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Introduction: Acupuncture and tuina, acknowledged as ancient and highly efficacious therapeutic modalities within the domain of Traditional Chinese Medicine (TCM), have provided pragmatic treatment pathways for numerous patients. To address the problems of ambiguity in the concept of Traditional Chinese Medicine (TCM) acupuncture and tuina treatment protocols, the lack of accurate quantitative assessment of treatment protocols, and the diversity of TCM systems, we have established a map-filling technique for modern literature to achieve personalized medical recommendations. Methods: (1) Extensive acupuncture and tuina data were collected, analyzed, and processed to establish a concise TCM domain knowledge base. (2)A template-free Chinese text NER joint training method (TemplateFC) was proposed, which enhances the EntLM model with BiLSTM and CRF layers. Appropriate rules were set for ERE. (3) A comprehensive knowledge graph comprising 10,346 entities and 40,919 relationships was constructed based on modern literature. Results: A robust TCM KG with a wide range of entities and relationships was created. The template-free joint training approach significantly improved NER accuracy, especially in Chinese text, addressing issues related to entity identification and tokenization differences. The KG provided valuable insights into acupuncture and tuina, facilitating efficient information retrieval and personalized treatment recommendations. Discussion: The integration of KGs in TCM research is essential for advancing diagnostics and interventions. Challenges in NER and ERE were effectively tackled using hybrid approaches and innovative techniques. The comprehensive TCM KG our built contributes to bridging the gap in TCM knowledge and serves as a valuable resource for specialists and non-specialists alike.
RESUMEN
Oxalate is commonly employed as adjuvant of pesticide agent, causing renal injury of human even in trace residues. Despite the great achievements of the existing point-of-care testing (POCT) technology, accurate on-site screening of oxalate remains a tricky issue. To this aim, we proposed a "lab in a tube" platform which integrated portable hydrogel kit with smartphone for real-time monitoring of oxalate to achieve quantitatively precise analysis. In this work, a stimuli-responsive hydrogel-based kit was constructed via embedding manganese dioxide (MnO2) nanosheets into sodium alginate hydrogel system. Based on the intrinsic oxidase-like activity, MnO2 nanosheets-based nanozyme triggered color reaction by introducing a common sensing probe 3,3',5,5'-tetramethylbenzidine. Meanwhile, the presence of oxalate would decompose MnO2 nanosheets, inducing the decrease of nanozyme activity, which resulted in the color response of portable kit. Coupling with ImageJ software, the image information of kit captured via smartphone could be transduced into the hue intensity, which provided a directly quantitative tool to detect oxalate with a detection limit of 8.0 µmol L-1. This portable smartphone biosensor was successfully applied for screening urine sample within 10 min for high-throughput analysis (twelve samples) without the need for any advanced analytical instruments. Based on the merits of simple operation, cost-efficiency, and good selectivity, the availability of the miniaturized biosensor platform for POCT will achieve the requirements of routine screening and disease prevention.