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.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

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.

Zoledronic acid (ZA), a nitrogen-containing bisphosphonate with established clinical utility in osteoporosis management, exhibits emerging antitumor potential in estrogen receptor-positive breast cancer. However, the molecular mechanisms underlying its nonapoptotic anticancer effects remain poorly characterized. This study revealed that ZA induced ferroptosis in ER+ breast cancer cells through dual suppression of cystine-glutamate antiporter SLC7A11 and glutathione peroxidase 4 (GPX4), key repressors of ferroptosis. Pharmacological inhibition of ferroptosis using Ferrostatin-1 significantly attenuated ZA-induced cytotoxicity, while combinatorial treatment with the GPX4 inhibitor RSL3 synergistically enhanced lipid peroxidation and cell death. Mechanistically, ZA activated the Hippo-YAP signaling pathway, promoting YAP phosphorylation, proteasomal degradation, and cytoplasmic retention, thereby silencing SLC7A11 and GPX4. We established a novel metabolic vulnerability in hormone-responsive malignancies.These findings position ZA as a bifunctional ferroptosis inducer in ER+ breast cancer, offering a promising strategy to overcome endocrine resistance.

Objective To summarize the diagnostic ideas, clinical characteristics and treatment methods of the rupture of pseudoaneurysm in the pararenal artery, so as to provide reference for the management of such condition.Methods The diagnosis and treatment process of a patient with massive retroperitoneal hemorrhage due to rupture of pseudoaneurysm in the left pararenal artery admitted to the Affiliated Hospital of Yan'an University were reported, and relevant literature was retrieved to summarize the etiology, pathogenesis, diagnosis and treatment of this disease.Results The patient was a 49-year-old male who presented with sudden onset of lumbar and abdominal pain.After admission, enhanced computed tomography (CT) scan indicated a cystic lesion in the left kidney, along with fluffy high-density and fluidic density shadows around the kidney.There was extensive extravasation of contrast agent in the lower polar artery of the left kidney, with rupture shadows, retention of contrast agent, and the extent of extravasation expanding in the venous phase and delayed phase, suggesting that the renal artery or pararenal artery had ruptured and bled.After consultation by the Department of Intervention, an urgent superselective left renal artery embolization procedure was performed.During the operation, angiography showed the “jetting sign” in the arterial phase, and the stenosis at the neck of the tumor.In the delayed phase, the contrast agent was retained accompanied with the “chimney sign”, which was consistent with the characteristics of a pseudoaneurysm.The final diagnosis was rupture and bleeding of a pseudoaneurysm of the left pararenal artery, along with the formation of a hematoma, as well as accumulation of blood and fluid in the abdominal and pelvic cavities.The patient recovered well after surgery.After a follow-up of 6 months, CT scan showed that the hematoma was basically absorbed and there were no obvious abdominal pain or other discomforts.Conclusion Rupture of pseudoaneurysm in the pararenal artery is rare in clinical practice.Treatment should be tailored to the anatomical features and the patients' condition.Multidisciplinary collaboration, precise imaging evaluation, and the application of interventional techniques can achieve efficient diagnosis and treatment, and protect the renal function to the greatest extent.

Objective To establish a rat model of venous thrombosis in a plateau hypobaric hypoxic environment and to investigate the effect of this environment on venous thrombosis.Methods A total of 144 healthy male SD rats were assigned randomly to four groups(n=36 rats per group):a plains sham operation(A)group,plains operation(B)group,plateau altitude 6000 m+sham operation(C)group,and plateau altitude 6000 m+surgery(D)group.Rats in A and B groups were maintained in a plains normoxic environment,while rats in C and D groups C and D were subjected to a plateau environment.Rats in the surgical groups underwent quantitative constriction to incompletely obstruct the inferior vena cava blood flow.Each group was further divided into subgroups based on time:1,3,5,7,14,and 21 d(n=6 rats per group).Regular vascular ultrasound monitoring was conducted,and blood samples were taken for whole blood viscosity testing and the assessment of inflammatory indicators,including endothelin-1(ET-1),interleukin-6(IL-6)and tissue factor(TF).Coagulation function was evaluated through the activated partial thromboplastin time(APTT),prothrombin time(PT),thrombin time(TT),fibrinogen(FIB)and D-dimer.After the observation period,the experimental animals were sacrificed and the limbs were removed.Thrombus samples were stained with hematoxylin/eosin(HE),and the thrombus wet mass was measured.Results The thrombosis incidence was significantly higher in the plateau D group than in B group,accompanied by a marked increase in blood viscosity and hematocrit(P＜0.01).Additionally,levels of ET-1,IL-6,and TF were significantly elevated(P＜0.05),indicating a coagulation disorder.Conclusions A plateau hypoxic environment model can be successfully simulated by quantitative coarctation of the inferior vena cava,combined with a specialized environmental chamber.The findings of this study suggest that a plateau hypoxic environment promotes venous thrombosis.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

Objective Network pharmacology and molecular docking techniques were used to predict the potential mechanisms by which the active components of Piper nigrum(PN)regulate depressive-like behaviors in chronic restraint stress(CRS)mice.Methods The major chemical components and targets of PN were screened using the Traditional Chinese Medicine Systems Pharmacology database.Targets related to ferroptosis and depression were obtained from the Online Mendelian Inheritance in Man,GeneCards,and FerrDB databases.The intersecting targets were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Gnomes(KEGG)pathway enrichment analyses,and molecular docking was performed to validate the binding capacities between the core targets and their corresponding active components.Finally,we established a CRS mouse model.Mice were treated with PN 75,150,and 300 mg/kg for 4 weeks,followed by behavioral assessments and reverse transcription-quantitative polymerase chain reaction(RT-qPCR)to verify the expression of core genes.Results Nine active components were screened from PN,corresponding to 27 targets,and 8377 targets related to depression and 547 targets associated with ferroptosis were screened from the databases.The intersection of these three sets resulted in 25 target genes.KEGG enrichment analysis revealed that these core targets were predominantly enriched in signaling pathways,including cholinergic synapses,serotonergic synapses,and neuroactive ligand-receptor interactions.Molecular docking result showed that the main active components of PN had strong binding affinities for the targets CHRM2,SLC6A4,PTGS2,and SLC6A2.Behavioral assessments demonstrated that PN significantly increased the sucrose preference index(P＜0.01,P＜0.001),reduced immobility time in the tail suspension and forced swimming tests(P＜0.01,P＜0.001),and enhanced exploratory behavior in the open field test(P＜0.05.P＜0.01,P＜0.001).PN significantly reduced the serum levels of inflammation markers(P＜0.05.P＜0.01,P＜0.001),as shown by enzyme-linked immunosorbent assay,and neurotransmitter analysis revealed that PN significantly increased the levels of serotonin and acetylcholine in the mouse hippocampus(P＜0.05).RT-qPCR showed that PN demonstrated the mRNA expression of SLC6A4(P＜0.05.P＜0.01,P＜0.001).Conclusions PN may improve depressive-like behavior in mice by modulating serotonin and acetylcholine levels,inhibiting inflammatory responses,participating in immune regulation,and exerting neuroprotective effects.

Objective To develop a refined management model for operating rooms and assess its clinical impact on op-erational efficiency and cost control.Methods The study included 10,728 elective surgeries from January to June 2024 as the study group and 9 414 elective surgeries from January to June 2023 as the control group.The differences in operational metrics before and after implementing the refined management model were compared.The model was developed through comprehensive management by hospital leadership and multi-department collaboration,focusing on management structure,systems,processes,information technology,and resource allocation.Results In terms of efficiency,the on-time start rate of the first surgeries in the study group was significantly higher than in the control group(P＜0.05).The turnover time between surgeries was shorter in the study group(P＜0.01),and the rate of unexpected surgery cancellations was lower(P＜0.01).The average cost per surgery for consumables,excluding the impact of centralized procurement of consumables,was approximately 971 yuan,representing an 11% reduction compared to the previous year,despite a 14% increase in surgical volume.The average daily operating cost per operating room was about 12 303 yuan,a 7% reduction.Economic benefits increased by 8.43 million yuan,a 38% year-on-year increase.Conclusion Implementing a refined management model in operating rooms can significantly enhance efficiency,re-duce costs,and achieve dual improvements in social and economic benefits.