Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

By systematically analyzing the bottlenecks in current traditional Chinese medicine （TCM） efficacy evaluation， this study addresses the limitations of TCM efficacy assessment methods in terms of individualization， holism， and complexity representation. Drawing on the concepts and methodologies of evidence-based medicine and systems biology， this paper proposes a new evaluation path by integrating multidisciplinary technologies such as big data， artificial intelligence （AI）， omics techniques， and bioinformatics， and encompassing from foundational data， individualized evaluation， and mechanistic analysis to evidence translation. The path first integrates real-world data， multi-omics profiling， and dynamic monitoring via smart devices to construct a high-dimensional dynamic data foundation. Subsequently， leveraging this foundation， it combines digital twins， dynamic symptom networks， and reinforcement learning to develop a dynamic efficacy evaluation method based on individual self-reference， enabling a shift from group mean comparisons to individual potential outcome comparisons. Furthermore， adopting the systems biology paradigm， it employs dynamic omics monitoring and deep learning models to dissect the synergistic mechanisms of TCM compound prescriptions from network regulation， emergent effects， and dynamic evolution dimensions. Finally， it enhances real-world evidence strength through target trial emulation and causal inference， achieving model iteration via incremental learning. This path aims to advance efficacy evaluation from "point validation" to "systematic characterization" and from "outcome assessment" to "process mechanism elucidation，" providing methodological support for the modernization of TCM.

Taking Xiaochaihu Decoction as an example,the application differences of classical prescriptions in modern medical context and Chinese medicine practice are compared and analyzed from the aspects of clinical application scope,understanding of pre-scription connotation,dosage specification,dosage form and decoction method.Strategies to solve the differences in efficacy are pro-posed:integrating the wisdom of classical prescriptions and reshaping the framework of Chinese medicine diagnosis and treatment;transforming the results of modern pharmacology and exploring the principles of classical prescriptions;controlling drug quality stand-ards and exploring new uses and dosages of classical prescriptions;keeping pace with the times in Chinese medicine decoction and strengthening management and control to ensure efficacy.It is believed that combining the essence of Chinese medicine with modern technology can make the application of classical prescriptions maintain traditional characteristics while meeting modern clinical require-ments.This can not only improve the adaptability of classical prescriptions to modern complex diseases,but also provide a reference for the modernization of traditional medicine.

Taking Xiaochaihu Decoction as an example,the application differences of classical prescriptions in modern medical context and Chinese medicine practice are compared and analyzed from the aspects of clinical application scope,understanding of pre-scription connotation,dosage specification,dosage form and decoction method.Strategies to solve the differences in efficacy are pro-posed:integrating the wisdom of classical prescriptions and reshaping the framework of Chinese medicine diagnosis and treatment;transforming the results of modern pharmacology and exploring the principles of classical prescriptions;controlling drug quality stand-ards and exploring new uses and dosages of classical prescriptions;keeping pace with the times in Chinese medicine decoction and strengthening management and control to ensure efficacy.It is believed that combining the essence of Chinese medicine with modern technology can make the application of classical prescriptions maintain traditional characteristics while meeting modern clinical require-ments.This can not only improve the adaptability of classical prescriptions to modern complex diseases,but also provide a reference for the modernization of traditional medicine.

ObjectiveTo investigate the mechanism of Biejiajian Wan in the intervention of primary liver cancer based on long non-coding RNA SNHG5 （lncRNA SNHG5）/micro RNA-26a-5p （miRNA-26a-5p）/glycogen synthase kinase-3β （GSK-3β） signal axis. MethodDouble luciferase reporting assay was used to verify the targeted interaction between lncRNA SNHG5 and miRNA-26a-5p， miRNA-26a-5p， and GSK-3β in HepG2 cells. Nude-mouse transplanted tumor model of human HepG2 were established and randomly divided into model group， Biejiajian Wan low-dose group （0.5 g·kg^-1）， medium-dose group （1.0 g·kg^-1）， and high-dose group （2.0 g·kg^-1）， and sorafenib group （100 mg·kg^-1）， with 10 mice in each group. The mice were given intragastric administration of normal saline or drug for 28 days， and the tumor volume was measured at different time. Hematoxylin-eosin （HE） staining was used to observe the histological changes of tumors. The nucleic acid levels of lncRNA SNHG5， miRNA-26a-5p， GSK-3β， and β-catenin mPNA in tumor tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. The protein expression levels of GSK-3β and β-catenin in tumor tissue were detected by western blot. ResultCompared with the SNHG5-WT （wild type） + miRNA NC （negative control） group， the relative luciferase activities of the SNHG5-WT + miRNA-26a-5p mimic group were decreased （P<0.05）. Compared with the GSK-3β-WT + miRNA NC group， the relative luciferase activity of the GSK-3β-WT + miRNA-26a-5p mimic group was decreased （P<0.05）. Compared with the model group， the tumor volume of Biejiajian Wan low-dose， medium-dose， and high-dose groups was significantly decreased （P<0.05， P<0.01）. Compared with the model group， the cells in the tumor tissue of nude mice in each dose group of Biejiajian Wan were sparsely arranged with necrocytosis， which showed concentration-dependent changes. Compared with the model group， the expression levels of lncRNA SNHG5， GSK-3β， and β-catenin were decreased （P<0.05， P<0.01）， while the expression of miRNA-26a-5p was increased in each dose group of Biejiajian Wan （P<0.05， P<0.01）. Compared with the model group， the protein expression levels of GSK-3β and β-catenin were decreased in each dose group of Biejiajian Wan （P<0.05， P<0.01）. ConclusionBiejiajian Wan may affect the necrosis of liver cancer cells through lncRNA SNHG5/miRNA-26a-5p/GSK-3β signal axis and thus play an anti-tumor role. This research will provide more theoretical basis for the clinical application of Biejiajian Wan.

Children and adults differ significantly in physiology,biochemistry and immune function,which leads to sig-nificant differences in blood transfusion strategies between children and adults.To guide the clinical transfusion practice of pediatric patients and improve the prognosis of children,the National Health Commission organized the formulation and re-lease of the health industry standard Guideline for Pediatric Transfusion(WS/T 795-2022).This paper will briefly introduce some concepts that help understand of the Standard and the preparation process of the Standard,and explain and interpret the preparation of the"scope","general provisions"and"factors to consider"of the Standard,hoping to contribute to the understanding and implementation of the Standard.

OBJECTIVE To evaluate the comprehensive value of four first-line combination immunotherapy for unresectable hepatocellular carcinoma， and provide a reference for determining the optimal clinical treatment decision for unresectable hepatocellular carcinoma. METHODS R4.2 software was used for network meta-analysis to obtain the effect values of the efficacy and safety indicators of four combination therapies [atezolizumab combined with bevacizumab （AB）， sintilimab combined with bevacizumab biosimilars （SB）， camrelizumab combined with apatinib （CA）， durvalumab combined with tremelimumab （DT）]. Combined with the efficacy， safety and economic indicators， the categorical based evaluation technique （M-MACBETH） was used to establish the value tree. At the same time， the comprehensive value scores of four therapies were calculated， and sensitivity analysis was performed to evaluate the robustness. RESULTS In terms of prolonging median overall survival， the advantage order of the four therapies was ranked as SB， CA， AB and DT. In terms of extending median progression-free survival， the advantage order of the four therapies was CA， SB， AB and DT. In terms of safety， the order of advantages was DT， AB， SB and CA. In terms of economy， the order of advantages was CA， SB， AB and DT. The comprehensive scores of SB， CA， AB and DT were 67.11， 57.77， 52.53 and 42.59 points， respectively. The results of the sensitivity analysis showed that the ranking results of comprehensive value for four regimens were robust. CONCLUSIONS Among the four first-line immune combination therapies for unresectable hepatocellular carcinoma， SB is the optimal treatment regimen， followed by CA， AB and DT.

The amount of data generated by the human experience in medical cases of classic formulas is large and the research value is high， but how to extract valuable information from these massive data is an important problem of researches on classical formulas. It is concluded that there are many problems in the current study of human experience in classical formulas， such as large amount of data， uneven quality， weak extrapolation and clinical application， which seriously affected the evidence strength of human experience in classical formulas and the contribution to experience accumulation and theoretical support. Therefore， from the structural perspective of the research questions， this paper proposed the research ideas of human experience in medical cases of classic formulas： firstly， according to the characteristics of traditional Chinese medicine （TCM） cases， based on the PICO model， which refers parti-cipants （P）， intervention （I）， comparisons （C）， and outcomes （O）， a TCM medical record evaluation tool in line with the evidence-based concept was constructed to evaluate the quality of medical cases； secondly， constructing a standardized database of human experience in classical formulas and using data mining algorithms to explore the deep relationship hidden in human experience； finally， the clinical value evaluation is carried out to verify the effectiveness of the diagnosis and treatment rules of classical formulas to achieve clinical transformation.

By organizing and studying on the original works of LI Wenrong， this paper aimed to explore his theories and methods for treating liver diseases. LI Wenrong believes that the liver is easily prone to physiological disturbances， difficult to pacify， and can be compared to a “chariot” that moves horizontally and vertically， acting as a “general” for both civil and military affairs. Pathologically， liver diseases tend to spread to other organs， resulting in ever-changing pathological changes， often affecting emotional health. In terms of therapeutic methods， LI Wenrong proposes ten methods including draining fire to calm the liver， nourishing water to moisten wood， clearing metal to calm the liver， calming gallbladder and harmonizing liver， subduing yang with shell-drug， treating liver diseases by supplementing spleen， soothing the liver with sweetness， astringing the liver with sourness， relieving the liver with spiciness， and draining the liver with excess-fire. These methods have great guidance and reference value for contemporary clinical practice in traditional Chinese medicine.