The Anti-Neuroinflammatory Effect of Extra-Virgin Olive Oil in the Triple Transgenic Mouse Model of Alzheimer's Disease.

Background: Chronic intake of extra virgin olive oil is beneficial for brain health and protects from age-related cognitive decline and dementia, whose most common clinical manifestation is Alzheimer's disease. Besides the classical pathologic deposits of amyloid beta peptides and phosphorylated tau proteins, another frequent feature of the Alzheimer's brain is neuroinflammation. Objective: In the current study, we assessed the effect that extra virgin olive oil has on neuroinflammation when administered to a mouse model of the disease. Methods: Triple transgenic mice were randomized to receive a diet enriched with extra virgin olive oil or regular diet for 8 weeks. At the end of this treatment period the expression level of several inflammatory biomarkers was assessed in the central nervous system. Results: Among the 79 biomarkers measured, compared with the control group, mice receiving the extra virgin olive oil had a significant reduction in MIP-2, IL-17E, IL-23, and IL-12p70, but an increase in IL-5. To validate these results, specific ELISA kits were used for each of them. Confirmatory results were obtained for MIP-2, IL-17E, IL-23, and IL-12-p70. No significant differences between the two groups were observed for IL-5. Conclusions: Our results demonstrate that chronic administration of extra virgin olive oil has a potent anti-neuroinflammatory action in a model of Alzheimer's disease. They provide additional pre-clinical support and novel mechanistic insights for the beneficial effect that this dietary intervention has on brain health and dementia.

Association between the consumption of ultra-processed foods and the incidence of peptic ulcer disease in the SUN project: a Spanish prospective cohort study.

PURPOSE: Consumption of ultra-processed foods (UPF) has increased despite potential adverse health effects. Recent studies showed an association between UPF consumption and some gastrointestinal disorders. We evaluated the association between UPF consumption and peptic ulcer disease (PUD) in a large Spanish cohort. METHODS: We conducted a prospective analysis of 18,066 participants in the SUN cohort, followed every two years. UPF was assessed at baseline and 10 years after. Cases of PUD were identified among participants reporting a physician-made diagnosis of PUD during follow-ups. Cases were only partially validated against medical records. Cox regression was used to assess the association between baseline UPF consumption and PUD risk. Based on previous findings and biological plausibility, socio-demographic and lifestyle variables, BMI, energy intake, Helicobacter pylori infection, gastrointestinal disorders, aspirin and analgesic use, and alcohol and coffee consumption were included as confounders.We fitted GEE with repeated dietary measurements at baseline and after 10 years of follow-up. Vanderweele's proposed E value was calculated to assess the sensitivity of observed associations to uncontrolled confounding. RESULTS: During a median follow-up of 12.2 years, we recorded 322 new PUD cases (1.56 cases/1000 person-years). Participants in the highest baseline tertile of UPF consumption had an increased PUD risk compared to participants in the lowest tertile (HR = 1.52, 95% CI: 1.15, 2.00, Ptrend=0.002). The E-values for the point estimate supported the observed association. The OR using repeated measurements of UPF intake was 1.39 (95% CI: 1.03, 1.87) when comparing extreme tertiles. CONCLUSION: The consumption of UPF is associated with an increased PUD risk.

[Stroke and stroke prevention in cardiac and thoracic aortic surgery]. / Ictus e prevenzione dell'ictus in cardiochirurgia e in chirurgia dell'aorta toracica.

Perioperative stroke and neurological injuries in general are complications that can occur during and after cardiac surgery, particularly in aortic surgery that involves the aortic arch. The overall incidence of early and delayed stroke is about 1% according to recent meta-analyses. This incidence depends on interindividual risk factor profile and type of surgery. In order to reduce cerebrovascular complications during cardiac surgery, a number of preventative measures can be taken, including the evaluation of atherosclerotic plaques, the site of cannulation and neuroprotection strategies. During aortic arch surgery, main strategies for cerebral protection are represented by deep hypothermic circulatory arrest, retrograde and antegrade cerebral perfusion.

Aluminum Nitride Thin Film Piezoelectric Pressure Sensor for Respiratory Rate Detection.

In this study, we propose a low-cost piezoelectric flexible pressure sensor fabricated on Kapton® (Kapton™ Dupont) substrate by using aluminum nitride (AlN) thin film, designed for the monitoring of the respiration rate for a fast detection of respiratory anomalies. The device was characterized in the range of 15-30 breaths per minute (bpm), to simulate moderate difficult breathing, borderline normal breathing, and normal spontaneous breathing. These three breathing typologies were artificially reproduced by setting the expiratory to inspiratory ratios (E:I) at 1:1, 2:1, 3:1. The prototype was able to accurately recognize the breath states with a low response time (~35 ms), excellent linearity (R2 = 0.997) and low hysteresis. The piezoelectric device was also characterized by placing it in an activated carbon filter mask to evaluate the pressure generated by exhaled air through breathing acts. The results indicate suitability also for the monitoring of very weak breath, exhibiting good linearity, accuracy, and reproducibility, in very low breath pressures, ranging from 0.09 to 0.16 kPa. These preliminary results are very promising for the future development of smart wearable devices able to monitor different patients breathing patterns, also related to breathing diseases, providing a suitable real-time diagnosis in a non-invasive and fast way.

Short-term effects of Mediterranean diet on nutritional status in adults affected by Osteogenesis Imperfecta: a pilot study.

BACKGROUND: Osteogenesis Imperfecta (OI) is a heterogeneous group of connective tissue disorders, characterized by varying degrees of skeletal fragility. Patients experience a range of comorbidities, such as obesity, cardiovascular, and gastrointestinal complications, especially in adulthood. All aspects that could benefit from dietary intervention. The aim of this study was to evaluate the effects of a 6-months restricted Mediterranean Diet (rMD) on nutritional status in adult patients affected by OI. We carried out a 6-months longitudinal pilot study. 14 adults (median age: 35 years; 7 women; 7 OI type III) where recruited in 2019 among the members of As.It.O.I., the Italian Association of Osteogenesis Imperfecta. As.It.O.I. All the evaluations were performed at the University of Milan, Italy. The rMD provided a reduction of 30% from daily total energy expenditure. 45% of calories derived from carbohydrates, 35% from fat and 0.7-1.0 g/kg of body weight from proteins. Comparisons of continuous variables after 6 months of intervention were performed by the paired t-test. All P-values were two-tailed, and p < 0.05 was considered significant. RESULTS: Patients showed significant improvement in anthropometric measurements (BMI = 30.5 vs 28.1 kg/cm2, p < 0.001; Body Fat % = 32.9 vs 29.9, p = 0.006; Waist circumferences = 83.6 vs 79.6 cm; p < 0.001; Arm Fat Area = 29.8 vs 23.07 cm2; p < 0.011) and energy expenditure (REE/kg = 27.2 vs 29.2 kcal/kg, p < 0.001). Glucose and lipid profiles improved (Δglycemia = - 8.6 ± 7.3 mg/dL, p = 0.003; ΔTC = - 14.6 ± 20.1 mg/dL, p = 0.036; ΔLDL = - 12.0 ± 12.1 mg/dL, p = 0.009). Adherence to the MD significantly increased, moving from a moderate to a strong adherence and reporting an increased consumption of white meat, legumes, fish, nuts, fruits and vegetables. CONCLUSION: A rMD was effective in improving nutritional status and dietary quality in adults with OI. These results underscores the need to raise awareness of nutrition as part of the multidisciplinary treatment of this disease.

Optimisation of an Industrial Optical Sorter of Legumes for Gluten-Free Production Using Hyperspectral Imaging Techniques.

The market demand for gluten-free food is increasing due to the growing gluten sensitivity and coeliac disease (CD) in the population. The market requires grass-free cereals to produce gluten-free food. This requires sorting methods that guarantee the perfect separation of gluten contaminants from the legumes. The objective of the research was the development of an optical sorting system based on hyperspectral image processing, capable of identifying the spectral characteristics of the products under investigation to obtain a statistical classifier capable of enabling the total elimination of contaminants. The construction of the statistical classifier yielded excellent results, with a 100% correct classification rate of the contaminants. Tests conducted subsequently on an industrial optical sorter validated the result of the preliminary tests. In fact, the application of the developed classifier was able to correctly select the contaminants from the mass of legumes with a correct classification percentage of 100%. A small proportion of legumes was misclassified as contaminants, but this did not affect the scope of the work. Further studies will aim to reduce even this small share of waste with investigations into optimising the seed transport systems of the optical sorter.

A Deep Learning-Based Platform for Workers' Stress Detection Using Minimally Intrusive Multisensory Devices.

The advent of Industry 4.0 necessitates substantial interaction between humans and machines, presenting new challenges when it comes to evaluating the stress levels of workers who operate in increasingly intricate work environments. Undoubtedly, work-related stress exerts a significant influence on individuals' overall stress levels, leading to enduring health issues and adverse impacts on their quality of life. Although psychological questionnaires have traditionally been employed to assess stress, they lack the capability to monitor stress levels in real-time or on an ongoing basis, thus making it arduous to identify the causes and demanding aspects of work. To surmount this limitation, an effective solution lies in the analysis of physiological signals that can be continuously measured through wearable or ambient sensors. Previous studies in this field have mainly focused on stress assessment through intrusive wearable systems susceptible to noise and artifacts that degrade performance. One of our recently published papers presented a wearable and ambient hardware-software platform that is minimally intrusive, able to detect human stress without hindering normal work activities, and slightly susceptible to artifacts due to movements. A limitation of this system is its not very high performance in terms of the accuracy of detecting multiple stress levels; therefore, in this work, the focus was on improving the software performance of the platform, using a deep learning approach. To this purpose, three neural networks were implemented, and the best performance was achieved by the 1D-convolutional neural network with an accuracy of 95.38% for the identification of two levels of stress, which is a significant improvement over those obtained previously.

Frozen elephant trunk technique using hybrid grafts: 15-year outcomes from a single-centre experience.

OBJECTIVES: The purpose of the study is to compare the short- and long-term outcomes of the frozen elephant trunk (FET) technique based on 2 different hybrid grafts implanted from January 2007 to July 2022. METHODS: The study includes patients who underwent an elective or emergency FET procedure. Short-term, long-term mortality and freedom from thoracic endovascular aortic repair (TEVAR) were the primary end points. Analyses were carried out separately for the periods 2007-2012 and 2013-2022. RESULTS: Of the 367 enrolled, 49.3% received E-Vita Open implantation and 50.7% received Thoraflex Hybrid implants. Overall mean age was 61 years [standard deviation (SD) = 11] and 80.7% were male. The average annual volume of FET procedures was 22.7 cases/year. Compared to E-Vita Open, patients implanted with Thoraflex Hybrid grafts were more likely to receive distal anastomosis in zone 2 (68.3% vs 11.6%, P < 0.001) with a shorter stent portion, mean = 103mm (SD = 11.3) vs mean = 149 mm (SD = 12.7; P < 0.001) and they underwent a reduced visceral ischaemia time, mean = 42.5 (SD = 14.2) vs mean= 61.0 (SD = 20.2) min, P < 0.001. In the period 2013-2022, overall survival at 1, 2 and 5 years was 74.8%, 72.5% and 63.2% for Thoraflex and 73.2%, 70.7% and 64.1% for E-Vita, without significant differences between groups (log-rank test = 0.01, P = 0.907). Overall freedom from TEVAR at 1, 2 and 5 years was 66.7%, 57.6% and 39.3% for Thoraflex and 79%, 69.7% and 66% for E-Vita, with significant differences between groups (log-rank test = 5.28, P = 0.029). In a competing risk analysis adjusted for chronic/residual aortic syndromes and stent diameter, the Thoraflex group was more likely to receive TEVAR during follow-up (subdistribution hazard ratio SHR = 2.12, 95% confidence interval 1.06-4.22). CONCLUSIONS: The FET technique addresses acute and chronic arch disease with acceptable morbidity and mortality. Downstream endovascular reinterventions are very common during follow-up.

Sex Differences in the Relationship between Chronotype and Eating Behaviour: A Focus on Binge Eating and Food Addiction.

BACKGROUND: Men are more likely than women to have subthreshold overeating disorders. Lifestyle plays a role as a determinant, while chronotype is an emerging factor. Chronotype explains the natural preferences of wakefulness and activity throughout the day: evening chronotypes (E-Types), those most productive in the evening, have been linked with unhealthy dietary patterns and a higher propensity to substance addiction than morning types (M-Types). METHODS: We carried out a cross-sectional study on 750 overweight or obese adults (70% females, 48 ± 10 years, BMI 31.7 ± 5.8 kg/m2). The Binge-Eating Scale, the Yale Food Addiction Scale 2.0 (YFAS 2.0), the reduced Morningness-Eveningness Questionnaire (rMEQ), and the MEDAS questionnaire were used to assess binge eating, food addiction, chronotype, and adherence to the Mediterranean diet, respectively. RESULTS: No differences in BES binge-eating and FA food-addiction scores occurred between chronotypes, but we found significant interactions between sex × rMEQ score. While women showed the same prevalence for binge eating and food addiction across all chronotypes, binge eating and food addiction risk increased with reducing rMEQ score in men, indicating that being male and E-Type increases the risk association of binge eating and/or food addiction prevalence. CONCLUSIONS: chronotype is associated with binge eating and food addiction in men, emphasizing the link between chronobiology and sex differences as determinants in appetite and eating behaviour dysregulation and in overweight and obesity.

Transcatheter Aortic Valve Replacement in Degenerated Perceval Bioprosthesis: Clinical and Technical Aspects in 32 Cases.

BACKGROUND: Sutureless aortic bioprostheses are increasingly being used to provide shorter cross-clamp time and facilitate minimally invasive aortic valve replacement. As the use of sutureless valves has increased over the past decade, we begin to encounter their degeneration. We describe clinical outcomes and technical aspects in patients with degenerated sutureless Perceval (CorCym, Italy) aortic bioprosthesis treated with valve-in-valve transcatheter aortic valve replacement (VIV-TAVR). METHODS: Between March 2011 and March 2023, 1310 patients underwent aortic valve replacement (AVR) with Perceval bioprosthesis implantation. Severe bioprosthesis degeneration treated with VIV-TAVR occurred in 32 patients with a mean of 6.4 ± 1.9 years (range: 2-10 years) after first implantation. Mean EuroSCORE II was 9.5 ± 6.4% (range: 1.9-35.1%). RESULTS: Thirty of thirty-two (94%) VIV-TAVR were performed via transfemoral and two (6%) via transapical approach. Vascular complications occurred in two patients (6%), and mean hospital stay was 4.6 ± 2.4 days. At mean follow-up of 16.7 ± 15.2 months (range: 1-50 months), survival was 100%, and mean transvalvular pressure gradient was 18.7 ± 5.3 mmHg. CONCLUSION: VIV-TAVR is a useful option for degenerated Perceval and appears safe and effective. This procedure is associated with good clinical results and excellent hemodynamic performance in our largest single-center experience.

The Effect of the Mediterranean Diet on Metabolic Health.

The Mediterranean Diet (MedDiet) is one of the healthiest and most balanced dietary patterns worldwide [...].

Distal stent graft-induced new entry (dSINE) after frozen elephant trunk: a scoping review.

Background: The introduction of hybrid total arch replacement with the frozen elephant trunk (FET) technique has improved the field of aortic surgery by allowing single-stage treatment of complex aortic pathologies. Although FET has been associated with favorable aortic remodeling, it is also associated with the potential development of distal stent graft-induced new entries (dSINEs). The aim of our review is to collect data about the incidence and the supposed conditions for the occurrence of dSINE after total hybrid arch replacement with FET technique. Methods: The literature review was performed using PubMed databases from inception to January 2022. A descriptive approach to detect and display supposed risk factors and predictors for dSINE occurrence has been adopted. Results: Eight studies summarized the state-of-the-art of dSINE in a total number of 544 FET procedures performed to treat acute and chronic aortic dissections. The scoping review showed dSINEs occurrence in 69 patients (12.7%). The mean time between surgery and the diagnosis ranged from 12.6 to 30.6 months. Most patients that developed dSINE received endovascular treatment, whereas a couple of them needed open surgery. According to our experience, from January 2007 to December 2021, in 225 FET procedures a total of 54 cases of dSINE, both with Thoraflex and E-vita grafts have been detected. The mean time between the surgical procedure and the diagnosis was 27.2±33.6 months. Conclusions: dSINEs are frequent complications after FET. Although not emergent, they require proper treatment. Due to dSINE's asymptomatic nature and potential harm, a rigorous follow-up including angio-computed tomography (CT) should be planned.

Browning of Adipocytes: A Potential Therapeutic Approach to Obesity.

The increasing prevalence of overweight and obesity suggests that current strategies based on diet, exercise, and pharmacological knowledge are not sufficient to tackle this epidemic. Obesity results from a high caloric intake and energy storage, the latter by white adipose tissue (WAT), and when neither are counterbalanced by an equally high energy expenditure. As a matter of fact, current research is focused on developing new strategies to increase energy expenditure. Against this background, brown adipose tissue (BAT), whose importance has recently been re-evaluated via the use of modern positron emission techniques (PET), is receiving a great deal of attention from research institutions worldwide, as its main function is to dissipate energy in the form of heat via a process called thermogenesis. A substantial reduction in BAT occurs during normal growth in humans and hence it is not easily exploitable. In recent years, scientific research has made great strides and investigated strategies that focus on expanding BAT and activating the existing BAT. The present review summarizes current knowledge about the various molecules that can be used to promote white-to-brown adipose tissue conversion and energy expenditure in order to assess the potential role of thermogenic nutraceuticals. This includes tools that could represent, in the future, a valid weapon against the obesity epidemic.

Consumption of Ultra-Processed Foods and Health Harm.

In recent decades, research has become increasingly interested in the relationship between diet and health [...].

Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy.

Smart living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for smart living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in smart living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of smart living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in smart living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of context awareness, data availability, personalization, and privacy in HAR, this paper offers a comprehensive resource for researchers and practitioners striving to advance smart living services and applications. The methodology for this literature review involved conducting targeted Scopus queries to ensure a comprehensive coverage of relevant publications in the field. Efforts have been made to thoroughly evaluate the existing literature, identify research gaps, and propose future research directions. The comparative advantages of this review lie in its comprehensive coverage of the dimensions essential for smart living services and applications, addressing the limitations of previous reviews and offering valuable insights for researchers and practitioners in the field.

Innovative technologies to enhance oil recovery.

The processes for extracting and refining edible oils are well-established in industry at different scales. However, these processing lines encounter inefficiencies and oil losses when recovering crude or refined oil. Palm oil and olive oil extraction methods are used mainly as a combination of physical, thermal, and centrifugal methods to recover crude oil, which results in oil losses in the olive pomace or in palm oil effluents. Seed oils generally require a seed steam conditioning, and cooking stage, followed by physical oil recovery through an inefficient expeller. Most of the crude oil remaining in the expeller cake is then recovered by hexane. Crude seed oil is further refined in stages that also undergo oil losses. This chapter provides an overview of innovative technologies using microwave, ultrasound, megasonic and pulsed electric field energies, which can be used in the above-mentioned crude and refined oil processes to improve oil recovery. This chapter describes traditional palm oil, olive oil, and seed oil processes, as well as the specific process interventions that have been tested with these technologies. The impact of such technology interventions on oil quality is also summarized.

Multi-Sensor Platform for Predictive Air Quality Monitoring.

Air quality monitoring is a very important aspect of providing safe indoor conditions, and carbon dioxide (CO2) is one of the pollutants that most affects people's health. An automatic system able to accurately forecast CO2 concentration can prevent a sudden rise in CO2 levels through appropriate control of heating, ventilation and air-conditioning (HVAC) systems, avoiding energy waste and ensuring people's comfort. There are several works in the literature dedicated to air quality assessment and control of HVAC systems; the performance maximisation of such systems is typically achieved using a significant amount of data collected over a long period of time (even months) to train the algorithm. This can be costly and may not respond to a real scenario where the habits of the house occupants or the environment conditions may change over time. To address this problem, an adaptive hardware-software platform was developed, following the IoT paradigm, with a high level of accuracy in forecasting CO2 trends by analysing only a limited window of recent data. The system was tested considering a real case study in a residential room used for smart working and physical exercise; the parameters analysed were the occupants' physical activity, temperature, humidity and CO2 in the room. Three deep-learning algorithms were evaluated, and the best result was obtained with the Long Short-Term Memory network, which features a Root Mean Square Error of about 10 ppm with a training period of 10 days.

Review on Human Action Recognition in Smart Living: Sensing Technology, Multimodality, Real-Time Processing, Interoperability, and Resource-Constrained Processing.

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, i.e., 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 further explore and advance the field of human action recognition in smart living.

Modelling the Rheology of Olive Paste for Oil Extraction Plant Automation: Effects of the Crushing Process on the Rheology of Olive Pastes.

In extra virgin olive oil production, it is essential to obtain a well-prepared olive paste which allows not only the extraction of the oil drops from the olives, but also the achievement of a high-quality oil while maintaining high yields. This work addresses the problem of determining the effect of three crushing machines on the viscosity of the olive paste: a hammer crusher, a disk crusher and a de-stoner were tested. The tests were repeated on both the paste leaving each machine and the paste to which water was added; this was done with the main aim of considering the different dilutions of the paste while entering the decanter. A power law and the Zhang and Evans model were used to analyse the rheological behaviour of the paste. The experimental results allow validation of the two models with a high (more than 0.9) coefficient of determination between experimental and numerical data. The results also show that the pastes obtained with the two classic crushing methods (hammers and disks) are almost identical, with a packing factor of about 17.9% and 18.6%, respectively. Conversely, the paste obtained with the de-stoner entails higher viscosity values and a smaller solid packing factor, of about 2.8%. At 30% dilution with water, the volume of the solid concentration dropped to about 11.6% for the hammer and disc crushers, while for the de-stoner it only reached 1.8%. This behaviour is also reflected in the evaluation of yields, which were 6% lower with the de-stoner. No significant differences regarding the legal parameters of oil quality were found using the three different crushing systems. Finally, this paper establishes some fundamental pillars in the research for an optimal model for identifying the rheological behaviour of the paste as a function of the crusher used. Indeed, since there is an increasing need for automation in the oil extraction process, these models can be of great help in optimizing this process.