Specific Areas Of Interest Research Articles

Validation of low-cost mobile phone applications and comparison with professional imaging systems for three-dimensional facial imaging: A pilot study

PurposeThe objective of this study was to investigate the accuracies of three-dimensional (3D) facial scanning mobile phone applications as compared to professional 3D facial imaging systems. Materials and MethodsA manikin head model was used as the subject for comparing six 3D facial imaging systems which comprised three professional 3D scanners (3dMDface, Artec Eva and Vectra H2) and three mobile phone applications (Bellus3D, ScandyPro and Hedges). For each system, five scans were taken to analyse (1) linear accuracy using 9 measurements (2) global and (3) regional 3D accuracy of the scanned surface by root mean square (RMS) and colour map analysis. Another set of five scans was repeated by a second operator to evaluate the inter-operator reproducibility for each system. ResultsAll the facial imaging systems had absolute errors lesser than 1.0 mm for the linear measurements. The technical error of measurement (TEM) for inter-examiner and intra-examiner linear measurements were within acceptable limits. Artec Eva, Vectra H2 and Scandy Pro had poor global 3D trueness (RMS > 1.0 mm) but good 3D regional trueness (RMS < 1.0 mm). 3dMDface, Bellus3D Face App and Heges had good global and regional 3D trueness. All the facial imaging systems had good global and regional 3D precision and reproducibility (RMS < 1.0 mm). ConclusionThis study demonstrated that mobile phone 3D scanning applications had comparable trueness, precision and reproducibility to professional systems. Colour map analysis supplemented the use of the RMS value to demonstrate facial regions of significant deviation. Clinicians should also consider the specific area or region of inaccuracies for each system to determine whether the chosen system is appropriate for the clinical condition or procedure. Clinical SignificanceMobile phone 3D facial imaging applications may be as accurate as 3D professional facial scanning systems for craniomaxillofacial purposes. However, the choice of the system may vary depending on the specific area of interest.

The financial vulnerability of non-profit entities: A theoretical framework proposal

NPOs (Non-Profit Organisations) are entities created to respond to the social needs of the economy, many of which fall into financial difficulties and are forced to close. Given the importance that these entities have both socially and economically, the study of their financial vulnerability is an area of special interest. It is important to highlight the factors that characterize this type of entity in a situation of vulnerability and also to anticipate future undesirable situations which could result in closure without timely supervision. In this way, the entity could redirect its management and make the necessary changes in its structure to ensure its continuity. Our study analyses the academic literature, from a theoretical perspective, in relation to this vulnerability allowing us to construct a pentagram of five dimensions, some interrelated, which we propose to be taken into consideration in the study of an entity’s vulnerability. These five dimensions are performance, operational dimension, leverage, liquidity and most importantly reputation. This research offers a proposal to evaluate financial vulnerability in NPOs in a more comprehensive way and facilitate its management.

Epigenetic Regulation in Lean Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD), the most prominent cause of chronic liver disease worldwide, is a rapidly growing epidemic. It consists of a wide range of liver diseases, from steatosis to nonalcoholic steatohepatitis, and predisposes patients to liver fibrosis, cirrhosis, and even hepatocellular carcinoma. NAFLD is strongly correlated with obesity; however, it has been extensively reported among lean/nonobese individuals in recent years. Although lean patients demonstrate a lower prevalence of diabetes mellitus, central obesity, dyslipidemia, hypertension, and metabolic syndrome, a percentage of these patients may develop steatohepatitis, advanced liver fibrosis, and cardiovascular disease, and have increased all-cause mortality. The pathophysiological mechanisms of lean NAFLD remain vague. Studies have reported that lean NAFLD demonstrates a close association with environmental factors, genetic predisposition, and epigenetic modifications. In this review, we aim to discuss and summarize the epigenetic mechanisms involved in lean NAFLD and to introduce the interaction between epigenetic patterns and genetic or non genetic factors. Several epigenetic mechanisms have been implicated in the regulation of lean NAFLD. These include DNA methylation, histone modifications, and noncoding-RNA-mediated gene regulation. Epigenetics is an area of special interest in the setting of lean NAFLD as it could provide new insights into the therapeutic options and noninvasive biomarkers that target this under-recognized and challenging disorder.

Analytical Solution for One-Dimensional Transient Thermal Conduction in a Hollow Cylinder

The primary use of analytical solutions in the area of thermal conduction problems is for verification purposes, comparing the calculated temperatures and heat flux values to the results from numerical codes. The contribution from the analytical solutions can be especially significant where large temperature gradients are found. This is because the temperature and heat flux results can be found very precisely: normally to eight or 10 significant figures using analytical solutions. Normally, numerical solutions require extremely fine grids in high-heat-flux locations, but analytical solutions can provide insight into the adequacy of grid densities in these types of situations. One area of particular interest is in nonrectangular analytical solutions because generalized numerical grids do not naturally lend themselves well to curved surfaces without a large number of nodes. In this current study, four solutions are offered in a geometry involving a hollow cylinder. Two of the solutions examine heating from the inside of the cylinder, and two involve heating from the outside. Development of the solutions is provided along with results that show the temperature responses to the various sets of boundary conditions. A mathematical identity is used as part of the solution, which eliminates the need to evaluate an infinite series, along with need to find roots of transcendental equations and evaluate Bessel functions. Intrinsic verification is also applied in order to provide assurance that the solutions are properly formulated and evaluated.

The Lung Microbiome in COPD and Lung Cancer: Exploring the Potential of Metal-Based Drugs.

Chronic obstructive pulmonary disease (COPD) and lung cancer 17 are two of the most prevalent and debilitating respiratory diseases worldwide, both associated with high morbidity and mortality rates. As major global health concerns, they impose a substantial burden on patients, healthcare systems, and society at large. Despite their distinct aetiologies, lung cancer and COPD share common risk factors, clinical features, and pathological pathways, which have spurred increasing research interest in their co-occurrence. One area of particular interest is the role of the lung microbiome in the development and progression of these diseases, including the transition from COPD to lung cancer. Exploring novel therapeutic strategies, such as metal-based drugs, offers a potential avenue for targeting the microbiome in these diseases to improve patient outcomes. This review aims to provide an overview of the current understanding of the lung microbiome, with a particular emphasis on COPD and lung cancer, and to discuss the potential of metal-based drugs as a therapeutic strategy for these conditions, specifically concerning targeting the microbiome.

Virtual Grid-Based Routing for Query-Driven Wireless Sensor Networks

In the context of query-driven wireless sensor networks (WSNs), a unique scenario arises where sensor nodes are solicited by a base station, also known as a sink, based on specific areas of interest (AoIs). Upon receiving a query, designated sensor nodes are tasked with transmitting their data to the sink. However, the routing of these queries from the sink to the sensor nodes becomes intricate when the sink is mobile. The sink’s movement after issuing a query can potentially disrupt the performance of data delivery. To address these challenges, we have proposed an innovative approach called Query-driven Virtual Grid-based Routing Protocol (VGRQ), aiming to enhance energy efficiency and reduce data delivery delays. In VGRQ, we construct a grid consisting of square-shaped virtual cells, with the number of cells matching the count of sensor nodes. Each cell designates a specific node as the cell header (CH), and these CHs establish connections with each other to form a chain-like structure. This chain serves two primary purposes: sharing the mobile sink’s location information and facilitating the transmission of queries to the AoI as well as data to the sink. By employing the VGRQ approach, we seek to optimize the performance of query-driven WSNs. It enhances energy utilization and reduces data delivery delays. Additionally, VGRQ results in ≈10% and ≈27% improvement in energy consumption when compared with QRRP and QDVGDD, respectively.

Effect of Proximal Caries-driven Access on the Biomechanical Behavior of Endodontically Treated Maxillary Premolars

IntroductionThis study investigated the effects from the carious cavity and access from it on the fracture resistance of endodontically treated maxillary premolars using finite element analysis (FEA). MethodsA maxillary premolar was used to compare 3 types of access cavity related to having a proximal carious defect: caries-driven access (CDA), conservative access that has a mesial component (MCA), as well as traditional access with the same mesial component (MTA). Cyclic loading was simulated on the occlusal surface, and number of cycles until failure (NCF) was compared with the intact tooth model (IT). Mathematical analysis was done to evaluate the stress distribution patterns and calculated maximum von Mises (vM) and maximum principal stresses (MPS), with emphasis on pericervical region as a specific area of interest. ResultsMaximum vM registered on the IT was 6.14 MPa. CDA provided the highest NCF with 92.28% of the IT, followed by MCA (84.90%) and MTA (83.79%). The vM and MPS analysis showed that the stress values and patterns are affected more by the proximity of the occlusal load to the tooth/restoration interface. Concerning the pericervical region, maximum vM was registered for IT (4.11 MPa), followed by CDA (4.85 MPa) and then MCA (8.13 MPa) and MTA (8.61 MPa), whereas the MPS analysis revealed that CDA showed the highest magnitude of tensile stresses. ConclusionsA proximal CDA benefits the mechanical properties of maxillary premolars; however, its impact on the biological aspect should be assessed to provide a ruling for/against it.

Domotics in inclusion and health: Descriptive Study

The present research is a bibliographic, exploratory, descriptive, and documentary study of the main contributions of the home automation area for people with disabilities, including mental, physical or temporary therapy. The study selects 30 journal articles or review articles from the Scopus database of the main quartiles Q1, Q2, Q3, that meet the purpose of the study and respond to the research question, from a total of 228 articles (208 articles, 20 reviews) of the last 10 years and that have English language. Among the main results, 3 specific areas of interest of the scientific community are identified: Telemedicine, home automation, Artificial Intelligence, in studies of remote monitoring for medical assistance of the elderly, disabled people, medical centers, additionally for intelligent energy management, portable sensors, IT Smart House, stress management, emergency calls, alternative communication with brain-computer interfaces, education and innovation of algorithms. The purpose of this research is to provide a first approach to the scientific, academic and business community that initiates learning in this area, in order to provide a review of the most relevant contributions in this line of knowledge.

An optimized XGBoost technique for accurate brain tumor detection using feature selection and image segmentation

An abnormal multiplication of cells in the brain forms malignant and benign brain tumors. Malignant brain tumors are more prevalent than benign ones. Detecting a tumor’s physical features may be tedious and time-consuming for medical experts due to the complexity of a tumor’s structure and noise growth in Magnetic Resonance Imaging (MRI) data. Detecting and localizing tumors at an early stage in their growth is crucial. Complex structures and precise clinical identification using segmentation are considered the norm in medical imaging. As the quantity of images rises, the radiologist’s manual tumor assessment might result in an incorrect conclusion. Due to the likelihood of human error, the evaluation and categorization of medical images require an automated method. This paper optimizes the eXtreme Gradient Boosting (XGBoost) approach through image processing and feature selection for the reliable identification of brain tumors. Images are improved using the Contrast-Limited Adaptive Histogram Equalization (CLAHE) method. The K-Means algorithm divides images into sections. This segmentation assists in pinpointing the specific area of interest. Particle Swarm Optimization (PSO) is used to choose characteristics. The data is classified by XGBoost, Naive Bayes, and the Iterative Dichotomiser 3 (ID3). According to the experimental results, the suggested PSO-XGBoost model achieved 97% accuracy, 97% specificity, 98% precision, and 98% recall.

EMOTIONAL AND SOCIAL FUNCTIONING ASPECTS OF WOMEN UNDERGOING CHEMOTHERAPY AND MASTECTOMYWITH VARIED TIME ELAPSES FROM TREATMENT COMPLETION

The aim of the study was a comparison of two groups of women who suffered from breast cancer in the past, selected on the basis of the time elapsed since treatment completion (&lt;7 and &gt;7 years). The specific areas of interest were the quality of life, sense of control, and level of depression.Results from 37 women were analysed. The average age in the research sample was 57. The study was conducted with the use of EORTC QLQ-C30, MHLC, and Depression Assessment Questionnaire.Women in whose case the time elapsed since the completion of anticancer treatment is no more than 7 years have a more negative assessment of the quality of life aspects, that is physical and social functioning, in comparison to persons in whose case the adaptation time to changes, following cancer and treatment, is longer (more than 7 years). The studied persons with a shorter period elapsed since the completion of anticancer therapy hold stronger beliefs concerning their own influence on their health in comparison to women who have not undergone oncological treatment for at least 7 years. The author’s own research highlights the trend pertaining to the differences in the intensity of experiencing guilt and anxiety between the groups. However, it requires further research involving a larger group of studied patients.Despite the progress in the diagnostics and treatment of breast cancer, patients with this type of cancer still experience long-term subjective difficulties in areas making up their physical, mental, and social well-being. The research proves the differences in functioning of women depending on the time that has elapsed since the completion of anticancer treatment.

자폐 범주성 장애 아동의 특별한 관심 영역을 활용한 사회적 기술 중재 연구 분석

In this study, the overall trend of social skill intervention using special interest area (SIA) for children with autism spectrum disorder (ASD) was examined; additionally, the types and characteristics of intervention studies were analyzed to discover what implications they have for the educational field. A total of 21 studies were selected according to the selection criteria. The intervention was conducted mainly in an inclusive environment using antecedent approach. Results showed that there was a positive effect when incorporating SIA to social skill intervention regardless of cognitive abilities. Most of the SIAs were in the facts/verbal memory and activities/visual memory categories and was often embedded into social games/activities or presented in Power Card strategies. SIA was used for interventions in order to improve both social engagement and social initiation behaviors. Based on the results of this study, the implications and recommendations for intervention using SIA for children with ASD were discussed.

The Art of Phenomena Construction: A Framework for Coming Up with Research Phenomena beyond ‘the Usual Suspects’

AbstractDespite the centrality of research phenomena, the process of their definition is often neglected and reduced to a simple choosing of pre‐established subjects of interest. However, good research not only includes empirical work aimed at more or less ‘given as fact’ phenomena. It also involves phenomena construction: that is, the process of generating and establishing phenomena to investigate and theorize. We contend that phenomena construction is not separate from, but integral to, both the empirical and theorizing phases in research. As few phenomena are truly ‘given’ or straightforward to observe, good research calls for careful and creative construction of the phenomenon under investigation. We propose and elaborate a framework that enables researchers to generate and establish research phenomena beyond those currently available in their specific area of interest and, based on this, to produce more imaginative and impactful research.

Efficient Mining of Anticancer Peptides from Gut Metagenome.

The gut microbiome plays a crucial role in modulating host health and disease. It serves as a vast reservoir of functional molecules that hold great potential for clinical applications. One specific area of interest is identifying anticancer peptides (ACPs) for innovative cancer therapies. However, ACPs discovery is hindered by a heavy reliance on experimental methodologies. To overcome this limitation, we here employed a novel approach by leveraging the overlap between ACPs and antimicrobial peptides (AMPs).By combining well-established AMP prediction methods with mining techniques in metagenomic cohorts, a total of 40 potential ACPs is identified. Out of the identified ACPs, 39 demonstrated inhibitory effects against at least one cancer cell line, exhibiting significant differences from known ACPs. Moreover, the therapeutic potential of the two most promising peptides in a mouse xenograft cancer model is evaluated. Encouragingly, the peptides exhibit effective tumor inhibition without any detectable toxic effects. Interestingly, both peptides display uncommon secondary structures, highlighting its distinctive characteristics. This findings highlight the efficacy of the multi-center mining approach, which effectively uncovers novel ACPs from the gut microbiome. This approach has significant implications for expanding treatment options not only for CRC, but also for other cancer types.

Preface: 2nd International Conference on Financial Technology and Market Management (FTMM 2023)

The 2023 2nd International Conference on Financial Technology and Market Management (FTMM 2023) have been conducted during May 27-28, 2023 in Tianjin, China. This conference aims to bring together leading academic scientists, researchers, and scholars to exchange and share their experiences and research results on all aspects of economics, business, and marketing management. It also provides a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of economics, business, and marketing management.&#x0D; More than 70 participants from China, Japan, Malaysia, France, and some other countries attended FTMM 2023. About 30 presentations including 6 plenary talks were presented. The presentations are grouped into 9 areas of particular interest: (1): Economic and monetary crisis, (2): Taxes and regulation, (3): Emerging markets issues, (4): Corporate finance and governance, (5): Asset pricing, investment, and portfolio management, (6): Financial markets, (7): Risk management and quantitative finance, (8) Econometric modeling and empirical issues, (9): Mathematical Finance.&#x0D; With best regards,&#x0D; Conference Organizing Chair&#x0D; Tianjin, China

Influence of molybdenum on Co3O4 coupled N-doped reduced graphene oxide composite for improved electrocatalytic alkaline oxygen evolution reaction: Stability and mechanism insights

The development of stable electrocatalysts for the catalysis of the electrochemical water-splitting process has become an area of particular interest in recent years. In this study, a simple interfacial method is proposed to fabricate a novel molybdenum (Mo)-substituted Co3O4 with N-doped reduced graphene oxide (N-rGO) composite for application as a high-performance oxygen evolution reaction (OER) electrocatalyst in a typical alkaline solution. Various efficient characterization methods are used to examine its structure, morphology, elemental composition, and surface area. The optimized 20MoCo/NRG composite exhibits improved electrocatalytic performance with robust electronic interfacial bonding, improved intrinsic activity, and high ECSA values. Furthermore, it exhibits remarkable electrocatalytic OER activity with a lower overpotential of 378 mV and minor Tafel slope value of 143 mV dec−1 at a current density of 10 mA cm−2 in a 1 M KOH solution compared with the other as-synthesized catalysts. Notably, the 20MoCo/NRG composite catalyst demonstrates exceptional durability for 15 h. Consequently, this effective interfacial nanostructure provides novel insights into the development of high-performance, long-lasting electrocatalysts for the water oxidation process.

Morphological effects on Pali gemination: A preliminary study

Around the turn of the 20th century (Childers, 1879; Müller, 1884; Whitney, 1889; Gray, 1899; Duroiselle, 1906), neogrammarians began studying the Pali language and its grammar. One area of particular interest was the phonological process of assimilation. Pali evidences both progressive and regressive assimilation and it is generally the case that a consonant geminate is formed (Krishnaswamy, et al., 2019). Recent studies (Junghare, 1979; Suzuki, 2002a,b; Gupta, 2003; Schmeiser, 2008; Dutta, 2017) have attempted to explain base-medial consonant gemination in phonological terms.&#x0D; Though these accounts have furthered our understanding of Pali base-medial consonant gemination, very few studies have considered morphological effects on Pali gemination. The current study, though exploratory in nature, suggests that a problem arises in phonological analyses of Pali geminates in that Pali words evidence different cluster realizations based on morphological factors. In short, the study analyzes the effects of affixes on Pali gemination and suggests that an explanation based solely on syllable structure or sonority is insufficient and calls for further research.

Impact of Drone Regulations on Drone Use in Geospatial Applications and Research: Focus on Visual Range Conditions, Geofencing and Privacy Considerations

The European Aviation Safety Agency (EASA) laid down the new EU drone regulations in December 2020, which are seen as a development step towards enabling a reliable legal framework for drone operation and use. At the same time, it is still not clear how the new rules will influence drone usage in various drone-based applications and sectors. Therefore, the paper aims to discuss and analyse how recent rules may influence drone use and affect its economic viability with the focus on the geospatial sector. The discussion of rules’ impact is achieved based on three key items: visual range limitations, geofencing systems (virtual geographic boundary around specific areas of interest) and, finally, the effect of privacy considerations. To enrich the discussion and get more insight into rules’ impact, important issues from different technical and economic aspects were distributed in a questionnaire to collect data from participants who are actively developing or using the drone technology. The questionnaire results revealed that the majority of participants (75%) were of the opinion that it is somehow difficult to judge how the new regulations will help/hinder the drone use at least in the current stage of rules implementation. In addition, there is a tendency in conducting drone flights under visual line of sight conditions even if there are difficulties in keeping a continuous contact with the drone during flight operations. Finally, the results pointed out that 44% of participants faced problems with privacy issues that affected their flight missions, and as a consequence some of the projects even got cancelled.

Blood-Based Biomarkers in Traumatic Brain Injury: A Narrative Review With Implications for the Legal System.

Traumatic brain injury (TBI) is an increasingly recognized diagnosis with significant, and often costly, associated consequences. Yet, despite their increased recognition, TBIs remain underdiagnosed. This issue is especially prominent in the context of mild TBI (mTBI), where there often exists little to no objective evidence of brain injury. In recent years, considerable effort has been made to better define and interpret known objective markers of TBI, as well as identify and explore new ones. An area of particular interest has focused on research related to blood-based biomarkers of TBI. Advancements in our understanding of TBI-related biomarkers can make it possible to characterize the severity of TBI with greater accuracy, improve our understanding of staging within both the injury process and the recovery process, and help us develop quantifiable metrics representative of reversal and recovery from a brain injury following trauma. Proteomic and non-proteomic blood-based biomarkers are being studied extensively and have shown promise for these purposes. Developments in this realm have significant implications not only for clinical care but also for legislation, as well as civil and criminal litigation. Despite their substantial potential, most of these biomarkers are not yet ready for use within the clinical setting, and therefore, are not appropriate for use within the legal or policy-making systems at this time. Given that existing standardization for the accurate and reliable use of TBI biomarkers is currently insufficient for use within either the clinical or legal realms, such data can be vulnerable to misuse and can even result in the abuse of the legal system for unwarranted gain. Courts will need to carefully evaluate the information presented in their role as gatekeepers of the admissibility of scientific evidence within the legal process. Ultimately, the development of biomarkers should lead to improved clinical care following TBI exposure, coherent and informed laws surrounding TBI, and more accurate and just results in litigation surrounding TBI-related sequelae.

Playing Blackjack Using Computer Vision

The field of computer vision is rapidly evolving, with a focus on analyzing, manipulating, and understanding images at a sophisticated level. The primary objective of this discipline is to interpret the visual input from cameras and utilize this knowledge to manage computer or robotic systems or to generate more informative and visually appealing images. The potential applications of computer vision are wide-ranging and include video surveillance, biometrics, automotive, photography, movie production, web search, medicine, augmented reality gaming, novel user interfaces, and many others. This paper outlines how computer vision technology will be utilized to achieve a winning outcome in the game of Blackjack. The game of Blackjack has long captivated the attention of enthusiasts and players worldwide. One area of particular interest is the development of a winning strategy that maximizes the player's chances of success. With the advent of sophisticated computer algorithms and machine learning techniques, there is enormous potential for research in this area. This paper explores the game-winning strategies for Blackjack, with a particular focus on utilizing advanced analytical methods to identify optimal plays. By analyzing large data sets and leveraging the power of predictive modeling, we aim to create a robust and reliable framework for achieving consistent success in this popular casino game. We believe that this research avenue holds enormous promise for unlocking new insights into the game of Blackjack and developing a more comprehensive understanding of its intricacies.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study

BackgroundThe current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients.MethodsThe LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management.DiscussionThe LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols.Ethics Committee approval number5420 − 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS – Università Cattolica del Sacro Cuore Ethics Committee.Trial registrationclinicaltrial.gov - NCT05802771.