Tea polysaccharides (TPS) is receiving global concern in past years due to their therapeutic effects in many diseases such as obesity and diabetes. Many publications imply that the unique physicochemical properties and bioactivities of TPS are prerequisites for its use as a biofilm, drug carrier and emulsifier. Despite numerous healthy benefits, studies on the in-deep structure-activity relationship of TPS still not well explored and explained yet. The main reasons for the research limitation are attributed mainly to the unbreakable advanced structural research technology and the formation of TPS conjugates. The present review also summarizes some similar parameters in primary structure of TPS with better bioactivities, discusses the relationships between their physicochemical properties and bioactivities, and suggests that function-specific TPS would be obtained in the future if the links between preparation methods, physicochemical properties and bioactivities of TPS could be well understood and established.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.foodchem.2023.137223 | DOI Listing |
Environ Sci Pollut Res Int
December 2024
Office Français de la Biodiversité (OFB), 5 Allée Félix Nadar, 94300, Vincennes, France.
This study offers an unprecedented valuation of the French surface waters WFD chemical monitoring dataset, covering 101 substances (metals, industrial and persistent organic pollutants (POPs), plant protection product (PPP) and biocides active substances, combustion residues) measured monthly on 4000 sites of the 6 main continental river basins, during 12 years (2009-2020). The concentration data were first made comparable through an original process removing the bias induced by the space-and-time heterogeneity of the monitoring labs performance, to gather a reference workable set of monthly contamination indicators. These were then used to display the substances' seasonal and interannual timeseries, revealing, e.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
December 2024
University of Minnesota Twin Cities College of Science and Engineering, Chemical Engineering and Materials Science, 421 Washington Ave SE, 55455, Minneapolis, UNITED STATES OF AMERICA.
We report the development of a small molecule-based barcoding platform for pooled screening of nanoparticle delivery. Using aryl halide-based tags (halocodes), we achieve high-sensitivity detection via gas chromatography coupled with mass spectrometry or electron capture. This enables barcoding and tracking of nanoparticles with minimal halocode concentrations and without altering their physicochemical properties.
View Article and Find Full Text PDFACS Nanosci Au
December 2024
Department of Physics, Malaviya National Institute of Technology Jaipur, Jaipur 302017, Rajasthan, India.
The development of supercapacitors is pivotal for sustainable energy storage solutions, necessitating the advancement of innovative electrode materials to supplant fossil-fuel-based energy sources. Zinc oxide (ZnO) is widely studied for use in supercapacitor electrodes because of its beneficial physicochemical properties, including excellent chemical and thermal stability, semiconducting characteristics, low cost, and environmentally friendly nature. In this study, ZnO nanorods were synthesized using a simple hydrothermal method and then combined with various Ni-based layered double hydroxides (LDHs) [NiM'-LDHs (M' = Mn, Co, and Fe)] to improve the electrochemical performance of the ZnO nanorods.
View Article and Find Full Text PDFACS Omega
December 2024
Grupo de Química Teórica e Estrutural de Anápolis, Universidade Estadual de Goiás, 75132-903 Anápolis, GO, Brasil.
Biodiesel offers an alternative to fossil fuels, primarily because it is derived from renewable sources, with the potential to mitigate issues such as pollutant and greenhouse gas emissions, resource scarcity, and the market instability of petroleum derivatives. However, lower durability and stability pose challenges. To address this, researchers worldwide are exploring technologies that employ specific molecules to slow down biodiesel's oxidation process, thereby preserving its key physicochemical properties.
View Article and Find Full Text PDFMachine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we introduce GSnet, a graph neural network (GNN) trained to predict physicochemical and geometric properties including solvation free energies, diffusion constants, and hydrodynamic radii, based on three-dimensional protein structures. By leveraging transfer learning, pre-trained GSnet embeddings were adapted to predict solvent-accessible surface area (SASA) and residue-specific p values, achieving high accuracy and generalizability.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!