ObjectiveTo observe the clinical effectiveness and safety of Qingfei Shenshi Decoction （清肺渗湿汤） combined with western medicine for patients with bronchial asthma of heat wheezing syndrome， and to explore its potential mechanism of action. MethodsEighty-six participants with bronchial asthma of heat wheezing syndrome were randomly divided into treatment group and control group， each group with 43 participants. The control group received conventional western medicine， and the treatment group was additionally administered Qingfei Shenshi Decoction orally on the basis of the control group， 1 dose per day. Both groups were treated for 14 days. The primary outcome measure was clinical effectiveness； secondary outcome measures included traditional Chinese medicine （TCM） syndrome score， asthma control test （ACT） score， pulmonary function indices such as forced expiratory volume in 1 second （FEV₁）， forced vital capacity （FVC）， peak expiratory flow （PEF）， serum inflammatory factor levels including interleukin-4 （IL-4）， tumour necrosis factor-α （TNF-α）， and high-sensitivity C-reactive protein （hs-CRP）， and immune function indices including CD3⁺， CD4⁺， CD8⁺， CD4⁺/CD8⁺. All outcome measures were evaluated before and after treatment. Vital signs were monitored， and electrocardiography， blood routine， urine routine， liver function， and renal function tests were performed before and after treatment. Adverse events and reactions during the study were recorded. ResultsA total of 80 patients completed the trial with 40 in each group. The total clinical effective rate of the treatment group was 97.5% （39/40）， which was significantly higher than that of the control group （85.0%， 34/40， P＜0.05）. After treatment， both groups showed decreased TCM syndrome scores， IL-4， TNF-α， hs-CRP， and CD8⁺ levels， as well as increased ACT scores， CD3⁺， CD4⁺， CD4⁺/CD8⁺， FEV₁， FVC， and PEF levels （P＜0.05 or P＜0.01）. Moreover， the improvements in these indices were more significant in the treatment group than in the control group （P＜0.05 or P＜0.01）. No significant abnormalities in safety indicators were observed in either group， and no adverse events or reactions occurred. ConclusionQingfei Shenshi Decoction combined with conventional western medicine for patients with bronchial asthma of heat wheezing syndrome can effectively improve the clinical symptoms， pulmonary function， and clinical effectiveness， with good safety. Its mechanism may be related to reducing inflammatory factor levels and regulating T lymphocyte subsets to improve immune function.

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 analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

ObjectiveBy exploring the influencing factors of readmission in patients with stable angina of coronary heart disease （CHD） based on real-world clinical data， to establish a risk prediction model of integrated traditional Chinese and western medicine， in order to provide a basis for early identification of high-risk populations and reducing readmission rates. MethodsA prospective clinical study was conducted involving patients with stable angina pectoris of CHD， who were divided into a training set and a validation set at a 7∶3 ratio. General information， traditional Chinese medicine （TCM）-related data， and laboratory test results were uniformly collected. After a one-year follow-up， patients were classified into a readmission group and a non-readmission group based on whether they were readmitted. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for readmission. A risk prediction model of integrated traditional Chinese and western medicine was constructed and visualized using a nomogram. The model was validated and evaluated in terms of discrimination， calibration， and clinical decision curve analysis. ResultsA total of 682 patients were included， with 477 in the training set and 205 in the validation set， among whom 89 patients were readmitted. Multivariate logistic regression analysis identified heart failure history ［OR = 6.93， 95% CI （1.58， 30.45）］， wiry pulse ［OR = 2.58， 95% CI （1.42， 4.72）］， weak pulse ［OR = 3.97， 95% CI （2.06， 7.67）］， teeth-marked tongue ［OR = 4.38， 95% CI （2.32， 8.27）］， blood stasis constitution ［OR = 2.17， 95% CI （1.06， 4.44）］， phlegm-stasis mutual syndrome ［OR = 3.64， 95% CI （1.87， 7.09）］， and elevated non-high-density lipoprotein cholesterol ［OR = 1.30， 95% CI （1.01， 1.69）］ as influencing factors of readmission. These factors were used as predictors to construct a nomogram-based risk prediction model for readmission in patients with stable angina. The model demonstrated moderate predictive capability， with an area under the receiver operating characteristic curve （AUC） of 0.818 ［95% CI （0.781， 0.852）］ in the training set and 0.816 ［95% CI （0.779， 0.850）］ in the validation set. The Hosmer-Lemeshow test showed good calibration （χ² = 4.55， P = 0.80）， and the model's predictive ability was stable. When the threshold probability exceeded 5%， the clinical net benefit of using the model to predict readmission risk was significantly higher than intervening in all patients. ConclusionHistory of heart failure， teeth-marked tongue， weak pulse， wiry pulse， phlegm-stasis mutual syndrome， blood stasis constitution， and non-high-density lipoprotein cholesterol are influencing factors for readmission in patients with stable angina of CHD. A clinical prediction model was developed based on these factors， which showed good discrimination， calibration， and clinical utility， providing a scientific basis for predicting readmission events in patients with stable angina.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

ObjectiveThis study aimed to explore the correlation between the quality of life （QOL） and different traditional Chinese medicine （TCM） syndromes in patients with myasthenia gravis （MG）， identifying potential influencing factors to provide new insights for clinical interventions and improving the QOL of patients with MG. MethodsA questionnaire survey was conducted on 93 adults with MG who visited the Department of Neurology at the Affiliated Hospital of Changchun University of Chinese Medicine from March 2023 to January 2024. Statistical analysis was performed on the clinical data collected using SPSS 24.0 software. ResultsAmong the 93 patients with MG， the average score for myasthenia gravis quality of life-15 （MGQOL-15） was 17.65±6.27， and that for the 36-item short form health survey （SF-36） was （106.13±11.83） scores. The QOL was rated as good for 16 patients and moderate for 77 patients. There were no statistically significant differences in the scores of MGQOL-15， SF-36， and their individual scales by gender or education level. Age showed statistically significant differences in MGQOL-15 and the role physical （RP） scale （P<0.05）， and occupational type showed significant differences in the vitality （VT） scale （P<0.01）. The Myasthenia Gravis Foundation of America （MGFA） classification had statistical significance on the total SF-36 score （P<0.01）， VT scale （P<0.01）， role emotional （RE） scale （P<0.05）， social functioning （SF） scale （P<0.05）， and physical functioning （PF） scale （P<0.01）. Among patients with different TCM syndromes， there were significant differences in MGQOL-15 scores （F=4.919， P<0.01）. Moreover， significant differences were observed in SF-36 scores （P<0.01）， VT scale （P<0.01）， RE scale （P<0.05）， mental health （MH） scale （P<0.01）， and SF scale （P<0.05）. ConclusionFactors affecting the QOL of patients with MG include age， occupational type， and clinical classification of MG. Specifically， a greater impact on the QOL of older patients is observed， while physical laborers have a poorer QOL compared to non-physical laborers. Patients classified as MGFA type Ⅱ and higher have a poorer QOL. Additionally， there is a potential correlation between the QOL and TCM syndromes， with patients presenting with spleen and kidney Qi deficiency having a lower QOL than those with spleen and stomach Qi deficiency or Qi and Yin deficiency， which is particularly evident in the VT， RE， MH， and SF scales.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.

ObjectiveWith the epidermal growth factor receptor（EGFR）/Signal Transducers and Activators of Transcription（STAT3）/Hexokinase 2（HK2） signaling pathway in atherosclerosis （AS） and ovarian cancer （OC） as the entry point， this paper discusses the molecular mechanism of Gypenoside L （Gyp-L） treating AS and OC with different diseases， provides a new perspective and theoretical basis for TCM treating AS and OC with EGFR-STAT3-HK2 pathway， and enriches the scientific connotation of the theory of "cytoskeleton in the heart". MethodsCCK-8 was used to detect the proliferation of HUVEC and OVCAR-3 cells， in order to determine the intervention concentration for subsequent experiments. The colorimetric method was used to detect the NO content in HUVEC and the contents of pyruvate and LDH in two cell lines. Cell cloning experiments and scratch experiments reflect the proliferation and migration ability of OVCAR-3 cells. Western blot was used to detect the expression levels of relevant proteins. Furthermore， two cell models overexpressing EGFR were constructed and co treated with Gyp-L. HUVEC cells were divided into control， ox-LDL， OE-NC， OE-EGFR， OE-NC+Gyp-L， and OE-EGFR+Gyp-L group. OVCAR-3 cells were divided into control， OE-NC， OE-EGFR ， OE-NC+Gyp-L， and OE-EGFR+Gyp-L group. The colorimetric method was used to detect the NO content in HUVEC and the contents of pyruvate and LDH in two cell lines. Western blot was used to detect the expression levels of EGFR-STAT3-HK2 pathway related proteins. Cell cloning experiments and scratch experiments reflect the proliferation and migration ability of OVCAR-3 cells. ResultsGyp-L can significantly reduce the NO content of HUVEC and the pyruvate and LDH content of two cell lines （P<0.05）； Inhibit the proliferation and migration ability of OVCAR-3 cells； Reduce the expression levels of EGFR/STAT3/HK2 pathway related proteins in HUVEC and OVCAR-3 cell lines （P<0.05）， and inhibit the glycolysis pathway. ConclusionGyp-L can inhibit glycolysis in HUVEC and OVCAR-3 cells through the EGFR/STAT3/HK2 pathway，thereby suppressing the occurrence and development of AS and OC.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.