ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

ObjectiveThis study aims to elucidate the potential mechanism of Zuojinwan in improving liver fibrosis through hepatic tissue metabolomics analysis. MethodsTwenty-four mice were randomly allocated into normal group， model group ， positive drug group （silymarin， 100 mg·kg^-1）， and Zuojinwan group （Zuojinwan solution， 2.5 g·kg^-1）， with per group six mice. Liver fibrosis model was induced via intraperitoneal injection of olive oil solution with 10% carbon tetrachloride （CCl₄） （0.5 μL·g^-1， three times weekly for 8 weeks） in all groups except the normal group. During the final 4 weeks， the silymarin group received silymarin （100 mg·kg^-1） by gavage thrice weekly， while the Zuojinwan group was administered Zuojinwan solution （2.5 g·kg^-1） under the same regimen. After the last administration， the levels of liver fibrosis indicators and liver injury markers in serum were detected. The pathological morphological changes of the liver tissues were observed. The levels of liver fibrosis markers α-smooth muscle actin （α-SMA） and Collagen Ⅰ（ColⅠ） were detected. Metabolomics was analyzed on mice's liver tissues. The mice's serum was collected for metabolomics analysis. ResultsCompared with the model group， Zuojinwan significantly improved indicators related to liver fibrosis and liver injury. Compared with the normal group， the model group showed significantly elevated levels of fibrosis markers such as laminin （LN）， hyaluronic acid （HA）， procollagen typeⅢ （PC-Ⅲ）， and type Ⅳ Collagen （Ⅳ-C）， while liver injury indicators such as alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， alkaline phosphatase （ALP）， lactate dehydrogenase （LDH）， and total bilirubin （TBIL）， exhibited a marked upward trend （P<0.05）. Compared with the model group， the silymarin group showed a significant decrease in the aforementioned indicators （P<0.05）. Notably， compared with the model group， the Zuojinwan group exhibited a significant reduction in all these indicators （P<0.05）， with efficacy comparable to that of the silymarin group. Zuojinwan reduced mRNA and protein levels of α-SMA and ColⅠ in the liver tissue. Metabolomics results revealed that compared with the model group， Zuojiinwan significantly reduced levels of glucose metabolism-related metabolites such as D-fructose 1，6-bisphosphate （FBP）， nicotinamide adenine dinucleotide phosphate （NADPH）， sodium beta-D-fructose 6-phosphate （F6P）， dihydroxyacetone phosphate （DHAP）， fumaric acid， and D-glucose 6-phosphate （G6P） （P<0.05）. Serum enzyme-linked immunosorbent assay （ELISA） was used to detect glucose metabolism indicators and further validate the regulatory effect of Zuojinwan on glucose metabolism. ConclusionThese results suggest that Zuojinwan may improve liver fibrosis by regulating the dysregulated levels of glucose metabolism during the progression of liver fibrosis.

At present， the systematic excavation of the clinical experience and academic thought of the Sichuan school of Chinese medicine vis-à-vis its dominant disease entities remains fragmentary， and replicable paradigms are scarce. Confronted with empirical fragmentation， data heterogeneity and decision-making subjectivity， the standardised distillation， inheritance and clinical translation of these distinctive experiences has become a critical bottleneck constraining the development of the Sichuan school. The integration of artificial-intelligence technologies in data processing， pattern recognition and intelligent decision-making has rendered deep mining of traditional Chinese medicine（TCM） clinical knowledge and patterns imperative. Constructing an intelligent modern TCM diagnostic-therapeutic-evaluative system is now the obligatory route for inheritance and innovation in Chinese medicine， and simultaneously provides a technological breakthrough for intelligent decision paradigms in the dominant diseases of the Sichuan school. Accordingly， this study adopts the regional academic school as its point of entry， focuses on the dominant diseases of the Sichuan school， and proposes an innovative pathway of "four-dimensional data-multi-modal fusion-multi-agent decision-making". Specifically， four data dimensions are defined and instantiated： （Ⅰ） knowledge from classical medical literature and historical case records. （Ⅱ） objective four-diagnosis phenotypic data. （Ⅲ） master physicians' prescribing regularities. （Ⅳ） characteristic mechanisms of renowned formulae. Leveraging multi-modal data fusion and generative artificial intelligence， the entire causal chain of Famous Physicians and Renowned Formulas is explicated to reconstruct the diagnostic-therapeutic cognitive logic of the regional school. Finally， a multi-agent collective-decision model is established and refined for the dominant diseases of the Sichuan school， capable of generating precise， individualised treatment regimens and thereby advancing an intelligent diagnostic-therapeutic paradigm that delivers more efficient and accurate clinical decision support.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

According to traditional Chinese medicine （TCM） theory， impaired spleen transportation function disrupts nutrient distribution， causing metabolic accumulation of lipids that transform into pathogenic phlegm-dampness. These pathological factors disseminate through the San Jiao and obstruct meridian pathways， ultimately forming the pathogenesis described as "all disorders involve phlegm". Phlegm and dampness share common pathogenic origins but manifest distinct clinical manifestations. Dampness， as the precursor， may congeal into phlegm， while existing phlegm accumulation can further exacerbate dampness stagnation， thereby establishing a self-perpetuating pathological cycle. Modern medical research has confirmed that the essence of "phlegm-dampness" syndrome is closely associated with energy metabolism disorders， serving as a common pathological basis for metabolic syndrome， type 2 diabetes mellitus， atherosclerosis， and other major chronic diseases. As a crucial vehicle for medical experimental research， disease-syndrome combination animal models serve as an indispensable means to advance the modernization of TCM. Currently， based on classical theories such as "rich and greasy foods produce phlegm" and "physical coldness combined with cold consumption causes external pathogens to invade the skin and hair， thereby generating internal dampness"， researchers primarily employ two paradigms to construct animal models of phlegm-turbidity， dampness obstruction， and phlegm-dampness syndromes： the first involves simulating TCM etiological factors （through methods like dietary irregularities， imblanace between work and rest， and combined internal-external dampness exposure）， while the second combines disease with syndrome differentiation （inducing pathological changes through physical， chemical， or biological interventions）. Through comprehensive evaluation incorporating macroscopic observation and microscopic index detection， model animals undergo systematic biological and pathological assessment， with further syndrome type verification achieved via the "prescription-based syndrome detection" approach. However， existing models still exhibit significant deficiencies in both the standardization of modeling methodologies and the systematization of evaluation criteria. This paper reviews the strategies for constructing "phlegm-dampness" syndrome animal models and their corresponding evaluation indices， focusing on the pathological correlations among different modeling approaches. The aim is to provide methodological guidance for research on TCM syndromes related to "phlegm-dampness" syndrome and to support the development of TCM therapies for resolving phlegm and eliminating dampness. This study not only contributes to advancing the standardization of TCM syndrome research but also provides crucial technical support for the modernization of TCM.

The chronicity of infectious diseases is an important field in the collaborative research of traditional Chinese and Western medicine. The warm disease theory of pathogen invading nutrient and blood aspects in traditional Chinese medicine （TCM） takes the struggle between healthy Qi and pathogenic Qi and cementation of Yin as the core pathogenesis， providing a unique theoretical framework for explaining the common pathology of infectious chronic diseases. This theory originated from Yin-Yang interaction in the Internal Classic and was enriched with WU Youke's theory of intruding pathogen interacting and lingering in blood vessels and YE Tianshi's theory of long-term illness entering collaterals. Combining the theory with modern medical knowledge， our team has condensed the dynamic pathogenesis model of deficiency （nutrient and blood aspects） and excess （pathogen） interacting in the blood collaterals of Yin aspect， the core feature of which is the four-dimensional interactions of cause （pathogen characteristics）， location （three Yin locations of diseases）， nature （deficiency and excess）， and potential （transmission trend）. The common pathology of infectious chronic diseases is reflected in interactions. That is， the interactions between nutrient and blood deficiency （immune exhaustion and metabolic disorder） and pathogen excess （pathogen persistence and fibrous hyperplasia） in the liver collaterals （Jueyin）， kidney collaterals （Shaoyin）， lung collaterals （Taiyin） and other blood collaterals of Yin aspect form the pathological damage characterized by immune inflammatory response-continuous tissue damage with excessive repair. Taking the inheritance and innovative development of classics as the main line， this paper systematically discusses the scientific connotation of the theory of pathogen invading nutrient and blood aspects and the paths of inheritance and innovation and clarifies the original significance of this theory in the chronic development of infectious diseases. Furthermore， taking clinical diseases as an example， this paper reflects the guiding value of this classical theory in the modern diagnosis and treatment of infectious diseases with integrated traditional Chinese and Western medicine and the application potential of this theory in solving complex medical problems through the construction of the innovative paradigm of precise diagnosis and treatment with integrated traditional Chinese and Western medicine.

Hepatocellular carcinoma （HCC）， a malignancy with high mortality， exhibits poor survival rates and prognosis. The profound suppression of the tumor immune microenvironment （TIME） and the abnormal hyperactivity of metabolic reprogramming （MR） are the two primary factors driving HCC progression. Traditional Chinese medicine has demonstrated significant efficacy in HCC treatment. The team proposed that "deficiency of healthy Qi and stasis toxins" was the core pathogenesis of HCC， closely associated with TIME suppression and MR hyperactivity. This paper proposed that a suppressed state of the TIME was the biological manifestation of "deficiency of healthy Qi"， where the functional exhaustion of effector T lymphocytes and natural killer cells reflected the decline of "healthy Qi" in eliminating pathogens. Conversely， the expansion and activation of immunosuppressive cells， such as regulatory T cells （Tregs）， M2-like tumor-associated macrophages （TAM-M2）， and myeloid-derived suppressor cells （MDSCs） ， represent the dysfunction of "healthy Qi" in maintaining homeostasis. MR serves as the material basis of "stasis toxins". Stasis toxins exhibit heat stagnation， manifested by abnormal hyperactivity of glycolysis and lipid synthesis. They demonstrate migratory propensity， as toxic metabolites like lactic acid and prostaglandin E2 promote tumor invasion and metastasis. They display a consumptive nature， reflected in the functional suppression of immune cells. The vicious cycle between TIME and MR is the biopathological reflection of "deficiency of healthy Qi intertwined with stasis toxins". Immunosuppression exacerbates MR， while toxic metabolites further impair immune function， establishing a pathogenic chain of "deficiency leading to stasis， and stasis toxins damaging healthy Qi". The primary therapeutic approach is reinforcing healthy Qi， resolving stasis， and removing toxins， which can reinforce and tonify healthy Qi to regulate pathways， such as phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt）， C-X-C chemokine receptor type 4/ C-X-C chemokine ligand 12 （CXCR4/CXCL12）， and toll-like receptor 4/ nuclear factor-kappa B/ signal transducer and activator of transcription 3 （TLR4/NF-κB/STAT3）， adjust T lymphocyte ratios， inhibit Tregs/TAM-M2 function， and downregulate immune checkpoints， including programmed death ligand 1/programmed death 1（PD-L1/PD-1）， and reshape TIME. It is also involved in resolving stasis and removing toxins to modulate phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin （PI3K/Akt/mTOR） and hypoxia-inducible factor-1α （HIF-1α） signaling pathways， suppress key enzymes in glycolysis and lipid synthesis， and block toxic metabolite production. Thus， this therapy synergistically regulates the immune and metabolic network， breaks the vicious cycle of "deficiency in healthy Qi and stasis toxins"， and offers a novel strategy for integrating traditional Chinese medicine and Western medicine in HCC treatment.

ObjectiveThis paper aims to investigate the differential mechanisms underlying the staged therapeutic effects of Qijia Rougan formula on liver fibrosis using proteomic technology. MethodsThe staged rat model of liver fibrosis was established by subcutaneous injection of carbon tetrachloride （CCl₄） and olive oil. One hundred and four SD rats were randomized into thirteen groups：a normal group，a two-week model group，a four-week model group，a six-week model group，an eight-week model group，a two-week Qijia Rougan formula group，a four-week Qijia Rougan formula group，a six-week Qijia Rougan formula group，an eight-week Qijia Rougan formula group，a two-week compound Biejia Ruangan tablet group，a four-week Compound Biejia Ruangan Tablet group，a six-week Compound Biejia Ruangan Tablet group，and an eight-week compound Biejia Ruangan tablet group. After two weeks of drug intervention，liver tissue and abdominal aortic blood samples were collected from the rats for testing. Hematoxylin-eosin （HE） staining，Masson staining，and Picro Sirius red staining were used to observe pathological damage and collagen fiber deposition in liver tissues. Immunohistochemistry （IHC） was employed to detect the contents of fibrosis markers in liver tissues. The contents of liver function indicators in the serum were measured using a fully automated biochemical analyzer，and the levels of liver fibrosis indicators in the serum were assessed by enzyme-linked immunosorbent assay （ELISA）. Liver tissues from the normal group，each model group，and each Qijia Rougan formula group were subjected to label-free quantitative proteomic analysis to identify differential proteins among the groups，with key proteins validated by Western blot. Finally，bioinformatics analysis was performed on the differential proteins. Results（1） The staged rat model of liver fibrosis constructed with CCl₄ and olive oil showed pathological results at the 2^nd，4^th，6^th，and 8^th weeks of modeling that were consistent with the Metavir standards for the F1，F2，F3，and F4 stages. Compared with those in the normal control group，the protein expressions of α-smooth muscle actin （α-SMA） and Collagen Ⅰ were significantly increased in each stage （P<0.05）. The levels of liver function indicators in the serum，including alanine aminotransferase （ALT），aspartate aminotransferase （AST），alkaline phosphatase （ALP），direct bilirubin （DBIL），and total bilirubin （TBil） in each model group，were significantly elevated in each stage （P<0.01）. The levels of liver fibrosis indicators in the serum，including procollagen Ⅲ peptide （PⅢP），type Ⅳ collagen（Ⅳ-C），hyaluronic acid （HA），and laminin （LN） in each model group，were significantly increased in each stage （P<0.05，P<0.01）. This study successfully established a staged rat model of liver fibrosis. （2） Compared with the model groups at each stage，the administration groups showed a reduction in hepatocyte ballooning degeneration，a more orderly arrangement of hepatocytes，and a decrease of inflammatory cell infiltration. The blue-stained collagen fibers became significantly thinner and finer，with reduced and narrowed fibrous septa. The areas of collagen fibers and Picro Sirius red staining were reduced （P<0.05）. The positive areas of α-SMA and Collagen Ⅰ expression were significantly decreased （P<0.05）. The levels of ALT，AST，ALP，DBIL，and TBil in the rats of the model groups at each stage were significantly reduced （P<0.05，P<0.01）. The levels of PⅢP，Ⅳ-C，HA，and LN in the rats of the model groups at each stage were significantly decreased （P<0.05）. Among these，the improvements in all indicators were most significant in the F3 stage （P<0.01）.（3） The proteomic results show that a total of 165 differential proteins exhibit a callback trend when comparing the model groups at four stages with the normal group，and when comparing the Qijia Rougan formula group with the model group. Western blot analysis reveals that the levels of NAD（P）H：quinone oxidoreductase 1 （NQO1），mitogen-activated protein kinase 1 （MAPK1），arginase 1 （Arg1），and glutathione S-transferase α1 （GSTA1） were consistent with the proteomic results. Bioinformatics results reveal that 165 differentially expressed proteins are enriched in multiple signaling pathways. Notably，signaling pathways such as drug metabolism-cytochrome P450，arginine biosynthesis，and the peroxisome proliferator-activated receptor （PPAR） signaling pathway were found to be closely associated with liver fibrosis，suggesting that the Qijia Rougan formula may exert its staged regulatory effects on liver fibrosis by regulating these pathways. ConclusionThe Qijia Rougan formula may achieve staged regulation of liver fibrosis by regulating drug metabolism-cytochrome P450，arginine biosynthesis，and the PPAR signaling pathway.

Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.