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*

Objective To propose a low-dose CT reconstruction algorithm across different scanners based on federated feature learning(FedCT)to improve the generalization of deep learning models for multiple CT scanners and protect data privacy.Methods In the proposed FedCT framework,each client is assigned an inverse Radon transform-based reconstruction model to serve as a local network model that participates in federated learning.A projection-domain specific learning strategy is adopted to preserve the geometry specificity in the local projection domain.Federated feature learning is introduced in the model,which utilizes conditional parameters to mark the local data and feed the conditional parameters into the network for encoding to enhance the generalization of the model in the image domain.Results In the cross-client,multi-scanner,and multi-protocol low-dose CT reconstruction experiments,FedCT achieved the highest PSNR(+2.8048,+2.7301,and +2.7263 compared to the second best federated learning method),the highest SSIM(+0.0009,+0.0165,and +0.0131 in the same comparison),and the lowest RMSE(-0.6687,-1.5956,and-0.9962).In the ablation experiment,compared with the general federated learning strategy,the model with projection-specific learning strategy showed an average improvement by 1.18 on Q1 of the PSNR and an average decrease by 1.36 on Q3 of the RMSE on the test set.The introduction of federated feature learning in FedCT further improved the Q1 of the PSNR on the test set by 3.56 and reduced the Q3 of the RMSE by 1.80.Conclusion FedCT provides an effective solution for collaborative construction of CT reconstruction models,which can enhance model generalization and further improve the reconstruction performance on global data while protecting data privacy.

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Objective To propose a low-dose CT reconstruction algorithm across different scanners based on federated feature learning(FedCT)to improve the generalization of deep learning models for multiple CT scanners and protect data privacy.Methods In the proposed FedCT framework,each client is assigned an inverse Radon transform-based reconstruction model to serve as a local network model that participates in federated learning.A projection-domain specific learning strategy is adopted to preserve the geometry specificity in the local projection domain.Federated feature learning is introduced in the model,which utilizes conditional parameters to mark the local data and feed the conditional parameters into the network for encoding to enhance the generalization of the model in the image domain.Results In the cross-client,multi-scanner,and multi-protocol low-dose CT reconstruction experiments,FedCT achieved the highest PSNR(+2.8048,+2.7301,and +2.7263 compared to the second best federated learning method),the highest SSIM(+0.0009,+0.0165,and +0.0131 in the same comparison),and the lowest RMSE(-0.6687,-1.5956,and-0.9962).In the ablation experiment,compared with the general federated learning strategy,the model with projection-specific learning strategy showed an average improvement by 1.18 on Q1 of the PSNR and an average decrease by 1.36 on Q3 of the RMSE on the test set.The introduction of federated feature learning in FedCT further improved the Q1 of the PSNR on the test set by 3.56 and reduced the Q3 of the RMSE by 1.80.Conclusion FedCT provides an effective solution for collaborative construction of CT reconstruction models,which can enhance model generalization and further improve the reconstruction performance on global data while protecting data privacy.

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

This study developed an optimal pre-processing technique for the reference substance of the classic formula Gualou Xiebai Banxia Decoction(GXBD) and established a comprehensive quality control method for GXBD reference substance to provide a reference for its overall quality evaluation. The authors prepared 15 batches of GXBD samples and innovatively used the extracted ion chromatogram under the base peak chromatogram mode to establish a liquid chromatography-mass spectrometry(LC-MS) fingerprint, identify characteristic peaks, and perform quantitative analysis of indicator components. The yield of the 15 batches of GXBD samples ranged from 50.28% to 76.20%. In the positive ion mode, 12 common characteristic peaks were detected in the LC-MS fingerprint, and the structures of five common peaks were identified by comparison with reference standards. The similarity between the fingerprint profiles of different batches of samples and the reference fingerprint profile ranged from 0.920 to 0.984. Finally, liquid chromatography-triple quadrupole mass spectrometry(LC-QQQ/MS) in multiple reaction monitoring(MRM) mode was used to determine the content of eight indicator components in GXBD, including loliolide, chrysoeriol, rutin, cucurbitacin D, macrostemonoside Ⅰ, 25S-timosaponin B Ⅱ, 25R-timosaponin B Ⅱ, and peptide proline-tryptophan-valine-proline-glycine(PWVPG). The method established in this study can reduce matrix interference in the compound, and it has good accuracy, stability, and practical value. It effectively reflects the quality attributes of GXBD samples and can be used for the comprehensive quality control of GXBD.
Chromatography, Liquid ; Tandem Mass Spectrometry/methods* ; Drugs, Chinese Herbal/chemistry* ; Proline ; Chromatography, High Pressure Liquid/methods*

Objective:To investigate the awareness of diabetes knowledge among the health examination population and its influencing factors.Methods:A cross-sectional study. From september to november 2022, the subjects of six health examination centers located in six different cities (Beijing, Shanghai, Tianjin, Chongqing, Xiamen, Hangzhou) in China were investigated in the form of questionnaires to investigate the awareness of diabetes core information and the level of trust to different information sources of diabetes knowledge. According to the questionnaire results, the subjects were divided into a high awareness group of diabetes core information and a low awareness group. Logistic regression was used to analyze the influencing factors of diabetes core information awareness; the t-test was used to compare the trust degree of the two groups to different information sources. Results:A total of 9 315 people were included in the six centers, including 4 932 men (52.90%) with an average age of (39.36±12.64) years and 4 383 women (47.10%) with a mean age of (37.47±11.85) years. Only 36% of the people had high awareness of diabetes core information; variables such as gender, age, education level, physical examination frequency in the past three years, package price of this physical examination, self-evaluation of diabetes knowledge, diabetes status, and city of residence were variables that affect the level of awareness of core information related to diabetes (all P<0.05). Compared with the low awareness group of diabetes core information, the high awareness group trusted professional medical staff ( t=-9.597, P<0.05) and community health promotion more ( t=-5.014, P<0.05), but did not trust the emerging popular science propaganda means, such as WeChat official accounts/WeChat groups/QQ groups, Internet web page, Tiktok/Kwai and other short video APPs. Conclusion:The awareness rate of diabetes knowledge among the health examination population is low, and it is affected by many factors; Health education on diabetes knowledge should be carried out for people undergoing physical examination.

Postoperative adhesion (PA) is currently one of the most unpleasant complications following surgical procedures. Researchers have developed several new strategies to alleviate the formation of PA to a great extent, but so far, no single measure or treatment can meet the expectations and requirements of clinical patients needing complete PA prevention. Chinese medicine (CM) has been widely used for thousands of years based on its remarkable efficacy and indispensable advantages CM treatments are gradually being accepted by modern medicine. Therefore, this review summarizes the formating process of PA and the efficacy and action mechanism of CM treatments, including their pharmacological effects, therapeutic mechanisms and advantages in PA prevention. We aim to improve the understanding of clinicians and researchers on CM prevention in the development of PA and promote the in-depth development and industrialization process of related drugs.
Humans ; Medicine, Chinese Traditional ; Tissue Adhesions/prevention & control* ; Industrial Development ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: To explore the influencing factors of low back pain and the relationship of the influence of bad working posture, weight load and frequency of load and the dose-response relationship among the occupational workers of key industries in China. METHODS: A total of 57 501 employees from 15 key industries in China were selected as research subjects using stratified cluster sampling method. The occurrence of low back pain in the past one year, as well as occupational factors such as job type, labor organization and work posture were investigated by using the Chinese version Musculoskeletal Disorders Questionnaire. RESULTS: The prevalence of low back pain in the occupational population of key industries in China was 16.4%(9 448/57 501). Multivariate Logistic regression analysis showed that the risk of low back pain in females was higher than that in males(P<0.01). Married, obese, occasional and frequent smokers, and a history of lower back disease were associated with increased risk of low back pain(all P<0.05). The risk of low back pain was associated with older age, higher education level, and lower frequency of physical exercise(all P<0.01). The risk of low back pain was higher with longer working time, greater back curvature, and the high frequency of long standing and sitting position work, uncomfortable working posture, repeated operation per minute, and lifting>5 kg weight(all P<0.01). CONCLUSION: The influencing factors of low back pain in the occupational population of key industries in China include bad working posture, high frequency load, weight load and other individual factors. There is a dose-response relationship with low back posture load and frequency of load.

Background and Objectives: p21, an important member of the Cip/Kip family, is involved in inhibitory effects of RUNX1b overexpression during the early stage of human hematopoiesis. Methods: and Results: We established a human embryonic stem cell (hESC) line with inducible expression of p21 (p21/hESCs). Overexpression of p21 did not influence either mesoderm induction or emergence of CD34＋ cells, but it significantly decreased the production of CD43＋ cells and changed the expression profile of hematopoiesis-related factors, leading to the negative effects of p21 on hematopoiesis. Conclusions In RUNX1b/hESC co-cultures when RUNX1b was induced from D0, perturbation of the cell cycle caused by upregulation of p21 probably prevented the appearance of CD43＋ cells, but not CD34＋ cells. The mechanisms via which CD34＋ cells are blocked by RUNX1b overexpression remain to be elucidated.