VNUHCM Journal of Natural Sciences

Chemical constituents from aerial parts of Mussaenda saigonensis

2023-11-12T16:38:17+07:00

The genus Mussaenda, belonging to the family Rubiaceae, comprising approximately 160 species, widely distributed in tropical and subtropical regions including Africa, Asia and Southeast Asia. 27 species were found in Viet Nam and several of them are used in folk medicine. An extensive survey of literature on phytochemicals and biological activities of Mussaenda indicated that most of the studies were on M. pubescens, M. macrophylla, M. frondosa, M. hirsutissima, M. arcuata. There are no reports on the chemical and biological data of the Mussaenda saigonensis. This paper reported the results of the isolation of some compounds from aerial parts of M. saigonensis. The dried powder of M. saigonensis aerial parts was exhaustively extracted with ethanol at room temperature to give the crude extract after evaporation of the solvent. This extract was applied to liquid‒liquid partition procedure and successively afford different polar extracts. Compound isolation was performed using column chromatography on silica gel. Chemical structures were elucidated by 1D, 2D-NMR, MS spectra and compared with the literature published data. Six compounds were isolated, including two triterpenoids, 2,3-dihydroxyurs-12-en-28-oic acid (1), 3,23-dihydroxyurs-12-en-28-oic acid (2), two phenolics, coumaric acid (3), caffeic acid (4) and two anthraquinones, aloe-emodin (5) and 11-O--rhamnopyranosylaloe-emodin (6). All compounds were the first reported for Mussaenda saigonensis.

A syntax‒aware deep‒learning model for biomedical semantic role labelling

2023-11-19T04:25:32+07:00

A deep learning model for biomedical semantic role labeling was build. Semantic role labeling is a useful task that enables the computer to comprehend the key facts expressed in each sentence, and is a necessary first step in the resolution of several other semantic-related tasks, such as event extraction, entity extraction, and Q-A systems... Semantic role labeling is a domain-dependent task. In the biomedical field, semantics are transmitted via more intricate grammatical structures and dependencies in addition to being built on a predicate argument frameset that differs greatly from that of the general domain. To effectively account for these unique characteristics, three types of information were integrated into this deep learning model: Context knowledge obtained from a pre-trained language model trained on a substantial corpus of biomedical texts, dependencies derived from the dependency parse trees and sentence structure obtained from constituency parse trees. To handle grammatical information that is naturally represented as graphs, the Graph Attention Network which is well-known for its remarkable graph learning capabilities, was used. To further boost the model effectiveness, predicate indicator embedding was additionally included in the proposed model. According to experimental findings, the two above-indicated forms of syntactic information along with the predicate indicator embedding, could boost F1 by up to 20%.

Electrochemical sensor for detection of uric acid using screen-printed electrodes modified with NiO/PANI-Graphene

2023-11-19T09:03:18+07:00

Uric acid (UA) is a product of the catabolism of purine bases (adenine and guanidine) of nucleic acids that occurs naturally in the human body. The analysis of UA plays an important role in diagnosing and treating diseases such as gout, kidney stones, diabetes, heart disease, and Lesch-Nyhan syndrome. UA is analysed in the laboratory by the enzymatic colorimetric method with a time consuming of approximately one hour. Currently, electrochemical sensors are considered as a potential approach in the rapid quantification of UA due to the advantages of rapid analysis, low cost, few samples required for analysis, compact design and easy to use and do not require highly skilled technicians like traditional analytical methods. In this study, a commercial printed electrode (SPE) was surface-modified with a polyaniline-graphene (PANI-Graphene) composite coating and functionalize the surface of a PANI-Graphene film with a NiO electrochemical catalyst by cyclic voltammetry (CV) method. The fabricated electrode (designated NiO/PANI-Graphene/SPE) was used for UA analysis in a simulated human fluid medium (PBS, pH 7.4). The results show that the NiO/PANI-Graphene/SPE sensor electrode has good electrocatalytic activity for the oxidation of UA in the potential range of 0.3 to 0.5 V. Characteristically, the sensor has a wide linear range in the concentration range of 10 to 1750 μM with a high sensitivity of 29.5 μA mM1 cm2 and a low detection limit of 5.00 μM (S/N = 3). The NiO/PANI-Graphene/SPE sensor electrode has potential applications in the development of non-enzymatic electrochemical sensors for the rapid quantification of UA content in human body fluids.

Conversion of fructose to 5-hydroxymethylfurfural using 1,4-bis(4-sulfobutyl)-DABCO-1,4-diium tetrachloroaluminate ionic liquid in [CholineCl][Citric acid] deep eutectic solvent

2023-11-19T09:39:00+07:00

In recent years, there has been a significant interest from both domestic and international researchers in ionic liquids as they are recognized as environmentally friendly solvents and catalysts. From 5-hydroxymethylfurfural (HMF), a substrate derived from carbohydrate, various important compounds particularly the 2,5-dimethylfuran can be synthesized because it could be used as a biofuel and valuable substance. Furan derivatives such as 5-alkoxymethylfurfural, 2,5-furandicarboxylic acid, 5-hydroxymethylfuroic acid, bis-hydroxymethylfuran and 2,5-dimethylfuran have significant applications in the fields of fuel and polymers. This paper presented the preparation of 8 ionic liquids containing Brønsted acid and Lewis acid site, intending to utilize them as catalysts for converting carbohydrates into 5-hydroxymethylfurfural (HMF). Several factors affecting the performance of HMF were investigated, including the type and catalyst loading, temperature, solvent, and reused. The results showed that 1,4-bis(4-sulfobutyl)-DABCO-1,4-diium tetrachloroaluminate (IL1) exhibited potential as a catalyst for the synthesis of HMF from fructose. This reaction was conducted at a temperature of 100℃ for 5 min with the yield of approximately 60% when using [CholineCl][Citric acid] deep eutectic solvent. This catalyst, IL1/[CholineCl][Citric acid], was successfully recovered and reused for four times. This demonstrated the efficacy of various ionic liquids as catalysts for the synthesis of HMF from fructose. Further study on this catalyst is needed for the application in the producing fuel precursors derived from carbohydrates on an larger scale.