To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Objective: To understand the epidemiological characteristics of a pertussis outbreak in Guangzhou, so as to provide references for outbreak response and prevention strategies. Methods: From April 5 to June 9, 2024, case screening was conducted among 246 preschool children, 35 staff members, and one full time school nurse in a kindergarten in Guangzhou based on case definition. Field epidemiological investigation methods were employed to collect relevant information, and screening samples were collected from individuals involved in the outbreak. The clinical manifestations, epidemiological characteristics, and risk factors for transmission of the outbreak were analyzed, with rate comparisons performed using the χ 2 test. Results: There were a total of 15 confirmed cases of pertussis in the kindergarten. The main clinical manifestations included intermittent cough in 14 cases ( 93.33 %), sputum production in 5 cases (33.33%), fever in 2 cases (13.33%), paroxysmal spasmodic cough in 1 case (6.67%), and vomiting in 1 case (6.67%). There was no statistically significant difference in the reporting rates of interrupted cough symptoms between pertussis cases (93.33%) and non pertussis cases (92.86%)( χ 2=3.74, P >0.05). The cases were aged 4-5 years, including 5 males and 10 females. The interval between symptom onset and diagnosis ranged from 2 to 25 days, with a median of 10 days. The outbreak involved two classes, with attack rates of 48.28% and 3.45%, respectively. Laboratory testing confirmed 14 close contacts positive for Bordetella pertussisnucleic acid. Among close contacts, only one received prophylactic medication as required. Conclusion The outbreak is a pertussis outbreak in a kindergarten caused by Bordetella pertussis infection, demonstrating distinct temporal and spatial clustering characteristics.

A 51-year-old male presented with nasal obstruction, followed by progressive hearing loss and blurred vision. Imaging identified space-occupying lesions in the paranasal sinuses, orbits, and paraspinal regions, while laboratory tests confirmed positive anti-proteinase 3 anti-neutrophil cytoplasmic antibody(PR3- ANCA) immunoglobulin G (IgG)and markedly elevated serum IgG4. Despite treatment with corticosteroids, immunosuppressants, and radiotherapy, the patient exhibited steroid dependency with relentless disease progression. Following multidisciplinary consultation, a diagnosis of inflammatory myofibroblastic tumor (IMT) coexisting with ANCA- associated vasculitis (AAV) was favored, though IgG4-related disease remained a critical differential. Ultimately, profound immunosuppression precipitated a severe herpesvirus infection, leading to disseminated intravascular coagulation and multiple organ dysfunction syndrome. This case underscores the rarity and diagnostic complexity of concurrent IMT and AAV, highlights the therapeutic dilemma of balancing primary disease control against fatal opportunistic infections, and emphasizes the critical role of multidisciplinary collaboration in the diagnosis and treatment of complex diseases.

OBJECTIVE To construct a dual-verification system integrating image pre-screening and Raman spectroscopy for inpatient pharmacy unit-dose dispensing in response to the issue of recognition blind spots for drugs of “same appearance but different spectrum” by drug inspection machines. METHODS An image feature and Raman spectroscopy database， covering 296 oral medications， were established. Spectral matching was performed using a cosine similarity algorithm （decision threshold 0.95）. A dual-verification system of “image pre-screening and Raman spectroscopy confirmation” was designed， and a self-controlled before-and-after study was conducted across 5 clinical wards. RESULTS The system achieved a mean recognition accuracy of 99.2% for all medications in the database， with 100% accurate identification of representative “same-appearance but different-spectrum” drugs. The average verification time per-unit in the experimental group （image recognition+Raman spectroscopy confirmation and verification） was reduced by 31.5%-43.3%， compared with the control group （image recognition+manual visual comparison with actual objects）（ P ＜0.001）. Nurses’ satisfaction scores in the dimensions of operational convenience， identification efficiency， verification confidence， and psychological stress relief in the experimental group were all significantly superior to those of the control group （ P ＜0.01）. CONCLUSIONS The dual-verification system of “image pre-screening and Raman spectroscopy confirmation” effectively overcomes the technical limitations of conventional machine vision. It enhances work efficiency and staff satisfaction while ensuring medication safety.

The philosophy of “treating disease before its onset” is a fundamental concept of traditional Chinese medicine (TCM), permeating its diagnostic and therapeutic framework, and is central to clinical practice. However, current TCM diagnostic and treatment models for the “pre-disease to disease” window period face several limitations, including the lack of comprehensive clinical parameters, difficulties in characterizing and integrating heterogeneous multimodal data, and insufficient dynamic precision in interventions and efficacy evaluations. To address these issues, guided by Professor Candong Li’s theory of TCM stateology, this study focuses on integrating objective multimodal data. It proposes a new model for personalized TCM diagnosis and treatment targeting the “pre-disease to disease” window period. This approach first proposes the idea of restructuring the conceptual framework of “symptom” and integrating multi-source heterogeneous data at macroscopic, mesoscopic, and microscopic levels to form a three-dimensional assessment indicator system. By integrating graph neural networks, convolutional neural networks, attention mechanisms, and knowledge graph-guided weight allocation, this approach enables collaborative representation, alignment, and fusion of multi-source data. Subsequently, it plans to construct a multimodal fusion model at both feature and decision levels, in order to establish mappings between indicators and TCM state elements, and to screen key indicators characterizing pathological evolution during the window period. Furthermore, it proposes a technical path for enhancing model interpretability using methods such as SHapley Additive exPlanations (SHAP) and Ablation-CAM++. Finally, with state assessment as the core, it proposes the concept of constructing a dynamic evaluation method for individualized diagnosis and treatment based on time-series data analysis using algorithms such as long short-term memory (LSTM) networks and gated recurrent units (GRUs). Moreover, a causal inference framework and semi-supervised learning strategies are introduced to enable quantitative evaluation of individual intervention effects and to provide interpretable therapeutic feedback, forming a complete technical path from data representation and fusion, weight adjustment, and interpretability analysis, to dynamic diagnosis feedback. This study aims to address deficiencies in the current TCM diagnosis and treatment model during the “pre-disease to disease” window period and to provide an operational framework for the clinical practice of TCM’s “treating disease before its onset”.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

Objective: To investigate the association of serum alanine aminotransferase (ALT) with left ventricular hypertrophy (LVH) in adolescents, and to provide scientific evidence for the early screening and intervention strategy of cardiac structure damage. Methods: Data were obtained from the third follow up survey (October 2023) of the "Huantai Childhood Cardiovascular Health Cohort Study", including 1 156 healthy adolescents aged 12-17 with complete information. The sample population was stratified into low ( Q 1 group), medium ( Q 2 group), and high ( Q 3 group) ALT levels based on tertiles within the same gender and age groups. Inter group comparisons were conducted using analysis of variance and trend test. A multivariate Logistic regression model was used to analyze the association between ALT levels and LVH, and stratified analyses were performed by gender and age groups. Results: With the increase of ALT quantile level, the detection rate of LVH showed an increasing trend ( Q 1: 3.7%; Q 2: 10.6%; Q 3: 16.7%, Z= 5.89 , P <0.01). After adjusting for potential covariates, compared with the ALT group ( Q 1), the group ( Q 3) increased the risk of developing LVH in adolescents ( OR=2.09, 95%CI =1.21-4.12). Stratified analyses by age and sex showed a significant association only in boys and younger individuals aged 12 to 14 years [ OR (95% CI ) were 2.64(1.04-7.67) and 3.24( 1.35 -9.06), both P <0.05)]. Conclusion Elevated serum ALT levels are associated with an increased risk of LVH in adolescents, and early detection and control of abnormal liver enzyme levels can help reduce early vascular structural damage and prevent adverse cardiovascular events.

BackgroundPostpartum depression can affect the physical and mental health of mothers and the quality of parenting. Most Chinese women perform traditional postpartum practices （commonly known as "doing the month"） after giving birth， while the existing findings are inconsistent and inconclusive regarding the potential of traditional Chinese postpartum practices to alleviate or exacerbate postpartum depression. ObjectiveTo explore the relationship between traditional Chinese postpartum practices and postpartum depression， so as to provide references for reducing the risk of postpartum depression. MethodsA total of 240 consecutive women who gave birth in the obstetrics department of the Mianyang Central Hospital and the Third Hospital of Mianyang from January to May 2024 were selected. Data were collected using Self-designed General Information Questionnaire， Chinese version of the Edinburgh Postnatal Depression Scale （EPDS）， the Social Support Rating Scale （SSRS）， the Patient Health Questionnaire-15 （PHQ-15）， the Adherence to Doing-the-Month Practices questionnaire （ADP）， and the Self-compiled Questionnaire on the Cognition of Doing-the-Month. The absolute value （A value） of the difference between scores of ADP and Cognition of Doing-the-Month Questionnaire was calculated to evaluate the degree of cognitive behavioral conflict of postpartum women. Pearson correlation analysis was performed to examine the correlations of EPDS score with SSRS score， PHQ-15 score， ADP total and dimensional scores， Cognition of Doing-the-Month Questionnaire total and dimensional scores， and A value. Logistic regression analysis was conducted to identify the protective and risk factors for developing postpartum depression. ResultsThe postpartum depression was detected in 22.50% of women. The postpartum women had a EPDS score of （6.21±5.00）， ADP score of （70.05±20.57）， SSRS score of （41.96±6.96）， PHQ-15 score of （4.63±3.77）， and Cognition of Doing-the-Month questionnaire score of （40.30±10.13）. The A value was （0.65±0.58）. Correlation analysis revealed that EPDS score was negatively correlated with the total ADP score and the four dimensional scores of the restrictions on social activities， diet， housework， and personal hygiene （r=-0.228， -0.146， -0.184， -0.275， -0.168， P<0.05 or 0.01）， and positively correlated with the A value （r=0.161， P<0.05）. Logistic regression analysis indicated that restriction on housework dimension in ADP was entered into the model （OR=0.930， 95% CI： 0.885~0.978）. ConclusionThe restriction on housework dimension in traditional Chinese postpartum practices may be a protective factor against postpartum depression.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

ObjectiveTo investigate the mechanism of Si Junzitang in treating liver injury in rats with spleen Qi deficiency syndrome based on transcriptomics and to experimentally verify its effects. MethodsSixty male SD rats were randomly divided into blank group， model group， low-dose Si Junzitang （6 g·kg^-1·d^-1）， medium-dose Si Junzitang group （12 g·kg^-1·d^-1）， high-dose Si Junzitang group （24 g·kg^-1·d^-1）， and natural recovery group， with 10 rats in each group. A composite multifactorial modeling method （forced swimming + intragastric administration of Xiao Chengqitang + irregular diet） was used to establish a spleen Qi deficiency model. After 30 days of continuous intervention， body weight and 3-hour food intake were measured， and macroscopic symptom scores for spleen Qi deficiency syndrome were evaluated. Serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT） in each group were detected， and hematoxylin and eosin （HE） staining was used to observe histopathological changes in liver tissue. Transcriptome sequencing （RNA-Seq） was used to identify differentially expressed genes （DEGs） among the blank， model， and high-dose Si Junzitang groups. Gene ontology（GO） and Kyoto encyclopedia of genes and genome（KEGG） enrichment analyses were performed on the DEGs. Immunofluorescence （IF） and Western blot were used to detect NOD-like receptor protein 3 （NLRP3）， apoptosis-associated speck-like protein （ASC）， Caspase-1， and the N-terminal domain of gasdermin D （GSDMD-N）. Immunohistochemistry （IHC） was used to detect the expression of downstream inflammatory cytokines interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and interleukin-18 （IL-18）. ResultsCompared with the blank group， the model group showed significantly reduced body weight and 3-hour food intake， significantly increased macroscopic symptom scores， and elevated serum AST and ALT levels （P<0.01）， with mild inflammatory liver injury observed histologically. Compared with the model group， Si Junzitang at all doses significantly improved these parameters and alleviated liver injury in a dose-dependent manner （P<0.05，P<0.01）. RNA-Seq analysis revealed 1 254 DEGs between the blank and model groups， and 842 DEGs between the model and high-dose Si Junzitang groups. GO and KEGG enrichment analyses indicated that the NOD-like receptor signaling pathway was activated in liver injury associated with spleen Qi deficiency， suggesting that the NLRP3 inflammasome may be a key target. Results from IF， IHC， and Westernblot showed that compared with the blank group， the expression of NLRP3， ASC， Caspase-1， GSDMD-N， and the downstream inflammatory cytokines IL-1β， IL-6， and IL-18 were significantly increased in the model group （P<0.01）， while these levels were markedly decreased in the high-dose Si Junzitang group （P<0.01）. ConclusionSi Junzitang effectively improves mild inflammatory liver injury in rats with spleen Qi deficiency syndrome in a dose-dependent manner. Its mechanism may be associated with inhibition of the NLRP3/ASC/Caspase-1 signaling pathway， downregulation of the pyroptosis executioner protein GSDMD-N， and reduction of pyroptosis-related inflammatory cytokine release.