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*

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Objective To propose a image processing strategy based on salient object detection algorithm for optimizing the presentation of prosthetic visual information at a limited resolution level,aiming to detect and enhance the salient objects in the scene and remove the background information.Methods A salient object detection model combining CNN and Transformer was used to extract salient objects.On this basis,methods such as object magnification,contour enhancement and contrast enhancement were utilized to optimize the image information.Psychophysical experiments were carried out at 5 resolution levels(16×16,24×24,32×32,48×48 and 64×64).Results In the simulated prosthetic vision,this image processing strategy had a remarkable effect on improving the object recognition ability of the subjects.Regardless of the resolutions of 16×16,24×24,32×32,48×48 and 64×64,the proposed strategy achieved the highest recognition accuracies,specifically 34%±6%,56%±9%,72%±9%,89%±4%and 96%±2%.Conclusion Using the salient object detection method and image processing strategy to extract and enhance salient objects can help prosthesis implant recipients effectively improve their object recognition ability.

Objective To design a performance testing platform to evaluate the working status and performance characteristics of the ventilator proportional solenoid valve.Methods The performance testing platform had its hardware including a high-pressure gas source,a pressure regulating valve,sensors and etc,and its software designed based on PyQt5 and composed of several modules for data acquisition,parameter setting,image display,indicator computation,result output and etc.Two kinds of proportional solenoid valves(Valve 1、Valve2)were selected for static and dynamic tests to verify the performance of the platform.Results The platform developed facilitated the proportional solenoid valve to carry out accurate computation of static and dynamic indicators at real time and time domain and waveform feature extraction of sensor data by precision control and data acquisition for the proportional solenoid valve.Static tests showed that Valve 1 gained advantages over Valve 2 in static flow characteristics involving in lowered repeatability,return error and offset while enhanced stability;dynamic tests indicated Valve 2 had rapid flow variations and significant flow fluctuation impacts,Valve 1 showed smooth dynamic response changes,and Valve 2 behaved better than Valve 1 in dynamic performance.Conclusion The testing platform developed comprehensively demonstrates the performance characteristics and working performance of the ventilator proportional solenoid valve,which is of great significance to enhance the reliability and safety of the ventilator.[Chinese Medical Equipment Journal,2025,46(1):13-19]

Objective To investigate the effects of short-term and long-term high-fructose diets on hippocampal neurometabolites and anxiety and depression-like behaviors in mice,revealing the potential mechanisms of high-fructose diets in mood disorders and providing a experimental basis for the prevention and treatment of related diseases.Methods C57BL/6J male mice were randomly divided into two groups,control group(standard diet,n=10)and experimental group(high-fructose diet,n=10).Four weeks(short-term)and eight weeks(long-term)later,each group of mice was examined for body weight and fasting blood glucose,and neurometabolites levels in the hippocampus were detected by hydrogen proton magnetic resonance spectroscopy(1H-MRS),followed by the open-field test,the forced-swimming test,and the tail-suspension test to evaluate anxiety-like and depression-like behaviors.Results High fructose diet for 4 weeks elevated glutamate levels and reduced glutathione and myo-inositol levels in mice,accompanied by shortened immobility time in the forced swim test.High fructose diet for 8 weeks not only led to abnormalities in body weight and glucose metabolism but also caused a reversal decrease in hippocampal glutamate levels and induced significant anxiety-like behaviors,and the decrease in hippocampal glutamate levels showed a significant negative correlation with the enhancement of anxiety-like behaviors.Conclusion Altered hippocampal glutamate levels may be a key contributing factor to the anxiety-like behaviors induced by long-term high-fructose diet.

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female

Objective To design a performance testing platform to evaluate the working status and performance characteristics of the ventilator proportional solenoid valve.Methods The performance testing platform had its hardware including a high-pressure gas source,a pressure regulating valve,sensors and etc,and its software designed based on PyQt5 and composed of several modules for data acquisition,parameter setting,image display,indicator computation,result output and etc.Two kinds of proportional solenoid valves(Valve 1、Valve2)were selected for static and dynamic tests to verify the performance of the platform.Results The platform developed facilitated the proportional solenoid valve to carry out accurate computation of static and dynamic indicators at real time and time domain and waveform feature extraction of sensor data by precision control and data acquisition for the proportional solenoid valve.Static tests showed that Valve 1 gained advantages over Valve 2 in static flow characteristics involving in lowered repeatability,return error and offset while enhanced stability;dynamic tests indicated Valve 2 had rapid flow variations and significant flow fluctuation impacts,Valve 1 showed smooth dynamic response changes,and Valve 2 behaved better than Valve 1 in dynamic performance.Conclusion The testing platform developed comprehensively demonstrates the performance characteristics and working performance of the ventilator proportional solenoid valve,which is of great significance to enhance the reliability and safety of the ventilator.[Chinese Medical Equipment Journal,2025,46(1):13-19]

Objective To propose a image processing strategy based on salient object detection algorithm for optimizing the presentation of prosthetic visual information at a limited resolution level,aiming to detect and enhance the salient objects in the scene and remove the background information.Methods A salient object detection model combining CNN and Transformer was used to extract salient objects.On this basis,methods such as object magnification,contour enhancement and contrast enhancement were utilized to optimize the image information.Psychophysical experiments were carried out at 5 resolution levels(16×16,24×24,32×32,48×48 and 64×64).Results In the simulated prosthetic vision,this image processing strategy had a remarkable effect on improving the object recognition ability of the subjects.Regardless of the resolutions of 16×16,24×24,32×32,48×48 and 64×64,the proposed strategy achieved the highest recognition accuracies,specifically 34%±6%,56%±9%,72%±9%,89%±4%and 96%±2%.Conclusion Using the salient object detection method and image processing strategy to extract and enhance salient objects can help prosthesis implant recipients effectively improve their object recognition ability.

italic>Acanthopanax senticosus is one of the genuine regional herb in Northeast China. In this study, we identified the germplasm resources of commercial A. senticosus samples based on atpI and atpB_rbcL according to the previous chloroplast genome sequencing results, and determinated the content of syringin by HPLC to evaluated the quality of commercial samples. A total of 80 A. senticosus samples were collected from 47 cities in 24 provinces. DNA was extracted to amplify the products of atpI and atpB_rbcL by PCR. The results showed that 7 haplotypes (H2, H5, H8, H10, H12, H14, H23) were formed by the combined analysis of the two gene fragments. H2 from Yichun in Heilongjiang, Shangzhi in Harbin, Suihua in Heilongjiang, Fushun in Liaoning, Benxi in Liaoning, Changbai in Jilin and Jingyu in Jilin were the dominant genotype, representing 58.75% of the total samples. H14 and H23 were the unique haplotypes of the producing area. It is speculated that the commercial A. senticosus samples with haplotypes of H14 and H23 are from Raohe, Shuangyashan, Heilongjiang and Mingshui, Suihua, Heilongjiang, respectively. HPLC analysis indicated that the content of syringin in 73.96% of the samples met the Pharmacopoeia standards. There was a significant difference in the content of syringin among the samples, ranging from 0.003 7% to 0.524 5%, with a difference of 0.520 8%, indicating that the quality of the samples in the market of A. senticosus was uneven. However, there were no significant differences in the contents of syringin in the commercial A. senticosus among different haplotypes. The content of syringin in the haplotype H23 in the market sample is relatively high, so it may be a germplasm with better quality. This study researched the germplasm resources and medicinal materials quality of commercial A. senticosus samples and will help guide the commercial circulation, reasonable medication of A. senticosus, and the screening of excellent germplasm.