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.

Objective To investigate the comparative neuroprotective effects of human umbilical cord mesenchymal stem cells(hUC-MSCs-Exos)administered via different routes on hypoxic ischemic brain damage(HIBD)in neonatal mice.Methods Healthy one-week-old SPF-grade BALB/c mice were randomly divided into 4 groups:sham operation group(n=6),model group(n=6),exosome group 1(n=8),exosome group 2(n=8).HIBD was induced using the Rice-Vannucci method.Exosome group 1 and Exosome group 2 were intraperitoneal injection/intranasal drip of phosphate buffer(PBS)100 μl containing 10 μl exosomes within 24 h after successful modeling,respectively.Sham operation and model groups were intraperitoneal injection of PBS 100 μl.On the 7th day after the intervention,neuromotor function was assessed using the horizontal grid test and pole climbing test.On the 2nd day after the evaluation,all mice were killed and their brains were removed by decapitation.HE staining was used to observe the pathological injury of brain tissue,toluidine blue staining was used to observe the survival of neurons in cerebral cortex,and TUNEL staining was used to observe the apoptosis of cerebral cortex cells.Results Compared with sham operation group,model group,exosome group 1 and exosome group 2 exhibited increased hind limb drops in horizontal grid test and climbing scores(P<0.05).No significant difference was found in model group,exosome group 1 and exosome group 2 in these measures(P<0.05).Significant pathology was observed in model group,exosome group 1 and exosome group 2 compared to sham operation group(P<0.05),with significantly reduced damage in exosome group 1 and exosome group 2 compared to model group(P<0.05).Compared with sham operation group,Nissl body count was lower in model group and exosome group 1 and exosome group 2,with a higher count in exosome group 2 compared to exosome group 1(P<0.05).Compared with sham operation group,apoptotic cells were higher in model group and exosome group 1 and exosome group 2,with a significant reduction in exosome group 1 and exosome group 2 compared to model group,and the lowest in exosome group 2(P<0.05).Conclusions hUC-MSCs-Exos can improve the neuronal motor function,promote neuron repair and inhibit apoptosis in HIBD mice.Intranasal administration of hUC-MSCs-Exos is more effective than intraperitoneal administration for reducing neuronal apoptosis in HIBP neonatal mice,offering a convenient and rapid method suitable for clinical application.

Objective To evaluate the changes in postoperative plasma β-endorphin(β-EP)levels in patients who had received perioperative electroacupuncture(EA)treatment in 10 randomized controlled trials(RCTs)and examine the impact of EA on postoperative pain.Methods This meta-analysis evaluated the changes in plasma β-EP levels and visual analog scale(VAS)12,24 and 48 hours after surgery in patients receiving perioperative EA.It also assessed the changes in plasma serotonin(5-hydroxytryptamine,5-HT)and prostaglandin E2(PGE2)levels at 24 hours postsurgery.A comprehensive search was conducted in the China National Knowledge Infrastructure(CNKI),Wanfang,Chongqing VIP database,Chinese Biomedical Database(CBM),Web of Science,and PubMed databases.RCTs on perioperative EA and β-EP published from the inception of the websites up to July 25,2023,were retrieved.Effect size aggregation,literature quality assessment,and bias analysis were performed using RevMan 5.3 software,and sensitivity analysis was conducted via R 4.3.1.Results A total of 10 RCTs involving 706 patients were included.EA in conjunction with conventional anesthesia significantly increased plasma β-EP levels at 12 hours postsurgery[standard mean difference(SMD)=2.79,95%CI(1.85,3.72),Z=5.81,P＜0.00001],24hours postsurgery[SMD=1.87,95%CI(0.9,2.83),Z=3.79,P=0.0001],and 48 hours postsurgery[SMD=2.02,95%CI(1.49,2.54),Z=7.50,P＜0.00001].EA reduced plasma PGE2 levels at 24 hours postsurgery and plasma 5-HT levels at 24 hours postsurgery,and the VAS at 12,24 and 48 hours after surgery also decreased.Conclusion These findings suggest that perioperative EA markedly elevates plasma β-EP levels,reduces pain-inducing factors in plasma,and effectively alleviates acute postoperative pain.

This article reports a first case of combined infection with severe fever with thrombocytopenia syndrome(SFTS)and scrub typhus in Dalian City.The patient was admitted to the hospital due to recurrent fever for 7 days and loss of consciousness for 1 day.Pathogen metagenomic sequencing(mNGS),SFTSV quantitative PCR,and enzyme-linked immunosorbent assay(ELISA)IgM tests were performed,showing positive results for Orientia tsutsugamushi and SFTSV nucleic acids.Based on clinical manifestations and epidemiological history,the patient was diagnosed with combined infections.

Based on the concept of"two-stage,four-phase,and three-phase treatments"of in vitro fertilization and embryo transfer(IVF-ET)assisted the whole-course management of TCM by national TCM master You Zhaoling,this article analyzed the treatment strategy assisted by acupuncture in five aspects:principle,method,prescription,acupoint,and technique.Principle:syndrome differentiation and treatment follow different cases;method establish guiding methods based on principles,while following stage diagnoses and treatments;prescription:determine the prescriptions based on therapeutic principles within the context of overall regulation;acupoint:precise acupoint taking and rational acupoint matching;technique:the primary method is acupuncture,supported by various therapeutic modalities,providing a comprehensive framework and evidence-based support for the clinical application of acupuncture and moxibustion in IVF-ET.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective:To investigate the intervention effect of five elements music of traditional Chinese medicine and western classical music on the sleep quality of stroke patients, and to compare the difference between the two, to provide a reference for the clinical care measures to improve the sleep quality of stroke patients.Methods:By adopting a randomized controlled trial, 75 stroke patients who were hospitalized in the rehabilitation hospital of the Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine from July 2022 to July 2023 were selected by convenience sampling method as the study subjects, and the patients were randomly divided the conventional treatment group, the five-element music group, and the classical music group according to the method of randomized numerical table with 25 cases in each group. On the basis of general treatment, the conventional treatment group took sleep health education, the five elements music group were given five-element music intervention based on conventional treatment, and the classical music group were given classical music intervention based on conventional treatment. The changes of Athens Insomnia Scale (AIS), Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG) examination parameters in the 3 groups were compared.Results:There were 2 cases of shedding in the conventional treatment group, and 23 cases were finally included, 15 males and 8 females, aged (54.02 ± 7.80) years; there were no cases of shedding in the five-element music group, and 25 cases were finally included, 12 males and 13 females, aged (53.69 ± 6.02) years; and there was 1 case of shedding in the classical music group, and 24 cases were finally included, 10 males and 14 females, aged (52.34 ± 7.08) years. Comparison of AIS, PSQI and PSG scores among the 3 groups of patients before intervention showed no statistically significant differences (all P>0.05). After the intervention, the AIS scores and PSQI scores of the 3 groups were (9.48 ± 1.53) and (12.22 ± 2.94), (6.76 ± 1.36) and (7.64 ± 2.08), (7.46 ± 1.38) and (10.33 ± 2.82), respectively, and the differences were statistically significant ( F=23.21, 18.44, both P<0.05). PSG sleep structure parameters showed that the total sleep time, REM latency time and sleep efficiency of the patients in the five-element music group after the intervention were (399.89 ± 51.76) min, (136.26 ± 25.36) min, (78.87 ± 8.21)%, higher than (368.45 ± 47.88) min, (124.46 ± 26.25) min, (73.36 ± 7.86)% in the classical music group and (345.48 ± 38.69) min, (111.37 ± 23.23) min, (69.44 ± 7.88)% in the conventional treatment group, and the differences between three groups were statistically significant ( F=8.27, 5.93, and 8.49, all P<0.05); the sleep latency time, awakening time, and number of awakenings in the five-element music group were (28.86 ± 17.68) min, (54.37 ± 25.15) min, and (2.72 ± 1.19) times, respectively, which were lower than those in the classical music group (35.67 ± 16.99) min, (64.28 ± 29.34) min, and (3.67 ± 1.12) times and (42.38 ± 18.96) min, (78.38 ± 37.26) min, (4.87 ± 1.46) times in the conventional treatment group, and the differences between three groups were statistically significant ( F=3.51, 3.66, and 17.56, all P<0.05). The results of the PSG sleep progression showed that the duration of the N1 stage of sleep in the five-element music group after the intervention was (95.71 ± 15.23) min, which was higher than (83.20 ± 18.34) min in the classical music group and (80.93 ± 16.47) min in the conventional treatment group, and the difference between three groups was statistically significant ( F=5.53, P<0.01); the N3 stage sleep time and the sleep percentage of the five-element music group after the intervention were respectively (84.23 ± 20.98) min and (23.98 ± 5.89)%, which were higher than (65.33 ± 18.82) min and (18.34 ± 3.78)% in the classical music group and (45.87 ± 18.65) min and (15.03 ± 5.56)% in the conventional treatment group, and the differences between three groups were statistically significant ( F=23.08, 18.50, both P<0.05). Conclusions:Both five elements music and classical music can improve the sleep quality of stroke patients, and the effect of five elements music to improve sleep is more significant.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.