This study explores the development of electrospun nanofibers incorporating bioactive compounds from (Ashwagandha) root extract, focusing on optimizing extraction conditions and nanofiber composition to maximize biological activity and application potential. Using the Design of Experiment (DoE) approach, optimal extraction parameters were identified as 80% methanol, 70 °C, and 60 min, yielding high levels of phenolic compounds and antioxidant activity. Methanol concentration emerged as the critical factor influencing phytochemical properties. Electrospinning technology was employed to produce nanofibers using polyvinylpyrrolidone (PVP) and hydroxypropyl-β-cyclodextrin (HPβCD) as carriers, ensuring encapsulation, stabilization, and an enhanced bioavailability of the active compounds. Nanofibers demonstrated a high surface-to-volume ratio, rapid dissolution, and significant mucoadhesive properties, making them suitable for oral mucosal applications. The optimal nanofiber composition was determined to be 2.5 mL extract, 25% PVP, and an extract-to-HPβCD ratio of 1:0.6. Statistical modeling confirmed that the electrospinning process did not compromise the antioxidant or anti-inflammatory properties of the extract, with extract content being the primary determinant of biological activity. These findings highlight the potential of integrating advanced extraction techniques with nanotechnology to develop innovative delivery systems for traditional herbal remedies. The developed nanofibers offer promising applications in pharmaceuticals, cosmetics, and functional foods, paving the way for a scalable and efficient utilization of Ashwagandha bioactives.
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http://dx.doi.org/10.3390/pharmaceutics17010061 | DOI Listing |
Eur Arch Otorhinolaryngol
January 2025
Faculty of Applied Sciences, Department of Accounting and Financial Management, Necmettin Erbakan University, Konya, Turkey.
Purpose: Vestibular neuritis (VN) is a common cause of vertigo with significant impact on patients' quality of life. This study aimed to analyze global research trends in VN using bibliometric methods to identify key themes, influential authors, institutions, and countries contributing to the field.
Methods: We conducted a comprehensive search of the Web of Science Core Collection database for publications related to VN from 1980 to 2024.
Sci Rep
January 2025
Faculty of Art and Science, Department of Chemistry, Yıldız Technical University, 34220, İstanbul, Türkiye.
In the present study, dispersive solid phase extraction - hydride generation integrated with micro-sampling gas-liquid separator - flame atomic absorption spectrometry was proposed to determine lead in lake water samples taken in the Horseshoe Island, Antarctica. In scope of this study, microwave assisted NiFeO nanoparticles were synthesized, and the characterization of nanoparticles were carried out by FT-IR, XRD and SEM. All influential parameters of dispersive solid phase extraction and hydride generation were optimized to enhance signal intensity belonging to the analyte.
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January 2025
School of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, People's Republic of China.
Accurate and rapid segmentation of key parts of frozen tuna, along with precise pose estimation, is crucial for automated processing. However, challenges such as size differences and indistinct features of tuna parts, as well as the complexity of determining fish poses in multi-fish scenarios, hinder this process. To address these issues, this paper introduces TunaVision, a vision model based on YOLOv8 designed for automated tuna processing.
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January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
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January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
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