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 establish a mouse model of rheumatoid arthritis with interstitial lung disease （RA-ILD） in DBA/1 mice using Porphyromonas gingivalis （Pg） infection combined with collagen-induced arthritis （CIA）， and to comprehensively evaluate pathological characteristics in joints， lungs， and serum. MethodsForty DBA/1 mice were randomly divided into four groups， i.e.， Control， Pg infection （Pg）， CIA， and Pg infection combined with CIA （Pg+CIA）， with 10 mice in each group. Arthritis clinical symptoms were evaluated by recording arthritis incidence and clinical scores. Micro-CT scanning was used to assess knee joint pathology. Histopathological changes and collagen deposition in knee joints and lung tissues were analyzed using hematoxylin-eosin （HE） and Masson staining. Immunohistochemistry was performed to detect protein expression of α-smooth muscle actin （α-SMA）， typeⅠ collagen （ColⅠ）， and fibronectin （FN） in lung tissues. Real-time quantitative polymerase chain reaction（Real-time PCR）was used to measure mRNA expression levels of α-SMA， ColⅠ， FN， tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and IL-1β in lung tissues. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of Pg， cyclic citrullinated peptide （CCP）， and immunoglobulin G （IgG）. ResultsJoint lesions： The CIA and Pg+CIA groups showed 100% arthritis incidence， with evident joint redness， swelling， and deformity. The number of affected limbs was 27 and 28， and clinical scores were 68 and 70， respectively. No obvious clinical symptoms were observed in the Pg group. Histopathological and imaging analyses showed severe joint lesions in the CIA and Pg+CIA groups， with significantly increased histopathological scores， bone mineral density， bone volume fraction， trabecular thickness， and trabecular number compared to the Control group （P<0.01）. No obvious joint pathology was observed in the Pg group. Lung lesions： The Pg+CIA group exhibited marked alveolar inflammation， interstitial inflammatory cell infiltration， and alveolar wall thickening， with pronounced blue staining of collagen fibers. Histopathological scores and collagen area ratios were significantly higher than those of the Control， Pg， and CIA groups （P<0.05）. Lung protein and mRNA expression levels of α-SMA， ColⅠ， and FN were markedly increased， and mRNA levels of IL-6， TNF-α， and IL-1β were significantly elevated compared to the Control group （P<0.05）. Serology： The Pg+CIA group showed significantly higher levels of CCP， Pg， and IgG compared with the Control， Pg， and CIA groups （P<0.05）. ConclusionDBA/1 mice subjected to Pg infection combined with CIA exhibited pronounced symptoms and pathological features of RA-ILD， along with elevated serum anti-CCP antibody levels. This model represents a novel RA-ILD mouse model， providing a valuable experimental tool for investigating RA-ILD pathogenesis and developing new therapeutics， and serves as a basis for establishing anti-cyclic citrullinated peptide antibody （ACPA）-positive RA-ILD animal models.

OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

To mine tacrolimus-related adverse event signals affecting the cardiovascular system based on an international authoritative database, aiming to provide a reference for clinical safe drug use.

Background: and Purpose Therapeutic target selection in noninvasive brain stimulation for poststroke motor recovery typically relies on the interhemispheric inhibition model, which is effective for mildly affected patients but offers limited benefits for severely affected individuals. The mechanisms governing recovery from moderate-to-severe stroke remain poorly understood, which hinders the development of targeted interventions. Methods: We analyzed resting-state functional magnetic resonance imaging data from patients with unilateral subcortical stroke and moderate-to-severe upper limb deficits, both pre- and postintervention, along with data from healthy controls. We developed a novel dynamic lag analysis method for identifying recovery-related homotopic sensorimotor regions with altered interhemispheric interactions. To further uncover the global reorganization pathway, we developed dynamic lateralization approaches to detect large-scale functional connectivity (FC) alterations associated with the identified regions in transient lateralization states. Results: Dynamic time-lag analysis revealed significantly reduced synchronized states in the homotopic dorsal premotor cortex (PMd) post-intervention compared with pre-intervention, which correlated with motor recovery. Further dynamic lateralization analysis revealed a prolonged segregation state in patients, characterized by weakened interhemispheric and strengthened intrahemispheric interactions. In this state, patients showed decreased FC in the ipsilesional PMd and increased FC in the contralesional PMd with bilateral subcortical networks. These recoveryrelated alterations were absent in the traditional static analysis. Conclusions Dynamic analyses targeting interhemispheric interactions are valuable for understanding neural reorganization after stroke. The diminished interactions between the homotopic PMd indicate a compensatory mechanism. Importantly, a state-dependent compensatory pathway was identified, wherein the contralesional PMd assumes the functions of the ipsilesional PMd through enhanced interactions with subcortical structures, potentially guiding more effective interventions.

Objective To investigate the protective effect of Indigo Naturalis on cerebral ischemia-reperfusion injury in mice. Methods The mouse model of middle cerebral artery occlusion/reperfusion (MCAO/R) was established using the filament ligation method. Mice were randomly divided into five groups: sham surgery, model, positive drug control, low-dose Indigo Naturalis, and high-dose Indigo Naturalis. After 7 d of drug administration, the relevant experiments were performed. Neurological function was assessed via behavioral scoring, balance beam test, forelimb grip strength, and tail lift test. Brain infarct volume was quantified using 2,3,5-triphenyl tetrazolium chloride (TTC) staining. Histopathological changes and neuronal apoptosis were systematically analyzed through hematoxylin-eosin (HE) staining, Nissl staining, and TUNEL staining. Finally, polymerase chain reaction (PCR) was employed to detect mRNA expression levels of inflammatory cytokines interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and microglial polarization markers (CD32, CD206) in the mouse cerebral cortex. Results Compared with the model group, the neurological function scores of mice in the high-dose Indigo Naturalis group showed significant improvement, and the motor ability recovery in each drug-administration group was remarkable (P<0.05, P<0.01). The cerebral infarct volume in the high-dose Indigo Naturalis group was significantly reduced (P<0.05). Histological results revealed that Indigo Naturalis could alleviate pathological damage in brain tissue and reduce neuronal apoptosis (P<0.01). PCR results demonstrated that after treatment with Indigo Naturalis, the expression of inflammatory factors and CD32 was significantly downregulated (P<0.05, P<0.01), while the expression of CD206 was significantly upregulated (P<0.05). Conclusion Indigo Naturalis could improve motor function in mice with cerebral ischemia-reperfusion injury, and its effects might be related to regulating inflammatory responses and reducing neuronal damage.

BACKGROUND:Cannabidiol is effective in ameliorating the body's inflammatory response,but no clear mechanistic studies have been conducted to ameliorate skeletal muscle inflammation induced by exhaustive exercise. OBJECTIVE:To explore the mechanism by which cannabidiol improves skeletal muscle inflammation during exhaustive exercise by using transcriptome sequencing technology. METHODS:Thirty-six Sprague-Dawley rats were randomly divided into six groups:blank control group,exercise coconut oil group,exercise control group,50 mg/kg cannabidiol group,60 mg/kg cannabidiol group,and 70 mg/kg cannabidiol group,with six rats in each group.Except for rats in the blank control group,rats in each group were subjected to swimming exercise for 9 days to produce the exhaustive exercise model.At the end of each swimming exercise,rats in the cannabidiol groups were given 2 mL of fat-soluble cannabidiol at different concentrations(50,60,and 70 mg/kg)by gavage;rats in the exercise coconut oil group were given the same volume of coconut oil by gavage until the end of the exercise on the 9th day;and rats in the blank control group and the exercise control group were not given any special treatment.The levels of inflammatory factors and differentially expressed genes in the skeletal muscle of rats in each group were determined using ELISA and transcriptome sequencing techniques.Differentially expressed genes obtained were subjected to KEGG analysis,and the accuracy of the sequencing data was verified by fluorescence quantitative PCR. RESULTS AND CONCLUSION:The results of ELISA showed that the contents of interleukin-6(P<0.05),tumor necrosis factor-α(P<0.01),interleukin-10 and other inflammatory factors in the exercise group increased significantly compared with the blank control group and the coconut oil group.After cannabidiol intervention,the mass concentrations of interleukin-6 and tumor necrosis factor-α showed a sequential decrease with increasing cannabidiol concentration.By comparing GO and KEGG databases,the functional properties of differentially expressed genes were analyzed,and the results showed that the differentially expressed genes were mainly involved in the tumor necrosis factor signaling pathway and the Toll-like receptor signaling pathway.RT-qPCR results showed that the trends of five randomly selected differentially expressed genes were in agreement with the transcriptome sequencing results.To conclude,cannabidiol can improve skeletal muscle inflammation caused by exhaustive exercise.

Objective To investigate the probability and dosimetric risk factors of lung injury after sequential immune checkpoint inhibitors (ICIs) and thoracic radiotherapy. Methods A retrospective analysis was conducted on 139 patients who received sequential ICIs and thoracic radiotherapy in Xuzhou Cancer Hospital and Affiliated Hospital of Xuzhou Medical University between February 2020 and February 2024. The relationships of clinical factors and lung and heart volume dose parameters with grade ≥ 2 acute lung injury (ALI) in patients with thoracic tumors were studied using univariable (χ² test, t test, nonparametric test) and multivariable (binary logistic regression analysis) methods. The thresholds of dosimetric risk factors were determined using the receiver operating characteristic curves. Clinical factors included age, gender, smoking history, type of ICIs, cycle of ICI application, and the interval between ICI application and thoracic radiotherapy. Dose parameters included total radiotherapy dose, single dose, planning target volume, maximum dose of planning target volume, average dose of planning target volume, total lung volume, heart volume, and the V₅, V₁₀, V₁₅, V₂₀, V₂₅, V₃₀, V₃₅, and V₄₀ of lung and heart. Results The incidence of grade ≥ 2 ALI in the included cases was 36% (50/139). The χ² test did not find any statistically significant clinical factors. In the univariable and binary Logistic regression analysis, lung V₁₅ and V₂₀, heart V₁₅ and V₂₀, and lung volume were independent risk factors for the occurrence of grade ≥ 2 ALI in sequential ICIs and thoracic radiotherapy. The thresholds were 18.51% for lung V₁₅, 14.43% for lung V₂₀, 32.41% for heart V₁₅, and 17.74% for heart V₂₀. Conclusion For patients who are going to receive thoracic radiotherapy after ICIs, the thresholds of lung V₁₅ and V₂₀ and heart V₁₅ and V₂₀ in the radiotherapy plan are recommended to be less than 18.51%, 14.43%, 32.41%, and 17.74%, respectively, which can effectively reduce the occurrence of grade ≥ 2 ALI.

Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

Objective To explore the preferences and needs of colorectal cancer patients for"Internet+TCM nursing services",aiming to provide a basis for the improvement of service quality and the formulation of relevant policies,so as to better meet the needs of patients.Methods A total of 189 patients with colorectal cancer who were admitted to a tertiary A Chinese Medicine hospital in Qingdao from September 2023 to July 2024 were selected as the research subjects.A general data questionnaire and Questionnaire on"Internet+Traditional Chinese Medicine Nursing Service"Preference of Colorectal Cancer Patients were used with 6 attributes,including average out-of-pocket cost,nurse qualification,service waiting time,service mode,comprehensiveness of service content,and platform service evaluation,each attribute with 2 to 3 levels.The preference,payment intention of"Internet+TCM nursing services"were analyzed by constructing a mixed Logit model,and the influencing factors of choice preference of different colorectal cancer patients was explored through subgroup analysis.Results Totally 189 questionnaires were sent out,and 156 valid questionnaires were collected,with an effective recovery rate of 82.54％.Among the respondents,112 patients(71.79％)actively accepted"Internet+TCM nursing services",and the attributes of"Internet+TCM nursing services"such as payment fee,service evaluation,service content and nurse qualification had an impact on nursing service preference of colorectal cancer patients(P＜0.05).Based on willingness to pay,the ranking of attributes was service evaluation,service content and nurse qualification.Factors such as education level and the presence of ostomy also affected the preference of"Internet+TCM nursing services"in patients with colorectal cancer(P＜0.05).Conclusion Patients with colorectal cancer prefer"Internet+TCM nursing services",which has an average service cost of 50 yuan per time,excellent platform service evaluation,comprehensive service content,specialized TCM nurses.The preferences and specific characteristics of patients with colorectal cancer can be considered to optimize the allocation of nursing resources and provide services in line with their preferences.