regarding the pros and cons of the studied operating conditions.

Although many devices have recently been proposed for pressure regulation and energy harvesting in water distribution and transport networks, very few applications are still documented in the scientific literature. A new in-line Banki turbine with positive outflow pressure and a mobile regulating flap, named PRS, was installed and tested in a real water transport network for pressure and discharge regulation. The PRS turbine was directly connected to a 55 kW asynchronous generator with variable rotational velocity, coupled to an inverter. The start-up tests showed how automatic adjustment of the flap position and the impeller velocity variation are able to change the characteristic curve of the PRS according to the flow delivered by the water manager or to the pressure set-point assigned downstream or upstream of the system, still keeping good efficiency values in hydropower production.

Malassezia species are part of human commensal microbiota and is also related to diseases. Little is known about the interaction of these microorganisms with their host. Here we established two standard culture conditions for Malassezia spp. to perform infection assays using C. elegans and T. molitor. Invertebrate hosts infected by Malassezia spp. cultured in M9M resulted in higher death rate on survival assays when compared to yeasts cultured in standard Dixon medium indicating that M9M cultured Malassezia species have increased virulence. The culture and infection conditions established in this work, using invertebrate alternative models, are valuable tools to understand Malassezia-host interaction.

Plants offer a simpler and cheaper alternative to mammalian animal models for the study of Endoplasmic Reticulum glycoprotein folding Quality Control (ERQC). In particular, the Arabidopsis thaliana (At) innate immune response to bacterial peptides provides an easy means of assaying ERQC function in vivo. A number of mutants that are useful to study ERQC in planta have been described in the literature, but only for a subset of these mutants the innate immune response to bacterial elicitors has been measured beyond monitoring plant weight and some physio-pathological parameters related to the plant immune response. In order to probe deeper into the role of ERQC in the plant immune response, we monitored expression levels of the PHI-1 and RET-OX genes in the At ER α-Glu II rsw3 and the At UGGT uggt1-1 mutant plants, in response to bacterial peptides elf18 and flg22. The elf18 response was impaired in the rsw3 but not completely abrogated in the uggt1-1 mutant plants, raising the possibility that the latter enzyme is partly dispensable for ERF signalling. In the rsw3 mutant, seedling growth was impaired only by concomitant application of the At ER α-Glu II NB-DNJ inhibitor at concentrations above 500 nM, suggesting residual activity in this mutant. The study highlights the need for extending plant innate immune response studies to assays sampling EFR signalling at the molecular level.

The decarbonization of the electricity grid as one among the actions to reduce fossil fuel emissions, and thus their impact on global warming in the future, will be achieved mainly via the integration and widespread diffusion of renewable power sources. This is going to be supported also by the shift from the paradigm production-transmission-distribution, where electricity production oversees large-size power plants, to renewable-based distributed/diffused production, where electricity is generated very close or even by the same (group of) user(s) (or prosumers in the latter case). The number of mid-/small-size installations based on renewable energy technologies will therefore increase substantially, and the related renewable generation will be dominant against that from large-size power plants. Unfortunately, this will reduce the reliability of the grid very likely, unless appropriate countermeasures are taken/implemented, hopefully at the same time the paradigm shift is being achieved. To this aim, it is important to identify the anomalies and main fault causes that might determine in renewable-based power systems. This paper surveys the current state-of-the-art on anomalies and faults affecting wind-PV-storage hybrid power systems, i.e., the main renewable technology ensemble that will establish the future grid, and highlights possible research directions that may help to fill the literature gaps.

Background: Systemic autoimmune rheumatic diseases (SARDs), including Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA), are characterized by chronic inflammation and autoimmunity. Identifying reliable biomarkers is crucial for enhancing diagnosis, monitoring disease progression, and evaluating therapeutic responses. This study explores the potential of serum Syndecan-1 (SDC-1) as a biomarker for these conditions and concurrently examines its relationship with free light chain (FLC) expression levels in the same patients. Methods: A retrospective analysis was performed on serum samples from 120 patients (60 RA, 60 SLE), alongside 50 healthy donors (HD). Serum levels of κ and λ FLCs were determined by turbidimetric assay, while SDC-1 levels were measured using ELISA. Statistical analyses, including the Kruskal-Wallis test, Wilcoxon-Mann-Whitney U test, multivariable linear regression and Spearman’s correlation, were employed to compare biomarker levels across groups and to explore correlations among them. Results: Significantly increased levels of SDC-1, κ-FLC, and λ-FLC were observed in patients diagnosed with RA and SLE compared to HD (p < 0.001), while no significant differences in the κ/λ ratio were noted among the groups (p = 0.4). A statistically significant difference in subject age was also identified. However, multivariate regression analysis indicated that RA and SLE statuses are significantly associated with the levels of these markers, with minimal confounding by age. A significant correlation was observed separately in all groups between the FLC markers. Conversely, no correlation was detected between SDC-1 and FLCs, nor between these markers and age. Conclusion: Elevated serum levels of FLCs and SDC-1 in RA and SLE patients compared to healthy controls underscore their potential as biomarkers for SARDs. The findings also suggest sustained plasma cells activation, supporting the SDC-1 role in the pathogenesis of these conditions.

(1) Background: A growing number of communities are re-discovering the value of their streets as important public spaces for many aspects of daily life, thus creating the need for a transformation in the quality of streets. An emerging concept is to accommodate all users of the transportation system, a concept that has been labelled ‘complete streets’. (2) Methods: In this paper, we present sustainable complete streets design criteria that integrate complete streets by adding in socio-environmental design criteria related to aesthetics, environment, liveability, and safety. (3) Results: Proposed design criteria provide a street network which provides improvements in aesthetics, to recover historical urban character and realize historical area planning goals; environment, to increase permeable surfaces, reduce the heat island, and absorb traffic-related air pollution; liveability, to create a public space destination in the urban landscape; and safety, to improve the safety of all road users. and (4) Conclusions: The case study of the urban rehabilitation of the “Mostra d’Oltremare” area and of its cultural and architectural assets in Naples, Italy, highlights the practical application of the proposed criteria and the possibility of using these criteria in other urban contexts.

The outbreak of novel Coronavirus (SARS-COV-2 ) disease (COVID-19) in Wuhan has attracted worldwide attention. SARS-COV-2 known to share a similar clinical manifestation that includes various symptoms such as pneumonia, fever, breathing difficulty, and in particular, SARS-COV-2 also causes a severe in ammation state that leads to death. Consequently, massive and rapid research growth has been observed across the globe to elucidate the mechanisms of infections and disease progression in genotype and phenotype scale. Data Science is playing a pivotal role in in-silico analysis to draw hidden and novel insights about the SARS-COV-2 origin, pathogenesis, COVID-19 outbreak forecasting, medical diagnosis, and drug discovery. With the availability of multi-omics, radiological, biomolecular, and medical data urges to develop novel exploratory and predictive models or customise exiting learning models to t the current problem domain. The presence of many approaches generates the need for the systematic surveys to guide both data scientists and medical practitioners. We perform an elaborate study on the state-of-the-art data science method ologies in action to tackle the current pandemic scenario. We consider various active COVID-19 data analytics domains such as phylogeny analysis, SARS-COV-2 genome identication, protein structure prediction, host-viral protein interactomics, clinical imaging, epidemiological analysis, and most importantly (existing) drug discovery. We highlight types of data, their generation pipeline, and the data science models in use. We believe that the current study will give a detailed sketch of the road map towards handling COVID-19 like situation by leveraging data science in the future. We summarise our review focusing on prime challenges and possible future research directions .

This retrospective observational study describes the results of an ad-hoc designated prevention protocol aimed at containing the spread of the scabies infestation among healthcare workers (HCWs) of a large University Hospital in Italy. The outbreak started on October 2022 and a preventive protocol was set up thanks to a multidisciplinary approach. HCWs at high scabies risk were defined as subjects working in UOs with more than five confirmed cases of scabies, close contacts of a confirmed case of scabies, or HCWs with signs and symptoms of the disease. All cases of at high scabies risk underwent a dermatological examination and the infested HCWs were suspended from work until definitive healing. Mass prophylactic treatment was established for all HCWs working in UOs with more than five confirmed cases of scabies. Until March 2023, out of 183 screening dermatological examinations, 21 (11.5%) were diagnostic for scabies. We obtain a prevalence of scabies of 2.6% (21/800) and a duration of the outbreak of 14.7 weeks. Statistical analysis shows a significant association between scabies and being a nurse and have an allergy to dust mites. We obtained a low prevalence of scabies infection, limiting the duration of the outbreak and the related economic burden.

In this study, we report a detailed experimental and theoretical investigation of three glycols, namely ethane-1,2-diol, 2-methoxyethan-1-ol and 1,2-dimethoxy ethane. For the first time, the X-Ray spectra of the latter two liquids was measured at room temperature, and they were compared with the newly measured spectrum of ethane-1,2-diol. The experimental diffraction patterns were interpreted very satisfactorily with molecular dynamics calculations, and suggest that in liquid ethane-1,2-diol most molecules are found in gauche conformation, with intramolecular hydrogen bond between the two hydroxyl groups. Intramolecular H-bonds are established in the mono-alkylated diol, but the interaction is weaker. The EDXD study also evidences strong intermolecular hydrogen-bond interactions, with short O···O correlations in both systems, while longer methyl-methyl interactions are found in 1,2-dimethoxy ethane. X-Ray studies are complemented by micro Raman investigations at room temperature and at 80°C, that confirm the conformational analysis predicted by X-Ray experiments and simulations.

Outdoor exercise is beneficial for psychophysical well-being. Limited studies have compared outdoor and virtual reality (VR) indoor physical activities, especially in coastal settings. Therefore, this study aimed to assess the impact of outdoor coastal walking and indoor walking in a VR simulation with a similar environment on physiological and psychological variables in healthy adults. Twenty-six subjects (14M and 12F; age 25.2 ± 2.5 years) voluntarily participated in this crossover randomized controlled and counterbalanced study and were allocated under three conditions: VR indoor walking (INVR), outdoor walking (OUT) and standard indoor walking (IN). IN and INVR conditions were performed on a treadmill (speed 4.5 Km/h) and the OUT was per-formed on a seaside pedestrian road. The same outdoor environment was displayed in the visor during the INVR. Heart rate (HRmean/max), Physical Activity Enjoyment (PACES-It) and State of Mindfulness for Physical Activity (SMS-PA) were assessed at the end of each condition. The OUT condition showed significantly greater PACES-It scores and HRmean than IN and INVR (p<0.001) and greater SMS-PA scores and HRmax than IN (p<0.01 and p<0.05, respectively). No significant dif-ferences were found between OUT and INVR regarding HRmax and SMS-PA scores (p>0.05). Findings suggest that physical activity in an immersive technology may lead to physiological loads comparable to the outdoor environment. OUT is more enjoyable than IN and INVR but exhibits a mindfulness response comparable to INVR. Therefore, INVR could be an alternative to OUT for those who cannot engage in outdoor activities for various reasons.

This study aimed to extract bioactive compounds from apple (Malus domestica) peel waste using supercritical CO2 extraction. The bioactive fractions from apple peels from the three Italian cultivars were extracted applying a temperature of 60 °C and a pressure of 250 bar for 15 min. 20% ethanol was used as a co-solvent. The extraction process was carried out at a flow rate of 2 mL/min and their total polyphenol (TP), anthocyanin (TA), ascorbic acid (AA), and antioxidant activity contents (TAC) were measured. The extracts from the Stark cultivar had the highest levels of polyphenols, anthocyanins, and ascorbic acid, while the Royal Gala cultivar had the highest total antioxidant activity. Chromatographic analyses were also performed to characterize polyphenols. The extracts were then tested for their effect on the mitochondrial NADH-ubiquinone oxidoreductase (Complex I) activity on mitochondria isolated from human embryonic kidney cells (HEK239) cells, with the Stark extracts showing the most positive response in terms of NADH oxidation. These findings highlight the potential of apple peel waste as a source of functional phytocompounds and suggest the Stark cultivar extracts may have pharmacological applications. This study supports the circular bioeconomy by promoting the use of waste products as a valuable resource.

This study investigates the effects of xylitol, a natural sugar alcohol, on tumor progression in syngeneic mouse cancer models. Xylitol has been known for its dental health benefits, but emerging evidence suggests broader biological roles, including potential anti-cancer properties. We explored xylitol's impact on two mouse cancer models: 4T1 mammary carcinoma and B16F10 melanoma. Xylitol's efficacy in inhibiting cancer cell lines and modulating tumor progression was assessed using immunocompetent female mice. The experiments involved intratumoral and peri-tumoral administration of a 20% xylitol solution in two mouse strains: BALB/c (4T1 mammary carcinoma) and C57BL/6 (B16F10 melanoma). Tumor volume, histopathology, and metabolomic analyses were conducted to gauge xylitol's influence. The study revealed that xylitol administration initially reduced tumor growth in the B16F10 melanoma model, accompanied by alterations in tumor metabolism. However, similar effects were not observed in the 4T1 mammary carcinoma model, and melanoma tumor growth re-commenced after stroma deterioration permitted xylitol solution leakage. These findings suggest that xylitol may have potential as an adjunct therapy in cancer treatment, specifically in melanoma. The differential response between the two cancer models underscores the complexity of cancer biology and the need for further investigation into xylitol's mechanisms of action and its role in cancer therapy.

The use of friction-based Beam-to-Column Connections (BCC)s for earthquake-resistant Moment Resistant Frames (MRFs), aiming at eliminating damage to beam end sections due to the development of plastic hinges, has taken hold since the early eighties. Different technical solutions were proposed for steel structures, some were also designed for timber structures, while few more recent studies concern friction joints employed in reinforced concrete structures. Research aimed at characterizing the behavior of joints has focused on the evaluation of the tribological properties of the friction materials, coefficient of friction, shape and stability of the hysteresis cycles, influence of the temperature, speed of load application, effects of the application method, stability of preload, the influence of seismic excitation characteristics on the structural response, statistical characterization of amplitude and frequency of the slip excursion during seismic excitation. Studies aimed at identifying the design parameters capable of optimizing performance have focused attention mainly on the slip threshold, device stiffness, and deformation capacity. This review compiles the main and most recent solutions developed for MRFs. Furthermore, the pros and cons for each solution are highlighted, focusing on the dissipative capacity, shape and stability of hysteresis loops. In addition, the common issues affecting all friction connections, namely characteristics of friction shims and the role of bolt preload, are discussed. Based on the above considerations, a guideline can be outlined, which can help to choose the appropriate solutions for beam-to-column connections for MRFs.

Bootstrap resampling techinques, introduced by Efron and Rubin, can be presented in a general Bayesian framework, approximating the statistical distribution of a statistical functional φ(F), where F is a random distribution function. Efron’s and Rubin’s bootstrap procedures can be extended introducing an informative prior through the Proper Bayesian bootstrap. In this paper different bootstrap techniques are used and compared in predictive classification and regression models based on ensemble approaches, i.e. bagging models involving decision trees. Proper Bayesian bootstrap, proposed by Muliere and Secchi, is used to sample the posterior distribution over trees, introducing prior distributions on the covariates and the target variable. The results obtained are compared with respect to other competitive procedures employing different bootstrap techniques. The empirical analysis reports the results obtained on simulated and real data.

Background: medical devices are designed, tested and placed on the market in a highly regulated environment. Wearable sensors are crucial components of various medical devices: design and validation of wearable sensors, if managed according to international standards, can foster innovation while respecting regulatory requirements. Material and methods: the purpose of this paper is to take into consideration the upcoming EU Medical Device Regulation 2017/245 and the current and future IEC and ISO standards that set methods for design and validation of medical devices, with a focus on wearable sensors. Risk classification according to the regulation is described. The international standards IEC 62304, IEC 60601, ISO 14971 and ISO 13485 are reviewed to define regulatory restrictions during design, pre-clinical validation and clinical validation of devices that include wearable sensors as crucial components. Results: current and future regulatory restrictions are described, and an integrated method for design planning, validation and clinical testing is described Discussion: application of this method to design wearable sensors should be evaluated in the future in order to assess its potentially positive impact to fostering innovation and to the time-to-market of the device.

Several eye-tracking technologies have been developed in the last 20 years. This paper aims to present a new kind of eye tracker that can produce detailed information on both eye and head movements using an array of magnetoresistive detectors fixed on the patient’s head and a small magnet inserted in a contact lens, tailored to the subject’s cornea curvature. The software used for data analysis can combine or compare the eye and the head movements and can draw them up as 2D or 3D images. Preliminary data concern a starter patient that was asked to perform several tasks to establish the accuracy, reliability and tolerance of the magnetic eye tracker and the software. The tasks included the evaluation of saccadic eye movements and pursuit, “drawing” shapes or alphabetical letters and reading. Finally, a Head Impulse Test (HIT) was performed for VOR gain estimation, comparing the standard deviation established through vHIT to the one established through this magnetic eye tracker (mHIT). This prototypic device is low invasive, light, relatively low cost and tolerable, with a high grade of reliability and accuracy. All these features might lead to future use of the magnetic eye tracker in neurological and otoneurological fields.

Airborne micro- and nanoplastics are widely spread and pose a risk to human health. The effects of virgin (v) and home oxidised (ox) nano- and micropolystyrene (nPS/mPS) (0.1 and 1 µm) were studied on the human alveolar cells (A549). Ox-nPS/mPS, simulating photoaging, allowed effects due to environmental wear to be assessed. Cellular uptake was quantified using FITC-functionalised nPS/mPS, while cytotoxicity, changes in the acidic compartment, ROS production, mitochondrial function and DNA damage were assessed to study the effects of internalised v- and ox-nPS/mPS. The uptake was dose-dependent and very fast, since, at the lowest dose, 20.8% and 21.8% of nPS and mPS, respectively, were internalised after 1 h. Compared to v-, significant ROS increases, DNA damage and mitochondrial impairment were observed after exposure to ox-nPS/mPS. The enhancement of effects due to environmental aging processes highlighted the true potential impact on human health of these airborne pollutants.