1.Transcriptome-based Mining of Genes Involved in Regulation of Cyclopeptide B Synthesis in Pseudostellaria heterophylla
Qingsu ZHOU ; Yishu HUANG ; Xiuwen WANG ; Jiao XU ; Xiaohong OU ; Hua HE ; Weike JIANG ; Tao ZHOU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(9):224-230
ObjectiveThe biosynthesis of heterophyllin B (HB), a cyclopeptide from Pseudostellaria heterophylla, is regulated by various abiotic stresses. Elucidating the transcriptional regulatory mechanism underlying HB biosynthesis is of great guiding significance for the directional improvement of P. heterophylla varieties and the enhancement of HB content. MethodsBased on transcriptome data from different tissues of P. heterophylla, transcription factors (TFs) specifically upregulated and highly expressed in the phloem of tuberous roots were screened through a combination of Mfuzz time-series clustering, transcription factor family prediction, and correlation analysis. Quantitative real-time polymerase chain reaction (Real-time PCR) was employed to analyze expression patterns of candidate TFs under abscisic acid (ABA) induction, and the dual-luciferase reporter assay was applied to verify their regulatory effects on HB precursor genes. ResultsContent determination showed that HB accumulated at the highest in the phloem of P. heterophylla tuberous roots (34 μg
2.An Attention-weighted Tri-modal Ultrasound Network (TUS-Net) for Screening of Atypical Hepatocellular Carcinoma From LR-M Liver Nodules
He-Chong ZHANG ; Liang-Hui HUANG ; Xue-Hua WANG ; Shang-Lin JIANG ; Ying-Ying CHEN ; Ya-Guang ZENG ; Wei ZHENG
Progress in Biochemistry and Biophysics 2026;53(5):1485-1498
ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.
3.An Attention-weighted Tri-modal Ultrasound Network (TUS-Net) for Screening of Atypical Hepatocellular Carcinoma From LR-M Liver Nodules
He-Chong ZHANG ; Liang-Hui HUANG ; Xue-Hua WANG ; Shang-Lin JIANG ; Ying-Ying CHEN ; Ya-Guang ZENG ; Wei ZHENG
Progress in Biochemistry and Biophysics 2026;53(5):1485-1498
ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.
4.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
5.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
6.Psychological stress-activated NR3C1/NUPR1 axis promotes ovarian tumor metastasis.
Bin LIU ; Wen-Zhe DENG ; Wen-Hua HU ; Rong-Xi LU ; Qing-Yu ZHANG ; Chen-Feng GAO ; Xiao-Jie HUANG ; Wei-Guo LIAO ; Jin GAO ; Yang LIU ; Hiroshi KURIHARA ; Yi-Fang LI ; Xu-Hui ZHANG ; Yan-Ping WU ; Lei LIANG ; Rong-Rong HE
Acta Pharmaceutica Sinica B 2025;15(6):3149-3162
Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.
7.The 5-HT Descending Facilitation System Contributes to the Disinhibition of Spinal PKCγ Neurons and Neuropathic Allodynia via 5-HT2C Receptors.
Xiao ZHANG ; Xiao-Lan HE ; Zhen-Hua JIANG ; Jing QI ; Chen-Chen HUANG ; Jian-Shuai ZHAO ; Nan GU ; Yan LU ; Qun WANG
Neuroscience Bulletin 2025;41(7):1161-1180
Neuropathic pain, often featuring allodynia, imposes significant physical and psychological burdens on patients, with limited treatments due to unclear central mechanisms. Addressing this challenge remains a crucial unsolved issue in pain medicine. Our previous study, using protein kinase C gamma (PKCγ)-tdTomato mice, highlights the spinal feedforward inhibitory circuit involving PKCγ neurons in gating neuropathic allodynia. However, the regulatory mechanisms governing this circuit necessitate further elucidation. We used diverse transgenic mice and advanced techniques to uncover the regulatory role of the descending serotonin (5-HT) facilitation system on spinal PKCγ neurons. Our findings revealed that 5-HT neurons from the rostral ventromedial medulla hyperpolarize spinal inhibitory interneurons via 5-HT2C receptors, disinhibiting the feedforward inhibitory circuit involving PKCγ neurons and exacerbating allodynia. Inhibiting spinal 5-HT2C receptors restored the feedforward inhibitory circuit, effectively preventing neuropathic allodynia. These insights offer promising therapeutic targets for neuropathic allodynia management, emphasizing the potential of spinal 5-HT2C receptors as a novel avenue for intervention.
Animals
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Neuralgia/physiopathology*
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Protein Kinase C/metabolism*
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Receptor, Serotonin, 5-HT2C/metabolism*
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Hyperalgesia/physiopathology*
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Mice, Transgenic
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Mice
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Spinal Cord/metabolism*
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Serotonin/metabolism*
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Male
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Neurons/metabolism*
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Mice, Inbred C57BL
8.Design and application of a nasogastric tube auxiliary pushing device and intubation kit.
Qiao HE ; Xiaoyun ZHANG ; Yinfen XIAO ; Hua HUANG ; Junyao FAN
Chinese Critical Care Medicine 2025;37(8):771-773
As a common clinical treatment technique, nasogastric tube insertion plays an important role in assisting in disease diagnosis and treatment, and promoting patient recovery. Nasogastric tubes currently used in clinical practice are packaged individually without accompanying sterile materials, hence additional materials need to be prepared before operation, which is complicated and prone to omission, consumes clinical manpower, and increases the proportion of departmental consumption. The operator needs to hold the nasogastric tube with one hand and place it with the other hand during operation, the lack of auxiliary tool for uniformly controlling the placement of gastric tubes may easily lead to tube failure due to patient intolerance, agitation, or uneven force exerted by the operator, and improper force may even result in violent tube placement, leading to adverse outcomes such as mucosal bleeding and aspiration into the airway. Medical staff of intensive care unit of department of infectious diseases of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology have designed a nasogastric tube auxiliary pushing device and an intubation kit to overcome the above problems, and obtaining National Utility Model Patent of China (patent number: ZL 2024 2 0300856.X). The device consists of two parts: a nasogastric tube auxiliary pushing device and a nasogastric tube insertion kit. Nasogastric tube auxiliary pushing device mainly consists of a nasogastric tube with guide wire, a circular wire harness, and a booster base with a pushing element. The tube insertion kit includes sterile treatment trays, main placement slots, and other operational accessory slots. The new nasogastric tube auxiliary pushing device and tube insertion kit integrates packaging and portable design, providing stable and uniform assistance for safe insertion of nasogastric tubes by a single person, which is able to reduce the occurrence of complications, ensure patient safety, improve patient comfort, and reduce occupational exposure risks, making it suitable for clinical promotion.
Intubation, Gastrointestinal/methods*
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Equipment Design
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Humans
9.International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025).
Sheng-Sheng ZHANG ; Lu-Qing ZHAO ; Xiao-Hua HOU ; Zhao-Xiang BIAN ; Jian-Hua ZHENG ; Hai-He TIAN ; Guan-Hu YANG ; Won-Sook HONG ; Yu-Ying HE ; Li LIU ; Hong SHEN ; Yan-Ping LI ; Sheng XIE ; Jin SHU ; Bin-Fang ZENG ; Jun-Xiang LI ; Zhen LIU ; Zheng-Hua XIAO ; Jing-Dong XIAO ; Pei-Yong ZHENG ; Shao-Gang HUANG ; Sheng-Liang CHEN ; Gui-Jun FEI
Journal of Integrative Medicine 2025;23(5):502-518
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*
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Humans
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Medicine, Chinese Traditional/methods*
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Practice Guidelines as Topic
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Drugs, Chinese Herbal/therapeutic use*
10.Exploration of OBE-Driven Experimental Teaching Model in Clinical Hematology Laboratory Testing
Qing ZHANG ; Zhuo LI ; Hong-yan HE ; Jun-hua HUANG ; Hai-yan LI
Progress in Modern Biomedicine 2025;25(18):3017-3022
With the continuous advancement of educational technology and the expanding scope of medical education,the limitations of traditional teaching models in clinical hematology laboratory instruction have become increasingly evident.To address the demands of cultivating laboratory medicine professionals in the new era,an innovative teaching approach has been explored using the"Clinical Hematology Laboratory"course at Xi'an Medical College as a practical platform,aiming to enhance the professional competence of laboratory medicine students.Guided by the Outcome-Based Education(OBE)concept,this study integrates diverse teaching methodologies,including Problem-Based Learning(PBL),Case-Based Learning(CBL),flipped classroom,and virtual simulation,to construct a student-centered,competency-oriented teaching system.Through the optimization of teaching objectives and the strategic combination of instructional methods,this research provides novel insights and practical paradigms for clinical hematology laboratory education,thereby contributing to the sustainable development of laboratory medicine training.

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