Pegylated interferon α-2b （PEG-IFN-α-2b） is currently a first-line drug for the treatment of chronic hepatitis B virus infection and is widely used in clinical practice. This drug has multiple effects of inhibiting viral replication， regulating immunity， and improving liver function， and some patients can achieve clinical cure. However， it often causes various adverse reactions during treatment， which are important factors for compromising treatment compliance and efficacy. This article systematically reviews the adverse reactions and their mechanisms during PEG-IFN-α-2b therapy for chronic hepatitis B， including influenza-like symptoms， peripheral blood cytopenia， thyroid dysfunction， and neuropsychiatric symptoms， and it also summarizes the monitoring and management strategies for these adverse reactions， in order to provide evidence-based guidance for clinical decision-making and emphasize the importance of individualized treatment.

OBJECTIVE To explore and establish a full-cycle management model for drug traceability codes that aligns with national policy requirements and the practical needs of healthcare institutions， thereby enhancing the refinement of drug management and the level of medication safety. METHODS A tripartite strategy integrating “hardware deployment， system transformation， and process re-engineering” was adopted. This involved the introduction of intelligent identification devices （personal digital assistant， high-definition industrial reader）， the modification of the hospital information system interface， and the re-engineering of workflows （drug warehousing， dispensing and distribution， drug withdrawal， uploading to the insurance platform） to achieve comprehensive， informatized collection and association of drug traceability codes throughout all stages. RESULTS A full-cycle management model for drug traceability codes was successfully established， realizing the goals of making drugs “traceable to their source， trackable in their distribution， and accountable in their responsibility”. The patient waiting time for medication dispensing before and after the implementation was [3.08（1.67，5.58）] min and [3.28（1.77，5.98）] min， respectively. Among them， the patient waiting time under the pre-preparation mode was [3.60（2.13，6.35）] min and [3.50（2.03，6.30）] min， respectively； the patient waiting time under the real-time mode was [2.05（0.83，4.03）] min and [2.78（1.18，5.38）] min， respectively； the number of dispensing errors was 3， 0， respectively； the staffing of relevant positions had not been increased. CONCLUSIONS The drug traceability code management model constructed from a full-cycle perspective effectively meets national policy requirements. It provides data support for refined hospital management and offers solid technical and procedural safeguards for ensuring patient medication safety and strengthening medical insurance fund supervision， demonstrating practical value.

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.

ObjectiveTo explore the relationship between negative life events and depression severity in adolescent patients with depressive disorder， as well as the chain mediating role of insomnia symptoms and quality of life. Methods374 outpatient patients and hospitalized patients with adolescent depressive disorders were enrolled. The Adolescent Life Event Scale （ASLEC）， the Insomnia Severity Index （ISI）， the World Health Organization Quality of Life Questionnaire Short Form （WHOQOL-BREF）， and the Center for Epidemiology Depression Scale （CES-D） were used to evaluate the negative life event situation， insomnia symptoms， quality of life level and depression severity of the subjects， respectively. In addition， the PROCESS 4.0 macroprogram was used to analyze the chain mediating effect of insomnia symptoms and quality of life between negative life events and depression severity in patients with adolescent depressive disorder. ResultsThe results of correlation analysis showed that there was a significant correlation between negative life events and insomnia symptoms， quality of life， and depression severity （all P<0.05）. In addition， the results of chain mediation showed that negative life events had a significant direct effect on depression severity， with an effect size of 0.12 （P<0.001）. Insomnia symptoms and quality of life played a mediating role in the relationship between negative life events and depression severity in patients with adolescent depressive disorders， with indirect effect sizes of 0.062 （95%CI： 0.040-0.087） and 0.091 （95%CI： 0.059-0.123）， respectively. It could also play a chain mediation role， and the effect size was 0.039 （95%CI： 0.024-0.057）. ConclusionNegative life events experienced by patients with adolescent depressive disorder not only directly affect the severity of depressive symptoms， but may also indirectly exacerbate depression through insomnia symptoms and quality of life.

Diabetic kidney disease （DKD）， a common complication of diabetes mellitus， is a leading global cause of end-stage renal disease （ESRD）. Current therapeutic strategies primarily focus on symptomatic management but exhibit limited efficacy in halting disease progression to ESRD， and some drugs carry non-negligible toxic side effects. Traditional Chinese medicine （TCM） has a long history in treating DKD， with single TCM and TCM compounds demonstrating unique advantages in multi-target， multi-pathway， and multi-effect therapeutic interventions. Tripterygium wilfordii （TW）， known for its effects in promoting blood circulation， dredging collaterals， dispelling wind， removing dampness， reducing swelling， and alleviating pain， contains bioactive components such as Tripterygium glycosides （TWG）， triptolide （TPL）， tripdiolide （TPD）， and celastrol （CEL）. The active ingredients possess various functions， including regulating immune-inflammatory balance， ameliorating renal fibrosis and glomerulosclerosis， combating oxidative stress， protecting podocytes， and improving glucose and lipid metabolism， all of which play a significant role in the treatment of DKD. This review summarized the mechanisms underlying the therapeutic effects of T. wilfordii and its active ingredients on DKD， aiming to provide insights for clinical management and novel drug development of DKD.

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.

Chronic obstructive pulmonary disease (COPD) is the most common chronic respiratory disease around the world, and pharmacotherapy is the foremost treatment method currently. In recent decades, with the rapid development of bronchoscopic interventional therapy, endoscopic physical ablation technology presents a therapeutic effect in treating COPD, with few treatment-related side effects, showing excellent application prospects in treating COPD. Since ablation techniques in this field are emerging technologies with low patient acceptance, they are not widely used in the clinical treatment of COPD. This article reviews the development process of physical ablation techniques. Moreover, their current application status and the prospects in the field of COPD treatment are also summarized and analyzed. We hope to promote the application of physical ablation in the clinical treatment of COPD and provide practical references and a theoretical basis for the clinical treatment of COPD.

OBJECTIVE To provide technical support for improving recognition rate of adverse drug events （ADEs） related to traditional Chinese medicine （TCM） formula granules and decoction pieces among inpatient patients. METHODS By referencing the global trigger tool （GTT） whitepaper， literature on adverse reactions to TCM， and expert review opinions， ADE trigger items for TCM formula granules and decoction pieces used in the inpatients were established. GTT was applied to analyze ADEs in inpatients who had used TCM formula granules and decoction pieces in our hospital from August 2013 to August 2023， utilizing the Chinese Hospital Pharmacovigilance System. The effectiveness of GTT and the characteristics of these ADEs were analyzed. RESULTS A total of forty-eight triggers were established， including thirty-two laboratory test indexes， thirteen clinical symptoms， and three antidotes. Among the 1 682 patients included， GTT identified 652 potential ADEs， 284 true positive ADEs，with a trigger rate of 38.76% and a positive predictive value of 43.56%. After review by the auditor， 278 cases of ADEs were finally confirmed， with an incidence rate of 16.53%， significantly higher than the number of spontaneously reported ADEs during the same period （0）. The 278 cases of ADEs were mostly grade 1 （223 cases）， mainly involving hepatobiliary system， gastrointestinal system， blood- lymphatic system， etc；a total of 219 types of TCMs are involved，and the top five suspected TCMs used at a frequency higher than 1% were Poria cocos， Codonopsis pilosula， Atractylodes macrocephala， fried Glycyrrhiza uralensis， and Scutellaria baicalensis. CONCLUSIONS The established GTT can improve the recognition rate of ADEs for hospitalized patients using traditional Chinese medicine formula granules and decoction pieces.

In recent years, there has been a significant surge in the prevalence of myopia at younger ages in China. Numerous studies have investigated methods for preventing and controlling myopia, including orthokeratology, low-concentration atropine eye drops, light therapy, posterior scleral reinforcement, and traditional Chinese medicine. These approaches can modulate choroidal thickness, blood flow, and target various molecular mechanisms. Orthokeratology and low-concentration atropine demonstrate a thickening effect on the choroid and regulate choroidal blood flow; the use of multi-point defocus control lenses also shows promise in thickening the choroid; the influence of light and light feeding therapy on myopia prevention and control is also reflected in the choroidal thickness and blood flow; and the traditional Chinese medicine has shown good prospect in influencing the microstructure of the choroid for myopia prevention and control. However, the long-term effects of various prevention and control measures on the choroid still need to be explored with a large sample size. This article provides an overview of various methods used to regulate the choroid and prevent myopia. The mechanisms by which these interventions act on the choroid are described to provide new insights and identity novel clinical strategies for myopia management.

Objective:To explore the application of dental scenario-based clinical thinking teaching and examination system in oral education.Methods:A total of 70 resident physicians from the 2022 class at the dental base of Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine were selected and randomly divided into a control group (30 participants) and an experimental group (40 participants). The control group was taught using traditional teaching methods, and the experimental group was taught and trained using the dental scenario-based clinical thinking teaching and examination system. After one year of teaching, both groups participated in a unified annual assessment. Finally, the teaching effectiveness was evaluated through a questionnaire survey on the experimental group. The questionnaire data were analyzed using the Chi-square test in IBM SPSS 24.0 statistical software, and the t-test was conducted using GraphPad Prism 8.0.2 software. Results:The average score before teaching was (78.83±2.61) in the control group and (78.28±3.29) in the experimental group, with no statistical significant difference between the two groups ( t=0.77, P=0.447). The average score in the annual assessment after teaching was (78.57±3.50) in the control group and (81.75±4.63) in the experimental group, with statistical significant difference between the two groups ( t=3.15, P=0.002). The questionnaire survey indicated that students highly recognized the dental scenario-based clinical thinking teaching and examination system, noting its advantages of innovative and interesting lectures, the ability to improve clinical thinking skills, and not being limited by location or time. Conclusions:The dental scenario-based clinical thinking teaching and examination system can stimulate students' interest and enthusiasm for independent learning. The system has received high levels of acceptance among students. The application and development of the dental scenario-based clinical thinking teaching and examination system hold significant value.