AIM:To prepare a complex of hyaluronic acid (HA) and phospholipids (PL), and study the improvement effect of PL on the oral absorption of HA. METHODS:The complex of HA-PL (named Haplex) was prepared by film dispersion and sonication method, its physico-chemical properties were identified by infrared spectra and differential scanning calorimetry (DSC). The oral absorption of Haplex was studied. Thirty-two healthy rats were divided into 4 groups randomly: (1) a normal saline (NS) control group; (2) an HA group; (3) a mixture group and (4) a Haplex group. After intragastric administration, the concentration of HA in serum was determined. RESULTS:The physico-chemical properties of Haplex were different from HA or PL or their mixture. After Haplex was administered to rats orally, the serum concentration of HA was increased when compared with the mixture or HA control groups from 4 h to 10 h (P < 0.05). The ∆AUC0-12 h of Haplex was also greater than that of the other three groups (P < 0.05). CONCLUSION:The method of film dispersion and sonication can prepare HA and PL complex, and PL can enhance the oral absorption of exogenous HA.© 2007 The WJG Press. All rights reserved.Key words: Hyaluronic acid; Phospholipids; Complex; Oral absorption; Infrared spectrum; Thermochemistry H u a n g S L , L i n g P X , Z h a n g T M . O ra l a b s o r p t i o n o f hyaluronic acid and phospholipids complexes in rat. World J Gastroenterol 2007; 13(6): 945-949
In order to understand the hydration effect of hyaluronic acid (HA) in aqueous solution, near-infrared (NIR) spectroscopy was used to investigate the HA aqueous solutions at different concentrations and temperature. As HA concentration was raised, there was a nonlinear change in absorption value in the first overtone region of OH, indicating the changes of hydration water. A reconstructed spectrum based on principal component analysis (PCA) was established and analyzed with the concept of aquaphotomics. The results showed that HA acted as a structure maker to make water molecules arranged in order. Water species with two hydrogen bonds (S 2 ) and three hydrogen bonds (S 3 ) showed the decrease at low concentration range of 0-40 mg/mL, but increased at higher concentration, indicating the difference in water species at different HA concentration. Meanwhile, HA had the ability to improve the thermal stability of water structure, suggesting a potential bio-protective function. this study provides a unique perspective on the molecular interactions between HA and water molecules, which is helpful for understanding the role of HA in life process and may serve as the basis for HA applications.Hyaluronic acid (HA) is a natural polysaccharide and one of the main component of the extracellular matrix 1 . It is widely distributed in various tissues and organs of animals as well as the capsules of some bacteria, and plays a significant role in life process 1 . Due to its high water retaining capacity, biocompatibility and non-immunogenicity, HA is an attractive material for various cosmetic, food and medical applications 2-4 .It is known that the structure and morphology of polysaccharides are strongly influenced by water molecules via controlling their conformations, various forms of aggregation, thermal properties and kinetics 5,6 . In this respect, the knowledge of the interaction between water and polysaccharide and the hydrated structure is of high importance for understanding its performance in the application. Studies on HA hydration have been reported by using various experimental techniques, including nuclear magnetic resonance (NMR) 7 , viscometry 8 , ultrasonic and densitometry analyses 9 , thermal analysis 10,11 , spectroscopic techniques 12-14 , and by means of computer simulations 15 . A complex relationship between HA and water molecules was partly discovered that the macroscopic properties of HA are significantly dependent on its degree of hydration and the function of HA relies on the hydration capacity 4,16-18 .Analysis of the hydration water in aqueous solution is challenging, and the structural changes in water induced by HA are yet to be fully understood. Near-infrared (NIR) spectroscopy, as a powerful analytical method, has unique advantages in studies of molecular structure and interaction [19][20][21][22] . It mainly reflects the overtones and combination modes of functional groups containing hydrogen atoms, such as CH, OH and NH, which play a significant role in chemical bonding and other chemical ph...
Abstractd-Glucaric acid (GA) is a value-added chemical produced from biomass, and has potential applications as a versatile platform chemical, food additive, metal sequestering agent, and therapeutic agent. Marketed GA is currently produced chemically, but increasing demand is driving the search for eco-friendlier and more efficient production approaches. Cell-based production of GA represents an alternative strategy for GA production. A series of synthetic pathways for GA have been ported into Escherichia coli, Saccharomyces cerevisiae and Pichia pastoris, respectively, and these engineered cells show the ability to synthesize GA de novo. Optimization of the GA metabolic pathways in host cells has leapt forward, and the titer and yield have increased rapidly. Meanwhile, cell-free multi-enzyme catalysis, in which the desired pathway is constructed in vitro from enzymes and cofactors involved in GA biosynthesis, has also realized efficient GA bioconversion. This review presents an overview of studies of the development of cell-based GA production, followed by a brief discussion of potential applications of biosensors that respond to GA in these biosynthesis routes.
Confusing low-molecular-weight hyaluronic acid (LMWHA) from acid degradation and enzymatic hydrolysis (named LMWHA–A and LMWHA–E, respectively) will lead to health hazards and commercial risks. The purpose of this work is to analyze the structural differences between LMWHA–A and LMWHA–E, and then achieve a fast and accurate classification based on near-infrared (NIR) spectroscopy and machine learning. First, we combined nuclear magnetic resonance (NMR), Fourier transform infrared (FTIR) spectroscopy, two-dimensional correlated NIR spectroscopy (2DCOS), and aquaphotomics to analyze the structural differences between LMWHA–A and LMWHA–E. Second, we compared the dimensionality reduction methods including principal component analysis (PCA), kernel PCA (KPCA), and t-distributed stochastic neighbor embedding (t-SNE). Finally, the differences in classification effect of traditional machine learning methods including partial least squares–discriminant analysis (PLS-DA), support vector classification (SVC), and random forest (RF) as well as deep learning methods including one-dimensional convolutional neural network (1D-CNN) and long short-term memory (LSTM) were compared. The results showed that genetic algorithm (GA)–SVC and RF were the best performers in traditional machine learning, but their highest accuracy in the test dataset was 90%, while the accuracy of 1D-CNN and LSTM models in the training dataset and test dataset classification was 100%. The results of this study show that compared with traditional machine learning, the deep learning models were better for the classification of LMWHA–A and LMWHA–E. Our research provides a new methodological reference for the rapid and accurate classification of biological macromolecules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.