Search Results (206)

Background: The aim of this study was to investigate the effects of matcha on lipid metabolism, insulin resistance (IR), inflammation, and gut dysbiosis in non-alcoholic fatty liver disease (NAFLD) induced by a cafeteria diet. Methods: Forty-eight 7-week-old male Wistar rats were divided into six groups (n = 8), including a control group (C), C + 0.2% matcha group (C + 0.2%), C + 1% matcha group (C + 1%), cafeteria group (Caf), Caf + 0.2% matcha group (Caf + 0.2%), and Caf + 1% matcha group (Caf + 1%). All rats were sacrificed at the end of the 12th week of the experiment. A one-way analysis of variance (ANOVA), followed by a Fisher’s post hoc test, was used to determine the significant differences among each of the groups. Results: The results indicated that plasma experiment triglycerides (TGs) significantly increased in the Caf group compared to the C group, and significantly decreased TG levels were found in the Caf + 1% group compared to the Caf group. In addition, the liver total cholesterol and TG had significantly increased in the Caf group, while the 0.2% Matcha intervention can mitigate hepatic lipid accumulation. Blood sugar, serum insulin, the homeostasis model assessment of IR (HOMA-IR), and plasma leptin significantly increased in the Caf group and were significantly lower in the Caf + 0.2% and Caf + 1% groups. Hepatic cytokines significantly increased in the Caf group, while, on the other hand, significantly lower concentrations were found in the Caf + 1% group. In addition, beneficial bacteria including Akkermansia, Faecalibacterium, and Parabacteroides increased after matcha supplementation. Conclusions: These results suggested that 12 weeks of a cafeteria diet can induce abnormal lipid metabolism, IR, liver inflammation, and an altered gut microbiotic composition, while both the 0.2% and 1% matcha interventions might regulate obesity, lipid accumulation, IR, and inflammatory responses, and help maintain a healthier gut microbiota, which may then ameliorate the development of NAFLD. Full article

Ready-to-eat (RTE) foods including sandwiches, pastries, shawarma, and burgers are widely consumed and may potentially increase the risk of foodborne infections. This study investigated the prevalence, serovar diversity, and antimicrobial resistance (AMR) of Salmonella spp. in RTE foods collected between January and June 2024 from street vendors and restaurants across Erbil, Iraq. A total of 350, including 85 sandwiches, 75 pastries, 95 shawarma, and 95 burgers obtained from 115 cafeteria, 120 street vendors, and 115 restaurants were analyzed. Salmonella was detected in 7.1% (n = 25) of samples, with a high contamination in shawarma (8.4%; n = 95), followed by sandwiches (7.1%; n = 85), pastries (6.7%; n = 75), and burgers (6.3%; n = 95). Street vendors exhibited a higher (9.2%; n = 120) contamination rate compared to the cafeteria (6.9%; n = 115) and restaurants (5.2%; n = 115). Among 25 Salmonella isolates, 10 serotypes were identified, with S. Anatum (20%) and S. Typhimurium (16%) being the most prevalent. All isolates were susceptible to colistin, cefadroxil, and gentamicin, while showing high resistance to streptomycin (52%) and levofloxacin (48%). Contamination peaked during the warmer months, particularly in June (15.4%) and May (11.5%), when compared to the other sampling months. These findings highlight significant food safety concerns related to Salmonella contamination and AMR in RTE foods, emphasizing the urgent need for enhanced hygiene practices and regulatory oversight especially among street vendors. Full article

Cycads are being endangered by several anthropogenic threats, and invasions of non-native herbivores are among those threats. Various country invasions by the cycad blue butterfly Luthrodes pandava have threatened the local horticulture cycad trade and native cycad populations. Little is known about behaviors of the larval stage of this specialist herbivore, the life phase that causes damage to cycad leaf tissue. The objective here was to determine larval ability to discriminate among Cycas species that are known to exhibit contrasting susceptibility to L. pandava herbivory. Dual-choice cafeteria protocols were used whereby a single larvae was provisioned with one leaflet of minimally damaged species (low quality) and one leaflet of heavily damaged species (high quality). Consumption after an 8 h feeding cycle was measured as loss in leaflet area. Wild L. pandava populations derived from in situ Philippine and Thailand Cycas habitats preferentially fed on high quality leaflets. In contrast, invasive L. pandava populations from urban locations in Guam, Philippines, and Thailand exhibited no preferences in leaflet feeding choice. The findings indicated that larvae of this Lycaenidae specialist herbivore exhibit complex selection behaviors that depend on origin of the butterfly and feeding history. Discrimination capabilities of the in situ populations that evolved with a single native Cycas species demonstrated beneficial behaviors that appear to be lost over time by invasive populations that feed on numerous novel Cycas hosts within the invasive range. Full article

Background: The Healthy, Hunger-Free Kids Act requires access to free drinking water in public school cafeterias during meal times. Previous studies suggest that increasing access to water in schools can increase its consumption among students, potentially reducing their intake of sugar-sweetened beverages. The current study provides a descriptive assessment of water availability, delivery methods, and quality in 96 public schools across four New Jersey school districts. Methods: As part of the New Jersey Child Health Study, we administered an online and paper survey to school nurses at 96 schools to evaluate the availability, delivery, and quality of water in the school cafeteria during lunchtime. Univariate and bivariate statistics were used to analyze the data. Results: In school year 2019–20, 83 (86.5%) schools reported providing free drinking water in the cafeteria during lunch. The most common source of water was water fountains, available in 64 schools (66.7%). Issues related to water quality, specifically cleanliness, temperature, pressure, and taste, were present in 20–30% of schools. Conclusions: While most schools surveyed provide access to clean, free drinking water, students in some schools still lack free access to drinking water during school meals, which may affect overall water consumption among students. Full article

Integrating renewable energy with biomass valorization offers a scalable pathway toward circular and climate-resilient campus operations. This study presents a replicable model implemented at Alanya Alaaddin Keykubat University (ALKU, Türkiye), where post-consumer food waste from 30 cafeteria menus is converted into pet food and compost using a 150 L ECOAIR-150 thermal drying and grinding unit powered entirely by a 1.7 MW rooftop photovoltaic (PV) system. The PV infrastructure, established under Türkiye’s first public-sector Energy Performance Contract (EPC), ensures zero-electricity-cost operation. On average, 260 kg of organic waste are processed monthly, yielding 180 kg of pet food and 50 kg of compost, with an energy demand of 1.6 kWh h⁻¹ and a conversion efficiency of 68.4%, resulting in approximately 17.5 t CO₂ emissions avoided annually. Economic analysis indicates a monthly revenue of USD 55–65 and a payback period of ~36 months. Sensitivity analysis highlights the influence of input quality, seasonal waste composition, PV output variability, and operational continuity during academic breaks. Compared with similar initiatives in the literature, this model uniquely integrates EPC financing, renewable energy generation, and waste-to-product transformation within an academic setting, contributing directly to SDGs 7, 12, and 13. Full article

Food security among college students is an increasing concern, with potential implications for their health, academic performance, and future well-being. This study investigated food security within a college community in Mexico, focusing on food availability, access (both economic and physical), and consumption patterns. A mixed-methods approach was employed at Ciudad Universitaria, BUAP, Mexico, between 2023 and 2024. Stratified random sampling was used, resulting in a final sample of 606 students. Data were collected through structured questionnaires covering sociodemographic characteristics and eating habits, the ELCSA, structured cafeteria observations, semi-structured interviews with key informants, and three focus groups. Statistical analysis was performed using chi-square tests (p < 0.05). Post hoc analysis with Bonferroni adjustment confirmed that origin (p = 0.0017), mode of transportation (p = 2.31 × 10⁻⁵) and private vehicles (p = 1.77 × 10⁻⁵) were the key determinants. Although the environment offered a variety of options, processed and ultra-processed products dominated the food choices. A total of 95.9% of students purchased food on campus, yet only 21.8% reported engaging in healthy eating habits. Focus groups revealed that students’ food choices were influenced by availability, access, and perceptions of affordability and convenience. These findings highlight the urgent need for targeted interventions to improve food security and promote healthier dietary practices within the college setting. Full article

Lactic acid (LA) synthesis through fermentation of food waste (FW) is an emerging techniques for utilizing perishable organic wastes with high value. Using food waste collected from a cafeteria as the substrate for fermentation, the current study was conducted by applying a micro electric field to the conventional LA fermentation process and performing open-ended electro-fermentation (EF) without sterilization and lactobacilli inoculation. Furthermore, the effects of pH adjustment on LA production were examined. The findings demonstrated that electrical stimulation enhances the electron transfer rate within the system, accelerates REDOX reactions, and thereby intensifies the lactic acid production process. The pH-regulated group produced LA and dissolved organic materials at considerably higher rates than the control group, which did not receive any pH modification. The maximum LA concentration and organic matter dissolution in the experimental group, where the pH was set to 7 every 12 h of fermentation, were 33.9 and 38.4 g/L, respectively. These values were 208 and 203% higher than those in the control group, indicating that the pH adjustment greatly aided the solubilization and hydrolysis of macromolecules. Among the several hydrolyzing bacteria (Actinobacteriota) that were enriched, Lactobacillus predominated, but Bifidobacterium also became a major genus in the neutral-acidic environment, and its abundance grew dramatically. This study provides a scientific basis for optimizing the LA process of FW. Full article

Healthy food service guidelines (HFSG) comprise food, nutrition, behavioral design, and other standards to guide the purchasing, preparation, and offering of foods and beverages in worksites and institutional food service. To date, there have been few attempts to synthesize evidence for HFSG effectiveness in non-K-12 or early childhood education sectors, particularly at worksites and institutional food services. We conducted a scoping review to achieve the following: (1) characterize the existing literature on the effectiveness of HFSG for improving the institution’s food environment, financial outcomes, and consumers’ diet quality and health, and (2) identify gaps in the literature. The initial search in PubMed and Web of Science retrieved 10,358 articles; after screening and snowball searching, 68 articles were included for analysis. Studies varied in terms of HFSG implementation settings, venues, and outcomes in both U.S. (n = 34) and non-U.S. (n = 34) contexts. The majority of HFSG interventions occurred in venues where food is sold (e.g., worksite cafeterias, vending machines). A diversity of HFSG terminology and measurement tools demonstrates the literature’s breadth. Literature gaps include quasi-experimental study designs, as well as interventions in settings that serve dependent populations (e.g., universities, elderly feeding programs, and prisons). Full article

Obesity and metabolic dysfunction are established risk factors for luminal breast cancer, yet current preclinical models inadequately recapitulate the complex metabolic and immune interactions driving tumorigenesis. To develop and characterize an immunocompetent rat model of luminal breast cancer induced by chronic exposure to a cafeteria diet mimicking Western obesogenic nutrition, female rats were fed a cafeteria diet or standard chow from weaning. Metabolic parameters, plasma biomarkers (including leptin, insulin, IGF-1, adiponectin, and estrone), mammary gland histology, tumor incidence, and gene expression profiles were longitudinally evaluated. Gene expression was assessed by PCR arrays and qPCR. A subgroup underwent dietary reversal to assess the reversibility of molecular alterations. Cafeteria diet induced significant obesity (mean weight 426.76 g vs. 263.09 g controls, p < 0.001) and increased leptin levels without altering insulin, IGF-1, or inflammatory markers. Histological analysis showed increased ductal ectasia and benign lesions, with earlier fibroadenoma and luminal carcinoma development in diet-fed rats. Tumors exhibited luminal phenotype, low Ki67, and elevated PAI-1 expression. Gene expression alterations were time point specific and revealed early downregulation of ID1 and COX2, followed by upregulation of MMP2, THBS1, TWIST1, and PAI-1. Short-term dietary reversal normalized several gene expression changes. Overall tumor incidence was modest (~12%), reflecting early tumor-promoting microenvironmental changes rather than aggressive carcinogenesis. This immunocompetent cafeteria diet rat model recapitulates key metabolic, histological, and molecular features of obesity-associated luminal breast cancer and offers a valuable platform for studying early tumorigenic mechanisms and prevention strategies without carcinogen-induced confounders. Full article

Background/Objectives: Deep learning (DL) has shown strong potential in analyzing food images, but few studies have directly predicted mass, energy, and macronutrient content from images. In addition to the importance of high-quality data, differences in country-specific food composition databases (FCDBs) can hinder model generalization. Methods: We assessed the performance of several standard DL models using four ground truth datasets derived from Nutrition5k—the largest image–nutrition dataset with ~5000 complex US cafeteria dishes. In light of developing an Italian dietary assessment tool, these datasets varied by FCDB alignment (Italian vs. US) and data curation (ingredient–mass correction and frame filtering on the test set). We evaluated combinations of four feature extractors [ResNet-50 (R50), ResNet-101 (R101), InceptionV3 (IncV3), and Vision Transformer-B-16 (ViT-B-16)] with two regression networks (2+1 and 2+2), using IncV3_2+2 as the benchmark. Descriptive statistics (percentages of agreement, unweighted Cohen’s kappa, and Bland–Altman plots) and standard regression metrics were used to compare predicted and ground truth nutritional composition. Dishes mispredicted by ≥7 algorithms were analyzed separately. Results: R50, R101, and ViT-B-16 consistently outperformed the benchmark across all datasets. Specifically, when replacing it with these top algorithms, reductions in median Mean Absolute Percentage Errors were 6.2% for mass, 6.4% for energy, 12.3% for fat, and 33.1% and 40.2% for protein and carbohydrates. Ingredient–mass correction substantially improved prediction metrics (6–42% when considering the top algorithms), while frame filtering had a more limited effect (<3%). Performance was consistently poor across most models for complex salads, chicken-based or eggs-based dishes, and Western-inspired breakfasts. Conclusions: The R101 and ViT-B-16 architectures will be prioritized in future analyses, where ingredient–mass correction and automated frame filtering methods will be considered. Full article

Obesity is a global health concern that elevates the risk of noncommunicable diseases (NCDs) such as type 2 diabetes, cardiovascular disease, and certain cancers. Phaseolus vulgaris (white bean) contains α-amylase inhibitors (αAIs) that can reduce carbohydrate digestion and absorption, potentially mitigating obesity and metabolic syndrome. This study investigated the impact of P. vulgaris extract (PVE) on obese rats. Male Wistar rats were fed either a standard diet (SD) or a cafeteria diet (CAF) for 17 weeks to induce obesity. Subsequently, rats in each dietary group were randomly assigned to receive a vehicle, low-dose PVE (200 mg/kg), high-dose PVE (300 mg/kg), or metformin (200 mg/kg) via an oral gavage for 6 weeks. The CAF group exhibited significantly greater weight gain compared to the SD group. In the CAF group, a low dose of PVE lowered postprandial glycemia during an oral glucose tolerance test (OGTT) at 60 and 120 min and decreased food and energy intake during weeks 17–20 and 18–19, respectively. In the SD group, a high dose of PVE reduced glycemia at 90 min in the OGTT, as well as body weight gain, food intake, and energy intake during week 17. However, the overall areas under the glucose curves in the OGTT were not significantly different across treatment groups (p > 0.05), and while individual time points showed changes, the overall glucose exposure (AUC) was not significantly altered. In conclusion, the αAIs present in P. vulgaris demonstrate the potential to reduce body weight, weight gain, glycemia, total cholesterol, and triglycerides in vivo, but in the CAF group, neither PVE dose significantly altered the TC or TG. This study provides strong support for further exploring Phaseolus vulgaris extract as a valuable functional ingredient in the food industry, particularly for developing products that aid in weight management and glycemic control. Full article

This preliminary study explores the use of a smart tray prototype equipped with a weight sensor to analyze consumer eating behavior in real-life conditions. Conducted in 2022, at the restaurant “La Confluence” in Namur, with 60 participants, the experiment involved tracking the progression of a standardized meal, “Scallops in sauce with vegetables”. The collected data allowed for the calculation of variables such as bite count, applied force, meal duration, and quantity consumed. Through mathematical processing, insights into individual and group eating patterns were developed, with 39 usable datasets analyzed. Our first results show that the smart tray is capable of estimating the weight consumed and the number of bites with over 97% accuracy. Statistical analysis enabled the identification of four distinct groups of individuals based on five behavioral variables related to eating behavior. The smart tray could be used in hospitality establishments including cafeterias, restaurants, or brasseries, where it could serve as a valuable tool for monitoring meal nutrition. Further improvements will aim to enhance utensil and action recognition through artificial intelligence, which will also support a more detailed characterization of eating behavior. Full article

Indoor environmental quality (IEQ), encompassing thermal comfort and indoor air quality (IAQ), plays a crucial role in occupant well-being and operational performance. Although widely studied individually, integrating thermal comfort and IAQ assessments remains limited, particularly in large-scale tropical commercial settings. Hypermarkets, characterised by spatial heterogeneity and fluctuating occupancy, present challenges that conventional HVAC systems often fail to manage effectively. This study investigates thermal comfort and IAQ variability in a hypermarket located in Gombak, Malaysia, under tropical rainforest conditions based on the Köppen–Geiger climate classification, a widely used system for classifying the world’s climates. Environmental parameters were monitored using a network of IoT-enabled sensors across five functional zones during actual operations. Thermal indices (PMV, PPD) and IAQ metrics (CO₂, TVOC, PM2.5, PM10) were analysed and benchmarked against ASHRAE 55 standards to assess spatial variations and occupant exposure. Results revealed substantial heterogeneity, with the cafeteria zone recording critical discomfort (PPD 93%, CO₂ 900 ppm, TVOC 1500 ppb) due to localised heat and insufficient ventilation. Meanwhile, the intermediate retail zone maintained near-optimal conditions (PPD 12%). Although findings are specific to this hypermarket, the integrated zone-based monitoring provides empirical insights that support the enhancement of IEQ assessment approaches in tropical commercial spaces. By characterising zone-specific thermal comfort and IAQ profiles, this study contributes valuable knowledge toward developing adaptive, occupant-centred HVAC strategies for complex retail environments in hot-humid climates. Full article

To ensure the effective implementation of food waste reduction in college cafeterias, Capital Normal University developed an automatic plate recognition system based on machine vision technology. The system operates by obtaining images of plates (whether clean or not) and the diners’ faces through multi-directional monitoring, then employs several deep learning models for the automatic localization and identification of the plates. Face recognition technology links the identification results of the plates to the diners. Additionally, the system incorporates innovative educational mechanisms such as online feedback and point redemption to encourage student participation and foster thrifty habits. These initiatives also provide more accurate training samples, enhancing the system’s precision and stability. Our findings indicate that machine vision technology is suitable for rapid identification and location of clean plates. Even without optimized network parameters, the U-Net network demonstrates high recognition accuracy (MIOU of 68.64% and MPA of 78.21%) and ideal convergence speed. Pilot data showed a 13% reduction in overall waste in the cafeteria and over 75% user acceptance of the mechanism. The implementation of this system has significantly improved the efficiency and accuracy of plate recognition, offering an effective solution for food waste prevention in college canteens. Full article

Mostly, public places are planned and designed by professionals rather engaging the community in the design process. Even if the community engaged, the engagement process was limited to hand drawings, manual mappings, or public discussions, which limited the general public to visualize and well-communicate their aspirations with the professionals. Against this backdrop, this study intends to develop a mobile application called “CityBuildAR”, which uses Augmented Reality technology that allows the end user to visualize their public spaces in a way they want. CityBuildAR was developed by the authors using the Unity Real-Time Development Platform, and the app was developed for an Android Operating System. The app was used to assess community interests in designing open spaces by categorizing participants into three groups: those with limited, average, and professional knowledge of space design. The open cafeteria of the University of Moratuwa, Sri Lanka served as the testbed for this study. The study findings revealed that: (a) Mobile Augmented Reality is an effective way to engage people with limited knowledge in space design to express their design thinking, (b) Compared to professionals, the general public wanted to have more green elements in the public space; (c) Compared to the professionals, the general public who were not conversant with the designing skills found the app more useful to express their ideas. The study guides urban authorities in their placemaking efforts by introducing a novel approach to effectively capture community ideas for creating inclusive public spaces. Full article