Search Results (171)

Shelf life of frozen foods is intrinsically linked to consumer sensory acceptability. However, quantifying the synergistic impact of extended storage and variable thermal cycles on perception remains challenging. This study proposes a non-destructive image-based approach for estimating the acceptability of frozen pizza using a machine learning model and identifying tomato sauce degradation as indicator of product quality decay. Qualitative consumer feedback (90%) identified tomato sauce saturation as the primary driver of visual rejection. Image processing pipeline was developed to isolate the sauce region from each sample for further color extraction (saturation in the HSV color space). A second-degree polynomial regression model was used to describe the saturation trend over time and, in parallel, a logistic regression classifier was trained to predict binary consumer acceptability based on both saturation and storage duration. The models were evaluated using frozen pizzas (−12 and −18 °C) for up to 200 days. The regression model achieved an R² of 0.68 and an RMSE of 12.8, while the classifier attained an accuracy of 88.2% and an AUC of 0.93. The resulting framework enables early, non-invasive estimation of product acceptability and shows strong potential for practical application in shelf life studies within the frozen food industry. Full article

Accurately estimating calorie intake and nutrient composition from what we eat remains one of the most practical challenges in maintaining a healthy lifestyle. Manual food logging and database-based estimations are often inaccurate because ingredient proportions and preparation styles vary widely. This paper presents a lightweight, privacy-preserving framework that estimates calories and detailed nutrient values from a single image. The model uses a Mask R-CNN-based segmentation network to identify visible food components, measure their area, estimate their volume using preset height values, and map them to nutritional information obtained from reliable datasets such as USDA and Food-a-pedia. The system integrates federated learning (FL) to ensure privacy by allowing the model to improve collaboratively without sharing raw user data. The proposed architecture achieved a mean Average Precision (mAP) of 96% for detection and 92% for segmentation, confirming its precision and efficiency. The model is trained and evaluated on a curated pizza dataset consisting of 1107 images across 50 topping categories, using a standard train-validation-test split (666/219/222) to ensure reliable performance assessment. The proposed system also achieves low nutrition estimation error, with calorie and nutrient deviations remaining within approximately 3.8% to 11.1% across evaluated metrics. A lightweight mobile interface is demonstrated through a Figma-based prototype mockup to illustrate potential real-world deployment and user interaction. Full article

Mild fasting hypertriglyceridemia is often accompanied by early insulin resistance and atherogenic dyslipidemia, making it an attractive target for pragmatic dietary prevention. This trial aims to determine whether substituting common cereal-based staples with functional low-glycemic index (low-GI) products improves the triglyceride–glucose (TyG) index in adults with fasting triglycerides >150 mg/dL. The GLOW study is an exploratory, randomized, double-blind, single-center crossover trial. Adults aged ≥18 years with fasting triglycerides >150 mg/dL and body mass index ≤30 kg/m² will be enrolled. Participants will follow a stabilized Mediterranean-style diet and will complete two 28-day intervention periods in random sequence: (i) functional low-GI Altograno^® pasta, pizza base and flatbread; and (ii) conventional standard wholegrain products. Intervention periods will be separated by a 28-day washout. Study foods will be consumed as fixed daily substitutions of usual staple servings (one bread portion and one pasta or pizza portion). The primary endpoint is the between-intervention difference in TyG response over each period, defined as the period-specific change from the corresponding period baseline to the end-of-period assessment. The primary analysis will compare end-of-period TyG between interventions while adjusting for the period-specific baseline value. Secondary endpoints include fasting triglycerides and glucose, atherogenic lipoproteins (non–high-density lipoprotein cholesterol and apolipoprotein B), inflammation (high-sensitivity C-reactive protein), endothelial reactivity assessed with the Endocheck^®/Vicorder^® system, and food acceptability. Safety endpoints include adverse event recording. Treatment effects will be estimated using linear mixed-effects models accounting for treatment, period and sequence, with prespecified carryover sensitivity analyses. A total of 40 participants will be recruited to generate feasibility data and effect size estimates. This protocol will provide crossover evidence on whether pragmatic, product-level low-GI staple substitution improves TyG and related cardiometabolic and vascular biomarkers in adults with suboptimal triglyceridemia, informing larger trials. Trial registration: ClinicalTrials.gov NCT07198789. Full article

Sleep disturbances are prevalent among children receiving pediatric palliative care (PPC) and have a substantial negative impact on the quality of life of both patients and their families. This scoping review aims to examine further key factors contributing to sleep disturbances in PPC by analyzing available clinical studies, focusing on child-related aspects such as pain, repositioning, and epilepsy, as well as environmental factors such as light, noise, and the care setting. In addition, we discuss the critical role of interdisciplinary collaboration in improving sleep outcomes for this population and provide clinical implications. Future research should prioritize developing evidence-based interventions to optimize sleep and enhance the well-being of children with PPC needs and their caregivers. Full article

Background/Objectives: The growing prevalence of mental health problems among medical students is a global concern, with dietary patterns emerging as potential modifiable factors. This study aimed to explore and evaluate whether higher consumption of ultra-processed foods may be associated with greater symptoms of anxiety and depression. Methods: This was an exploratory cross-sectional study integrated into a previous cohort of medical students, conducted based on the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology. Sixty-seven medical students completed a Food Frequency Questionnaire-based index. Dietary patterns and the associations between these patterns and symptoms of anxiety and/or depression were assessed statistically. Results: There were differences in the consumption of unprocessed or minimally processed foods, including fruits, vegetables, legumes and unsweetened juices between groups with/without anxiety or depression (p < 0.05). A higher intake of ultra-processed foods such as pizza, hot dogs, cereals high in fat and sugar, processed beverages and sweets was linked to greater symptoms (p < 0.05; Cohen’s d = 0.3–0.7). Three to four dietary patterns were identified, explaining between 60% and 86% of the variance. High consumption of cereals with added fat and sugars increased the risk by 7.4 times (OR = 7.4, 95% CI 1.2–12.2, p < 0.05). Conclusions: Dietary intake was associated, but not causally linked, to emotional symptoms among medical students. Lower consumption of unprocessed foods and higher intake of ultra-processed foods formed consistent behavioral profiles associated with anxiety and depression. Consuming more than three daily servings of cereals with added fat and sugar increased the risk of severe depressive symptoms by more than sevenfold, highlighting a strong dietary determinant. Future research should assess nutritional interventions aimed to improve mental health and academic performance in medical students. Full article

The increasing incidence of metabolic disorders, including diabetes, as well as diseases related to gluten sensitivity, has increased the demand for healthier foods, particularly those with both a low glycemic index and that are gluten-free. However, baked goods of this type of product generally do not have good physical properties. In the present study, specific moisture content maximized studied properties: specific volume, hardness, stickiness and adhesiveness. In addition, small variations in the moisture content of the mini pizzas made from cassava starch modified by alpha amylase and Ca lactate caused the physical parameters studied to vary significantly. On the other hand, strong positive and negative correlations were found between moisture content and the studied physical parameters. Thus, moisture content could be a determining factor in studied pizza’s physical properties and can be a predictor of these properties. The objective of this study was to evaluate the physical properties of a gluten-free, low-glycemic-index mini-pizza made from modified cassava starch with alpha amylase and Ca lactate. Cassava of the INIAP 651 variety grown in Manabí, Ecuador, was used. The starch was extracted, sun-dried, and subsequently modified with alpha-amylase (6 U/g) and Ca lactate (6 mg/g). Water, oil, egg, and salt were added to the resulting modified starch to prepare mini-pizza doughs, which were tested at different moisture levels (39.5, 40.5, 41.5, 42.5, and 43.5%) to evaluate their expansive and textural properties. The evaluation results of the pizza at specific volumes (0.954–1.313 mL/g) showed that the highest value was obtained at 39.5% moisture content. However, the hardness (12.654–23.498 N), stickiness (−0.347–−0.246 N), and adhesiveness (−1.328–−1.547 N·mm) determined the lowest values at 43.5% moisture content. Positive correlations were found between moisture content vs. specific volume, as well as between specific volume vs. stickiness. Likewise, negative correlations were found between moisture content vs. specific volume, hardness and stickiness, as well as between specific volume vs. stickiness. Thus, moisture content could be a determining factor in pizza’s physical properties and can be a predictor of certain properties such as specific volume, hardness, stickiness and adhesiveness. Full article

Background: EHEC O157:H7 causes severe gastrointestinal illness by first colonizing the large intestine. It intimately attaches to the epithelial lining, orchestrating distinctive “attaching and effacing” lesions that disrupt the host’s cellular landscape. While much is known about the well-established virulence factors, there are much to learn about the surface proteins’ roles in a living host. Methods: This study presents the first in vivo characterisation of the surface proteome, i.e., proteosurfaceome, of Escherichia coli O157:H7 EDL933 during intestinal infection, revealing spatial and temporal adaptations critical for colonisation and survival. Using a murine ileal loop model, surface proteomic profiles were analysed at early (3 h) and late (10 h) infection stages across the ileum and colon. Results: In total, 272 proteins were identified, with only 13 shared across all conditions, reflecting substantial niche-specific adaptations. Gene ontology enrichment analyses highlighted dominant roles in metabolic, cellular, and binding functions, while subcellular localisation prediction uncovered cytoplasmic moonlighting proteins with surface activity. Comparative analyses revealed dynamic changes in protein abundance. Conclusions: These findings indicate a coordinated shift from stress adaptation and virulence to nutrient acquisition and persistence and provide a comprehensive view of EHEC O157:H7 surface proteome dynamics during infection, highlighting key adaptive proteins that may serve as targets for future therapeutic and vaccine strategies. Full article

This study aims to develop nutritionally improved alternative fast-food products by incorporating anchovy (Engraulis encrasicolus), a fish with high nutritional value, into three popular fast-food items (toast, burger, and pizza) frequently consumed by fast-food consumers. Anchovies, due to their rich content of omega-3 fatty acids, high-quality protein, vitamins A and D, and minerals, are a valuable food source for public health. Within the scope of this study, the nutritional compositions (crude protein, crude fat, crude ash, moisture, carbohydrate, energy) and sensory properties of the developed products were determined. According to the results of the analysis, the highest crude protein (18.64%) and crude ash (4.38%) content were found in anchovy-enriched toast, while the highest crude fat content (10.82%) was observed in anchovy burger (p < 0.05). Sensory analyses indicated that the panelists generally accepted all products. Specifically, the anchovy-enriched burger received the highest scores for appearance (90%) and aroma (40%). These findings demonstrate that anchovy-enriched fast-food products are both nutritionally rich and consumer-accepted, nutritionally improved food alternatives. Furthermore, this study identifies significant potential for utilizing aquatic products within the nutritionally enriched, seafood-based product sector. Full article

Background/Objectives: Adolescence is a critical developmental phase marked by rapid cognitive, emotional, and social changes that influence how individuals experience psychological energy and exhaustion. Self-Determination Theory recently proposed a dual-process model, based on two distinct, yet related, constructs: Subjective Vitality, associated with well-being and positive health outcomes, and Subjective Depletion, associated with illbeing and negative emotions. Since, to date, no study has investigated vitality and depletion during adolescence, this study aims to validate the Subjective Vitality/Depletion Scale (SVDS) in a large sample of adolescents. Methods: A total of 1111 Italian adolescents (Mage = 14.49, SDage = 1.49; 48% females) completed the SVDS and other validated self-report measures. Specifically, the psychometric properties of the SVDS across biological sex and age groups and latent mean differences across these groups were assessed. Results: Findings supported the dimensionality of the SVDS with two correlated factors, and its construct validity through associations with positive and negative affect and basic psychological needs satisfaction. Full invariance for the SVDS was achieved across biological sex and age groups. Latent mean analyses indicated that males reported higher levels of vitality compared to females (Cohen’s d = 0.46), with no significant differences for depletion; older adolescents reported lower levels of vitality (d = −0.23) and higher levels of depletion (d = 0.20) compared to younger adolescents. Conclusions: These findings support the SVDS as a valid and reliable instrument for assessing energy-related experiences in adolescence. The results suggest meaningful sex differences and a potential developmental trend of declining subjective energy from early to later adolescence. Full article

Adolescent school victimization is a socially regulated experience, making it important to consider classroom-level compositional effects beyond individual characteristics. This study investigated the role of classroom characteristics, specifically, classroom socioeconomic status, average academic achievement, sex composition, immigrant density, and class size, in shaping students’ experiences of school victimization. Victimization was analyzed using a doubly latent multilevel modeling approach, which accounts for measurement error at both individual and classroom levels. The analyses drew on the entire Italian 10th grade student population (N = 254,177; M_age = 15.58 years; SD_age = 0.74) and a considerable number of classrooms (N classrooms = 14,278), a sample size rarely available in the social sciences. Results indicated that classroom characteristics played a significant role in victimization, beyond individual-level variables. The most important factors were sex and prior academic achievement: classrooms with a higher proportion of male students experienced greater victimization, whereas higher average achievement was associated with lower victimization. A greater proportion of second-generation immigrant students, but not first-generation students, was also associated with increased victimization. By contrast, classroom socioeconomic status and class size were not significant predictors of victimization. In conclusion, these findings highlight the importance of considering the additional influence of the classroom context for school-based interventions, particularly the composition of classrooms in terms of sex and academic achievement, when addressing student victimization. Full article

This study aimed to characterize access to food establishments through a meal delivery application in university and non-university settings within a Brazilian metropolis. This cross-sectional study used data from a leading meal delivery platform. All establishments delivering to four public and four private university campuses in Belo Horizonte, Brazil were identified. For comparison, one corresponding non-university location was selected for each campus (yielding eight campus–location pairs). Each location corresponds to a central address within the paired neighborhood that was entered into the app to simulate delivery availability. Pairing criteria were based on geographic region and income levels. Information on establishment categories (classified by keywords), delivery distances, delivery fees, and geographic centrality was collected and analyzed descriptively. The number of available establishments ranged from 7176 to 11,440 across the assessed locations. Most establishments were categorized under keywords referring to snacks (e.g., burgers, savory snacks, pizza), regardless of location. Delivery distances ranged from 0 to 19.6 km, with shorter distances observed for university addresses and corresponding locations situated in central neighborhoods of the city, and longer distances for peripheral areas. Only 4.7% of establishments offered free delivery, and higher delivery fees were more frequent in non-university locations. No significant differences were observed between public and private universities. Food establishments are widely accessible via the app; however, central areas tend to have broader service coverage. Regardless of whether the location is a university or non-university setting, or whether it is central or peripheral, there is a predominance of establishments classified under keywords associated with unhealthy food options. Full article

Currently, at least one third of greenhouse gas (GHG) emissions come from the agricultural sector, with meat production making a particularly significant contribution. Therefore, alongside the ongoing efforts to transform transport and cut its emissions, it is essential to adopt urgent measures that limit GHG emissions from food production, consumption and distribution. Without them, the Paris Agreement goal of net-zero GHG emissions by 2050 cannot be met, and the most severe impacts of climate change will not be avoided. In principle, lowering emissions from the global food system may appear simple, as no new technology (for example, electric cars or carbon-neutral fuels) is required to decarbonize transport. However, since meat consumption accounts for the majority of food related GHG emissions, it must be coupled with a sharp reduction in the large-scale production and consumption of animal foods. Encouragingly, a growing number of consumers already choose diets that are both healthy and environmentally sustainable. As meat reduction gains popularity in these groups, plant-based products are expanding in the marketplace, mainly in the form of snacks, pasta, pizzas and especially vegan or vegetarian burgers. Thus, almost spontaneously, components of the Westernized diet, rich in ultra-processed foods, salt, sugar and animal protein, are gradually being replaced by plant-derived nutrients that are healthier and more environmentally friendly. To accelerate this trend, legal measures could be introduced to improve the nutritional quality of widely consumed, low-nutrient snacks and to promote agricultural reforms that encourage the production of nutrient-dense legumes and pseudocereals. Full article

Unmanned aerial vehicles (UAVs) play an increasingly vital role in wilderness search and rescue (SAR) operations by enhancing situational awareness and extending the capabilities of human teams. Yet, a lack of standardized benchmarks has impeded the systematic evaluation of single- and multi-agent path-planning algorithms. This paper introduces an open-source dataset and evaluation framework to address this gap. The framework comprises 60 geospatial scenarios across four distinct European environments, featuring high-resolution probability maps. We present a lost person probabilistic model derived from statistical models of lost person behavior. We provide a suite of tools for evaluating search paths against four baseline methods: Concentric Circles, Pizza Zigzag, Greedy, and Random Exploration, using three quantitative metrics: Accumulated probability of detection, time-discounted probability of detection, and lost person discovery score. We provide an evaluation framework to facilitate the comparative analysis of single- and multi-agent path-planning algorithms, supporting both the baseline methods presented and custom user-defined path generators. By providing a structured and extensible framework, this work establishes a foundation for the rigorous and reproducible assessment of UAV search strategies in complex wilderness environments. Full article

Introduction: Staphylococcus aureus is a high-priority foodborne pathogen contributing to several food poisoning outbreaks. Methicillin- and vancomycin-resistant S. aureus (MRSA and VRSA), pose significant public health concerns due to their potential for serious illness, antibiotic resistance, and transmission within both healthcare and community settings. These bacteria can cause numerous infections, ranging from skin and soft tissue infections to life-threatening conditions like bloodstream infections, pneumonia, and endocarditis. Although several publications are concerned with Staphylococcus aureus contamination in ready-to-eat (RTE) food products, little published data is available about its prevalence in pizza, which is widely distributed and consumed worldwide. Methods: The current study is intended to determine the prevalence, virulence genes, and antimicrobial resistance profiles of S. aureus in three hundred ready-to-eat pizza samples (100 each of meat, chicken, and canned tuna pizzas) collected from different restaurants in Mansoura City, Egypt. The typical colonies on Baird–Parker selective agar supplemented with egg yolk tellurite emulsion were counted and further confirmed based on Gram staining, coagulase testing, catalase testing, carbohydrate fermentation, and thermostable nuclease production. The genomic DNA of the confirmed coagulase-positive isolates was prepared and subjected to PCR analyses for detecting the nuc gene, mecA (methicillin resistance gene), and vancomycin resistance gene (vanA), as well as six selected S. aureus virulence genes: sea, seb, sec, sed, hla, and tsst. The antimicrobial resistance profile of the S. aureus isolates was determined against 16 antimicrobial agents belonging to six classes using the agar disc diffusion method according to the Clinical and Laboratory Standards Institute guidelines (CLSI), except for oxacillin and vancomycin, which were assessed using the MIC test. Results: The results revealed that 56% (56/100), 56% (56/100), and 40% (40/100) of chicken, meat, and canned tuna pizzas were positive for S. aureus, with an overall prevalence of 50.7% (152/300). All 560 isolates (100%) were verified as S. aureus based on molecular confirmation of the nuc gene. Interestingly, 48.6% (272/560) and 8.6% (48/560) of the isolates tested were identified as methicillin- and vancomycin-resistant S. aureus (MRSA and VRSA) through detection of mecA and vanA genes, respectively. Among the S. aureus isolates tested, the hla gene was detected in 87.1% (488/560), while the enterotoxin genes sea, seb, sec, and sed were identified in 50% (280/560), 78.6% (440/560), 9.8% (55/560), and 24.5% (137/560) of isolates, respectively. All recovered isolates (n = 560) were classified as multidrug-resistant and were resistant to penicillin, oxacillin, and ampicillin. Moreover, 77% (431/560), 24% (134/560), 8% (45/560), and 8.6% (48/560) of isolates were resistant to cefotaxime, ciprofloxacin, azithromycin, and vancomycin, respectively. Conclusions: The current study emphasizes that ready-to-eat pizza is highly contaminated with multidrug-resistant S. aureus, highlighting the urgent need for rationalizing antibiotic use in both veterinary and human medicine to prevent the transmission of resistant bacteria through the food chain. Additionally, strict adherence to good hygienic practices throughout all stages of the food chain is essential to minimize overall contamination and enhance food safety. Full article

Background: Narcolepsy type 1 (NT1) is a rare neurological sleep disorder characterized by excessive daytime sleepiness and cataplexy. NT1 is thought to be caused by the loss of hypocretin-producing neurons in the hypothalamus due to autoimmunity. Since cerebrospinal fluid hypocretin testing is invasive and not always feasible in clinical practice, there is a critical need for less invasive biomarkers to improve diagnostic accuracy and accessibility. Very few studies have explored serum-based biomolecules that could serve as biomarkers for NT1. Methods: This study examines the differential abundance of serum metabolites in patients with NT1 using an LC-MS/MS-based comprehensive metabolomics approach. Results: An untargeted analysis identified a total of 1491 metabolites, 453 of which were differentially abundant compared to the control cohort. Ingenuity pathway analysis revealed that key pathways, such as the inflammatory response (p-value of 0.01, activation z-score of 0.5), generation and synthesis of reactive oxygen species (p-value of 0.0008, z-score of 1.3), and neuronal cell death (p-value of 0.04, z-score of 0.4), are predicted to be activated in NT1. A targeted analysis using parallel reaction monitoring validated 49 metabolites, including important downregulated metabolites such as uridine (fold change (FC) of 0.004), epinephrine (FC of 0.05), colchicine (FC of 0.2), corticosterone (FC of 0.3), and arginine (FC of 0.6), as well as upregulated metabolites such as p-cresol sulfate (FC of 2601.7), taurine (FC of 1315.4), inosine (FC of 429.7), and malic acid (FC of 7.9). Conclusions: Understanding the pathways identified in this study and further investigating the differentially abundant metabolites associated with them may pave the way for gaining insight into disease pathogenesis and developing novel therapeutic interventions. Full article