Objective:To explore the value of ultrasound imaging characteristics combined with clinical indicators in assessing the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).Methods:A retrospective analysis was conducted for patients who underwent pancreatic contrast-enhanced ultrasound (CEUS) from September 2017 to October 2023 at Peking Union Medical College Hospital and were diagnosed with PDAC based on pathological findings. Various parameters were recorded, including CA19-9 levels, tumor size, location, morphologic features, echogenicity, presence of internal cystic components, dilatation of the main pancreatic duct, peripheral vascular invasion, CEUS characteristics, presence or absence of liver metastasis, and treatment methods. In April 2024, patient survival information was obtained through telephone follow-up or review of medical records. Based on the results of the cox regression model analysis, a nomogram model of the risk of death was developed. The receiver operating characteristic (ROC) curves were applied to evaluate the predictive efficacy of the model. The calibration curves were plotted to evaluate the accuracy of the model, and clinical decision curves were used to evaluate the clinical benefit of the model.Results:This study included a total of 207 patients with PDAC. As of April 2024, 71 patients were alive and 136 died, with a median survival time of 14 months (95% CI: 12 -17). Multivariate analysis confirmed that the elevated CA19-9 ( HR=1.689, 95% CI: 1.102-2.588), tumor size >4 cm ( HR=1.641, 95% CI: 1.159-2.322), taller-than-wide shapes ( HR=1.450, 95% CI: 1.019-2.065), incomplete hypo-enhancement ( HR=1.618, 95% CI: 1.100-2.380), and liver metastasis ( HR=1.687, 95% CI: 1.175-2.423) were independent risk factors for survival in patients with PDAC. A nomogram model was further constructed for 6-month, 12-month and 3-year survival of patients with PDAC. The areas under the ROC curve were 0.679, 0.705 and 0.815, respectively. The calibration curves suggested that the model was more accurate, and the clinical decision curves showed that the model had a better clinical benefit. Conclusion:The combined use of ultrasound imaging characteristics and clinical indicators could effectively predict the prognosis of PDAC patients. Specifically, tumor size >4 cm, taller-than-wide shapes, incomplete hypo-enhancement, elevated CA19-9, and the presence of liver metastasis are correlated with poorer survival outcomes. The nomogram model constructed on the basis of these factors can be used to assess the survival of patients with PDAC.

Objective:To investigate the predictive value of serum 25 hydroxyvitamin D3[25 (OH) D3], insulin-like growth factor 1 (IGF-1) and bone mineral density (BMD) in the occurrence of osteoporosis (OP) in postmenopausal women.Methods:A total of 87 postmenopausal women admitted to Shanxi Children’s Hospital from Jan. 2020 to Dec. 2023 were chosen and separated into OP group ( n=40) and non-OP group ( n=47) . The differences of clinical features, serum 25 (OH) D3, IGF-1 and BMD were compared, and the correlation analysis between serum 25 (OH) D3, IGF-1 and BMD (including L 1-4 BMD, femoral neck BMD and total hip BMD) was analyzed. Multivariate Logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the influencing factors of OP occurrence in postmenopausal women and the predictive value of serum 25 (OH) D3 and IGF-1 combined with BMD for OP occurrence. Results:Compared with non-OP group, there were no significant differences in age, body mass index (BMI) , menopause time, serum calcium, serum phosphorus, alanine aminotransferase (ALT) , or aspartate aminotransferase (AST) levels in OP group ( t=1.42, 1.03, 1.71, 0.93, 0.76, 0.43, 0.04; P=0.161, 0.306, 0.092, 0.354, 0.452, 0.670, 0.966) , but the proportion of diabetes mellitus significantly increased ( χ2=4.37, P=0.037) . Compared with non-OP group, the levels of serum 25 (OH) D3 and IGF-1 and the values of L1-4 BMD, femoral neck BMD and total hip BMD in OP group significantly decreased ( t=5.37, 4.83, 8.31, 2.01, 3.11; P<0.001, P<0.001, P<0.001, P=0.048, P=0.003) . Correlation analysis showed that serum 25 (OH) D3 and IGF-1 were significantly positively correlated with L 1-4 BMD, femoral neck BMD and total hip BMD ( r=0.37, 0.42, 0.29, 0.33, 0.28, 0.29; P<0.001, P<0.001, P=0.024, P=0.015, P=0.032, P=0.021) . Multivariate Logistic analysis showed that serum 25 (OH) D3, IGF-1 and L 1-4 BMD were independent influencing factors for OP occurrence in postmenopausal women ( P=0.007, 0.019, 0.001) ROC curve showed that the area under the curve (AUC) values of serum 25 (OH) D3, IGF-1, L 1-4 BMD and their combination in the prediction of the occurrence of OP in postmenopausal women were 0.764, 0.752, 0.957 and 0.985, respectively. Conclusion:Serum 25 (OH) D3, IGF-1 and L 1-4 BMD can be used as predictors of OP occurrence in postmenopausal women, and the combined value of the three is higher.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Hepatocellular carcinoma(HCC), the third leading cause of cancer-related death worldwide, is characterized by high mortality and recurrence rates. Common treatments include hepatectomy, liver transplantation, ablation therapy, interventional therapy, radiotherapy, systemic therapy, and traditional Chinese medicine(TCM). While exhibiting specific advantages, these approaches are associated with varying degrees of adverse effects. To alleviate patients' suffering and burdens, it is crucial to explore additional treatments and elucidate the pathogenesis of HCC, laying a foundation for the development of new TCM-based drugs. With emerging research on gut microbiota, it has been revealed that microbiota plays a vital role in the development of HCC by influencing intestinal barrier function, microbial metabolites, and immune regulation. TCM, with its multi-component, multi-target, and multi-pathway characteristics, has been increasingly recognized as a vital therapeutic treatment for HCC, particularly in patients at intermediate or advanced stages, by prolonging survival and improving quality of life. Recent global studies demonstrate that TCM exerts anti-HCC effects by modulating gut microbiota, restoring intestinal barrier function, regulating microbial composition and its metabolites, suppressing inflammation, and enhancing immune responses, thereby inhibiting the malignant phenotype of HCC. This review aims to elucidate the mechanisms by which gut microbiota contributes to the development and progression of HCC and highlight the regulatory effects of TCM, addressing the current gap in systematic understanding of the "TCM-gut microbiota-HCC" axis. The findings provide theoretical support for integrating TCM with western medicine in HCC treatment and promote the transition from basic research to precision clinical therapy through microbiota-targeted drug development and TCM-based interventions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Carcinoma, Hepatocellular/microbiology* ; Liver Neoplasms/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional

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.

The rapid and non-destructive detection of constituent content of fresh tea leaves shows an important reference value for quality identification of tea.Visible near infrared(Vis-NIR)spectroscopy has been used for qualitative and quantitative analysis of chemical components in plant samples with the advantages such as simple,rapid and non-destructive detection.In this study,residual attention convolutional neural network(RACNN)was used to predict the internal constituent content of fresh tea leaves.Firstly,the reflectance spectral data of the samples in the Vis-NIR band range and the constituent contents of gallic acid(GA),gallocatechin(GC),epigallocatechin(EGC),and epigallocatechin gallate(ECG)in fresh tea leaves were collected.Based on the preprocessing of the spectral data,the contents of the four components were predicted using a partial least squares regression(PLSR)model,and the optimal preprocessing was determined.Subsequently,the characteristic bands were extracted using the random forest(RF)algorithm.Finally,the performances of PLSR,convolutional neural network(CNN)and RACNN models were compared.The results showed that for GA,the RACNN model worked best with a validation set coefficient of determination(R2)of 0.946 and a root mean square error of the prediction set(RMSEP)of 1.173;for GC,the RACNN model works best with a validation set R2 of 0.928 and RMSEP of 6.081;for EGC,the RACNN model works best with a validation set R2 of 0.891 and a RMSEP of 15.197;for ECG,the RACNN model worked best with a validation set R2 of 0.878 and a RMSEP of 7.837.The RACNN model established by Vis-NIR spectroscopy combined with chemometrics could realize the accurate detection of the contents of components in fresh tea.

Objective:To explore the role and possible mechanism of ACOT11 in renal fibrosis model mice.Methods:A mouse model of renal fibrosis was established by unilateral ureteral obstruction(UUO)(Sham group and UUO7 group),and the expression of ACOT11 in the kidneys of UUO induced fibrosis mouse models was detected by protein immunoblotting and real-time fluorescence quantitative PCR(qRT-PCR).Subsequently,immunohistochemistry,Masson staining,H&E staining,PAS staining,and other experimental methods were used to detect the expression levels of fibrosis biomarkers fibronectin,α-SMA,and COL-1 in the kidneys of control and experimental group mice.In addition,by constructing ACOT11 gene knockout model mice and using the gene knockout model mice to construct a renal fibrosis model,the expression levels of fibrosis biomarkers such as fibronectin,α-SMA,COL-1,as well as fibrosis mechanism pathway related indicators TGF-β and Smad2 in the kidneys of each group of mice were further detected.Results:The results of WB and qRT-PCR experiments showed that the expression of ACOT11 in the kidney tissue of UUO model mice was significantly reduced compared to the Sham group.After knocking out the ACOT11 gene,H&E staining,PAS staining,and Masson staining showed that pathological inflammatory reactions such as abnormal glomerular and tubular structures,inflammatory cell infiltration and interstitial fibrous tissue proliferation in mice were significantly aggravated compared to the control group,and the expression of fibrosis markers Fibronectin,α-SMA,and COL-1 was significantly higher than that of the control group.Conclusion:ACOT11 plays a protective role in mice with unilateral ureteral obstruction model.After ACOT11 gene knockout,the fibrosis biomarkers of the mouse kidney increases and the degree of fibrosis worsens.

Objective:To investigate the predictive value of serum 25 hydroxyvitamin D3[25 (OH) D3], insulin-like growth factor 1 (IGF-1) and bone mineral density (BMD) in the occurrence of osteoporosis (OP) in postmenopausal women.Methods:A total of 87 postmenopausal women admitted to Shanxi Children’s Hospital from Jan. 2020 to Dec. 2023 were chosen and separated into OP group ( n=40) and non-OP group ( n=47) . The differences of clinical features, serum 25 (OH) D3, IGF-1 and BMD were compared, and the correlation analysis between serum 25 (OH) D3, IGF-1 and BMD (including L 1-4 BMD, femoral neck BMD and total hip BMD) was analyzed. Multivariate Logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the influencing factors of OP occurrence in postmenopausal women and the predictive value of serum 25 (OH) D3 and IGF-1 combined with BMD for OP occurrence. Results:Compared with non-OP group, there were no significant differences in age, body mass index (BMI) , menopause time, serum calcium, serum phosphorus, alanine aminotransferase (ALT) , or aspartate aminotransferase (AST) levels in OP group ( t=1.42, 1.03, 1.71, 0.93, 0.76, 0.43, 0.04; P=0.161, 0.306, 0.092, 0.354, 0.452, 0.670, 0.966) , but the proportion of diabetes mellitus significantly increased ( χ2=4.37, P=0.037) . Compared with non-OP group, the levels of serum 25 (OH) D3 and IGF-1 and the values of L1-4 BMD, femoral neck BMD and total hip BMD in OP group significantly decreased ( t=5.37, 4.83, 8.31, 2.01, 3.11; P<0.001, P<0.001, P<0.001, P=0.048, P=0.003) . Correlation analysis showed that serum 25 (OH) D3 and IGF-1 were significantly positively correlated with L 1-4 BMD, femoral neck BMD and total hip BMD ( r=0.37, 0.42, 0.29, 0.33, 0.28, 0.29; P<0.001, P<0.001, P=0.024, P=0.015, P=0.032, P=0.021) . Multivariate Logistic analysis showed that serum 25 (OH) D3, IGF-1 and L 1-4 BMD were independent influencing factors for OP occurrence in postmenopausal women ( P=0.007, 0.019, 0.001) ROC curve showed that the area under the curve (AUC) values of serum 25 (OH) D3, IGF-1, L 1-4 BMD and their combination in the prediction of the occurrence of OP in postmenopausal women were 0.764, 0.752, 0.957 and 0.985, respectively. Conclusion:Serum 25 (OH) D3, IGF-1 and L 1-4 BMD can be used as predictors of OP occurrence in postmenopausal women, and the combined value of the three is higher.