To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveTo analyze the research status, hotspots and development trends in the application of virtual reality (VR) technology in managing negative emotions and postoperative rehabilitation of perioperative patients over the past decade. MethodsLiteratures related to the application of VR technology in managing negative emotions and postoperative rehabilitation of perioperative patients were retrieved from Web of Science Core Collection database and CNKI, covering the period from January, 2015 to August, 2025, and CiteSpace 6.3.R1 was used for bibliometric analysis. ResultsA total of 267 English literatures and 130 Chinese literatures were included, with the annual number of publications showing an upward trend. The United States was the country with the largest number of publications in English literatures, and Erasmus University Rotterdam was the institution with the largest number of publications. High-frequency keywords included virtual reality, pain, surgery, anxiety and distraction. Research hotspots mainly focused on functional exercise, negative emotions, pain management and multimodal intervention strategies. English researches were deepening towards virtual reality exposure therapy, mechanism exploration and personalized schemes, while Chinese researches focused more on the verification of rehabilitation effects. ConclusionResearches on the application of VR technology in the management of perioperative patients are rapidly developing, with research hotspots shifting from single technology application to multimodal and personalized integrated intervention. Future research should focus on exploring its intervention mechanisms, personalized schemes and the breadth of cross-departmental applications.

As a patented characteristic medicine of Yi ethnic minority， Pingxuan capsules have the effects of nourishing the liver and kidney， pacifying the liver， and subduing Yang. With the main indications of dizziness， headache， palpitations， tinnitus， insomnia， dreaminess， waist and knee soreness caused by liver-kidney deficiency and liver Yang upward disturbance， Pingxuan capsules are widely used in the treatment of posterior circulation ischemic vertigo， vestibular migraine， benign paroxysmal positional vertigo. However， the current knowledge is limited regarding the efficacy， syndrome differentiation， and safety of this medicine. On the basis of summarizing the experience of clinicians and the existing evidence， this study invites clinical experts of traditional Chinese and Western medicine， pharmaceutical experts， and methodological experts from relevant fields across China to conduct evidence-based evaluation of Pingxuan capsules. The evaluation follows the Specifications for the Development of Clinical Expert Consensus on Chinese Patent Medicines issued by the Standardization Office of the China Association of Chinese Medicine， and reaches 5 recommendations and 16 consensus suggestions. The consensus clarifies the clinical applications， efficacy， dose， course of treatment， combination of medicines， precautions， and contraindications of Pingxuan capsules in the treatment of vertigo and explains the safety of clinical application. This consensus is applicable to clinicians （traditional Chinese medicine， Western medicine， and integrated traditional Chinese and Western medicine） and pharmacists in tertiary hospitals， secondary hospitals， and community-level medical and health institutions across China， providing a reference for the rational use of Pingxuan capsules in the treatment of vertigo. It is hoped that the promotion of this consensus can facilitate the rational use of drugs in clinical practice， reduce the risk of drug use， and give full play to the advantages of Pingxuan capsules in the treatment of vertigo diseases. This consensus has been reviewed and published by the China Association of Chinese Medicine， with the number GS/CACM330-2023.

Objective To explore the accuracy of artificial intelligence-based diagnosis of ovarian malignant tumors and the identification of benign and malignant tumors under transabdominal scanning and transvaginal scanning methods. Methods A dataset of transabdominal and transvaginal two-dimensional ultrasound images was used and the images were preprocessed to enhance quality. The region of interest was segmented and divided into a training set and a test set. A convolutional neural network (CNN) was trained on the images in the training set, and the accuracy of the model on the test set was calculated. Results Transvaginal scanning was 14% more accurate in diagnosing malignant ovarian tumors than transabdo-minal scanning on the test set. For identifying the benign and malignant ovarian tumors containing cystic components, a mixture of transvaginal and transabdominal scanning increased the accuracy by 9.7% over transabdominal scanning alone. Conclusion CNN can identify ovarian malignant tumors under both scanning methods, but the accuracy of transvaginal scanning is higher than that of transabdominal scanning, and the CNN model has a higher accuracy in identifying benign and malignant ovarian tumors under transvaginal scanning.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.