Influence of ultra-high pressure homogenization (UHPH) in the fermentability of Tempranillo musts by Saccharomyces and non-Saccharomyces

Ultra-high-pressure homogenization eliminates native microbiota in grapes. The microorganism's inactivation occurred at 300 MPa which reduce the size of all particles, including microorganisms, to the nanometric scale. Tempranillo musts were evaluated to see whether the physical-chemical and microbiological properties are optimal for conducting alcoholic fermentations using yeast starters, both Saccharomyces and non-Saccharomyces. To assess the ability of musts to be fermented, oenological parameters, aromatic volatile compounds, and chromatic properties of wines have been measured. The elimination of yeasts with UHPH treatments allowed the implantation of non-Saccharomyces yeast starters. For instance, L. thermotolerans produce 2 g/L lactic acid which avoided pigment loss when used in a consortium with T. delbrueckii strains. The possibility of having a sterile must without heat markers with required nutritional quality for yeast starters to be used is one of the features that makes UHPH interesting to be used in the winemaking industry

Oral anticoagulation versus no anticoagulation for stroke prevention in patients with intracranial haemorrhage and atrial fibrillation: An updated meta-analysis of randomised controlled trials

Background: Oral anticoagulation (OAC) effectively reduces stroke risk in patients with atrial fibrillation (AF), but its use after intracranial haemorrhage (ICH) remains controversial due to bleeding concerns. This study aimed to update the evidence on the efficacy and safety of OAC in patients with AF with a history of ICH. Methods: A systematic review and meta-analysis were conducted according to Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. We searched PubMed, Scopus and EMBASE for randomised controlled trials (RCTs) comparing OAC versus avoiding anticoagulation in patients with AF post-ICH. The primary outcomes were ischaemic stroke and recurrent ICH. Secondary outcomes included all-cause mortality, cardiovascular mortality, major adverse cardiovascular events (MACE), major haemorrhage and a composite endpoint of clinical benefit' (first incident ischaemic stroke and first incident recurrent ICH). Pooled risk ratios (RRs) with 95% CIs were calculated using a random-effects model. Results: Four RCTs with 653 participants were included. Anticoagulation was associated with a reduced risk of ischaemic stroke (RR 0.23, 95% CI 0.06 to 0.91) and increased risk of recurrent ICH (RR 3.60, 95% CI 1.40 to 9.30). No significant differences were observed in all-cause mortality (RR 0.93, 95% CI 0.59 to 1.46), cardiovascular death (RR 1.01, 95% CI 0.32 to 3.18) and for net clinical benefit (RR 0.72, 95% CI 0.42 to 1.24). Anticoagulation was associated with a significant increased risk of any major haemorrhage (RR 2.49, 95% CI 1.29 to 4.81) and reduced MACE (RR 0.64, 95% CI 0.44 to 0.94). Conclusions: OAC in patients with AF and prior ICH was associated with a reduced risk of ischaemic stroke and an increased risk of recurrent ICH. PROSPERO registration number: CRD42025637606

Automatic Measurement of Driving Simulators Acceptability through Design of Wearable Sensors and Implementation of Machine Learning Algorithms

This doctoral research provides an in-depth investigation into driver cognitive state recognition through the development of a next-generation wearable edge-AI sensor platform, the design and execution of advanced experimental setups and analysis, and the creation of innovative deep learning (DL) models for multimodal sensor fusion, achieving high classification accuracy. A series of carefully designed driving simulator experiments evaluated stress, attention, motion sickness, and mental engagement across diverse scenarios, encompassing both manual and autonomous driving phases. Physiological signals, including six-channel electroencephalogram (EEG) signals, and in specific studies, skin potential response (SPR) and electrocardiogram (ECG) signals, were recorded using custom-developed graphical user interfaces (GUIs) that enabled real-time data acquisition, synchronization, filtering, and storage. Comprehensive preprocessing techniques, such as artifact removal and advanced filtering methods, ensured high data reliability and quality. Stress assessment focused on EEG beta band power, a well-established marker of stress and cognitive load, revealing consistently higher beta power during manual driving compared to autonomous phases. Attention levels were quantified through eye blink rate (EBR) derived from EEG frontal channels, with results demonstrating a negative correlation between EBR and beta power, indicating that heightened attention corresponds to reduced blink frequency. Motion sickness was investigated through sensory conflict experiments, with findings establishing the beta/alpha power ratio as a robust indicator of motion sickness. This research further advanced the field by developing and evaluating DL models for mental engagement prediction through multimodal sensor fusion. A proposed feature-fusion approach integrating EEG, SPR, and ECG signals achieved superior accuracy (82.2%), outperforming a data-fusion model (74.4%). These findings underscore the effectiveness of multimodal physiological signal fusion using advanced convolutional neural networks (CNNs). Another contribution of this research is the conceptualization and development of VersaSens, a modular and multimodal wearable platform designed for next-generation edge-AI applications. VersaSens integrates sensor, processor, and co-processor modules, providing versatility, scalability, and energy-efficient performance. A CNN-based DL model for mental engagement prediction was deployed on the platform’s System-on-Chip (SoC), achieving an accuracy of 72.8% with low energy consumption, validating its real-time edge-AI capabilities. In conclusion, this research marks a significant advancement in driver cognitive state recognition through the integration of multimodal sensor fusion, advanced DL architectures, and edge-AI wearable technologies. These contributions establish a strong foundation for future innovations in driving simulators, autonomous vehicles, human-machine interaction, and next-generation smart wearable systems.This doctoral research provides an in-depth investigation into driver cognitive state recognition through the development of a next-generation wearable edge-AI sensor platform, the design and execution of advanced experimental setups and analysis, and the creation of innovative deep learning (DL) models for multimodal sensor fusion, achieving high classification accuracy. A series of carefully designed driving simulator experiments evaluated stress, attention, motion sickness, and mental engagement across diverse scenarios, encompassing both manual and autonomous driving phases. Physiological signals, including six-channel electroencephalogram (EEG) signals, and in specific studies, skin potential response (SPR) and electrocardiogram (ECG) signals, were recorded using custom-developed graphical user interfaces (GUIs) that enabled real-time data acquisition, synchronization, filtering, and storage. Comprehensive preprocessing techniques, such as artifact removal and advanced filtering methods, ensured high data reliability and quality. Stress assessment focused on EEG beta band power, a well-established marker of stress and cognitive load, revealing consistently higher beta power during manual driving compared to autonomous phases. Attention levels were quantified through eye blink rate (EBR) derived from EEG frontal channels, with results demonstrating a negative correlation between EBR and beta power, indicating that heightened attention corresponds to reduced blink frequency. Motion sickness was investigated through sensory conflict experiments, with findings establishing the beta/alpha power ratio as a robust indicator of motion sickness. This research further advanced the field by developing and evaluating DL models for mental engagement prediction through multimodal sensor fusion. A proposed feature-fusion approach integrating EEG, SPR, and ECG signals achieved superior accuracy (82.2%), outperforming a data-fusion model (74.4%). These findings underscore the effectiveness of multimodal physiological signal fusion using advanced convolutional neural networks (CNNs). Another contribution of this research is the conceptualization and development of VersaSens, a modular and multimodal wearable platform designed for next-generation edge-AI applications. VersaSens integrates sensor, processor, and co-processor modules, providing versatility, scalability, and energy-efficient performance. A CNN-based DL model for mental engagement prediction was deployed on the platform’s System-on-Chip (SoC), achieving an accuracy of 72.8% with low energy consumption, validating its real-time edge-AI capabilities. In conclusion, this research marks a significant advancement in driver cognitive state recognition through the integration of multimodal sensor fusion, advanced DL architectures, and edge-AI wearable technologies. These contributions establish a strong foundation for future innovations in driving simulators, autonomous vehicles, human-machine interaction, and next-generation smart wearable systems

Exploring the influence of polystyrene-nanoplastics on two distinct in vitro systems in farm animals: A pilot study

The harmful effects of micro- and nanoplastics (MNPs) on the aquatic ecosystem are already well established, and several studies have demonstrated that MNPs can contaminate the soil. However, the impact of MNPs on farm animals, whose products are intended for human consumption, as well as the accumulation and translocation of these particles in their bodies, is less investigated and not well understood. To address this issue, we evaluated the cellular uptake and the effects of three different concentrations (5, 25, and 75 μg/mL) of 100 nm polystyrene nanoplastics (PS-NPs) on ovarian bovine granulosa cells (GCs) and porcine myoblasts derived from skeletal muscle satellite cells as in vitro primary cell culture models. The uptake of PS-NPs was shown for all the concentrations tested, both for GCs and for myoblasts. The results for GCs reported a significant decrease in cell viability (P < 0.05) for all concentrations of nanoplastics tested compared to the control. However, steroid hormone production and the mRNA expression of GC physiology marker genes were not affected. The results for myoblasts showed a significant decrease in the mean confluence (P < 0.05) after exposure to a concentration of 75 μg/mL of nanoplastics compared to the control. This may be indicative of an initial inhibition of muscle fibre formation. However, cell viability, proliferative capacity, and the mRNA expression of myogenesis-associated genes were not affected. As there is currently no standard method for assessing the quantity of particles that overcome the anatomical barriers and accumulate in various parts of the body, recognizing the implications of exposure to MNPs in farm animals can help us to better comprehend the potential risks to human health. This knowledge is critical for developing informed treatment and avoidance strategies, ensuring the safety of both the food we consume and the environment in which it is produced

The Properties and Applicability of Bioprinting in the Field of Maxillofacial Surgery

Perhaps the most innovative branch of medicine is represented by regenerative medicine. It deals with regenerating or replacing tissues damaged by disease or aging. The innovative frontier of this branch is represented by bioprinting. This technology aims to reconstruct tissues, organs, and anatomical structures, such as those in the head and neck region. This would mean revolutionizing therapeutic and surgical approaches in the management of multiple conditions in which a conspicuous amount of tissue is lost. The application of bioprinting for the reconstruction of anatomical areas removed due to the presence of malignancy would represent a revolutionary new step in personalized and precision medicine. This review aims to investigate recent advances in the use of biomaterials for the reconstruction of anatomical structures of the head-neck region, particularly those of the oral cavity. The characteristics and properties of each biomaterial currently available will be presented, as well as their potential applicability in the reconstruction of areas affected by neoplasia damaged after surgery. In addition, this study aims to examine the current limitations and challenges and to analyze the future prospects of this technology in maxillofacial surgery

New oxygen carriers for efficient syngas and H2 production by chemical looping steam methane reforming

The research work illustrate the development of catalyst-promoted Fe-based Oxygen Carriers (OC) for the Chemical Looping Steam Reforming (CL-SMR) process. Goal of the study was to explore novel methods for preparing oxygen carrier materials that combine the advantages of Fe-containing oxides, including environmental compatibility, relatively low cost, and the ability to be partially or fully reoxidized by steam, with the high CH4 activation ability of Ni. The process enables the simultaneous production of pure hydrogen, along with the syngas derived from the partial oxidation of the hydrocarbons feed. The work provides guidance for the design of physically mixed OC-supported catalyst composite carrier systems, through the investigation of the CL-SMR performances, chemical compatibility, stability, and composition of such systems. Furthermore, a preliminary investigation into the use of an exsolving Ni-doped Fe-based perovskite highlights the potential of this class of materials in chemical looping processes—a potential that has remained largely unexplored until recently

Amyloid-related imaging abnormalities: manifestations, metrics and mechanisms

Three monoclonal antibodies directed against specific forms of the amyloid-β (Aβ) peptide have been granted accelerated or traditional approval by the FDA as treatments for Alzheimer disease, representing the first step towards bringing disease-modifying treatments for this disease into clinical practice. Here, we review the detection, underlying pathophysiological mechanisms and clinical implications of amyloid-related imaging abnormalities (ARIA), the most impactful adverse effect of anti-Aβ immunotherapy. ARIA appears as regions of oedema or effusions (ARIA-E) in brain parenchyma or sulci or as haemorrhagic lesions (ARIA-H) in the form of cerebral microbleeds, convexity subarachnoid haemorrhage, cortical superficial siderosis or intracerebral haemorrhage. Analysis of the radiographic appearance of ARIA, its clinical risk factors and underlying neuropathology, and results from animal models point to a central role for cerebral amyloid angiopathy — a condition characterized by cerebrovascular Aβ deposits — as a key component, either as a direct target for antibody-mediated inflammation or as recipient of Aβ mobilized from plaques in the Alzheimer brain parenchyma. The great majority of ARIA occurrences are associated with mild or no clinical symptoms. However, ~5% of all ARIA events are severe enough to result in hospitalization, permanent disability or death and thus raise challenging clinical questions regarding patient selection and use of concomitant agents. Therefore, identifying novel approaches to predicting, modelling, preventing and treating ARIA remains a key step towards allowing safe use of anti-Aβ immunotherapy for the world’s rapidly ageing population

BEETter AGING: Short-Term Dietary Nitrate Supplementation Enhances Muscle Contractile Properties in Older But Not in Young Adults

Purpose: Dietary nitrate (NO3-) supplementation has been shown to improve skeletal muscle contractile function and reduce fatigue, potentially due to alterations in skeletal muscle Ca2+ handling/sensitivity. Since aging muscle can have impaired Ca2+ handling, the aim of the study was to evaluate the effects of dietary NO3- supplementation on muscle contractile properties in young and older adults. Methods: Eleven older (69±4yrs, O) and 11 young (26±2yrs, YG) adults consumed either NO3-rich beetroot juice (BR) or placebo (PLA), for 7 days. After supplementations, plantar flexors of dominant leg were evaluated as follow: a) maximal voluntary isometric contraction (MVIC); b) potentiated single twitches (Twpot) and double twitches electrical stimulations at the frequency of 100Hz (Db100) on the tibial posterior nerve; c) a fatigue isometric (70% of MVIC) test until exhaustion. The force-frequency relationship was assessed with trains of electrical pulses across a wide range of frequencies on the muscle belly of the non-dominant leg. Results: BR supplementation increased plasma [NO3-] and nitrite [NO2-] in both O and YG compared to PLA (more than 7-fold; all P≤0.02). No changes were observed in MVC, Twpot, and Db100 force after BR compared to PLA in both YG and O. Only in O, Db100 area under the curve (-7±6 N∙s change from PLA) and half relaxation time (-0.05±0.06s change from PLA) were significantly reduced. and time to exhaustion (+32±43s change from PLA) was significantly longer (all P<0.02) after BR. In O, BR also significantly increased submaximal force produced by trains of electrical pulses (P < 0.001). Conclusions: NO3- supplementation positively affects muscle contractile proprieties, submaximal electrically evoked force production and fatigue resistance in older adults while these positive results were not found in young

An approach based on B-spline quaternion curves for planning the orientation trajectories of spray-painting robots

Planning smooth orientation trajectories is a complex challenge in robotic spray painting, especially due to the need to ensure continuity in velocity and acceleration while avoiding singularities associated with Euler angles. This paper introduces a method for planning the orientation trajectories of spray-painting robots. The proposed approach leverages cubic B-splines with cumulative basis functions and unit quaternions to achieve a global interpolation of input orientations, guiding the robot tool along the required path. The approach is first compared with a standard strategy in which orientations are expressed as Euler angles, to demonstrate that the use of unit quaternions for orientation representation helps circumvent potential singularity issues associated with Euler angles. Then, the experimental validation on an industrial spray-painting robot with six degrees of freedom, following the trajectory needed to paint a three-dimensional model of a car bumper, illustrates the effectiveness of the proposed strategy in approximating input orientations. The approach also allows maintaining continuity in velocity and acceleration, crucial for successful industrial spray painting, while meeting joint velocities and accelerations limits. Furthermore, the maximum variation of the tangential velocity of the robot end-effector, relative to the imposed value, reaches 4% near the car bumper headlights, where the orientation changes rapidly

Precision oncology in biliary tract cancer: the emerging role of liquid biopsy

Liquid biopsy has already proven effective in aiding diagnosis, risk stratification and treatment personalization in several malignancies, and it could represent a practice-changing tool also in biliary tract cancer, even though clinical applications are currently still limited. It is promising for early diagnosis, especially in high-risk populations, and several studies on circulating free DNA (cfDNA), circulating tumour cells and differential microRNA (miRNA) profiles in this setting are ongoing. Circulating tumour DNA (ctDNA) also appears as a feasible noninvasive biomarker in the curative setting, in detecting minimal residual disease after resection and in monitoring disease recurrence. As of today, it can be particularly valuable in biliary tract cancer for genomic profiling, with a good concordance with tissue samples for most molecular alterations. CtDNA analysis may especially be considered in clinical practice when the tumour tissue is not sufficient for next-generation sequencing, or when urgent therapeutic decisions are needed. Moreover, it offers the possibility of providing a real-time picture to monitor treatment response and dynamically identify resistance mutations, potentially representing a way to optimize treatment strategies