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22 pages, 1496 KiB  
Review
Drosophila melanogaster: How and Why It Became a Model Organism
by Maria Grazia Giansanti, Anna Frappaolo and Roberto Piergentili
Int. J. Mol. Sci. 2025, 26(15), 7485; https://doi.org/10.3390/ijms26157485 (registering DOI) - 2 Aug 2025
Abstract
Drosophila melanogaster is one of the most known and used organisms worldwide, not just to study general biology problems but above all for modeling complex human diseases. During the decades, it has become a central tool to understand the genetics of human disease, [...] Read more.
Drosophila melanogaster is one of the most known and used organisms worldwide, not just to study general biology problems but above all for modeling complex human diseases. During the decades, it has become a central tool to understand the genetics of human disease, how mutations alter the behavior and health of cells, tissues, and organs, and more recently to test new compounds with a potential therapeutic use. But how did this small insect become so crucial in genetics? And how is it currently used in the study of human conditions affecting millions of people? In this review, we retrace the historical origins of its adoption in genetics laboratories and list all the advantages it provides to scientific research, both for its daily usage and for the fine tuning of gene regulation through genetic engineering approaches. We also provide some examples of how it is used to study human diseases such as cancer, neurological and infectious diseases, and its importance in drug discovery and testing. Full article
(This article belongs to the Special Issue Drosophila: A Versatile Model in Biology and Medicine—2nd Edition)
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41 pages, 1921 KiB  
Article
Digital Skills, Ethics, and Integrity—The Impact of Risky Internet Use, a Multivariate and Spatial Approach to Understanding NEET Vulnerability
by Adriana Grigorescu, Teodor Victor Alistar and Cristina Lincaru
Systems 2025, 13(8), 649; https://doi.org/10.3390/systems13080649 (registering DOI) - 1 Aug 2025
Abstract
In an era where digitalization shapes economic and social landscapes, the intersection of digital skills, ethics, and integrity plays a crucial role in understanding the vulnerability of youth classified as NEET (Not in Education, Employment, or Training). This study explores how risky internet [...] Read more.
In an era where digitalization shapes economic and social landscapes, the intersection of digital skills, ethics, and integrity plays a crucial role in understanding the vulnerability of youth classified as NEET (Not in Education, Employment, or Training). This study explores how risky internet use and digital skill gaps contribute to socio-economic exclusion, integrating a multivariate and spatial approach to assess regional disparities in Europe. This study adopts a systems thinking perspective to explore digital exclusion as an emergent outcome of multiple interrelated subsystems. The research employs logistic regression, Principal Component Analysis (PCA) with Promax rotation, and Geographic Information Systems (GIS) to examine the impact of digital behaviors on NEET status. Using Eurostat data aggregated at the country level for the period (2000–2023) across 28 European countries, this study evaluates 24 digital indicators covering social media usage, instant messaging, daily internet access, data protection awareness, and digital literacy levels. The findings reveal that low digital skills significantly increase the likelihood of being NEET, while excessive social media and internet use show mixed effects depending on socio-economic context. A strong negative correlation between digital security practices and NEET status suggests that youths with a higher awareness of online risks are less prone to socio-economic exclusion. The GIS analysis highlights regional disparities, where countries with limited digital access and lower literacy levels exhibit higher NEET rates. Digital exclusion is not merely a technological issue but a multidimensional socio-economic challenge. To reduce the NEET rate, policies must focus on enhancing digital skills, fostering online security awareness, and addressing regional disparities. Integrating GIS methods allows for the identification of territorial clusters with heightened digital vulnerabilities, guiding targeted interventions for improving youth employability in the digital economy. Full article
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29 pages, 28274 KiB  
Article
Long-Term Neuroprotective Effects of Hydrogen-Rich Water and Memantine in Chronic Radiation-Induced Brain Injury: Behavioral, Histological, and Molecular Insights
by Kai Xu, Huan Liu, Yinhui Wang, Yushan He, Mengya Liu, Haili Lu, Yuhao Wang, Piye Niu and Xiujun Qin
Antioxidants 2025, 14(8), 948; https://doi.org/10.3390/antiox14080948 (registering DOI) - 1 Aug 2025
Abstract
Hydrogen-rich water (HRW) has shown neuroprotective effects in acute brain injury, but its role in chronic radiation-induced brain injury (RIBI) remains unclear. This study investigated the long-term efficacy of HRW in mitigating cognitive impairment and neuronal damage caused by chronic RIBI. Fifty male [...] Read more.
Hydrogen-rich water (HRW) has shown neuroprotective effects in acute brain injury, but its role in chronic radiation-induced brain injury (RIBI) remains unclear. This study investigated the long-term efficacy of HRW in mitigating cognitive impairment and neuronal damage caused by chronic RIBI. Fifty male Sprague Dawley rats were randomly divided into five groups: control, irradiation (IR), IR with memantine, IR with HRW, and IR with combined treatment. All but the control group received 20 Gy whole-brain X-ray irradiation, followed by daily interventions for 60 days. Behavioral assessments, histopathological analyses, oxidative stress measurements, 18F-FDG PET/CT imaging, transcriptomic sequencing, RT-qPCR, Western blot, and serum ELISA were performed. HRW significantly improved anxiety-like behavior, memory, and learning performance compared to the IR group. Histological results revealed that HRW reduced neuronal swelling, degeneration, and loss and enhanced dendritic spine density and neurogenesis. PET/CT imaging showed increased hippocampal glucose uptake in the IR group, which was alleviated by HRW treatment. Transcriptomic and molecular analyses indicated that HRW modulated key genes and proteins, including CD44, CD74, SPP1, and Wnt1, potentially through the MIF, Wnt, and SPP1 signaling pathways. Serum CD44 levels were also lower in treated rats, suggesting its potential as a biomarker for chronic RIBI. These findings demonstrate that HRW can alleviate chronic RIBI by preserving neuronal structure, reducing inflammation, and enhancing neuroplasticity, supporting its potential as a therapeutic strategy for radiation-induced cognitive impairment. Full article
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23 pages, 511 KiB  
Article
Dietary Acrylamide Exposure and Its Correlation with Nutrition and Exercise Behaviours Among Turkish Adolescents
by Mehtap Metin Karaaslan and Burhan Basaran
Nutrients 2025, 17(15), 2534; https://doi.org/10.3390/nu17152534 - 1 Aug 2025
Abstract
Background/Objectives: Acrylamide is a probably carcinogenic to humans that naturally forms during the thermal processing of foods. An individual’s lifestyle—especially dietary habits and physical activity—may influence the severity of acrylamide’s adverse health effects. This study aimed to examine the relationship between adolescents’ dietary [...] Read more.
Background/Objectives: Acrylamide is a probably carcinogenic to humans that naturally forms during the thermal processing of foods. An individual’s lifestyle—especially dietary habits and physical activity—may influence the severity of acrylamide’s adverse health effects. This study aimed to examine the relationship between adolescents’ dietary and exercise behaviors and their dietary acrylamide exposure and associated health risks. Methods: This descriptive and cross-sectional study was conducted with 370 high school students in Türkiye. Data were collected using the Nutrition Exercise Behavior Scale (NEBS) and a retrospective 24-h dietary recall questionnaire. Acrylamide exposure was calculated based on food intake to estimate carcinogenic (CR) and non-corcinogenic (target hazard quotient: THQ) health risks and analyzed in relation to NEBS scores. Results: Findings indicated that while adolescents are beginning to adopt healthy eating and exercise habits, these behaviors are not yet consistent. Emotional eating and unhealthy food choices still occur. Higher acrylamide exposure and risk values were observed in boys and underweight individuals. This can be explained mainly by the fact that boys consume more of certain foods—especially bread, which contains relatively higher levels of acrylamide—than girls do, and that underweight individuals have lower body weights despite consuming similar amounts of food as other groups. Bread products emerged as the primary source of daily acrylamide intake. Positive correlations were found between NEBS total and subscale scores and acrylamide exposure and health risk values. Conclusions: The study demonstrates a significant association between adolescents’ health behaviors and acrylamide exposure. These results underscore potential public health concerns regarding acrylamide intake during adolescence and emphasize the need for targeted nutritional interventions to reduce risk and promote sustainable healthy behaviors. Full article
(This article belongs to the Section Nutrition Methodology & Assessment)
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30 pages, 1583 KiB  
Systematic Review
How Does Outdoor Spatial Design Shape the Microclimate, Comfort, and Behavior in Traditional Chinese Villages? A Systematic Review Across Scales, Contexts, and Users
by Zixi Wan, Huihui Liu, Yan Yu, Yan Wu, Mark Melchior, Pim Martens, Thomas Krafft and David Shaw
Sustainability 2025, 17(15), 6960; https://doi.org/10.3390/su17156960 (registering DOI) - 31 Jul 2025
Abstract
Traditional Chinese villages, which have long supported villagers’ comfort level of daily activities, are increasingly affected by global climate change and rural reconstruction, prompting growing research interest in their outdoor microclimate design. This systematic review aims to synthesize and evaluate the outdoor microclimate [...] Read more.
Traditional Chinese villages, which have long supported villagers’ comfort level of daily activities, are increasingly affected by global climate change and rural reconstruction, prompting growing research interest in their outdoor microclimate design. This systematic review aims to synthesize and evaluate the outdoor microclimate spatial design mechanism studies in traditional Chinese villages noted for their uniqueness and complexity. Following the PRISMA method, this study was carried out on November 27, 2024, by retrieving studies from the Scopus and CNKI databases and applying predefined inclusion and exclusion criteria; 42 empirical studies were systematically reviewed. It identifies current research trends, summarizes concepts, frameworks, indicators, and methodologies with a focus on the design mechanisms considering scales, contexts, and user groups, and outlines directions for future research. The findings reveal a growing number of publications, with case studies predominantly concentrated on three concepts: physical microclimates, human comfort, and behavioral responses, characterized as distributed in south-east areas. Based on these concepts and their correlations, this study proposes a classification framework based on multiple scales, contexts, and user groups. Within this framework, the study found that relative humidity and PET (physiological equivalent temperature) emerge as the most commonly used indicators, while field measurements, simulations, surveys, and observations are identified as the primary methods. The review further reveals that unique outdoor spatial design characteristics shape physical microclimates, human comfort, and behavior indicators influenced by contexts and users from the macro to the micro scale. Future research should advance existing studies by enriching the current contextual framework and explore more microclimatic factors. This review offers a comprehensive overview and actionable insights for outdoor microclimate design, policymaking, and the promotion of climate adaptation and villagers’ public health in different traditional rural settings. Full article
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14 pages, 635 KiB  
Article
Sweet and Fat Taste Perception: Impact on Dietary Intake in Diabetic Pregnant Women—A Cross-Sectional Observational Study
by Inchirah Karmous, Rym Ben Othman, Ismail Dergaa, Halil İbrahim Ceylan, Cyrine Bey, Wissem Dhahbi, Amira Sayed Khan, Henda Jamoussi, Raul Ioan Muntean and Naim Akhtar Khan
Nutrients 2025, 17(15), 2515; https://doi.org/10.3390/nu17152515 - 31 Jul 2025
Viewed by 64
Abstract
Background: Taste changes are common during pregnancy and can have a significant impact on dietary habits. Objective: This study aimed to investigate the influence of the perception of sweet and fat taste on diet in pregnant diabetic women. Methods: This [...] Read more.
Background: Taste changes are common during pregnancy and can have a significant impact on dietary habits. Objective: This study aimed to investigate the influence of the perception of sweet and fat taste on diet in pregnant diabetic women. Methods: This cross-sectional observational study included 66 pregnant women, 33 with gestational diabetes and 33 with pre-gestational type 2 diabetes. Taste perception tests were conducted to evaluate thresholds for detecting sweet and fatty tastes. Dietary surveys were used to assess daily nutrient intake, and various biochemical parameters, such as glycemia, HbA1c, and cholesterol, were analyzed. Results: The low-fat taster group (threshold > 0.75 mmol/L) included more patients with diabetes compared to those with gestational diabetes. All diabetic patients had low sucrose perception. Although pregnant women with gestational diabetes detected sweetness at high concentrations, pregnant women with diabetes detected it at lower concentrations (0.012 ± 0.023 mmol/L vs. 0.006 ± 0.005 mmol/L; p = 0.3). High-fat tasters exhibited elevated glycemia compared to low-fat tasters (6.04 ± 1.88 mmol/L vs. 7.47 ± 3.4 mmol/L; p = 0.03). They also had higher cholesterol (p = 0.04) and lower HDL-C levels (4.96 ± 1.04 mmol/L vs. 1.36 ± 0.29 mmol/L; p = 0.03). High-fat tasters showed more frequent daily consumption of oil, butter, cheese, and chocolate. The highly sweet tasters had higher cholesterol levels and lower LDL levels. Individuals who reported being highly sensitive to sweet taste consumed more daily oil, sweetened yogurt, or cream desserts, as well as white sugar. Conclusions: These findings indicate that altered sensitivity to fat and sweet tastes is associated with different dietary habits and metabolic profiles in pregnant women with diabetes. Specifically, reduced sensitivity to the taste of fat is associated with higher consumption of high-fat foods and poorer lipid profiles. In contrast, sensitivity to sweet taste correlates with an increased intake of sugary and fatty foods. Understanding these taste-related behaviors can help develop personalized nutritional strategies to improve metabolic control and maternal–fetal outcomes in this high-risk group. Full article
(This article belongs to the Section Nutrition and Diabetes)
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25 pages, 2064 KiB  
Systematic Review
The Cognitive Cost of Motor Control: A Systematic Review and Meta-Analysis of Parkinson’s Disease Treatments and Financial Decision-Making
by Nektaria Kandylaki, Panayiotis Patrikelis, Spiros Konitsiotis, Lambros Messinis and Vasiliki Folia
Healthcare 2025, 13(15), 1850; https://doi.org/10.3390/healthcare13151850 - 29 Jul 2025
Viewed by 151
Abstract
Background: Despite growing interest in the literature on Parkinson’s disease (PD) on cognitive functioning, financial incompetence—a crucial aspect of daily living—and its modulation susceptibility by PD treatment regimens remains relatively understudied. Objective: This systematic review and meta-analysis aimed to synthesize existing evidence on [...] Read more.
Background: Despite growing interest in the literature on Parkinson’s disease (PD) on cognitive functioning, financial incompetence—a crucial aspect of daily living—and its modulation susceptibility by PD treatment regimens remains relatively understudied. Objective: This systematic review and meta-analysis aimed to synthesize existing evidence on how PD treatments affect financial capacity, assessing both direct financial competence and cognitive or behavioral proxies of financial decision-making. Methods: A comprehensive literature search according to PRISMA protocol was conducted across major biomedical databases, supplemented by gray literature and manual reference list checks. Eligible studies assessed financial capacity directly or indirectly through cognitive proxies (e.g., executive function, decision-making) or financial risk behaviors (e.g., impulse control disorders). Two separate meta-analyses were performed. Heterogeneity (I2), publication bias (Egger’s test), and sensitivity analyses were conducted to assess robustness. Results: Twenty-three studies met inclusion criteria. One study directly measured financial capacity and was analyzed narratively, reporting diminished competence in patients on levodopa therapy. A meta-analysis of cognitive proxies (10 studies) showed a moderate effect size (Hedges’ g = 0.70, 95% CI [0.45, 0.92], p < 0.001), indicating that PD treatments negatively affect executive function and financial decision-making. A second meta-analysis of impulse control and financial risk behaviors (12 studies) revealed a larger effect size (Hedges’ g = 0.98, 95% CI [0.75, 1.22], p < 0.001), strongly linking dopamine agonists to increased financial risk-taking. Moderate heterogeneity (I2 = 45.8–60.5%) and potential publication bias (Egger’s test p = 0.027) were noted. Conclusions: These findings suggest that PD treatments negatively impact financial decision-making both directly and indirectly through cognitive and behavioral pathways. Integrating financial decision-making assessments into PD care, particularly for patients on dopamine agonists, is recommended. Future research should prioritize longitudinal studies and standardized neuropsychological measures to guide clinical practice and optimize patient outcomes. Full article
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17 pages, 996 KiB  
Article
The Profiles of Diet- or Exercise-Related Self-Efficacy and Social Support Associated with Insufficient Fruit/Vegetable Intake and Exercise in Women with Abdominal Obesity
by Yanjing Zeng, Qing Long, Yan Jiang, Jieqian Li, Zhenzhen Rao, Jie Zhong and Jia Guo
Nutrients 2025, 17(15), 2478; https://doi.org/10.3390/nu17152478 - 29 Jul 2025
Viewed by 171
Abstract
Background/Objectives: Prioritizing diet- or exercise-related self-efficacy and social support with their interactions may improve the effectiveness of interventions aimed at increasing daily fruit/vegetable intake and exercise, thereby reducing the risk of metabolic disorders in abdominally obese women. This study aimed to identify the [...] Read more.
Background/Objectives: Prioritizing diet- or exercise-related self-efficacy and social support with their interactions may improve the effectiveness of interventions aimed at increasing daily fruit/vegetable intake and exercise, thereby reducing the risk of metabolic disorders in abdominally obese women. This study aimed to identify the profiles of diet- or exercise-related self-efficacy and social support among women with abdominal obesity, examine profiles related to insufficient fruit/vegetable intake and exercise, and explore associating factors of these profiles. Methods: A cross-sectional investigation in central south mainland China collected sociodemographic, anthropometric, and health-related variables, diet-related self-efficacy (Diet-SE) and social support (Diet-SS), exercise-related self-efficacy (Exercise-SE) and social support (Exercise-SS), and daily fruit/vegetable intake and exercise. We used latent profile analysis to identify distinct profiles, and binary logistic regression to examine the profiles’ behaviors and associating factors. Results: A total of 327 abdominally obese women were categorized into four profiles of Diet-SE and Diet-SS, and five profiles of Exercise-SE and Exercise-SS. Women in the Diet Dual-Low Group were associated with insufficient daily fruits/vegetables intake. Women in the Exercise Dual-Low Group or Exercise-SS Medium–Low Group were more likely to engage in insufficient daily exercise. Conclusions: Our findings align with previous evidence that women with low diet- or exercise-related self-efficacy and social support are at increased risk for insufficient daily fruit/vegetable intake or exercise. Additionally, medium Exercise-SS is associated with insufficient exercise behaviors, suggesting that interventions targeting healthy exercise should be initiated earlier among women with medium Exercise-SS, rather than waiting for it to decline to low level. Full article
(This article belongs to the Section Nutrition in Women)
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19 pages, 690 KiB  
Article
Lots of Digital Files? How Digital Hoarding Is Related to the Academic Performance of University Students
by Natalia Bravo-Adasme, Alejandro Cataldo, Hedy Acosta-Antognoni, Elizabeth Grandón, Nicolás Bravo and Margarita Valdés
Int. J. Environ. Res. Public Health 2025, 22(8), 1186; https://doi.org/10.3390/ijerph22081186 - 29 Jul 2025
Viewed by 294
Abstract
Digital hoarding (DH) is an emerging behavior with potential implications for psychological well-being and daily functioning. While traditionally associated with physical hoarding disorder, DH presents unique challenges in digital environments, particularly among university students increasingly immersed in technology. This study examines the relationship [...] Read more.
Digital hoarding (DH) is an emerging behavior with potential implications for psychological well-being and daily functioning. While traditionally associated with physical hoarding disorder, DH presents unique challenges in digital environments, particularly among university students increasingly immersed in technology. This study examines the relationship between DH and academic performance, proposing a theoretical model in which academic engagement and academic burnout act as mediating mechanisms. Drawing on the Job Demands–Resources Theory, we provide evidence that DH contributes to a health impairment process that negatively affects student outcomes. Our findings reveal DH as a novel predictor of academic burnout, highlighting its detrimental impact on academic performance. These results carry significant theoretical and practical implications, offering new insights into the role of technology-related anxiety disorders in educational settings. From a practical perspective, our study underscores the need for higher education institutions to implement targeted interventions focused on emotional regulation and learning strategies to mitigate the negative effects of DH. Despite limitations related to sample specificity and cross-sectional data, this research opens avenues for future longitudinal studies and interventions aimed at addressing DH in both academic and professional contexts. By linking digital behaviors to mental health and performance, this work aligns with public health interests in understanding technology’s impact on youth well-being. Full article
(This article belongs to the Section Behavioral and Mental Health)
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14 pages, 298 KiB  
Review
Asthma Symptom Self-Monitoring Methods for Children and Adolescents: Present and Future
by Hyekyun Rhee and Nattasit Katchamat
Children 2025, 12(8), 997; https://doi.org/10.3390/children12080997 - 29 Jul 2025
Viewed by 220
Abstract
Asthma is the leading chronic condition in children and adolescents, requiring continuous monitoring to effectively prevent and manage symptoms. Symptom monitoring can guide timely and effective self-management actions by children and their parents and inform treatment decisions by healthcare providers. This paper examines [...] Read more.
Asthma is the leading chronic condition in children and adolescents, requiring continuous monitoring to effectively prevent and manage symptoms. Symptom monitoring can guide timely and effective self-management actions by children and their parents and inform treatment decisions by healthcare providers. This paper examines two conventional monitoring methods, including symptom-based and peak expiratory flow (PEF) monitoring, reviews early efforts to quantify respiratory symptoms, and introduces an emerging sensor-based mHealth approach. Although symptom-based monitoring is commonly used in clinical practice, its adequacy is a concern due to its subjective nature, as it primarily relies on individual perception. PEF monitoring, while objective, has shown weak correlations with actual asthma activity or lung function and suffers from suboptimal adherence among youth. To enhance objectivity in symptom monitoring, earlier efforts focused on quantifying respiratory symptoms by harnessing mechanical equipment. However, the practicality of these methods for daily use is limited due to the equipment’s bulkiness and the time- and labor-intensive nature of data processing and interpretation. As an innovative alternative, sensor-based mHealth devices have emerged to provide automatic, objective, and continuous monitoring of respiratory symptoms. These wearable technologies offer promising potential to overcome the issues of perceptual inaccuracy and poor adherence associated with conventional methods. However, many of these devices are still in developmental or testing phases, with limited data on their clinical efficacy, usability, and long-term impact on self-management behaviors. Future research and robust clinical trials are warranted to establish their role in asthma monitoring and management and improving asthma outcomes in children and adolescents. Full article
14 pages, 2649 KiB  
Article
Study on the Liquid Transport on the Twisted Profile Filament/Spun Combination Yarn in Knitted Fabric
by Yi Cui, Ruiyun Zhang and Jianyong Yu
Polymers 2025, 17(15), 2065; https://doi.org/10.3390/polym17152065 - 29 Jul 2025
Viewed by 162
Abstract
The excellent moisture transport properties of yarns play a crucial role in improving the liquid moisture transfer behavior within textiles and maintaining their thermal-wet comfort. However, the current research on the moisture management performance of fabrics made from yarns with excellent liquid transport [...] Read more.
The excellent moisture transport properties of yarns play a crucial role in improving the liquid moisture transfer behavior within textiles and maintaining their thermal-wet comfort. However, the current research on the moisture management performance of fabrics made from yarns with excellent liquid transport properties primarily compares the wicking results, without considering the varying requirements of testing conditions due to differences in human sweating rates during daily activities. Moreover, the understanding of moisture transport mechanisms in yarns within fabrics under different testing conditions remains insufficient. In this study, two types of twisted combination yarns, composed of hydrophobic profiled polyester filaments and hydrophilic spun yarns to form a hydrophobic-hydrophilic gradient along the axial direction of the yarn, were developed and compared with profiled polyester filaments to understand the liquid migration behaviors in the knitted fabrics formed by these yarns. Results showed that hydrophobic profiled polyester filament yarn demonstrated superior liquid transport performance with infinite saturated liquid supply (vertical wicking test). In contrast, the twisted combination yarns exhibited better moisture diffusion properties under limited liquid droplet supply conditions (droplet diffusion test and moisture management test). These contradictory findings indicated that the amount of liquid moisture supply in testing conditions significantly affected the moisture transport performance of yarns within fabrics. It was revealed that the liquid moisture in the twisted combination yarns migrated through capillary wicking for moisture transfer. Under an infinite saturated liquid supply condition, the higher the content of hydrophilic fibers in the spun yarns, the greater the amount of moisture transferred, demonstrating an excellent liquid transport performance. Under the limited liquid droplet supply conditions, both the volume of liquid water and the moisture absorption capacity of the yarn jointly influence internal moisture migration within the yarn. It provided a theoretical reference for testing the internal moisture wicking performance of fabrics under different states of human sweating. Full article
(This article belongs to the Section Polymer Applications)
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22 pages, 786 KiB  
Article
Diet to Data: Validation of a Bias-Mitigating Nutritional Screener Using Assembly Theory
by O’Connell C. Penrose, Phillip J. Gross, Hardeep Singh, Ania Izabela Rynarzewska, Crystal Ayazo and Louise Jones
Nutrients 2025, 17(15), 2459; https://doi.org/10.3390/nu17152459 - 28 Jul 2025
Viewed by 153
Abstract
Background/Objectives: Traditional dietary screeners face significant limitations: they rely on subjective self-reporting, average intake estimates, and are influenced by a participant’s awareness of being observed—each of which can distort results. These factors reduce both accuracy and reproducibility. The Guide Against Age-Related Disease (GARD) [...] Read more.
Background/Objectives: Traditional dietary screeners face significant limitations: they rely on subjective self-reporting, average intake estimates, and are influenced by a participant’s awareness of being observed—each of which can distort results. These factors reduce both accuracy and reproducibility. The Guide Against Age-Related Disease (GARD) addresses these issues by applying Assembly Theory to objectively quantify food and food behavior (FFB) complexity. This study aims to validate the GARD as a structured, bias-resistant tool for dietary assessment in clinical and research settings. Methods: The GARD survey was administered in an internal medicine clinic within a suburban hospital system in the southeastern U.S. The tool assessed six daily eating windows, scoring high-complexity FFBs (e.g., fresh plants, social eating, fasting) as +1 and low-complexity FFBs (e.g., ultra-processed foods, refined ingredients, distracted eating) as –1. To minimize bias, patients were unaware of scoring criteria and reported only what they ate the previous day, avoiding broad averages. A computer algorithm then scored responses based on complexity, independent of dietary guidelines. Internal (face, convergent, and discriminant) validity was assessed using Spearman rho correlations. Results: Face validation showed high inter-rater agreement using predefined Assembly Index (Ai) and Copy Number (Ni) thresholds. Positive correlations were found between high-complexity diets and behaviors (rho = 0.533–0.565, p < 0.001), while opposing constructs showed moderate negative correlations (rho = –0.363 to −0.425, p < 0.05). GARD scores aligned with established diet patterns: Mediterranean diets averaged +22; Standard American Diet averaged −10. Full article
(This article belongs to the Section Nutrition Methodology & Assessment)
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15 pages, 239 KiB  
Article
Examining Puppetry’s Contribution to the Learning, Social and Therapeutic Support of Students with Complex Educational and Psychosocial Needs in Special School Settings: A Phenomenological Study
by Konstantinos Mastrothanasis, Angelos Gkontelos, Maria Kladaki and Eleni Papouli
Disabilities 2025, 5(3), 67; https://doi.org/10.3390/disabilities5030067 - 28 Jul 2025
Viewed by 774
Abstract
The present study focuses on investigating the contribution of puppetry as a pedagogical and psychosocial tool in special education, addressing the literature gap in the systematic documentation of the experiences of special education teachers, concerning its use in daily teaching practice. The main [...] Read more.
The present study focuses on investigating the contribution of puppetry as a pedagogical and psychosocial tool in special education, addressing the literature gap in the systematic documentation of the experiences of special education teachers, concerning its use in daily teaching practice. The main objective is to capture the way in which puppetry enhances the learning, social and therapeutic support of students with complex educational and psychosocial needs. The study employs a qualitative phenomenological approach, conducting semi-structured interviews with eleven special education teachers who integrate puppetry into their teaching. Qualitative data were analyzed using thematic analysis. The findings highlight that puppetry significantly enhances cognitive function, concentration, memory and language development, while promoting the active participation, cooperation, social inclusion and self-expression of students. In addition, the use of the puppet acts as a means of psycho-emotional empowerment, supporting positive behavior and helping students cope with stress and behavioral difficulties. Participants identified peer support, material adequacy and training as key factors for effective implementation, while conversely, a lack of resources and time is cited as a key obstacle. The integration of puppetry in everyday school life seems to ameliorate a more personalized, supportive and experiential learning environment, responding to the diverse and complex profiles of students attending special schools. Continuous training for teachers, along with strengthening the collaboration between the arts and special education, is essential for the effective use of puppetry in the classroom. Full article
13 pages, 634 KiB  
Article
Rare Variant Burden and Behavioral Phenotypes in Children with Autism in Slovakia
by Gabriela Repiská, Michal Konečný, Gabriela Krasňanská, Hana Celušáková, Ivan Belica, Barbara Rašková, Mária Kopčíková, Petra Keményová, Daniela Ostatníková and Silvia Lakatošová
Genes 2025, 16(8), 893; https://doi.org/10.3390/genes16080893 - 28 Jul 2025
Viewed by 337
Abstract
Background: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders characterized by a complex, multifactorial etiology with a strong genetic contribution. Our study aimed to evaluate the link between the burden of rare genetic variants within a specific panel of ASD [...] Read more.
Background: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders characterized by a complex, multifactorial etiology with a strong genetic contribution. Our study aimed to evaluate the link between the burden of rare genetic variants within a specific panel of ASD and intellectual disability-associated genes and phenotypic variability in a cohort of children with autism in Slovakia. Methods: Gene burden scores were calculated based on pathogenic, likely pathogenic, and uncertain significance rare DNA variants identified by whole-exome sequencing. We then assessed the effect of three different scoring methods on the variance across 15 psycho-behavioral parameters describing the phenotypic profiles of 117 ASD probands. Results: The burden score showed a significant multivariate effect on the combination of psycho-behavioral parameters. This score was associated with the social affect of ADOS-2, as well as with the socialization domain, and total adaptive behavior scores from the Vineland Adaptive Behavior Scales-3 (VABS). While a score based solely on count of pathogenic and likely pathogenic variants did not show a multivariate effect, incorporating variants of uncertain significance revealed a multivariate effect on two adaptive behavior parameters: daily living skills and total adaptive behavior score (VABS). Conclusions: Our findings partially explain the variability in phenotypic manifestation in our ASD patient cohort, highlighting the importance of considering the cumulative effect of rare genetic variants, including those of uncertain significance, in shaping the diverse clinical presentation of ASD. Full article
(This article belongs to the Section Human Genomics and Genetic Diseases)
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10 pages, 6510 KiB  
Proceeding Paper
Energy Consumption Forecasting for Renewable Energy Communities: A Case Study of Loureiro, Portugal
by Muhammad Akram, Chiara Martone, Ilenia Perugini and Emmanuele Maria Petruzziello
Eng. Proc. 2025, 101(1), 7; https://doi.org/10.3390/engproc2025101007 - 25 Jul 2025
Viewed by 512
Abstract
Intensive energy consumption in the building sector remains one of the primary contributors to climate change and global warming. Within Renewable Energy Communities (RECs), improving energy management is essential for promoting sustainability and reducing environmental impact. Accurate forecasting of energy consumption at the [...] Read more.
Intensive energy consumption in the building sector remains one of the primary contributors to climate change and global warming. Within Renewable Energy Communities (RECs), improving energy management is essential for promoting sustainability and reducing environmental impact. Accurate forecasting of energy consumption at the community level is a key tool in this effort. Traditionally, engineering-based methods grounded in thermodynamic principles have been employed, offering high accuracy under controlled conditions. However, their reliance on exhaustive building-level data and high computational costs limits their scalability in dynamic REC settings. In contrast, Artificial Intelligence (AI)-driven methods provide flexible and scalable alternatives by learning patterns from historical consumption and environmental data. This study investigates three Machine Learning (ML) models, Decision Tree (DT), Random Forest (RF), and CatBoost, and one Deep Learning (DL) model, Convolutional Neural Network (CNN), to forecast community electricity consumption using real smart meter data and local meteorological variables. The study focuses on a REC in Loureiro, Portugal, consisting of 172 residential users from whom 16 months of 15 min interval electricity consumption data were collected. Temporal features (hour of the day, day of the week, month) were combined with lag-based usage patterns, including features representing energy consumption at the corresponding time in the previous hour and on the previous day, to enhance model accuracy by leveraging short-term dependencies and daily repetition in usage behavior. Models were evaluated using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and the Coefficient of Determination R2. Among all models, CatBoost achieved the best performance, with an MSE of 0.1262, MAPE of 4.77%, and an R2 of 0.9018. These results highlight the potential of ensemble learning approaches for improving energy demand forecasting in RECs, supporting smarter energy management and contributing to energy and environmental performance. Full article
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