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.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveThis paper aims to conduct the feature analysis and correlation analysis on the ocular collateral features and differential metabolites in patients with chronic hepatitis B （CHB） complicated by glucose metabolism disorder （GMD），particularly those with the damp-heat syndrome type，by integrating shadowless scleral imaging and metabolomics technologies. MethodsA total of 313 patients were recruited from the Hepatology and Endocrinology Outpatient Departments of Public Health Clinical Center of Chengdu according to the inclusion/exclusion criteria，and they were divided into a CHB group and a CHB complicated by GMD groups （damp-heat syndrome group and non-damp-heat syndrome group）. All patients underwent high-definition ocular image acquisition and feature extraction using an intelligent analysis system for shadowless scleral imaging to analyze the differences in the counting of morphological feature scores of ocular collaterals among groups. By using a digital sampling method，24 patients from each group were randomly selected，along with 20 healthy volunteers，for untargeted metabolomic analysis of peripheral serum. Differential metabolites were identified，statistically analyzed，and subjected to potential biomarker analysis and pathway enrichment. Spearman method was performed to conduct the correlation analysis on the differential ocular collateral features and differential metabolites，followed by correlation network construction. ResultsCompared with those in the CHB group，patients with CHB complicated by GMD showed significant changes in ocular collateral feature scores such as "hillock"，"blood vessels"，and "pale dusky coloration" （P<0.05）. In comparison with those in the healthy group，metabolites including N-acetylglucosamine，acetylhomoserine，and myo-inositol （AUC>0.7） were identified as potential biomarkers for the disease. Compared with those in the CHB complicated by GMD group with non-damp-heat syndrome，patients with damp-heat syndrome exhibited significant changes in feature scores of "plaques"，"yellow coloration"，"spleen"，and "gallbladder" （P<0.05）. In comparison with those in the healthy group，metabolites such as O²′-4a-cyclic tetrahydrobiopterin，theobromine，xanthurenic acid，and L-glutamic acid 5-phosphate （AUC>0.7） were identified as potential biomarkers for the damp-heat syndrome type. The Spearman correlation analysis reveals weak to moderate linear correlations between the differential scleral collateral features and metabolites. By constructing a "disease-syndrome" network of ocular diagnosis and metabolites，"xanthurenic acid-gallbladder" and "theobromine-plaque/yellow coloration" were identified as specific molecular-phenotypic correlated biomarker clusters for CHB complicated by GMD with dampness-heat syndrome. ConclusionPatients with CHB complicated by GMD demonstrate differential ocular diagnostic features and serum metabolites corresponding to disease states and dampness-heat syndrome. These objective biomarkers can guide both clinical syndrome differentiation and medication. The macro-micro integration based on ocular feature clusters and potential metabolic biomarkers offers an innovative approach to a combined traditional Chinese and Western medicine diagnosis and treatment model for this disease.

Nonalcoholic steatohepatitis （NASH） is a chronic metabolic disease characterized by hepatocyte fatty degeneration and ballooning degeneration， and it plays an important role in the progression of hepatic steatosis. Recent studies have shown that immune homeostasis imbalance between T helper 17 （Th17） and regulatory T （Treg） cells are closely associated with the pathological process of NASH. Transforming growth factor-β1 （TGF-β1） is a key cytokine for regulating the differentiation and proliferation of Th17/Treg cells， and TGF-β1 binds to its receptor and activates the Smad signaling pathway， thereby regulating the immune balance of Th17/Treg cells and the expression of inflammatory factors and participating in the repair of liver inflammation. This article systematically reviews the molecular mechanism of the TGF-β1/Smad signaling pathway in affecting NASH by regulating the immune balance of Th17/Treg cells， in order to provide a theoretical basis for the research on the pathogenesis of NASH and related treatment strategies.

OBJECTIVE: The analgesic effect of acupuncture has been widely accepted. Nevertheless, the mechanism behind its analgesic effect remains elusive, thus impeding the progress of research geared toward enhancing the analgesic effect of acupuncture. This paper investigated the role of acupuncture needle surface textures on acupuncture's analgesic effect by creating four experimental acupuncture needles with different patterns of surface augmentation. METHODS: Four types of acupuncture needles with different surface textures (the lined needle, circle needle, sandpaper needle, and threaded needle) were designed. Additionally, the force/torque measurement system used a robot arm and mechanical sensor to measure the force on the needle during insertion and manipulation. To perform acupuncture analgesia experiments, four experimental acupuncture needles and a normal needle were inserted into the Zusanli (ST36) acupoint of rats with inflammatory pain. By comparing the force and torque and the analgesic efficacy of the different acupuncture needles, these experiments tested the role of acupuncture needle body texture on acupuncture analgesia. RESULTS: The analgesic effects of different acupuncture needle body textures varied. Specifically, the force required to penetrate the skin with the lined needle was not greater than that for the normal needle; however, the needle with inscribed circles and the sandpaper-roughened needle both required greater force for insertion. Additionally, the torque of the lined needle reached 2 × 10^-4 N·m under twisting manipulation, which was four times greater the torque of a normal needle (5 × 10^-5 N·m). Furthermore, the lined needle improved pain threshold and mast cell degranulation rate compared to the normal needle. CONCLUSION Optimizing the texture of acupuncture needles can enhance acupuncture analgesia. The texture of our experimental acupuncture needles had a significant impact on the force needed to penetrate the skin and the torque needed to manipulate the needle; it was also linked to variable analgesic effects. This study provides a theoretical basis for enhancing the analgesic efficacy of acupuncture through the modification of needles and promoting the development of acupuncture therapy. Please cite this article as: Sun MZ, Wang X, Li YC, Liu YH, Yu Y, Ren LJ, Gu W, Yao W. Effects of acupuncture needle modification on acupuncture analgesia. J Integr Med. 2025; 23(1): 66-78.
Needles ; Acupuncture Analgesia/methods* ; Animals ; Rats ; Male ; Acupuncture Points ; Rats, Sprague-Dawley

To develop a milestone-based evaluation system for the core "knowledge and skills" competency of neurology residents that is tailored to China's medical context, so as to provide precise guidance for their training and assessment.

Objective To compare the application effect of platelet rich fibrin(PRF)prepared at different centrifugal speeds in tooth extraction wounds using network meta-analysis statistical method.Methods PubMed,Co-chrane Library,Embase,Web of Science,CNKI,Wanfang,VIP and China Biology Medicine disc(CBM)databases were searched to collect the randomized controlled trials on the effect of PRF in tooth extraction from January 1,2024.Note-Express software was used to select literatures,RevMan5.3 was used to evaluate the quality of the included literatures,and Stata14.0 software was used to perform mesh meta-analysis on outcome indicators such as bone mineral density,bone height loss,visual analog scale of pain(VAS),dry groove,and bleeding after tooth extraction.Results A total of 31 randomized controlled trials were included,including 2 824 extraction sites,involving 7 rotational speeds for PRF preparation(3 000,2 800,2 700,2 300,1 500,1 400,1 300 r/min).The results of cu-mulative sequencing showed that PRF prepared by 2 700 r/min centrifugation had the best effect in improving bone mineral density.In terms of improving the buccal bone height,the PRF prepared by 2 700 r/min centrifu-gation had the best effect.In terms of pain improvement,PRF prepared by 1 500 r/min centrifugation had the best effect;PRF prepared by 2 500 r/min centrifugation had the best effect in reducing the incidence of dry trough.PRF prepared by 2 500 r/min centrifugation was the most effective in reducing bleeding.Conclusion Based on the available evidence,PRF prepared with 2 700 r/min has the best effect on improving bone density and bone height after tooth extraction.In terms of pain improvement,1 500 r/min was the most effective;2 500 r/min was the most effective in improving the incidence of dry trough and bleeding.

Objective:To explore the clinical and biochemical characteristics of patients with hyperuricemia according to different pathophysiological subtypes. This may facilitate rapid identification of each subtype in clinical settings and provide evidence for personalized urate-lowering treatment.Methods:Patients diagnosed with hyperuricemia at the Department of Endocrinology and Metabolism, Tenth People′s Hospital of Tongji University between October 2015 and January 2024 were included. Based on 24-h urinary uric acid excretion(UUE) and the fractional excretion of uric acid(FEUA), patients were classified into four subtypes: renal uric acid underexcretion type(RUE), renal uric acid overload type(ROL), combined type and renal normal type. Clinical and biochemical variables-including sex, age, BMI, smoking history, comorbidities, blood glucose, and serum uric acid-were analyzed. Binary logistic regression was used to identify factors associated with each subtype.Results:Among 2 073 patients with hyperuricemia, 55.8% were RUE type, 6.9% were ROL type, 31.3% were combined type and 6.0% were renal normal type. RUE type had lower blood glucose levels and fewer cases of diabetes [ OR=0.685(95% CI 0.478-0.980), P<0.05]. ROL type showed a higher incidence of tophi, positively correlated with smoking history [ OR=1.672(95% CI 1.009-2.771), P<0.05], and negatively correlated with serum uric acid levels [ OR=0.994(95% CI 0.990-0.998), P=0.001]. Combined type had the youngest onset age, shortest disease duration, and the fewest comorbidities, and was associated with higher BMI [ OR=1.035(95% CI 1.001-1.070), P<0.05]. Renal normal type had the oldest age of onset, the highest proportion of female patients and comorbidities, and was associated with lower serum uric acid levels[ OR=0.994(95% CI 0.989-0.998), P=0.007], higher BMI[ OR=1.064(95% CI 1.003-1.129), P<0.05], and increased tophi incidence[ OR=2.261(95% CI 1.206-4.237), P=0.011]. Conclusion:Each pathophysiological subtype of hyperuricemia exhibits distinct clinical and biochemical characteristics, which may serve as useful references for subtype identification and personalized management in clinical practice.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.