OBJECTIVE To investigate the improvement effects and mechanism of Achyranthes bidentata total saponins （ABS） extract on vascular endothelial dysfunction in spontaneously hypertensive rat （SHR） based on cytochrome P450 4A （CYP4A）/20-hydroxyeicosatetetraenoic acid （20-HETE）/G protein-coupled receptor 75 （GPR75） axis. METHODS Ten Wistar- Kyoto rats were taken as the normal control group. Forty SHR were first stratified by systolic blood pressure and then， within each stratum， randomly assigned using a random-number table to the model group （MOD group）， captopril positive control group （CAP group， 10 mg/kg）， ABS low- and high-dose extract groups （ABS-L group， ABS-H group， 60 and 120 mg/kg）， with 10 rats in each group. Animals in each group were given the corresponding drug or equal volume of pure water by gavage， once a day， for 28 consecutive days. After the last administration， systolic blood pressure of rats was measured. The levels of vasoactive substances， inflammatory factors and oxidative stress indicators in serum were measured. The pathological changes of rat thoracic aorta were observed. The level of reactive oxygen species （ROS） in aortic tissue was analyzed. The expressions of endothelial nitric oxide synthase （eNOS）， CYP4A， GPR75， nuclear factor-κB p65 （NF-κB p65）， phosphorylated NF-κB p65， p22phox， and reduced nicotinamide adenine dinucleotide phosphate oxidase 4（NOX4） in thoracic aorta tissue were detected. RESULTS After 28 d of treatment， compared with MOD group， the systolic blood pressure of rats in the ABS-L and ABS-H groups decreased significantly. The levels of 20-HETE， angiotensin Ⅱ， interleukin-1β， interleukin-6， tumor necrosis factor-α， intercellular cell adhesion molecule-1 and malondialdehyde in serum were significantly reduced （P＜0.05 or P＜0.01）， while the levels of nitric oxide， superoxide dismutase， glutathione peroxidase and catalase were significantly increased （P＜0.05 or P＜0.01）. Intimal damage of thoracic aorta was reduced， and endothelial cell morphology was improved. The expressions of ROS， CYP4A， GPR75， p22phox， NOX4 and the phosphorylation level of NF-κB p65 protein in thoracic aorta were down-regulated or reduced （P＜0.05 or P＜0.01）， while the expression of eNOS was up-regulated （P＜0.05 or P＜0.01）. CONCLUSIONS ABS extract may alleviate the inflammatory response and oxidative stress in SHR effectively by down-regulating the expression of CYP4A， reducing the production of 20-HETE， inhibiting the activation of GPR75， and subsequently suppressing the activation of downstream NF-κB and NOX4， thereby improving hypertension-related vascular endothelial dysfunction.

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.

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.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

BACKGROUND: There is a gap in understanding the effects of different acupoints and treatment methods (acupuncture and moxibustion) on microcirculatory changes in the lumbar region. OBJECTIVE: This study aimed to assess the thermal effects of acupuncture at Weizhong (BL40), with acupuncture at Chize (LU5) and moxibustion at both acupoints as control interventions. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: In this randomized controlled trial, 140 healthy participants were equally divided into four groups: acupuncture at BL40 (Acu-BL40), acupuncture at LU5 (Acu-LU5), moxibustion at BL40 (Mox-BL40) and moxibustion at LU5 (Mox-LU5). Participants underwent a 30-minute session of their assigned treatment. Infrared thermal imaging was used to collect temperature data on the areas of interest for analysis. MAIN OUTCOME MEASURES: The primary measure was the change in average temperature of the observed area after the intervention. The secondary measures included periodic temperature changes every 5 min and the temperature changes of the Governor Vessel and Bladder Meridian in the observed area after the intervention. RESULTS: Significant interactions were observed between treatments and acupoints affecting temperature (P < 0.001). The Acu-BL40 group showed a notably higher increase in mean temperature after 30 min compared to the Acu-LU5 and Mox-BL40 groups, with increases of 0.29 (95% confidence interval [CI] = 0.17 to 0.41) and 0.24 (95% CI = 0.08 to 0.41) °C, respectively. CONCLUSION: Acupuncture at BL40 acupoint can significantly increase the mean temperature in the observed area, highlighting the specific thermal effect of acupuncture compared to moxibustion in the lumbar area. This suggests a potential therapeutic benefit of acupuncture at BL40 for managing lumbar conditions. TRIAL REGISTRATION ClinicalTrials.gov (NCT05665426). Please cite this article as: Zheng SY, Wang XY, Lin LN, Liu S, Huang XX, Liu YY, Yu XS, Pan W, Fang JQ, Liang Y. Lumbar temperature change after acupuncture or moxibustion at Weizhong (BL40) or Chize (LU5) in healthy adults: A randomized controlled trial. J Integr Med. 2025; 23(2): 145-151.
Adult ; Female ; Humans ; Male ; Young Adult ; Acupuncture Points ; Acupuncture Therapy ; Body Temperature ; Healthy Volunteers ; Lumbosacral Region/physiology* ; Moxibustion ; Adolescent

The structure of intestinal tissue is complex. In vitro simulation of intestinal structure and function is important for studying intestinal development and diseases. Recently, organoids have been successfully constructed and they have come to play an important role in biomedical research. Organoids are miniaturized three-dimensional (3D) organs, derived from stem cells, which mimic the structure, cell types, and physiological functions of an organ, making them robust models for biomedical research. Intestinal organoids are 3D micro-organs derived from intestinal stem cells or pluripotent stem cells that can successfully simulate the complex structure and function of the intestine, thereby providing a valuable platform for intestinal development and disease research. In this article, we review the latest progress in the construction and application of intestinal organoids.
Organoids/cytology* ; Intestines/physiology* ; Humans ; Animals ; Pluripotent Stem Cells

Objective:To explore the deubiquitination modification of the deubiquitinase BRCC3 in rats with neuropathic pain (NPP) treated with meridian tuina of Zhuang medicine and its analgesic molecular mechanism.Methods:Rats were divided into normal group, sham-operation group, model group, sham-tuina group, and meridian tuina of Zhuang medicine group using a random number table method, with 9 rats in each group. Except for the normal and sham operation groups, spinal nerve ligation models were prepared in all other groups. On the first day after surgery, intervention was carried out on the meridian tuina of Zhuang medicine and sham-tuina groups for 14 days, while the other three groups were not intervened; the paw withdrawal mechanical threshold (PWMT) and paw withdrawal thermal latency (PWTL) of each group of rats were measured at 0 days before operation, 1, 7, and 14 days after operation. Western blot was used to detect the expressions of BRCC3 and NLRP3 proteins in spinal cord tissue, and ELISA was used to detect the level of IL-1β in serum.Results:On postoperative 7 and 14 d, compared with the model group, the meridian tuina of Zhuang medicine group showed an increase in PWMT and PWTL, a decrease in NLPR3 and BRCC3 expression in spinal cord tissue, and a decrease in serum IL-1β levels ( P<0.05). Compared with the sham-tuina group, the meridian tuina of Zhuang medicine group showed an increase in PWMT and PWTL, a decrease in NLRP3 protein expression in spinal cord tissue, and a decrease in IL-1β levels in serum ( P<0.05). Conclusion:Meridian tuina of Zhuang medicine can alleviate pain sensitivity in SNL model rats, and its mechanism is related to the inhibition of the expression of deubiquitinase BRCC3 by meridian massage of Zhuang medicine, which increases the ubiquitination level of NLRP3 and hinders its activation, thereby blocking the immune inflammatory response mediated by inflammatory factors.

The zebrafish model has attracted much attention due to its strong reproductive ability, short research cycle, and ease of maintenance. It has always been an important vertebrate model system, often used to carry out human disease research. Its motor behavior features have the advantages of being simpler, more intuitive, and quantifiable. In recent years, it has received widespread attention in the study of traditional Chinese medicine(TCM)for the treatment of sleep disorders, neurodegenerative diseases, fatigue, epilepsy, and other diseases. This paper reviews the characteristics of zebrafish motor behavior and its applications in the pharmacodynamic verification and mechanism research of TCM extracts, active ingredients, and TCM compounds, as well as in active ingredient screening and safety evaluation. The paper also analyzes its advantages and disadvantages, with the aim of improving the breadth and depth of zebrafish and its motor behavior applications in the field of TCM research.
Zebrafish/physiology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Drug Evaluation, Preclinical/methods* ; Animals ; Sleep Wake Disorders/physiopathology* ; Epilepsy/physiopathology* ; Neurodegenerative Diseases/physiopathology* ; Fatigue/physiopathology* ; Behavior, Animal/physiology* ; Motor Activity/physiology*