Objective:To develop and evaluate a medical visual question answering (VQA) model for neonatal lung ultrasound (LUS) images to enhance intelligent auxiliary diagnosis of neonatal pulmonary diseases.Methods:Using data from neonates admitted to Beijing Obstetrics and Gynecology Hospital, Capital Medical University (January 2023 to December 2024), an image-question-answer dataset comprising 251 LUS images was constructed [43 pneumonia (17.1%), 42 neonatal respiratory distress syndrome (16.7%), 83 transient tachypnea (33.1%), and 83 normal (33.1%) images] with a four-tier medical question-answer framework. Building upon the Qwen2.5-VL-7B base model and integrating LoRA fine-tuning with chain-of-thought prompting, we developed the NLUS-VQA model to enhance visual-language semantic alignment and enable stepwise clinical reasoning, achieving efficient small-sample adaptation. Model performance was comprehensively assessed through natural language generation metrics (BLEU-4, ROUGE-1/2/L), qualitative evaluation of characteristic recognition, and clinical consistency analysis.Results:(1) Quantitative evaluation demonstrated that NLUS-VQA achieved scores of 22.38 (BLEU-4), 48.26 (ROUGE-1), 22.40 (ROUGE-2), and 37.20 (ROUGE-L), representing significant improvements over baseline models. (2) Qualitatively, the model exhibited strong performance in identifying lung consolidation, coalescent B-lines, and snowflake signs, with its chain-of-thought strategy enhancing clinical interpretability and answer accuracy. (3) Clinically, NLUS-VQA achieved a Cohen's Kappa coefficient of 0.78 and diagnostic accuracy of 80.8% (21/26), indicating substantial agreement with clinical experts.Conclusion:The NLUS-VQA model demonstrates robust interpretability in recognizing key sonographic patterns (e.g. lung consolidation, confluent B-lines, and snowflake signs), providing a scalable framework for small-sample medical image analysis, though diagnostic performance on complex conditions remains limited by dataset scale and minority class representation.

Objective To analyze the spatiotemporal evolution patterns of mortality and disease burden of smoking-related prostate cancer(PCa)from 1990 to 2021 and to predict the future trends,so as to provide evidence-based insights for optimizing regional PCa prevention policies and smoking cessation interventions.Methods Based on data from the Global Burden of Disease Study(GBD)2021,annual mortality,disability-adjusted life years(DALYs),years of life lost(YLLs),years lived with disability(YLDs),and age-standardized rates(ASRs)for PCa across 204 countries and 21 regions from 1990 to 2021 were obtained.Estimated annual percentage change(EAPC)was used to assess the disease burden and mortality of smoking-related PCa across global,regional,socio-demographic index(SDI),and age groups.An autoregressive integrated moving average(ARIMA)model was employed to predict trends in these indicators up to 2050.Results In 2021,smoking-related PCa caused 12 992 global deaths,a 30.74％increase compared to 1990.However,from 1990 to 2021,the global age-standardized mortality rate(ASMR),age-standardized DALYs rate(ASDR),age-standardized YLDs rate(ASYR),and age-standardized YLLs rate(ASLR)for smoking-related PCa declined,with EAPCs being-1.43(95％CI:-1.77--1.12),-1.39(95％CI:-1.66--1.12),-0.41(95％CI:-0.67--0.15)and-1.51(95％CI:-1.78--1.23).In 2021,the region with the highest number of deaths from PCa was Asia(4663 deaths),followed by Europe(4647 deaths),and Oceania had the lowest number of deaths(9 deaths).From 1990 to 2021,the mortality rate of PCa in most regions generally showed a downward trend.High SDI regions showed the most significant declines in ASMR,ASDR,and ASLR[EAPCs:-3.17(95％CI:-3.31--3.02),-2.91(95％CI:-3.02--2.83),and-3.22(95％CI:-3.35--3.09)].For ASYR,only high-SDI regions exhibited a decline,whereas low-middle-SDI regions saw the largest increase[EAPC:1.26(95％CI:1.19-1.33)].In 2021,the number of PCa deaths was more concentrated in the age groups of 70-74 and 75-79,with 2312 and 2278 deaths,respectively.From 1990 to 2021,ASMR,ASDR,and ASLR showed an overall downward trend,EAPC were-2.84(95％CI:-3.21--1.83),-2.77(95％CI:-3.13--1.75),and-2.84(95％CI:-3.14--1.71),with the most significant decline observed in individuals aged 35-39.Projections to 2050 indicated continuing declines in all burden metrics,which would stabilize in later years.Conclusion Despite a global decline in smoking-related PCa burden over the past three decades,significant regional disparities persist,with low-and middle-income countries facing ongoing challenges.Implementing stricter tobacco control policies is critical to mitigating smoking-related health risks.

Objective To analyze the spatiotemporal evolution patterns of mortality and disease burden of smoking-related prostate cancer(PCa)from 1990 to 2021 and to predict the future trends,so as to provide evidence-based insights for optimizing regional PCa prevention policies and smoking cessation interventions.Methods Based on data from the Global Burden of Disease Study(GBD)2021,annual mortality,disability-adjusted life years(DALYs),years of life lost(YLLs),years lived with disability(YLDs),and age-standardized rates(ASRs)for PCa across 204 countries and 21 regions from 1990 to 2021 were obtained.Estimated annual percentage change(EAPC)was used to assess the disease burden and mortality of smoking-related PCa across global,regional,socio-demographic index(SDI),and age groups.An autoregressive integrated moving average(ARIMA)model was employed to predict trends in these indicators up to 2050.Results In 2021,smoking-related PCa caused 12 992 global deaths,a 30.74％increase compared to 1990.However,from 1990 to 2021,the global age-standardized mortality rate(ASMR),age-standardized DALYs rate(ASDR),age-standardized YLDs rate(ASYR),and age-standardized YLLs rate(ASLR)for smoking-related PCa declined,with EAPCs being-1.43(95％CI:-1.77--1.12),-1.39(95％CI:-1.66--1.12),-0.41(95％CI:-0.67--0.15)and-1.51(95％CI:-1.78--1.23).In 2021,the region with the highest number of deaths from PCa was Asia(4663 deaths),followed by Europe(4647 deaths),and Oceania had the lowest number of deaths(9 deaths).From 1990 to 2021,the mortality rate of PCa in most regions generally showed a downward trend.High SDI regions showed the most significant declines in ASMR,ASDR,and ASLR[EAPCs:-3.17(95％CI:-3.31--3.02),-2.91(95％CI:-3.02--2.83),and-3.22(95％CI:-3.35--3.09)].For ASYR,only high-SDI regions exhibited a decline,whereas low-middle-SDI regions saw the largest increase[EAPC:1.26(95％CI:1.19-1.33)].In 2021,the number of PCa deaths was more concentrated in the age groups of 70-74 and 75-79,with 2312 and 2278 deaths,respectively.From 1990 to 2021,ASMR,ASDR,and ASLR showed an overall downward trend,EAPC were-2.84(95％CI:-3.21--1.83),-2.77(95％CI:-3.13--1.75),and-2.84(95％CI:-3.14--1.71),with the most significant decline observed in individuals aged 35-39.Projections to 2050 indicated continuing declines in all burden metrics,which would stabilize in later years.Conclusion Despite a global decline in smoking-related PCa burden over the past three decades,significant regional disparities persist,with low-and middle-income countries facing ongoing challenges.Implementing stricter tobacco control policies is critical to mitigating smoking-related health risks.

Objective:To develop and evaluate a medical visual question answering (VQA) model for neonatal lung ultrasound (LUS) images to enhance intelligent auxiliary diagnosis of neonatal pulmonary diseases.Methods:Using data from neonates admitted to Beijing Obstetrics and Gynecology Hospital, Capital Medical University (January 2023 to December 2024), an image-question-answer dataset comprising 251 LUS images was constructed [43 pneumonia (17.1%), 42 neonatal respiratory distress syndrome (16.7%), 83 transient tachypnea (33.1%), and 83 normal (33.1%) images] with a four-tier medical question-answer framework. Building upon the Qwen2.5-VL-7B base model and integrating LoRA fine-tuning with chain-of-thought prompting, we developed the NLUS-VQA model to enhance visual-language semantic alignment and enable stepwise clinical reasoning, achieving efficient small-sample adaptation. Model performance was comprehensively assessed through natural language generation metrics (BLEU-4, ROUGE-1/2/L), qualitative evaluation of characteristic recognition, and clinical consistency analysis.Results:(1) Quantitative evaluation demonstrated that NLUS-VQA achieved scores of 22.38 (BLEU-4), 48.26 (ROUGE-1), 22.40 (ROUGE-2), and 37.20 (ROUGE-L), representing significant improvements over baseline models. (2) Qualitatively, the model exhibited strong performance in identifying lung consolidation, coalescent B-lines, and snowflake signs, with its chain-of-thought strategy enhancing clinical interpretability and answer accuracy. (3) Clinically, NLUS-VQA achieved a Cohen's Kappa coefficient of 0.78 and diagnostic accuracy of 80.8% (21/26), indicating substantial agreement with clinical experts.Conclusion:The NLUS-VQA model demonstrates robust interpretability in recognizing key sonographic patterns (e.g. lung consolidation, confluent B-lines, and snowflake signs), providing a scalable framework for small-sample medical image analysis, though diagnostic performance on complex conditions remains limited by dataset scale and minority class representation.

Objective·To evaluate the relationship between body mass index(BMI)and chronic metabolic diseases.Methods·The elderly(≥60 years old)who were underwent physical examination in the Physical Examination Center of Renji Hospital,Shanghai Jiao Tong University School of Medicine from 2014 to 2021 were studied.Their results of biochemical indicators were collected.Their height,body weight,and blood pressure were measured by trained nurses.The history of chronic metabolic diseases was collected by self-reported questionnaire.Systolic blood pressure≥140 mmHg(1 mmHg=0.133 kPa),diastolic blood pressure≥90 mmHg,or self-reported hypertension history was defined as hypertension.Fasting blood glucose≥7.0 mmol/L or self-reported history of diabetes was defined as diabetes.Total cholesterol≥6.2 mmol/L,triglyceride≥2.3 mmol/L,or self-reported history of dyslipidemia was defined as dyslipidemia.The relationship between BMI and hypertension,diabetes,and dyslipidemia was evaluated by using receiver operator characteristic(ROC)curve analysis and binary logistic regression.Results·Data of 59 083 subjects were collected[30 807 men and 28 276 women,average age:(67.9±6.3)years old].The prevalence of hypertension,diabetes and dyslipidemia was 76.5%(45 219/59 083),24.1%(14 225/59 083)and 50.0%(29 544/59 083),respectively.Compared to the elderly people aged 60?74 years,those aged 75 years and above had a higher proportion of hypertension and diabetes,and a lower proportion of dyslipidemia and no metabolic abnormalities.With ROC analysis,the BMI cut-off values for hypertension,diabetes,and dyslipidemia were 24.3,23.9,and 23.9 kg/m2.The BMI cut-off values for hypertension and diabetes in elderly men were similar to those in elderly women(for hypertension:24.3 kg/m2 in elderly men vs 24.2 kg/m2 in elderly women;for diabetes:24.0 kg/m2 in elderly men vs 23.7 kg/m2 in elderly women);however,BMI cut-off value for dyslipidemia was obviously higher in elderly men than that in elderly women(24.0 kg/m2 in elderly men vs 22.5 kg/m2 in elderly women).The BMI cut-off value for chronic metabolic diseases was higher in the elderly people aged 60?74 years than that in the elderly people aged 75 years and above(24.2?24.7 kg/m2 vs 22.9?23.8 kg/m2).Conclusion·Elderly people aged 60?74 years should maintain the BMI below 24.0 kg/m2,while those aged 75 years and above should aim for the BMI below 23.0 kg/m2,so as to reduce the risk of chronic metabolic diseases.