, a tropical seagrass, is known for its significant contribution to marine ecosystems and its potential health benefits due to bioactive compounds. This study aims to compare the carotenoid levels in using green extraction via ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) and to evaluate the biological properties of these extracts against oxidative stress, diabetes, and obesity through in silico and in vitro analyses. samples were collected from Manado City, Indonesia, and subjected to UAE and MAE. The extracts were analyzed using UHPLC-ESI-MS/MS to identify carotenoids, including β-carotene, lutein, lycopene, β-cryptoxanthin, and zeaxanthin. In silico analysis was conducted to predict the compounds' bioactivity, toxicity, and drug-likeness using WAY2DRUG PASS and molecular docking with CB-Dock2. The compounds C3, C4, and C7 demonstrated notable interactions, with key metabolic proteins and microRNAs, further validating their potential therapeutic benefits. In vitro assays evaluated antioxidant activities using DPPH and FRAP assays, antidiabetic properties through α-glucosidase and α-amylase inhibition, and antiobesity effects via lipase inhibition and MTT assay with 3T3-L1 cells. Results indicated that both UAE and MAE extracts exhibited significant antioxidant, antidiabetic, and antiobesity activities. MAE extracts showed higher carotenoid content and greater biological activity compared to UAE extracts. These findings suggest that , mainly when extracted using MAE, has promising potential as a source of natural bioactive compounds for developing marine-based antioxidant, antidiabetic, and antiobesity agents. This study supplements existing literature by providing insights into the efficient extraction methods and the therapeutic potential of carotenoids.
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http://dx.doi.org/10.3390/md22080365 | DOI Listing |
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
View Article and Find Full Text PDFHeliyon
January 2025
Department of Software Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Saudi Arabia.
The prediction of energy consumption in households is essential due to the reliance on electrical appliances for daily activities. Accurate assessment of energy demand is crucial for effective energy generation, preventing overloads and optimizing energy storage. Traditional techniques have limitations in accuracy and error rates, necessitating advancements in prediction techniques.
View Article and Find Full Text PDFSci Rep
January 2025
School of Electronics and Information Engineering, Wuyi University, Jiangmen, 529020, Guangdong, China.
Facial beauty prediction (FBP) is a leading area of research in artificial intelligence. Currently, there is a small amount of labeled data and a large amount of unlabeled data in the FBP database. The features extracted by the model based on supervised training are limited, resulting in low prediction accuracy.
View Article and Find Full Text PDFSci Rep
January 2025
College of Management and Economics, Tianjin University, Nankai District, Tianjin, 300072, China.
Accurate carbon accounting is essential for power generation enterprises to participate in carbon markets and implement carbon reduction strategies. However, due to excessive reliance on detailed energy data and manual calculations, carbon emission accounting in power generation enterprises suffers from low frequency, significant lag, and poor reliability. Some evidences suggest a strong correlation between internal carbon emissions and electricity consumption in power generation enterprises.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Biological Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
This study aimed to evaluate the potential of phytochemicals from two native UAE plant species, Arthrocnemum macrostachyum and Tamarix nilotica, as anti-cancer agents. The plant extracts were obtained using two methods, maceration, and microwave-assisted extraction (MAE), and were subsequently evaluated for their in vitro cytotoxicity against three cancer cell lines: breast (MDA-MB-231), colon (HCT-116), and lung (A-549). Results suggest that: 1) MAE is more efficient than maceration in recovering metabolites from plant biomass based on measurements of total phenolic content, radical scavenging activity, and bioactivity of extracts based on in vitro cytotoxicity.
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