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.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

With the rapid development of network technology， live surgery has become the new way of surgery teaching. However， the issue of patient privacy protection caused by live surgery has received widespread attention. Based on the evolutionary game theory， this paper constructed an evolutionary game model from the three-party perspectives of doctors， patients， and government and analyzed the game behaviors of the three parties in the process of live surgery. Matlab software was utilized to conduct dynamic simulation and numerical simulation analysis. It was found that the factors affecting the choice of doctors’ strategies included protection costs， the cost of privacy leakage， the benefits of protection， high-traffic benefits， and other aspects； the factors affecting the choice of patient strategies encompassed surgical costs， the risk of privacy leakage， additional benefits， and other aspects； the factors affecting the choice of government strategies embodied regulatory costs and the improvement of credibility. To realize a win-win situation among doctors， patients， and the government， the three parties need to work together to ensure that patient privacy is not violated and find a balance between expanding the influence of medical education and protecting patient privacy.

Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.

With the rapid development of artificial intelligence （AI） technology， the ethical governance of AI has gained increasing attention. The Recommendation on the Ethics of Artificial Intelligence was issued by the United Nations Educational， Scientific and Cultural Organization in 2021， which clarified several principles for the ethical governance of AI. In the field of rehabilitation medicine， the research and application of AI technology have significantly improved patients’ quality of life and survival. However， due to the specificity of the service population in rehabilitation medicine， which is mostly for the sick， injured， disabled， and elderly， a series of complex ethical issues have also arisen. This paper analyzed in detail the ethical issues and challenges encountered in the research and application of AI technology in the field of rehabilitation medicine from various aspects， such as informed consent， security of privacy and data， patients’ physical and mental rehabilitation， compliance regulation， protection of specific groups， and promotion of equity. According to the principles of the Recommendation on the Ethics of Artificial Intelligence and others， response strategies were proposed， including multi-party collaboration and interdisciplinary cooperation， improving and refining relevant laws and regulations， strengthening ethical education across society， establishing accountability mechanisms， increasing investment， promoting equity， and other measures， to promote the healthy development of research and application of AI technology in the field of rehabilitation， as well as benefit humanity.

Objective To establish a scientific, comprehensive, and operable community resilience evaluation index system for emergent major infectious diseases. Methods Based on the social ecosystem theory, a preliminary evaluation index system was formed by using content analysis and boundary analysis. The index system was then supplemented and revised through panel discussions. The final index system and index weights were clarified by two rounds of Delphi method. Results The expert positive coefficient, expert authority coefficient, and expert coordination coefficient of the two rounds of expert consultations were examined. According to the screening principle of the ^“threshold method^”, the indicators were screened, and the weights of each indicator were determined in the second round of Delphi expert consultation. The analysis of the reliability of the indicator system showed Cronbach's α= 0.399 , indicating that the indicator system had a relatively high reliability. Factor analysis was carried out on 7 primary indicators, and the measure of sampling adequacy (MSA) values were all greater than 0.5, which passed the validity test. Conclusion A set of evaluation index system that can accurately reflect the resilience level of communities with emergent major infectious diseases has been constructed, including 7 primary indicators, 21 secondary indicators, 54 tertiary indicators, and 108 tertiary indicators, which has realized the quantitative evaluation of the hidden resilience level of communities.

ObjectiveTo establish the specific chromatogram and quantitative analysis of multi-components by single-marker（QAMS） based on linear calibration using two reference substances（LCTRS）， explore the consistency between Hedyotis Herba dispensing granules and standard decoction， and evaluate the quality of the dispensing granules. MethodsHigh performance liquid chromatography（HPLC） specific chromatogram was established based on 15 batches of Hedyotis Herba standard decoction and 10 batches of the dispensing granules， and LCTRS was used to locate chromatographic peaks. The actual retention times of 7 characteristic peaks in the specific chromatogram was measured on 24 different types of C₁₈ columns， taking deacetyl asperulosidic acid and asperulosidic acid as the dual standard compounds， the retention times of the other 5 characteristic peaks were predicted and validated. Based on this， QAMS was developed to determine the contents of four components（deacetyl asperulosidic acid， deacetyl asperulosidic acid methyl ester， asperulosidic acid， and p-coumaric acid）. Then， the relative correction factors of deacetyl asperulosidic acid， deacetyl asperulosidic acid methyl ester and p-coumaric acid were calculated using the reference peak of asperulosidic acid in the dual standard compounds， and each component was quantified accordingly. Finally， the consistency between the dispensing granules and standard decoction was assessed by taking extract rate of the standard decoction， consistency of the specific chromatograms， contents and transfer rates of the indicator components as indexes， and the quality of the dispensing granules was evaluated. ResultsThere were 7 common peaks in the characteristic chromatogram of samples of Hedyotis Herba standard decoction and the dispensing granules， and four of them were identified by reference standards， namely deacetyl asperulosidic acid（peak 1）， deacetyl asperulosidic acid methyl ester（peak 3）， asperulosidic acid（peak 6） and p-coumaric acid（peak 7）. The similarity between the dispensing granules and the standard decoction was >0.9. The absolute deviation in the predicted retention time for each component by LCTRS was lower than that of the relative retention time method. The extract rate of the 15 batches of Hedyotis Herba standard decoction ranged from 7.89% to 14.60%， the contents of deacetyl asperulosidic acid， deacetyl asperulosidic acid methyl ester， asperulosidic acid and p-coumaric acid were 6.62-19.70， 3.83-17.99， 1.57-6.69， 1.62-4.52 mg·g^-1， and the transfer rates of these components from decoction pieces to the standard decoction were 22.89%-39.60%， 34.03%-62.24%， 24.25%-43.70%， and 40.58%-73.71%， respectively. The extract rate， index component contents and transfer rates from decoction pieces to the three batches of Hedyotis Herba dispensing granules（P1-P3）， produced by manufacturer A， were similar to those of the standard decoction prepared from the same batch of decoction pieces， and all fell within the specified range. The contents of the 4 indicator components in 7 batches of the dispensing granules（P4-P10） from manufacturers B-E were all within the range of the content converted from the standard decoction based on the quantity of the dispensing granules. ConclusionThe established specific chromatogram and QAMS based on LCTRS are reasonable and reliable. Based on the evaluation indicators of standard decoction yield， consistency of specific chromatograms， contents and transfer rates of the four index components， the 10 batches of Hedyotis Herba dispensing granules from various manufacturers have exhibited good consistency with the standard decoction， indicating that the current production process is relatively reasonable.

ObjectiveTo investigate the features of serum HBV RNA in different stages of the natural history of chronic hepatitis B virus （HBV） infection without antiviral treatment， as well as its correlation with serum HBV DNA and HBsAg. MethodsA total of 306 treatment-naïve patients with chronic HBV infection who attended Department of Infections Diseases and Hepatoloty， the Second Hospital of Shandong University from January 2023 to June 2024 were divided into six groups based on the different stages of natural history， i.e.， HBeAg-positive chronic HBV infection group with 29 patients， HBeAg-positive chronic hepatitis B （CHB） group with 107 patients， HBeAg-negative chronic HBV infection group with 18 patients， HBeAg-negative CHB group with 60 patients， HBeAg-positive indeterminate-phase chronic HBV infection group with 7 patients， and HBeAg-negative indeterminate-phase chronic HBV infection group with 85 patients. Real-time isothermal RNA amplification was used to measure serum high-sensitivity HBV RNA. The Kruskal-Wallis H test was used for comparison between multiple groups of continuous data， while the Mann-Whitney U test was used for comparison between two groups. The Spearman method was used to investigate the correlation of HBV RNA with HBV DNA and HBsAg. ResultsThe HBeAg-positive chronic HBV infection group showed the highest level of serum HBV RNA ［7.5 （7.4‍ ‍—‍ ‍7.9） log₁₀ copies/mL］， followed by the HBeAg-positive CHB group ［7.4 （6.4‍ ‍—‍ ‍7.9） log₁₀ copies/mL］， the HBeAg-negative CHB group ［4.5 （3.0‍ ‍—‍ ‍5.7） log₁₀ copies/mL］， and the HBeAg-negative chronic HBV infection group ［1.0 （1.0‍ ‍—‍ ‍2.0） log₁₀ copies/mL］； the HBeAg-positive indeterminate-phase chronic HBV infection group had a serum HBV RNA level of 3.9 （3.7‍ ‍—‍ ‍5.7） log₁₀ copies/mL， and the HBeAg-negative indeterminate-phase chronic HBV infection group had a serum HBV RNA level of 2.0 （1.0‍ ‍—‍ ‍3.0） log₁₀ copies/mL； there was a significant difference in serum HBV RNA level between the six groups （H=830.770， P<0.001）. There was a significant difference in HBV RNA level between the HBeAg-positive chronic HBV infection group and all the other groups except the HBeAg-positive CHB group （all P<0.001）. In the 306 patients with HBV infection， HBV RNA was strongly correlated with HBV DNA （r=0.92， P<0.001） and was moderately correlated with HBsAg （r=0.67， P<0.001）. The correlation between serum HBV RNA and HBsAg in HBeAg-positive patients （r=0.61， P<0.001） was stronger than that in HBeAg-negative patients （r=0.31， P<0.001）. For the patients with HBeAg-positive chronic HBV infection， the male patients with ALT>30 U/L and the female patients with ALT>19 U/L had a significantly lower serum HBV RNA level than the male patients with ALT≤30 U/L and the female patients with ALT≤19 U/L （P<0.001）， and there was no significant difference in serum HBV RNA level between the latter group of patients and the HBeAg-positive CHB group （P>0.05）. ConclusionIn patients with chronic HBV infection who do not receive antiviral therapy， there is a difference in serum HBV RNA level in different stages of natural history， and serum HBV RNA level has the strongest correlation with HBV DNA and a relatively weak correlation with HBsAg. In patients with HBeAg-positive chronic HBV infection， serum HBV RNA level in male patients with ALT>30 U/L and female patients with ALT>19 U/L are in the transition stage between HBeAg-positive chronic HBV infection and HBeAg-positive CHB.

Objective To investigate the value of artificial intelligence-assisted compressed sensing (ACS) technology for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear using three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence. Methods The patients received gadolinium contrast-enhanced magnetic resonance imaging using ACS and united compressed sensing (uCS) 3D-FLAIR at Zhongshan Hospital, Fudan University from January to November 2024 were prospectively enrolled. The repetition time was 16 000 ms, and acquisition time was 6 min 40 s and 10 min 24 s in ACS 3D-FLAIR and uCS 3D-FLAIR, respectively. The images on the two sequences were evaluated independently by two radiologists. The image quality of the two sequences was subjectively evaluated and compared. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the two sequences. The grading consistencies using two sequences and between the two doctors were analyzed. Results There was no statistically difference in subjective score of image quality between the two sequences. SNR and CNR of the ACS 3D-FLAIR sequence were significantly higher than those of the uCS 3D-FLAIR sequence (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops were 0.942 and 0.888 using two sequences (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops using the ACS 3D-FLAIR sequence between the two doctors were 0.784 and 0.831, respectively (P＜0.001); the kappa values of grades of cochlear and vestibular endolymphatic hydrops using uCS 3D-FLAIR sequence between the two doctors were 0.725 and 0.756, respectively (P＜0.001). Conclusions ACS 3D-FLAIR could provide higher SNR and CNR than uCS 3D-FLAIR, and is more suitable for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear; the endolymphatic hydrops grades using ACS 3D-FLAIR is similar to use uCS 3D-FLAIR.