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ObjectiveThis research aims to explore how Puerariae Lobatae Radix regulates sebaceous gland secretion using network pharmacology, and validate its effects on important targets through animal studies.MethodsThis study utilized UPLC-EQ-MS to analyze Puerariae Lobatae Radix extract and identify potential bioactive compounds. Predicted targets of these compounds were obtained from the Swiss Target Prediction database, while targets associated with sebaceous gland secretion were obtained from the GeneCards database. Common targets between the databases were identified and a protein-protein interaction (PPI) network was established using the STRING platform. The PPI network was further analyzed using Cytoscape software. Pathway enrichment analysis was performed using Reactome, and molecular docking experiments targeted pivotal pathway proteins. Animal experiments were then conducted to validate the regulatory effects of the primary active compounds of Puerariae Lobatae Radix on key pathway proteins.ResultsThis research identified 17 active compounds in Puerariae Lobatae Radix and 163 potential targets associated with the regulation of sebum secretion. Pathway enrichment analysis indicates that these targets may modulate lipid metabolism pathways through involvement in peroxisome proliferator-activated receptor α, SREB, steroid metabolism, and arachidonic acid metabolism pathways. Molecular docking analysis demonstrates that puerarin and daidzein show favorable binding interactions with key targets in these pathways. Animal experiments demonstrated that the administration of Puerariae Lobatae Radix resulted in a significant reduction in the area of sebaceous gland patches compared to the control group. Histological analysis revealed notable alterations in the structure of sebaceous glands, including reductions in size, thickness, and density. Furthermore, the expression levels of TG, DHT, and IL-6 were significantly decreased in the Puerariae Lobatae Radix group (p < 0.05), and immunoblotting indicated a significant decrease in the expression of PPARG and ACC1 (p < 0.05).ConclusionThis study demonstrates that Puerariae Lobatae Radix can regulate skin lipid metabolism by targeting multiple pathways. The primary mechanism involves inhibiting sebaceous gland growth and reducing TG secretion by modulating the expression of PPARG and ACC1. Puerarin and Daidzein are identified as key bioactive compounds responsible for this regulatory effect. These findings highlight the therapeutic potential of Puerariae Lobatae Radix in addressing sebaceous gland-related conditions.

Password-based authentication has been widely used as the primary authentication mechanism.However, occasional large-scale password leaks have highlighted the vulnerability of passwords to risks such as guessing or theft.In recent years, research on password analysis using natural language processing techniques has progressed, treating passwords as a special form of natural language.Nevertheless, limited studies have investigated the impact of password text segmentation granularity on the effectiveness of password analysis with large language models.A multi-granularity password-analyzing framework was proposed based on a large language model, which follows the pre-training paradigm and autonomously learns prior knowledge of password distribution from large unlabelled datasets.The framework comprised three modules: the synchronization network, backbone network, and tail network.The synchronization network module implemented char-level, template-level, and chunk-level password segmentation, extracting knowledge on character distribution, structure, word chunk composition, and other password features.The backbone network module constructed a generic password model to learn the rules governing password composition.The tail network module generated candidate passwords for guessing and analyzing target databases.Experimental evaluations were conducted on eight password databases including Tianya and Twitter, analyzing and summarizing the effectiveness of the proposed framework under different language environments and word segmentation granularities.The results indicate that in Chinese user scenarios, the performance of the password-analyzing framework based on char-level and chunk-level segmentation is comparable, and significantly superior to the framework based on template-level segmentation.In English user scenarios, the framework based on chunk-level segmentation demonstrates the best password-analyzing performance.

With the new concept of computing force network being put forward, how to manage, cooperate and deploy after the integration of computing power and network has become an urgent problem for telecom operators. To better solve the problems of unified management, perceptual dispatch, and collaborative arrangement of multi-dimensional resources such as network, computing, and storage, we study from the direction of computing force network management and control. Then we investigate the overall architecture design of computing force network management and control system, the core capabilities, and the evolution of underlying network technology. Based on the principle of "the network changes with the computing force, and the network strengthens the computing force", the collaborative mode of "horizontal connection and vertical dispatch" of the computing force network is formed with the help of the management and control system capabilities. Eventually, we believe it will effectively support the development demands of computing force network business and help the development of the national "Eastern Data and Western Computing" project.