Mahidol University's Institutional Repository
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Nutraceuticals and functional food from food and agro-industrial wastes
(2025-01-01) Taduru A.S.; Singhal P.; Kaushik G.; Chaudhery H.; Kalimuthu K.; Taduru A.S.; Mahidol University
Food, industrial, and agricultural wastes are of great value in the current world because of their effectiveness as natural sources of bioactive composites, which can further induce by-products that add value to life. Restoring bioactive composites from similar scribes to create functional/healthy nourishments is an effective method to exercise trash. Various investigations in the past have shown that agricultural waste can be developed by the processing industries and are productive in bioactive composites, similar to phenolic composites, organic acids, carotenoids, flavonoids, etc. The increasing demand for substituting artificial antioxidants and antimicrobial composites with real ones has prompted a search for these bioactive composites from industrial resources, notably fruit and vegetable processing waste. The agro-industrial products from varied food manufacturing diligence release a considerable amount of fruit and vegetable waste that causes deposits in the external tips. Several secondary metabolites, vitamins, and minerals have been extracted from colorful food waste. In the future, the prismatic curtain-raisers could give a contemporary approach to increasing the production of composites for use as nutraceuticals or as basics in designing functional foods. Hence, this study discusses their practical application in developing nutraceutical products, health benefits, bioprocess development, and the benefits of incorporating food waste products.
pWCP is a widely distributed and highly conserved Wolbachia plasmid in Culex pipiens and Culex quinquefasciatus mosquitoes worldwide
(2023-12-01) Ghousein A.; Tutagata J.; Schrieke H.; Etienne M.; Chaumeau V.; Boyer S.; Pages N.; Roiz D.; Eren A.M.; Cambray G.; Reveillaud J.; Ghousein A.; Mahidol University
Mosquitoes represent the most important pathogen vectors and are responsible for the spread of a wide variety of poorly treatable diseases. Wolbachia are obligate intracellular bacteria that are widely distributed among arthropods and collectively represents one of the most promising solutions for vector control. In particular, Wolbachia has been shown to limit the transmission of pathogens, and to dramatically affect the reproductive behavior of their host through its phage WO. While much research has focused on deciphering and exploring the biocontrol applications of these WO-related phenotypes, the extent and potential impact of the Wolbachia mobilome remain poorly appreciated. Notably, several Wolbachia plasmids, carrying WO-like genes and Insertion Sequences (IS), thus possibly interrelated to other genetic units of the endosymbiont, have been recently discovered. Here we investigated the diversity and biogeography of the first described plasmid of Wolbachia in Culex pipiens (pWCP) in several islands and continental countries around the world—including Cambodia, Guadeloupe, Martinique, Thailand, and Mexico—together with mosquito strains from colonies that evolved for 2 to 30 years in the laboratory. We used PCR and qPCR to determine the presence and copy number of pWCP in individual mosquitoes, and highly accurate Sanger sequencing to evaluate potential variations. Together with earlier observation, our results show that pWCP is omnipresent and strikingly conserved among Wolbachia populations within mosquitoes from distant geographies and environmental conditions. These data suggest a critical role for the plasmid in Wolbachia ecology and evolution, and the potential of a great tool for further genetic dissection and possible manipulation of this endosymbiont.
THE EFFECTIVENESS OF COLD BEVERAGES VERSUS ICE-SLURRY DRINKS ON THE ATHLETIC PERFORMANCE OF THAI FUTSAL PLAYERS USING K-MEANS CLUSTERING
(2025-01-01) Pariyavuth P.; Panurushthanon P.; Punthipayanon S.; Klabchom K.; Thongtha K.; Chottidao M.; Pochai N.; Pariyavuth P.; Mahidol University
Cooling interventions during futsal halftime breaks show substantial individual variability in physiological responses, yet standardized protocols fail to account for athlete-specific thermal stress susceptibility. This study employed This study used K-means clustering to compare the effectiveness of cold beverages versus ice slurry and to identify distinct physiological response phenotypes for personalized cooling strategy optimization. Ten competitive male futsal players (22.4 ± 2.1 years; 68.5 ± 8.2 kg) completed a randomized crossover design. Following the Futsal Intermittent Shuttle-Run Protocol (FIRP), participants consumed either ice slurry (-1°C) or cold sports beverages (4°C) at 7.5 g/kg body mass during 10-minute recovery. Futsal-specific reactive agility tests (RAG-D, RAG-T), blood lactate, heart rate, urine specific gravity, and perceived exertion were measured. K-means clustering analysis with silhouette validation identified response patterns. Three distinct physiological phenotypes emerged (silhouette coefficient = 0.67). Cluster 1 (High-Response, n=4): elevated blood lactate (>8.0 mmol/L), highest cardiovascular stress, superior ice-slurry response. Cluster 2 (Moderate-Response, n=3): balanced responses to both modalities. Cluster 3 (Low-Response, n=3): conservative responses with maintained performance, preferential ice-slurry benefits. Strong correlations existed between body mass and response magnitude (r = 0.78, p < 0.01). Unsupervised machine learning effectively discerned unique cooling response phenotypes, facilitating evidence-based customization of cooling therapies. This signifies a substantial progression in the accuracy of sports performance enhancement.
PRECISION HEALTH THROUGH WEARABLE TECHNOLOGY: K-MEANS CLUSTERING FOR CULTURALLY ADAPTED NCD PREVENTION
(2025-01-01) Pochai N.; Klabchom K.; Siriussawakul A.; Pariyavuth P.; Panurushthanon P.; Al-Umaree P.; Chottidao M.; Punthipayanon S.; Pochai N.; Mahidol University
Introduction: Non-communicable diseases (NCDs) represent a critical global health challenge, accounting for 71% of deaths worldwide, with disproportionate burden in underserved populations including religious communities. Thai Buddhist monks face exceptionally high NCD prevalence attributed to sedentary lifestyles, dietary constraints, and limited physical activity opportunities inherent to monastic practices. This study introduces a novel machine learning framework for culturally-adapted health monitoring, addressing the urgent need for scalable, technology-driven solutions in traditional religious communities globally. Methods: This cross-sectional study employed an innovative K-means clustering approach to analyze wearable device data from 28 Thai Buddhist monks over one month (November-December 2024). Polar Pacer Pro devices captured daily step counts, average heart rate (beats per minute), and energy expenditure (kilocalories). Following Min-Max normalization, unsupervised K-means clustering identified distinct physical activity phenotypes. Optimal cluster determination utilized the Elbow Method through Within-Cluster Sum of Squares (WCSS) analysis. This represents the first application of unsupervised machine learning for health pattern recognition in monastic populations, demonstrating methodological innovation in small-sample clustering validation for culturally-specific healthcare contexts. Results: K-means clustering successfully identified distinct activity profiles within the monastic population, revealing significant heterogeneity in physical activity patterns. The analysis differentiated monks into meaningful clusters based on step count (range: 700-18,650 daily steps), heart rate (50-87 bpm), and energy consumption (1,623-3,758 kcal) profiles. Cluster centroids demonstrated clear stratification: low-activity groups (1,079-3,763 steps daily) representing 39% of participants with sedentary behavior patterns, moderate-activity clusters (4,495-5,164 steps), and high-activity groups (9,381-12,664 steps) approaching recommended cardiovascular health guidelines. These quantitative classifications provide empirical foundations for precision health interventions tailored to individual risk profiles. Discussion: The research evaluates scalable digital health system that holds great potential for implementation in many religious and cultural groups globally. The clustering approach was able to identify actionable health phenotypes that inform targeted NCD prevention strategies that do not violate cultural restrictions. Low-activity clusters could be seen as the straightforward target of intervention, and the higher-activity cluster indicates that the promotion of physical activity practices is successful in the traditional approach. The methodology is a potentially effective method that is feasible in resource-restricted environments, about consumer-level wearable technology and open-source machine learning algorithms. Strategies of cultural adaptation, such as the application of Buddhist walking meditation and mindful movements in health promotion, serve as sustainable avenues of health promotion at the community level. This framework offers a replicable template related to health disparities in religious community members around the world (estimated 500+ million) and can lead to Sustainable Development Goal 3 (Good Health and Well-being) via innovative and culturally relevant digital health technologies. These results can guide policymaking based on evidence related to community health initiatives and illustrate how the precision health vision can empower traditional in the development of precision health to address modern NCDs in contemporary society.
Digital twins and cloud computing
(2025-01-01) Pathare P.B.; Patil H.; Nirmal N.; de Waal J.M.; Jagtap S.; Mahanti N.K.; Sharma P.; Prasath V.A.; Pathare P.B.; Mahidol University
Seafood products play a major role in ensuring global food security and are a valuable source of numerous minerals and micronutrients for the human diet. As seafood items decay quickly and their quality deteriorates over time, processing seafood has historically been difficult. The seafood sector is under growing pressure to improve operational efficiency, traceability, and sustainability. Advances in technology and shifting consumer demands are driving a digital transformation in the seafood business. Businesses that use digital tools and solutions are in a good position to increase productivity, boost sustainability, and spur market expansion. Technologies like digital twins and cloud computing present feasible solutions to these challenges. Cloud solutions enable real-time monitoring of intricate supply chains and environmental conditions by offering scalable infrastructure for data processing, analytics, and storage. Throughout the seafood value chain, from aquaculture farms to processing facilities and distribution networks, digital twins-virtual copies of physical assets and processes-allow for simulation, optimization, and predictive maintenance. The potential of combining cloud computing and digital twins to improve resource management, quality assurance, and seafood production is examined in this chapter. Data from sensors, Internet of Things devices, and other sources can be combined and examined using cloud-based platforms to produce dynamic digital twins that simulate important variables like fish growth, water quality, and processing efficiency. Improved traceability, decreased waste, and better decision-making are made possible by this integration, which eventually helps to make the seafood sector more resilient and sustainable.