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Abstract The most prevalent form of malignant tumors that originate in the brain are known as gliomas. In order to diagnose, treat, and identify risk factors, it is crucial to have precise and resilient segmentation of the tumors, along with an estimation of the patients’ overall survival rate. Therefore, we have introduced a deep learning approach that employs a combination of MRI scans to accurately segment brain tumors and predict survival in patients with gliomas. To ensure strong and reliable tumor segmentation, we employ 2D volumetric convolution neural network architectures that utilize a majority rule. This method helps to significantly decrease model bias and improve performance. Additionally, in order to predict survival rates, we extract radiomic features from the tumor regions that have been segmented, and then use a Deep Learning Inspired 3D replicator neural network to identify the most effective features. The model presented in this study was successful in segmenting brain tumors and predicting the outcome of enhancing tumor and real enhancing tumor. The model was evaluated using the BRATS2020 benchmarks dataset, and the obtained results are quite satisfactory and promising.

Adaptability (adjustment to new and uncertain situations) and grit (perseverance and passion for long-term goals) both sustain students, but their joint contribution has never been explored, and recent studies propose they could compose a single factor. In this study we aim to test whether (1) they actually belong to a single overarching factor as recently posited by the Triarchic Model of Grit and (2) they have specific effects on different outcomes. We show that, in a sample of 602 students (11-18 years old), perseverance of effort, consistency of interests (the two facets of grit), and adaptability are distinct factors, that uniquely contribute to the outcomes considered (academic self-efficacy, achievement emotions, learning goals, self-regulated learning, achievement, and life satisfaction). Perseverance resulted as the strongest predictor, followed by adaptability and consistency. Conscientiousness was positively related to all three. We conclude that adaptability and grit are two separate but correlated factors that can promote a host of positive outcomes.

Abstract Artificial Intelligence has the potential to reshape the landscape of clinical trials through innovative applications, with a notable advancement being the emergence of synthetic patient generation. This process involves simulating cohorts of virtual patients that can either replace or supplement real individuals within trial settings. By leveraging synthetic patients, it becomes possible to eliminate the need for obtaining patient consent and creating control groups that mimic patients in active treatment arms. This method not only streamlines trial processes, reducing time and costs but also fortifies the protection of sensitive participant data. Furthermore, integrating synthetic patients amplifies trial efficiency by expanding the sample size. These straightforward and cost‐effective methods also enable the development of personalized subject‐specific models, enabling predictions of patient responses to interventions. Synthetic data holds great promise for generating real‐world evidence in clinical trials while upholding rigorous confidentiality standards throughout the process. Therefore, this study aims to demonstrate the applicability and performance of these methods in the context of onco‐hematological research, breaking through the theoretical and practical barriers associated with the implementation of artificial intelligence in medical trials.

Background: Adaptability regulates individuals' cognitive, behavioural and emotional responses to new, unexpected and uncertain situations, but to date no study has analysed whether adaptability contemporarily favours cognitive, behavioural and emotional aspects of learning. Aims: This study aims to address this gap by examining (i) the direct relations between adaptability and achievement emotions, self-regulated learning strategies and academic self-efficacy and (ii) the direct and indirect relations between adaptability and academic achievement and life satisfaction through and over the other study-related factors. Sample: A total of 1083 students (415 males, M[subscript age] = 13.37, SD[subscript age] = 1.97, age range = 10-18) in grades 6-12 participated to the study. Method: Questionnaires were used to measure students' adaptability, positive and negative achievement emotions, self-regulated learning strategies, academic self-efficacy and life satisfaction. Schools provided grades obtained by each student at the end of the academic year. Results: A path analysis based on 1083 students (10-18 years old) confirmed that adaptability directly relates to the three study-related factors considered and to life satisfaction and indirectly relates to academic achievement and life satisfaction--through the mediation of the other variables. Conclusions: The results, discussed in accordance with the self-regulated learning theory, enlarge the nomological framework of adaptability and highlight its importance for emotional, behavioural and cognitive aspects of self-regulated learning.

The role of soft skills at school is still debated, but they have emerged as important factors for students' academic achievement and life satisfaction. This study focuses on the combined influence of soft skills (in terms of adaptability, curiosity, leadership, initiative, perseverance, and social awareness), extracurricular activities, achievement emotions, self-regulated learning, motivation, and cognitive abilities on academic achievement and life satisfaction. A sample of 603 students (5th to 12th graders) participated in the study. The results of a Bayesian path analysis based on meta-analytical priors show that soft skills were (i) directly positively associated with students' achievement emotions, self-regulated learning, motivation, and life satisfaction and (ii) indirectly related with academic achievement through the mediation of self-regulated learning and motivation. On the other hand, only soft skills and achievement emotions were directly related to life satisfaction. Extracurricular activities showed a positive association with both soft skills and cognitive abilities. These results are the first to demonstrate the importance of soft skills and extracurricular activities when integrating all the above-mentioned factors in a model of students' academic achievement and life satisfaction.

IntroductionThis study investigates the interplay between body composition, dietary patterns, and physical activity across genders, focusing on gender-specific differences in food preferences and eating behaviors. Understanding these interactions is crucial for developing targeted nutritional and lifestyle interventions.MethodsA cross-sectional study was conducted with 1,333 participants (58.7% female, 41.3% male), aged 18–65 years. Participants were categorized into tertiles based on their fat mass to fat-free mass (FM-to-FFM) ratio. Data on dietary choices, eating behaviors, and physical activity were collected and analyzed to identify gender-specific trends.ResultsSignificant gender-specific differences were observed in food preferences and eating behaviors. Males experienced greater hunger in the late afternoon, while females felt more hunger in the morning. Males showed a preference for processed and red meats, whereas females preferred cooked vegetables. Eating behaviors such as meal skipping, uncontrolled eating, nocturnal eating, and taste preferences (sweet or salty) varied distinctly between FM-to-FFM tertiles and genders. Higher FM-to-FFM ratios correlated with lower physical activity levels, particularly in strength training and general sports engagement.DiscussionThese findings highlight the complex interactions between body composition, dietary habits, and lifestyle factors, emphasizing gender-specific differences. The results suggest that body composition and BMI significantly impact health-related behaviors, necessitating tailored interventions to address these differences and promote healthier lifestyles.

Il contributo approfondisce una proposta formativa dell’Università degli Studi di Padova legata all’orientamento attivo nella transizione scuola-università, sulla base di quanto previsto dal Decreto Ministeriale MUR 934/2022. In particolare, è stato progettato un percorso online, dedicato agli studenti1 dell’ultimo triennio di scuola secondaria di secondo grado del territorio, che mira allo sviluppo di alcune competenze trasversali utili in vista della transizione post-diploma. Il modulo di tre ore è fruibile in modo asincrono sulla piattaforma Moodle di Ateneo, e si compone di quattro attività principali, relative a: introduzione sulle soft skills, abilità e motivazione allo studio, abilità sociali e interpersonali, orientamento alla scelta. Le attività rappresentano una proposta inedita e innovativa per l’Ateneo, e si svolgono tramite brevi video creati ad hoc, questionari e attività di riflessione guidata iniziali e finali, sia di tipo quantitativo che qualitativo. La prima edizione si è svolta da aprile ad agosto 2023, ed è attualmente in corso la seconda edizione 2023/24. La presentazione della proposta, qui dettagliata nei suoi obiettivi e caratteristiche operative, può configurarsi come esempio di pratica e accrescere il dibattito scientifico rispetto all’importante tema dell’orientamento attivo nella transizione scuola-università, fungendo anche da confronto e riflessione per altri contesti che stanno affrontando questa importante sfida. 1 Per rendere più fluida l’esposizione, nel testo utilizzeremo il maschile ma intendiamo includere tutti i generi.

Summary: Background: Paediatric hepatocellular carcinomas (HCC) traditionally arise in the context of a normal structural and functional liver and carry a dismal prognosis. While chemotherapy is the frontline standard, there is emerging interest in the study of immunotherapies for paediatric patients with relapsed/refractory disease. There is limited data to support whether immunotherapies will be of utility in this patient population. Methods: Six paediatric patients (median age:16 years, range: 12–17 at the time of treatment) with advanced hepatocellular neosplams, either conventional hepatocellular or fibrolamellar carcinoma, were treated with immunotherapy. Patients were consented to institutional genomic profiling and biobanking protocols. Baseline samples and serial tissue samples, when available, were evaluated for somatic mutation rate, actionable gene mutations, and pan-immune bulk RNA expression profiling. Results were correlated with clinical course. Findings: Three patients responded to checkpoint inhibition: one achieved a complete, durable response and the other two, prolonged stable disease. Three additional patients progressed. Diagnostic tissue from the complete responder demonstrated a higher relative mutational burden and robust immune infiltrate. Pre-treatment samples from the three responders demonstrated decreased expression of genes associated with T-cell dysfunction. Interpretation: A subset of patients with primary paediatric hepatocellular tumours will respond to immunotherapy. Immunotherapies are currently under prospective study for relapsed/refractory liver tumours in paediatric patients. Results from this report support the prospective collection of serial serum and tissue samples which may further identify genomic and immunophenotypic patterns predictive of response. Funding: This work was supported by Philanthropic funds (Pan Mass Challenge, Team Angus and Team Perspective).

Abstract Background Migraine is the second world’s cause of disability. Among non-pharmacological treatments, nutritional intervention, particularly ketogenic diet, represents one of the most promising approaches. Methods This a prospective, single center, randomized, controlled study aimed at evaluating the efficacy of a very low-calorie ketogenic diet (VLCKD) compared to a hypocaloric balanced diet (HBD) in migraine prophylaxis in patients affected by high-frequency episodic migraine (HFEM) with a Body Mass Index (BMI) > 27 kg/m2. Fifty-seven patients were randomly assigned to a VLCKD (group 1) or HBD (group 2). Group 1 patients followed a VLCKD for 8 weeks, followed by a low calorie diet (LCD, weeks 9–12), and a HBD (weeks 13–24), whereas group 2 patients followed a HBD from week 0 to 24. Anthropometric indexes, urine and blood chemistry were assessed at enrollment, baseline, weeks 4, 8, 12, and 24. Migraine characteristics were evaluated at baseline, weeks 8, 12 and 24. Change in monthly migraine days (MMDs) at weeks 5–8 compared to baseline was the primary endpoint. Secondary endpoints encompassed changes in visual analogue scale (VAS), Headache Impact Test-6 (HIT-6) and Short Form Health Survey-36 (SF-36) scores. We also studied effects on circulating lymphocytes and markers of inflammation, changes in plasma aldosterone and renin levels before and after VLCKD or HBD treatment. Results Reduction from baseline in MMDs was greater in VLCKD compared to HBD group at week 8 (p = 0.008), at week 12 (p = 0.007), when ketosis had been interrupted by carbohydrates reintroduction, and at week 24 (p = 0.042), when all patients were following the same dietary regimen. Quality of life scores (SF-36) were improved in VLCKD group at week 8 and 12, and were also improved in HBD group, but only at week 12. Weight-loss was significantly higher in VLCKD group at week 8 (p = 0.002) and week 12 (p = 0.020). At the end of the study weight loss was maintained in VLCKD group whereas a slight weight regain was observed in HBD group. Inflammatory indexes, namely C reactive protein (CRP), neutrophil to lymphocyte ratio (NLR) and total white blood cell count (WBC) were significantly reduced (p

IntroductionFood preferences are influenced by various factors, such as culture, age, and gender. The relationship between food tastes, meal preferences, and eating habits has been studied extensively in recent years; however, research on gender differences in these fields still needs to be addressed. The aim of this study was to investigate gender differences in food preferences and eating habits through self-administered questionnaires in a large Italian population sample.MethodsThe online survey included questions on food tastes, meal preferences, eating habits, and sport involvement.ResultsThe results of the study underline significant gender-specific dietary tendencies among the 2198 participants (1314 females and 884 males, average age 41.1 ± 12.7 yrs). The majority of subjects were in the annual income range between €20,000 and €40,000. Our analysis reveals significant gender differences in dietary preferences and eating habits. Men prefer red and processed meat, with significantly higher consumption rates than women. Women, on the other hand, show a greater inclination towards vegetables, whole grains, tofu, and high-cocoa-content dark chocolate, aligning with healthier food choices. The study also found differences in eating behaviors, including the frequency of meals, snacking habits, and hunger patterns: women tend to eat more frequently and report higher levels of hunger in the morning, while men tend to skip snacks. Furthermore, differences extend to eating contexts, such as the speed of eating, eating out, and eating alone, with men more likely to eat quickly and dine out. Episodes of uncontrolled eating without hunger also differ, with women reporting these behaviors more frequently than men. In addition, the analysis of sports preferences showed distinct patterns, with a lower percentage of women playing sports and those who do play sports preferring endurance and strength training, while men prefer strength training and endurance sports.DiscussionThese findings elucidate the complex interplay of biological, cultural, and gender-based factors in shaping dietary preferences and eating behaviors. In particular, our study reveals that gender dynamics significantly influence food choice and eating habits: women tend to choose healthier foods and eat regular meals, while men show preferences for specific tastes and meal-related behaviors. This analysis underscores the nuanced differences between male and female dietary patterns, influenced not only by inherent biological factors such as genetics and hormonal responses but also by societal norms and cultural contexts. Taken together, our results highlight the importance of integrating different perspectives, thus providing valuable insights into the development of public health strategies and tailored nutrition interventions aimed at chronic disease prevention.

Abstract Background Pediatric interventional oncology (PIO) is a growing field intended to provide additional or alternative treatment options for pediatric patients with benign or malignant tumors. Large series of patients treated uniformly and subjected to rigorous endpoints for efficacy are not available. Methods We designed a collaborative initiative to capture data from pediatric patients with benign and malignant tumors who underwent a therapeutic interventional radiology procedure. Modified Response Evaluation Criteria in Solid Tumors (mRECIST) was utilized as a measure of radiologic response and data were collected regarding improvement in pain and functional endpoints. Cumulative incidence of progressive disease was calculated using both the treated site and the patient as the analytic unit. Findings Forty patients, 16 with malignant tumors and 24 with benign tumors, underwent a total of 88 procedures. Cryo‐ and radiofrequency ablation were the most frequently utilized techniques for both cohorts of patients. A complete or partial response, or prolonged disease stability, were achieved in approximately 40% of patients with malignant tumors and 60% of patients with benign tumors. No patients had progressive disease as their best response. Resolution of pain and improved mobility with return‐to‐baseline activity were demonstrated across patients from both cohorts. Only minor complications were experienced. Interpretation Interventional radiology‐guided interventions can serve as an alternative or complementary approach to the treatment of benign and malignant tumors in pediatric patients. Prospective, multi‐institutional trials are required to adequately study utility, treatment endpoints, and durability of response.

To deepen the development of positive affect during early adolescence and shed new light on its predictors, this study adopts an exploratory network approach to first identify the main domains that describe the variability of children's psychological, environmental, and behavioral characteristics, and then use these domains to longitudinally predict positive affect and its development within a latent growth framework. To this aim, we considered 10,904 US participants (9 years old at baseline; 13 years old 42 months later), six measurement occasions of positive affect, and 46 baseline indicators from the ABCD study. Our results not only confirm that positive affect declines between 9 and 13 years old, but also show that among the five domains identified (behavioral dysregulation, cognitive functioning, psychological problems, supportive social environment, and extracurricular activities), only a supportive social environment consistently predicts positive affect. This is crucial for practitioners and policymakers, as it can help them focus on the elements within our complex network of psychological, social, and environmental variability.

Soft skills are important in several life domains, but their role in academic achievement has not been systematically investigated. This study examines how soft skills work together with self-regulated learning, motivation, and cognitive aspects in sustaining success at school. How extracurricular activities relates to these variables is examined too. A sample of 460 school students in years 5 to 12 was enrolled and examined on 6 personal soft skills (i.e. adaptability, personal initiative, perseverance, curiosity, leadership, and social awareness), cognitive abilities (i.e. reasoning, problem solving, mental rotation, working memory), motivation to learn, and self-regulated learning as predictors of their academic achievement. A measure of extracurricular activities was also included in the analysis. The results of a path model show that soft skills predicted self-regulated learning and motivation at school, and -- through the latter -- they indirectly fostered academic achievement over cognitive abilities. While cognitive abilities also predicted academic achievement and motivation, they were found unrelated to soft skills. Extracurricular activities influenced soft skills. Overall, these findings contribute to enlarging the theoretical framework on soft skills and their relationship with other variables involved in success at school.

The aim of the paper is to demonstrate that Quirinus in Enn. ann. 100 Skutsch is to be identified with Romulus. In addition to the comparison with Ov. met. 14.849 ss., new arguments are presented: the comparison with Liv. 1.16.6 and the use of the verb venerari, which is connected etymologically with Venus, who is a deity related to Romulus and the origins of Rome.

This cross-sectional study analyses differences in dietary habits, taste preferences, variety of protein sources and body composition (BC) profiles among individuals following omnivorous, flexitarian, lacto-ovo-vegetarian and pescatarian diets. Furthermore, it assesses the correlations between these dietary patterns and various sports, classified by exercise intensity, in relation to BC parameters. The study analysed the eating habits and BC data of 1342 participants aged 18–65 years, classified into four diet groups based on their 7-day food diaries and questionnaire responses. Our analysis revealed gender- and age-related differences in weekly food consumption and protein source variety, with men generally consuming more meat, processed meat and fish than women, especially in younger age groups. Differences in dairy and soy consumption were also noted between age groups, while legume and soy preferences showed no gender disparity across all ages. Among non-sporting individuals, vegetarians exhibited lower fat mass (FM%) compared to other diets, while among athletes, vegetarians and pescatarians in in endurance and strength sports, respectively, displayed lower FM%, with flexitarians and omnivores in endurance sports showing higher FM%. Non-athletic omnivores and vegetarians demonstrated a greater proportion of body protein, while among athletes, those engaged in strength training exhibited a higher body protein content across all dietary groups compared to those in endurance training. Among non-athletic groups, vegetarians exhibited the lowest FM/FFM (fat mass/fat-free mass) ratio, while among athletes, vegetarians in endurance sports and participants in strength training across other diets showed lower FM/FFM ratios. The results emphasise the complex interaction between diet, BC and lifestyle choices, revealing how different combinations of diet and sport are associated with optimised BC.

The most prevalent form of malignant tumors that originate in the brain are known as gliomas. In order to diagnose, treat, and identify risk factors, it is crucial to have precise and resilient segmentation of the tumors, along with an estimation of the patients' overall survival rate. Therefore, we have introduced a deep learning approach that employs a combination of MRI scans to accurately segment brain tumors and predict survival in patients with gliomas. To ensure strong and reliable tumor segmentation, we employ 2D volumetric convolution neural network architectures that utilize a majority rule. This method helps to significantly decrease model bias and improve performance. Additionally, in order to predict survival rates, we extract radiomic features from the tumor regions that have been segmented, and then use a Deep Learning Inspired 3D replicator neural network to identify the most effective features. The model presented in this study was successful in segmenting brain tumors and predicting the outcome of enhancing tumor and real enhancing tumor. The model was evaluated using the BRATS2020 benchmarks dataset, and the obtained results are quite satisfactory and promising. [ABSTRACT FROM AUTHOR]

Promoting environmental sustainability is becoming a priority for organizations. There is thus increasing interest in understanding to what extent green workplace behaviors are linked, alongside contextual determinants, to employees' characteristics. This study investigated the relationship between green workplace behaviors, various employee characteristics, and organizational determinants. A sample of 513 employees from the energy sector was administered a survey assessing green workplace behaviors and the management of events (e.g., weak signals) which could anticipate the occurrence of incidents with harmful environmental impacts. Employees' job-related (proneness toward behaving pro-environmentally at work) and broader individual characteristics (personality and human-nature connectedness), as well as their perceived organizational support (e.g., green climate and leadership), were also examined. The results from the structural equation models showed that green workplace behaviors were associated with employees' proneness toward behaving pro-environmentally at work and perceived organizational support. Indirect effects from organizational support, personality, and human-nature connectedness on green workplace behaviors, mediated by employees' proneness toward behaving pro-environmentally at work, also emerged. These findings highlight that employees' characteristics also favor their adoption of green workplace behaviors, with important implications for developing interventions promoting environmental sustainability in organizations. [ABSTRACT FROM AUTHOR]

Clustering methods are increasingly used in social science research. Generally, researchers use them to infer the existence of qualitatively different types of individuals within a larger population, thus unveiling previously "hidden" heterogeneity. Depending on the clustering technique, however, valid inference requires some conditions and assumptions. Common risks include not only failing to detect existing clusters due to a lack of power but also revealing clusters that do not exist in the population. Simple data simulations suggest that under conditions of sample size, number, correlation and skewness of indicators that are frequently encountered in applied psychological research, commonly used clustering methods are at a high risk of detecting clusters that are not there. Generally, this is due to some violations of assumptions that are not usually considered critical in psychology. The present article illustrates a simple R tutorial and a Shiny app (for those who are not familiar with R) that allow researchers to quantify a priori inferential risks when performing clustering methods on their own data. Doing so is suggested as a much‐needed preliminary sanity check, because conditions that inflate the number of detected clusters are very common in applied psychological research scenarios. [ABSTRACT FROM AUTHOR]