ObjectiveTo observe the effects of Yiqi Huoxue Jiedu formula（YHJF） on immune cell exhaustion in the spleen of septic mice and to explore and validate its potential intervention targets. MethodsMice were randomly divided into the sham-operated， model， low-dose YHJF（4.1 g·kg^-1）， and high-dose YHJF（8.2 g·kg^-1） groups. Except for the sham-operated group， a cecal ligation and puncture（CLP） procedure was performed to establish a mouse sepsis model. The treatment groups received oral administration of the corresponding doses， while the sham-operated and model groups received an equal volume of physiological saline. After the intervention， the 7-day survival rate of each group was recorded， and spleen samples were collected 72 h post-intervention， and the spleen index was calculated. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate（dUTP） nick end labeling（TUNEL） staining was used to detect apoptosis in spleen cells. Enzyme-linked immunosorbent assay（ELISA） was performed to measure the levels of interleukin（IL）-4 and IL-10 in the serum. Transcriptomics and metabolomics were used to screen for differentially expressed genes（DEGs） and differential metabolites in the spleen， followed by bioinformatics analysis to identify key targets. Real-time quantitative polymerase chain reaction（Real-time PCR）， flow cytometry， and multiplex immunofluorescence were used to verify the expressions of key genes and proteins. ResultsThe high-dose YHJF group significantly improved the 7-day survival rate of septic mice（P0.05）. Compared with the sham-operated group， the model group showed a significant increase in apoptosis of spleen cells and a decrease in the spleen index at 72 h post-modeling， with markedly elevated peripheral serum IL-4 and IL-10 levels（P0.01）. Compared with the model group， the high-dose YHJF group showed a reduction in apoptosis of spleen cells， an increase in the spleen index， and a significant decrease in peripheral serum IL-4 and IL-10 levels（P0.05）. Spleen transcriptomics identified 255 DEGs between groups， potentially serving as intervention targets for YHJF. Gene Ontology（GO） enrichment analysis revealed that DEGs were mainly involved in biological processes such as natural killer（NK） cell-mediated positive immune regulation， cell killing， cytokine production， positive regulation of innate immune cells， and interferon production. Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis showed that DEGs were mainly involved in cytokine-cytokine receptor interactions， viral protein interactions with cytokines and cytokine receptors， chemokine signaling pathway， and nuclear transcription factor-κB（NF-κB） signaling pathway. Protein-protein interaction（PPI） network analysis identified CD160， granzyme B（GZMB）， and chemokine ligand 4（CCL4） as key targets for YHJF in treating sepsis. Metabolomics identified 46 differential metabolites that were significantly reversed by YHJF intervention， and combined transcriptomics and metabolomics analysis identified 17 differential metabolites closely related to CD160. Pathway enrichment revealed that these metabolites were mainly involved in glycerophospholipid metabolism， arachidonic acid metabolism， glycosylphosphatidylinositol（GPI） anchor biosynthesis， linoleic acid metabolism， and α-linolenic acid metabolism pathways. Verification results showed that， compared with the sham-operated group， the model group exhibited significantly elevated CD160 mRNA expression level in the spleen， along with markedly decreased CCL4 and GZMB mRNA expression， and had a significant increase in CD160 expression on the surface of natural killer T（NKT） cells in the spleen（P0.01）. Compared with the model group， the high-dose YHJF group had a significant decrease in CD160 mRNA expression in the spleen， a significant increase in CCL4 and GZMB mRNA expressions. Further flow cytometry and immunofluorescence revealed that compared with the sham-operated group， CD160 expression on the surface of splenic NKT cells in the model group was significantly increased（P0.01）， while high-dose YHJF intervention significantly reduced CD160 expression（P0.01）. ConclusionYHJF may alleviate NKT cell exhaustion in sepsis by downregulating the expression of the negative co-stimulatory molecule CD160， and this regulatory effect is closely related to fatty acid metabolism pathways. This study provides new insights and targets for further exploration of strengthening vital Qi and detoxifying strategy to improve immune cell exhaustion in acute deficiency syndrome of sepsis.

The Dunhuang manuscript Fuxing Jue takes the "Tangye Jingfa Tu" as the core of its theory on prescription and compatibility. Its medication principles mainly include the "five elements principle of tonifying and purging" and the "five elements principle of elimination and transformation". Based on the differentiation of deficiency and excess in the five Zang organs， it flexibly applies medicinal properties， usage， and flavor transformation for tonifying and purging， forming its unique method of medication and compatibility. In Taiyin disease， "fullness syndrome" often occurs together with "diarrhea"， and these two conditions also serve as the primary indications for the middle-regulating formulas. Among them， Lizhong Wan （Tang） mainly address Taiyin deficiency. The three Xiexin Tang （Banxia Xiexin Tang， Gancao Xiexin Tang， Shengjiang Xiexin Tang） address Taiyin deficiency accompanied by pathogenic excess. The Sini Tangand Tongmai Sini Tang primarily treat dysfunction of the liver， spleen， and kidney with impaired opening and closing of Taiyin， manifesting as diarrhea. The medicinal flavors of middle-regulating formulas are pungent， sweet， and bitter， acting directly on the spleen of Taiyin. The pungent flavor induces purging of the spleen， sweet flavor tonifies the spleen， and bitter flavor eliminates lumps. When the constituent medicinal units of middle-regulating formulas are unified， the ratio of pungent to sweet flavors reflects the tonic and purgative strength of the formula. In addition， the two decoction methods， "short-term decoction to extract Qi" and "long-term decoction to extract flavor"， also influence the formula's tonifying and purgative effects. Based on the composition of flavors and special decoction methods， this article discusses the differences in the use of middle-regulating formulas for treating "“fullness syndrome" versus "diarrhea". Dysfunction of the spleen can give rise to various diseases. Therefore， middle-regulating formulas are not limited to treating "deficiency， cold， and dampness" syndromes. Later generations of physicians further modified Lizhong Tang to treat "excess， heat， and dryness" syndromes， laying a solid foundation for more flexible and effective clinical application of middle-regulating formulas.

ObjectiveTo observe the effects of Yiqi Huoxue Jiedu formula（YHJF） on immune cell exhaustion in the spleen of septic mice and to explore and validate its potential intervention targets. MethodsMice were randomly divided into the sham-operated， model， low-dose YHJF（4.1 g·kg^-1）， and high-dose YHJF（8.2 g·kg^-1） groups. Except for the sham-operated group， a cecal ligation and puncture（CLP） procedure was performed to establish a mouse sepsis model. The treatment groups received oral administration of the corresponding doses， while the sham-operated and model groups received an equal volume of physiological saline. After the intervention， the 7-day survival rate of each group was recorded， and spleen samples were collected 72 h post-intervention， and the spleen index was calculated. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate（dUTP） nick end labeling（TUNEL） staining was used to detect apoptosis in spleen cells. Enzyme-linked immunosorbent assay（ELISA） was performed to measure the levels of interleukin（IL）-4 and IL-10 in the serum. Transcriptomics and metabolomics were used to screen for differentially expressed genes（DEGs） and differential metabolites in the spleen， followed by bioinformatics analysis to identify key targets. Real-time quantitative polymerase chain reaction（Real-time PCR）， flow cytometry， and multiplex immunofluorescence were used to verify the expressions of key genes and proteins. ResultsThe high-dose YHJF group significantly improved the 7-day survival rate of septic mice（P0.05）. Compared with the sham-operated group， the model group showed a significant increase in apoptosis of spleen cells and a decrease in the spleen index at 72 h post-modeling， with markedly elevated peripheral serum IL-4 and IL-10 levels（P0.01）. Compared with the model group， the high-dose YHJF group showed a reduction in apoptosis of spleen cells， an increase in the spleen index， and a significant decrease in peripheral serum IL-4 and IL-10 levels（P0.05）. Spleen transcriptomics identified 255 DEGs between groups， potentially serving as intervention targets for YHJF. Gene Ontology（GO） enrichment analysis revealed that DEGs were mainly involved in biological processes such as natural killer（NK） cell-mediated positive immune regulation， cell killing， cytokine production， positive regulation of innate immune cells， and interferon production. Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis showed that DEGs were mainly involved in cytokine-cytokine receptor interactions， viral protein interactions with cytokines and cytokine receptors， chemokine signaling pathway， and nuclear transcription factor-κB（NF-κB） signaling pathway. Protein-protein interaction（PPI） network analysis identified CD160， granzyme B（GZMB）， and chemokine ligand 4（CCL4） as key targets for YHJF in treating sepsis. Metabolomics identified 46 differential metabolites that were significantly reversed by YHJF intervention， and combined transcriptomics and metabolomics analysis identified 17 differential metabolites closely related to CD160. Pathway enrichment revealed that these metabolites were mainly involved in glycerophospholipid metabolism， arachidonic acid metabolism， glycosylphosphatidylinositol（GPI） anchor biosynthesis， linoleic acid metabolism， and α-linolenic acid metabolism pathways. Verification results showed that， compared with the sham-operated group， the model group exhibited significantly elevated CD160 mRNA expression level in the spleen， along with markedly decreased CCL4 and GZMB mRNA expression， and had a significant increase in CD160 expression on the surface of natural killer T（NKT） cells in the spleen（P0.01）. Compared with the model group， the high-dose YHJF group had a significant decrease in CD160 mRNA expression in the spleen， a significant increase in CCL4 and GZMB mRNA expressions. Further flow cytometry and immunofluorescence revealed that compared with the sham-operated group， CD160 expression on the surface of splenic NKT cells in the model group was significantly increased（P0.01）， while high-dose YHJF intervention significantly reduced CD160 expression（P0.01）. ConclusionYHJF may alleviate NKT cell exhaustion in sepsis by downregulating the expression of the negative co-stimulatory molecule CD160， and this regulatory effect is closely related to fatty acid metabolism pathways. This study provides new insights and targets for further exploration of strengthening vital Qi and detoxifying strategy to improve immune cell exhaustion in acute deficiency syndrome of sepsis.

The Dunhuang manuscript Fuxing Jue takes the "Tangye Jingfa Tu" as the core of its theory on prescription and compatibility. Its medication principles mainly include the "five elements principle of tonifying and purging" and the "five elements principle of elimination and transformation". Based on the differentiation of deficiency and excess in the five Zang organs， it flexibly applies medicinal properties， usage， and flavor transformation for tonifying and purging， forming its unique method of medication and compatibility. In Taiyin disease， "fullness syndrome" often occurs together with "diarrhea"， and these two conditions also serve as the primary indications for the middle-regulating formulas. Among them， Lizhong Wan （Tang） mainly address Taiyin deficiency. The three Xiexin Tang （Banxia Xiexin Tang， Gancao Xiexin Tang， Shengjiang Xiexin Tang） address Taiyin deficiency accompanied by pathogenic excess. The Sini Tangand Tongmai Sini Tang primarily treat dysfunction of the liver， spleen， and kidney with impaired opening and closing of Taiyin， manifesting as diarrhea. The medicinal flavors of middle-regulating formulas are pungent， sweet， and bitter， acting directly on the spleen of Taiyin. The pungent flavor induces purging of the spleen， sweet flavor tonifies the spleen， and bitter flavor eliminates lumps. When the constituent medicinal units of middle-regulating formulas are unified， the ratio of pungent to sweet flavors reflects the tonic and purgative strength of the formula. In addition， the two decoction methods， "short-term decoction to extract Qi" and "long-term decoction to extract flavor"， also influence the formula's tonifying and purgative effects. Based on the composition of flavors and special decoction methods， this article discusses the differences in the use of middle-regulating formulas for treating "“fullness syndrome" versus "diarrhea". Dysfunction of the spleen can give rise to various diseases. Therefore， middle-regulating formulas are not limited to treating "deficiency， cold， and dampness" syndromes. Later generations of physicians further modified Lizhong Tang to treat "excess， heat， and dryness" syndromes， laying a solid foundation for more flexible and effective clinical application of middle-regulating formulas.

Based on the thinking of programmatization and proceduralization， this study integrated traditional Chinese medicine （TCM） classic theories with modern knowledge expression technologies to construct a "formula-symptom" syndrome differentiation thinking model centered on "symptom clustering-main syndrome screening-formula adaptation"， and explored the standardization and intelligentization path of TCM syndrome differentiation and treatment. By establishing the mapping relationship model between formulas and syndromes including quantitative weight analysis of chief， deputy， assistant and envoy medicines， designing the logical hierarchical structure of formula-syndrome decision tree （application of three-level decision tree and fuzzy logic）， and formulating the procedural design of four diagnostic methods （structured collection， correlation model， and dynamic correction mechanism）， the standardization and visualization of the syndrome differentiation process are realized. This model can be transformed into the core data set for artificial intelligence training. Through ternary knowledge graph and machine learning algorithms， it can improve the repeatability of syndrome differentiation and the efficiency of diagnosis and treatment， and implement the strategy of "group model + individual modification" to balance the conflict between quantification and individualization. The core value of this model lies in promoting the objectification and precision development of TCM syndrome differentiation and treatment through the integration of traditional syndrome differentiation thinking and modern system science.

As a pivotal strategy to alleviate the shortage of organ donors, xenotransplantation has achieved remarkable advances in both pre-clinical and clinical studies in recent years, driven by continuous optimization of gene modification techniques and immunosuppressive regimens. Nevertheless, clinical translation still confronts formidable challenges, including rejection and heightened infection risks, which severely compromise long-term graft survival. Consequently, the role of immunosuppressive regimens in xenotransplantation has become increasingly prominent. This article summarizes the mechanisms underlying xenogeneic immune rejection, the latest developments in immunosuppressive regimens, cutting-edge strategies for inducing immune tolerance and the major hurdles facing clinical xenotransplantation. It delves into potential optimization strategies and directions for future clinical research, aiming to offer theoretical insights and practical guidance for the safe and effective application of clinical xenotransplantation.

ObjectiveThis paper aims to observe the role of Danlou tablet in treating coronary heart disease （CHD） with phlegm-stasis intermingling syndrome in minipigs by improving platelet function and explore the potential pharmacological mechanism of Danlou tablet in regulating platelet function by using proteomics technology. MethodsThirty Bama minipigs were randomly divided into a normal control group （6 pigs） and a high-fat diet group （24 pigs）. After 2 weeks of high-fat diet feeding， the high-fat diet group was randomly subdivided into a model group， an atorvastatin group （1 mg·kg^-1）， and Danlou tablet groups （0.6 g·kg^-1 and 0.3 g·kg^-1）. All groups continued to receive a high-fat diet for 8 weeks after the procedure. The normal control group was given a regular diet， underwent only coronary angiography， and did not receive an interventional injury procedure. The model group and each administration group were fed a high-fat diet. Two weeks later， they underwent a coronary angiography injury procedure. After the procedure， drugs were mixed into the feed every morning for 8 consecutive weeks， with the minipigs maintained on a continuous high-fat diet during this period. Quantitative proteomics technology was further used to study platelet proteins， and differential proteins were obtained by screening. Bioinformatics analysis was performed to analyze key regulatory proteins and biological pathways involved in the therapeutic effect of Danlou tablet on CHD with phlegm-stasis intermingling syndrome. ResultsCompared with the normal control group， the model group showed a significant increase in total cholesterol （TC）， triglyceride （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） of minipigs' serum （P<0.01）， a significant shortening in prothrombin time of （PT） （P<0.01）， a coagulation function index， and an increase in whole blood viscosity （P<0.01） and platelet aggregation rate （P<0.01）. Moreover， the platelet morphology was altered， and the contents of endothelin-1 （ET-1） and nitric oxide （NO） were significantly increased （P<0.01）. Hemodynamic parameters were obviously abnormal， including significantly decreased systolic blood pressure （SBP）， diastolic blood pressure （DBP）， mean arterial pressure （MAP）， left ventricular systolic pressure （LVSP）， and left ventricular maximal positive dp/dt （LV+dp/dt_max） （P<0.01）. Left ventricular maximal negative dp/dt （LV-dp/dt_max） was significantly increased （P<0.01）. Besides， there were myocardial cell hypertrophy， obvious edematous degeneration， massive interstitial inflammatory cell infiltration， high degree of fibrosis， and coronary endothelial atherosclerosis. TC and TG levels in minipigs' serum were significantly reduced in Danlou tablet groups with 0.6 g·kg^-1 and 0.3 g·kg^-1 （P<0.05， P<0.01）， compared with those in the model group. LDL-C was decreased in the Danlou tablet group with 0.6 g·kg^-1 （P<0.05）. The whole blood viscosity under low and high shear conditions was significantly reduced in the Danlou tablet group with 0.6 g·kg^-1 （P<0.05）. In groups with all doses of Danlou tablet， maximum aggregation rate （MAR） and average aggregation rate （AAR） were significantly decreased （P<0.05， P<0.01）， and platelets' morphological changes such as pseudopodia extension were reduced. ET-1 levels in the serum were significantly reduced. In the Danlou tablet group with 0.6 g·kg^-1， NO level in the serum was reduced （P<0.05）. In groups with all doses of Danlou tablet， DBP and MAP were significantly increased （P<0.05）. In the Danlou tablet group with 0.6 g·kg^-1， LVSP and LV+dp/dt_max were significantly increased （P<0.05， P<0.01）， and LV-dp/dt_max was significantly decreased （P<0.05）. In groups with all doses of Danlou tablet， edematous degeneration in myocardial tissue was milder， and coronary artery lesion degree was significantly alleviated. Compared with the normal control group， there were 94 differentially expressed proteins in the model group， including 81 up-regulated and 13 down-regulated proteins. Compared with the model group， the Danlou tablet group with 0.6 g·kg^-1 showed 174 differentially expressed proteins， including 100 up-regulated and 74 down-regulated proteins. A total of 30 proteins were reversed after Danlou tablet intervention. Bioinformatics analysis revealed that its pharmacological mechanism may exert anti-platelet activation， aggregation， and adhesion effects through biological pathways such as regulation of actin cytoskeleton， platelet activation pathway， Fcγ receptor-mediated phagocytosis， as well as proteins such as growth factor receptor-bound protein 2 （GRB2）， Ras-related C3 botulinum toxin substrate 2 （RAC2）， RAC1， and heat shock protein 90 alpha family class A member 1 （HSP90AA1）. ConclusionDanlou tablet can effectively reduce platelet activation and aggregation， exerting a good therapeutic effect on CHD with phlegm-stasis intermingling syndrome in minipigs. Its pharmacological mechanism may involve regulating biological pathways such as actin cytoskeleton and platelet activation pathway， as well as proteins like GRB2， RAC2， RAC1， and HSP90AA1， thereby exerting a pharmacological effect in anti-platelet activation， aggregation， and adhesion.

Metabolic reprogramming， as one of the core hallmarks of malignant tumors， plays a key role in the occurrence， development and treatment of breast cancer （BC）. Abnormal changes in glucose metabolism， amino acid metabolism， lipid metabolism， as well as the tricarboxylic acid （TCA） cycle and oxidative phosphorylation （OXPHOS） pathways significantly influence the pathogenesis and progression of BC. Studies have shown that various active components of traditional Chinese medicine （TCM） （such as berberine， matrine， quercetin， curcumin， etc.） and their compound formulations （e.g. Xihuang pill， Danzhi xiaoyao powder， Yanghe decoction， etc.） can inhibit the proliferation and migration of BC cells and induce apoptosis by regulating key metabolic pathways such as glycolysis， lipid synthesis， and amino acid metabolism. TCM demonstrates multi-target and holistic regulatory advantages in intervening in BC metabolic reprogramming， showing significant potential in modulating key molecules like hypoxia inducible factor-1α， hexokinase-2， pyruvate kinase M2， lactate dehydrogenase A， glucose transporter-1， fatty acid synthase， and signaling pathways such as AKT/mTOR. However， current researches still focus predominantly on glucose metabolism， with insufficient mechanistic studies on lipid metabolism， amino acid metabolism， the TCA cycle， and OXPHOS. The precise targets， molecular mechanisms， and clinical translation value of these interventions require further validation and clarification through more high-quality experimental studies and clinical trials.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.