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.

Diabetic retinopathy(DR)is a late-stage peripheral micro-neurovascular complication of chronic hyperglycemia, leading to blood-retinal barrier impairment and retinal dysfunction. Recent studies have found that diabetic neuroretinopathy(DN)may be one of the earliest events in diabetic retinal alterations. The main features include defective electroretinographic responses in newly diagnosed patients, early self-activation of microglia and Müller cells, reduced activity of neurotransmitters(e.g., DOPA/GABA), and early mitochondrial dysfunction, such as persistent Drp1-Fis1 fission and mtDNA methylation mismatches. Understanding the molecular basis of DN is essential for elucidating its pathogenesis and developing early treatments. This review summarizes pathological changes and mechanisms of retinal function, glial cells, neurotransmitters, mitochondria, and other factors in early diabetes mellitus, in order to provide a theoretical foundation for investigating early DN mechanisms and developing targeted therapies.

The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

Objective: To explore the association of screening myopia and sitting posture habits as well as screen viewing distance among primary school students, providing a scientific basis for myopia prevention and intervention among primary school students. Methods: From April to June 2024, a convenient sampling method was used to enroll 1 394 fourth grade students from four primary schools in a district of Beijing for vision examinations and questionnaire surveys. Logistic regression models were employed to analyze the relationship of screening myopia detection and sitting posture habits as well as viewing distance. Results: The screening myopia prevalence among primary school students was 63.8%. About 13.1% of students self reported poor sitting posture, and 47.1% selfreported a viewing distance of ≤20 cm. After adjusting for covariates including age, gender, school, sleep quality, parental myopia status, physical fitness level, daily high intensity physical activity, weekend outdoor activity time and types of after school services, Logistic regression analysis showed that students with poor sitting posture were more likely to have screening myopia than those with normal sitting posture ( OR =1.73,95% CI =1.03-2.92); students with a viewing distance of ≤20 cm were more likely to have screening myopia than those with a viewing distance of >20 cm( OR =1.32, 95% CI =1.02-1.71)( P <0.05). The association between sitting posture and screening myopia was more significant among boys( OR =2.00, 95% CI =1.03-3.88, P < 0.05 ). A multiplicative interaction was observed between sitting posture and viewing distance. Compared to primary school students with normal posture and a viewing distance of >20 cm, those with poor posture and a viewing distance of >20 cm were more likely to have screening myopia ( OR =1.82, 95% CI =1.12-2.96， P <0.05). Conclusions Both sitting posture habits and screen viewing distance are related to screening myopia in primary school students. Poor sitting posture poses a higher risk than screen distance, and the two factors exhibit an interactive effect on myopia risk.

Objective: To explore the association between vitamin D levels and sleep in children and adolescents，so as to provide a reference for promoting the sleep health of children and adolescents. Methods: From October to December, 2021, 4 827 primary and middle school students aged 6-17 in Shenzhen were selected by multistage cluster random sampling method, and their demographic information, family background, lifestyle and sleep status were obtained by facetoface questionnaire survey, and their fasting venous blood in the morning was collected to detect the serum 25(OH)D level. The relationship between serum vitamin D level and sleep characteristics was analyzed by binary Logistic regression, and stratified analysis was carried out according to gender. Results: The proportion of vitamin D deficiency was 41.1%, and the proportion of sleep deficiency was 19.4%. With the increase of vitamin D level, daily sleep duration of children and adolescents tended to increase (r=0.10,P<0.01). After adjusting for covariates such as gender and age, it was found that children and adolescents with insufficient vitamin D levels were more likely to experience sleep insufficiency, social jetlag, and late sleep on weekdays, with ORs being 1.32(95%CI=1.12-1.56), 1.35(95%CI=1.19-1.54), and 1.26(95%CI=1.05-1.52)(P<0.05). Sexstratified analysis showed that, among boys, vitamin D deficiency was associated with sleep deficiency, social jetlag, and late bedtime on weekdays and weekends[OR(95%CI)=1.42(1.14-1.77),1.25(1.04-1.49),1.39(1.06-1.82),1.86(1.19-2.92),P<0.05]. In girls, however, serum vitamin D levels were only associated with social jetlag with OR being 1.47 (95%CI=1.21-1.79, P<0.05). Conclusion Vitamin D levels are associated with various sleep characteristics in children and adolescents, with this association being more pronounced among boys.

OBJECTIVE To summarize the current situation of pharmaceutical clinic service in our hospital over the past five years， and explore sustainable development strategies for service models of pharmaceutical clinics. METHODS A retrospective analysis was conducted on the consultation records of patients who registered and established files at the pharmaceutical clinic in our hospital from January 2019 to December 2023. Statistical analysis was performed on patients’ general information， medication- related problems， and types of pharmaceutical services provided by pharmacists. RESULTS A total of 963 consultation records were included， among which females aged 20-39 years accounted for the highest proportion （66.04%）； obstetrics and gynecology- related consultations accounted for the largest number of cases. Additionally， 80 patients attended follow-up visits at our hospital’s pharmaceutical clinic. A total of 1 029 medication-related issues were resolved， including 538 cases of drug consultations （52.28%）， 453 medication recommendations （44.02%）， 22 medication restructuring（2.14%）， and 16 medication education （1.55%）； the most common types of medication-related problems identified were adverse drug events（70.07%）. CONCLUSIONS Although the pharmaceutical clinic has achieved recognition from clinicians and patients， challenges such as low awareness among healthcare providers and the public persist. Future efforts should focus on strengthening information technology construction， enhancing pharmacist training， and establishing various forms of outpatient pharmaceutical service models.

The inherent clinical uncertainties, substantial costs, and small patient cohorts of orphan drugs limit the applicability of randomized controlled trial (RCT)-based health technology assessments (HTAs) in guiding coverage criteria, sustainable financing models, and equitable reimbursement frameworks for medical financial assistance policies for rare diseases.The digital transformation in healthcare system leads to solutions to the challenges in designing the policy by using data-driven decision-making. This article summarizes the decision-making issues in policy design, discusses the current status and trends of digital transformation, and analyzes the important new opportunities for AI-driven policy design for medical financial assistance policies for rare diseases. Decision-making that is digital intelligence driven and using techniques such as big data analytics and real-world research methods will enhance targeting efficiency, improve the quality of financing, and realize the performance-based reimbursement in the medical financial assistance, providing significant value in facilitating the policy reform and development for rare diseases healthcare.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.