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.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

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.

Intervertebral disc degeneration （IVDD） is the core cause of chronic low back pain， which severely impairs patients’ quality of life and imposes a heavy social and medical burden. The hypoxia-pyroptosis-inflammation cascade mediated by hypoxia-inducible factor-1α （HIF-1α） is the core pathological mechanism driving the initiation and progression of IVDD. Natural active ingredients derived from traditional Chinese medicine （TCM） have become a research hotspot in the field of IVDD prevention and treatment due to their advantages of multi-target effects， favorable efficacy， and low toxicity. This paper systematically reviews the mechanism of HIF-1α-mediated hypoxia-pyroptosis-inflammation cascade in degenerative nucleus pulposus tissue and the intervention of related active ingredients. It is found that natural active ingredients such as baicalein， curcumin and resveratrol can intervene in the HIF-1α-mediated pathological cascade through four core links to delay IVDD progression： targeting the HIF-1α oxygen sensing pathway to block the initiation of pyroptosis cascade， inhibiting NOD-like receptor protein 3 inflammasome activation to cut off the cascade amplification of inflammatory signals， intervening in the Gasdermin D-mediated pyroptosis execution stage to protect cell membrane integrity， and regulating extracellular matrix metabolism to reconstruct intervertebral disc homeostasis.

Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

OBJECTIVE To formulate Guidelines for the standardized implementation of pharmacist-managed clinics （ 2026 edition ） in response to the challenges faced by such clinics in China， including uneven development， large discrepancies in service specifications， insufficient patient awareness， and limited medical insurance coverage. METHODS Led by the Pharmaceutical Affairs Professional Committee of the Chinese Hospital Association， the Evidence-based Pharmacy Professional Committee of the Chinese Pharmaceutical Association， and the Hospital Pharmacy Professional Committee of the Cross-strait Medical and Health Exchange Association， a total of 19 domestic hospital pharmacy experts were organized. Through a systematic review of national policies and literature research， current practical experience was summarized. Consensus on the contents of the guidelines was reached after in-depth discussions. RESULTS &CONCLUSIONS The guidelines covered five sections： definition and connotation of pharmacist-managed clinics， establishment requirements， implementation and management， post competency， and practical research. Firstly， the definition and connotation included three operational forms of pharmacist-managed clinics （independent mode， physician-pharmacist joint mode， and online pharmacist-managed clinic mode） and classified service modes （specialty-specific， drug-specific， and disease-specific pharmacist-managed clinics）. The establishment requirements were further refined， covering system construction （pharmaceutical service management system， quality control and assessment mechanism）， personnel qualifications （professional credentials， continuing education and professional training， etc）， service recipients， as well as service venues and facilities. Subsequently， the implementation and management of pharmacist-managed clinics were proposed， involving service procedures， intervention measures， documentation and records， patient education and follow-up， humanistic care， as well as risk management and quality control. Finally， post competency encompassed the competency requirements for pharmacists providing services in pharmacist-managed clinics， as well as the suggestions on teaching methods； practical research encouraged the conduct of high-quality pharmaceutical practice in the setting of pharmacist-managed clinics. The guidelines provide valuable guidance for the standardized implementation of pharmacist-managed clinics in China in terms of establishment， management， teaching， and research， fill the guideline gap in this field， and can promote the high-quality development of pharmacist-managed clinics.

Objective: To develop a convenient, direct, and highly sensitive method for screening trace chemical additives in complex Chinese patent medicines, thereby addressing core technological bottlenecks in pharmaceutical analysis and quality control. Methods: A brush ionization probe device was independently designed and constructed, and an efficient detection method was established through systematic optimization of key parameters. Twenty-three Chinese patent medicine samples, representing 6 dosage forms (capsules, tablets, pills, granules, powders, and liquid preparations), were analyzed using 10 common chemical additives as target analytes. Results: All samples were successfully analyzed without complex pretreatment, and 5 chemical additives were detected in 7 Chinese patent medicines. The brush ionization probe device exhibited cost-effectiveness (~0.2 USD per probe), operational simplicity, rapid analysis (~10s per sample), high efficiency, and minimal reagent consumption (~10 μL per sample). Conclusion: This advancement is expected to provide an innovative scientific tool for improving the generality and convenience of on-site quality control, while promoting technological progress in disciplines such as pharmacology and traditional Chinese medicine.

ObjectiveTo analyze the current research status, hotspots and future trends of the application of digital health technology (DHT) in the rehabilitation of upper limb motor function after stroke. MethodsRelevant literature on the application of DHT in upper limb motor rehabilitation for stroke patients published between January, 2015 and December, 2025 was retrieved from Web of Science Core Collection, CNKI and Wanfang database. CiteSpace 6.4.R1 was used for visualized bibliometric analysis. ResultsA total of 1 295 publications were included, comprising 454 in Chinese and 841 in English. The annual number of publications generally showed an upward trend. China ranked first in publication output in English literature. The institutions with the highest numbers of publications were Huashan Hospital Affiliated to Fudan University and Swiss Federal Institute of Technology in Zurich. Both Chinese and English keywords formed ten clustering groups. Chinese clusters mainly involved occupational therapy, neural mechanisms and home-based rehabilitation, whereas English clusters focused on virtual reality, brain-computer interfaces and machine learning. High-frequency keywords included virtual reality, brain-computer interface, machine learning and deep learning. Chinese keywords with a strong burst included rehabilitation training, while deep learning showed a strong burst in English keywords. Stroke was the most frequently cited journal. Highly cited journals covered multiple disciplines, including rehabilitation medicine, neuroscience and computer science, reflecting the interdisciplinary characteristics of this field. ConclusionResearches on DHT for upper limb motor function rehabilitation in stroke are increasing annually, focusing on core interaction technologies, neural mechanism and artificial intelligence. Future research trends may include inter-disciplinary integration of artificial intelligence with core rehabilitation technologies, neuroimaging-guided targeted interventions, optimisation of home-based rehabilitation systems, and development of multidimensional quantitative assessment models.