Isolation, Identification, Phytochemical Characterization, and In Vitro Anti-Inflammatory Property of an Endophytic Trametes versicolor CL-1 Isolated from Rosa roxburghii.

This study explores the anti-inflammatory potential of an endophytic fungus, Trametes versicolor CL-1, isolated from the fruit tissues of Rosa roxburghii. Morphological and molecular analyses confirmed the identity of CL-1. An ethyl acetate extract (CL-E) from its fermentation broth was subjected to UPLC-HRMS and GNPS molecular networking. The analysis revealed a diverse array of secondary metabolites, including 11 terpenes, 7 flavonoids, 10 cinnamic acid derivatives, 6 oligopeptides, and 9 fatty acids, as verified by LC-MS/MS. Notably, CL-E exhibited significant in vitro anti-inflammatory activity in RAW264.7 cells. Furthermore,  molecular docking studies predicted favorable binding interactions of key compounds 1 within CL-E with the NLRP3 inflammasome (PDB ID: 6NPY). These findings suggest T. versicolor CL-1 as a promising source of natural anti-inflammatory agents and unveil R. roxburghii as a potential reservoir for discovering novel bioactive metabolites.

Combined Metabolite and Transcriptomic Profiling Unveil a Potential Gene Network Involved in the Triterpenoid Metabolism of Rose roxburghii.

Rose roxburghii, a horticulturally significant species within the Rosa genus of the Rosaceae family, is renowned for its abundance of secondary metabolites and ascorbate, earning it the title 'king of vitamin C'. Despite this recognition, the mechanisms underlying the biosynthesis and regulation of triterpenoid compounds in R. roxburghii remain largely unresolved. In this study, we conducted high-performance liquid chromatography profiling across various organs of R. roxburghii, including fruit, root, stem, and leaves, revealing distinct distributions of triterpenoid compounds among different plant parts. Notably, the fruit exhibited the highest total triterpenoid content, followed by root and stem, with leaf containing the lowest levels, with leaf containing the lowest levels. Transcriptomic analysis unveiled preferential expression of members from the cytochrome P450 (CYP) and glycosyltransferase (UGT) families, likely contributing to the higher accumulation of both ascorbate and triterpenoid compounds in the fruits of R. roxburghii compared to other tissues of R. roxburghii. Transcriptomic analysis unveiled a potential gene network implicated in the biosynthesis of both ascorbate and triterpenoid compounds in R. roxburghii. These findings not only deepen our understanding of the metabolic pathways in this species but also have implications for the design of functional foods enriched with ascorbate and triterpenoids in R. roxburghii.

Research on Non-Contact Monitoring System for Human Physiological Signal and Body Movement.

With the rapid increase in the development of miniaturized sensors and embedded devices for vital signs monitoring, personal physiological signal monitoring devices are becoming popular. However, physiological monitoring devices which are worn on the body normally affect the daily activities of people. This problem can be avoided by using a non-contact measuring device like the Doppler radar system, which is more convenient, is private compared to video monitoring, infrared monitoring and other non-contact methods. Additionally real-time physiological monitoring with the Doppler radar system can also obtain signal changes caused by motion changes. As a result, the Doppler radar system not only obtains the information of respiratory and cardiac signals, but also obtains information about body movement. The relevant RF technology could eliminate some interference from body motion with a small amplitude. However, the motion recognition method can also be used to classify related body motion signals. In this paper, a vital sign and body movement monitoring system worked at 2.4 GHz was proposed. It can measure various physiological signs of the human body in a non-contact manner. The accuracy of the non-contact physiological signal monitoring system was analyzed. First, the working distance of the system was tested. Then, the algorithm of mining collective motion signal was classified, and the accuracy was 88%, which could be further improved in the system. In addition, the mean absolute error values of heart rate and respiratory rate were 0.8 beats/min and 3.5 beats/min, respectively, and the reliability of the system was verified by comparing the respiratory waveforms with the contact equipment at different distances.