Institute of Scientific and Technical Information of China

This research aimed to study changes in the diversity of the soil bacterial community in a jujube forest with different years of abandonment. To this end, we took the mountain jujube forest with different abandoned years (1 a, 3 a, 6a and 20 a) in the Qijiashan jujube experimental demonstration base in Yanchuan County as the research object; we used Illumina Miseq high-throughput sequencing technology to analyze the changes in the soil bacterial community structure and reveal the key environmental drivers of bacterial community variation in the abandoned jujube forest in the study area. The results showed the following findings: (1) Phylum Actinomycetota (34%), Proteobacteria (29%), and Acidobacteriota (13%) were the dominant phyla of the soil bacterial community in the abandoned jujube forest. (2) Abandonment altered the composition of soil bacteria at the OTU level in jujube plantations. (3) There are differences in the soil bacterial community structure across different periods of abandonment in the jujube forest. (4) Soil water content is the main factor affecting the bacterial community structure of the abandoned jujube forest. There are differences in the soil water content of abandoned woodlands, which affects the community structure of soil microorganisms.

Stroke is a leading cause of death and disability worldwide. Despite the extensive use of traditional Chinese medicine (TCM) formulas in stroke treatment, systematic analyses of their multi-drug synergy and compatibility patterns remain scarce. This study leverages knowledge graph technology to integrate multi-source TCM formula data and constructs a knowledge graph for stroke-related TCM prescriptions. By combining frequency analysis, cluster analysis, and association rule mining, the study systematically uncovers medication patterns. A total of 1,403 validated formulas were included, identifying nine high-frequency herbs (frequency ≥ 200), such as Saposhnikoviae Radix and Glycyrrhizae Radix. These were categorized into four synergistic clusters. Five strong association rules were identified (e.g., “Ligustici Rhizoma and Almond → Ephedrae Herba” and “Scutellaria Baicalensis and Saposhnikoviae Radix → Glycyrrhizae Radix”). The utility of the knowledge graph in multidimensional retrieval and intelligent reasoning was validated. This study provides data support and a methodological paradigm for the standardized application and modernization of TCM in stroke treatment.

The purpose of this paper is to construct ontology based on ‘Compendium of Materia Medica’ and to explore the knowledge organization, representation and mining methods of ancient Chinese medicine books. The classification system of ‘Compendium of Materia Medica’ was introduced, including the three-level structure and classification basis of department, class and species, which provided the basis of class and attribute definition for ontology construction. The concept category extraction method is described, and the categories such as origin and release are extracted according to the drug description structure. The ontology construction adopts the Stanford seven-step method, and the ontology visualization is displayed. The research results can be applied to clinical diagnosis and treatment to assist doctors in obtaining drug information.