Atopic dermatitis （AD） is a common pruritic and chronic inflammatory dermatosis in clinical practice and is one of the diseases responding specifically to traditional Chinese medicine （TCM）. With the launch of biological agents and small molecule drugs and the development and implementation of guidelines of diagnosis and treatment， clinical pathways of treatment of moderate to severe AD， and consensus on the whole-process management of AD， the clinical efficacy of moderate to severe AD has been significantly improved. However， there are still many unmet clinical needs that require more effective methods to meet. In response to the Opinions of the CPC Central Committee and the State Council on Facilitating the Inheritance， Innovation， and Development of Traditional Chinese Medicine and the spirit of the National Conference on TCM， the China Association of Chinese Medicine organized more than 20 experts in TCM dermatology， Western medicine dermatology， interdisciplinary fields， and industries to discuss the difficulties and advantages of TCM in the treatment of AD. TCM treatment for AD can not only improve rash and relieve itching but also solve many concomitant syndromes. The abundant external treatment methods of TCM have advantages for different special populations and rash characteristics. The concept of treating disease before its onset in TCM is in line with the chronic disease management mode of prevention and treatment of atopic march and prevention of recurrence. In addition， TCM therapy can reduce the use of topical glucocorticoids and has good safety. Regarding the comorbidity of AD， equal emphasis on TCM and Western medicine and multidisciplinary joint treatment should be advocated to achieve maximum benefit for patients. The exchange of TCM and Western medicine has clarified the positioning and advantages of TCM intervention in AD， providing guidance for clinical and scientific research.

Objective: To investigate the trends in incidence and mortality of lung cancer in Huangpu District, Shanghai Municipality from 2002 to 2019, so as to provide the evidence for formulating lung cancer prevention and control measures. Methods: Data of lung cancer incidence and mortality among residents in Huangpu District from 2002 to 2019 were collected through the Shanghai Cancer Registration and Reporting Management System. The crude incidence and mortality of lung cancer was calculated, and standardized by the data from the Chinese Fifth National Population Census in 2000 (Chinese-standardized rate) and the Segi's world standard population in 1960 (world-standardized rate). The trends in incidence and mortality of lung cancer among residents by age and gender were evaluated using annual percent change (APC). Results: A total of 12 965 cases of lung cancer were reported in Huangpu District from 2002 to 2019, and the crude incidence rate was 80.66/105, the Chinese-standardized incidence rate was 34.54/105, and the world-standardized incidence rate was 31.30/105, all showing upward trends (APC=4.588%, 2.933% and 3.247%, all P<0.05). A total of 10 102 deaths of lung cancer were reported, and the crude mortality rate was 62.30/105, showing an upward trend (APC=0.959%, P<0.05); the Chinese-standardized mortality was 25.93/105, and the world-standardized mortality was 22.05/105, both showing downward trends (APC=-1.282% and -1.263%, both P<0.05). The crude incidence and mortality rates of lung cancer in males were higher than those in females (101.39/105 vs. 60.52/105, 85.45/105 vs. 39.87/105, both P<0.05). The crude incidence and mortality rates of lung cancer showed upward trends with age (both P<0.05), reaching their peaks in the age groups of 80-<85 years (341.37/105) and 85 years or above (355.97/105), respectively. Conclusions The incidence of lung cancer showed an upward trend, while the mortality showed a downward trend in Huangpu District from 2002 to 2019. Elderly men were the high-risk group for lung cancer incidence and mortality.

Objective: To evaluate and compare the accuracy of responses to pediatric preventive dentistry-related questions between the domestic large language model, ChatGLM-6B, and the international large language model, ChatGPT-3.5, in order to provide insights for further research and development of domestic language models in the field of oral medicine. Methods: A total of 100 common pediatric preventive dentistry questions of varying difficulty levels [basic (n = 35), intermediate (n = 35), and advanced (n = 30) ] were provided by pediatric preventive dentistry experts. Two doctors independently registered these questions with ChatGPT-3.5 and ChatGLM-6B and collected the answers. A cohort of 16 dentists assessed responses generated by ChatGLM-6B and ChatGPT-3.5 using a predefined 3-point Likert scale. The average score of the ratings from 16 doctors was taken as the answer score. If the answer score was higher than 2.8, it was accepted as a accurate answer; if the score was lower than 1.4, it was accepted as an inaccurate answer; if the score was between 1.4 and 2.8, it was accepted as a partially accurate answer. Comparative analysis was conducted on the accuracy rates and evaluation outcomes between the two groups. Consistency analysis of the ratings was conducted Results: The answer accuracy rates of ChatGPT-3.5 and ChatGLM-6B for 100 pediatric preventive dentistry questions were comparable: ChatGPT-3.5 demonstrated 68% accurate, 30% partially accurate, and 2% inaccurate responses, while ChatGLM-6B showed 67% accurate, 31% partially accurate, and 2% inaccurate responses, with no statistically significant differences (P>0.05). Both models exhibited equivalent accuracy across questions of varying difficulty levels (basic, intermediate, advanced), showing no statistical differences (P>0.05). The overall average scores for ChatGPT3.5 and ChatGLM-6B in answering all questions were both 2.65, with no statistically significant difference (P>0.05). For questions of different difficulty levels, ChatGPT3.5 had an average score of 2.66 for basic questions while ChatGLM-6B had an average score of 2.70. For intermediate questions, ChatGPT3.5 had an average score of 2.63 and ChatGLM-6B had an average score of 2.64. For advanced questions, ChatGPT3.5 had an average score of 2.68, and ChatGLM-6B had an average score of 2.61. No statistically significant differences were observed across any difficulty category (P>0.05). The consistency of the experts’ grading ranged from fair to moderate. Conclusion This study demonstrates the potential of both ChatGLM-6B and ChatGPT-3.5 in answering pediatric preventive dentistry questions. ChatGLM-6B performed similarly to ChatGPT-3.5 in this field, but the accuracy rates of both models fell short of expectations and are not suitable for clinical use. Future efforts should focus on improving the accuracy and consistency of large language models in providing medical information, as well as developing specialized medical models for the field of oral medicine.

Background: A 2018 study on the global burden of disease, accidents, and risk factors reported that 1.6 million peo ple died in 2017 due to household air pollution. Poor indoor air quality has been highlighted as a contributing factor to respiratory diseases, cardiovascular conditions, and exacerbation of asthma and allergies. A 2019 study estimated that long-term exposure to fine particulate matter (PM2.5) with a diameter of 2.5 micrometers or less reduces average life expectancy by 1.8 years, with more severe effects in highly polluted regions. Additionally, a study by Miller et al. (2007) found that prolonged exposure to PM2.5 increases the risk of cardiovascular diseases, particularly among women. Direct measurement devices are highly effective in determining indoor PM2.5 concentrations, identifying sources of pollution, tracking pollutant dispersion, and monitoring temporal variations. Studies suggest that direct measurement is an accurate, cost-effective method that provides detailed data suitable for local conditions. Aim: To investigate the indoor air quality of houses and apartments in Darkhan city during the winter season using the Purple Air monitoring device. Materials and Methods: A cross-sectional study was conducted with a targeted sample of 128 households in Darkhan city. The study examined factors such as stove type, type of coal used, annual and daily coal consumption, frequency of heating, and chimney sealing conditions. To collect data, the Purple Air monitoring device was installed in each house hold for a month, after which it was retrieved. During retrieval, participants completed a questionnaire. The questionnaire consisted of 55 questions across 7 pages at the time of device installation and 25 questions across 3 pages at the time of device retrieval. The collected data was analyzed using SPSS 25.0. Results: A total of 128 households in Darkhan city participated in the study. The average duration of residence in the current home was 9.5 years, with no statistically significant variation. The distribution of housing types was as follows: traditional Mongolian gers (40.6%), houses (39.1%), and apartments (20.3%). The 24-hour average PM2.5 concentration was highest in gers (70.9 μg/m³), followed by houses (46.8 μg/m³) and apartments (22.8 μg/m³), with a statistically significant difference (p=0.0001). PM2.5 levels were most variable in gers, followed by houses and then apartments. House holds using central heating (apartments) had an average 24-hour PM2.5 concentration of 22.8 μg/m³, whereas households using stoves (gers and houses) had a significantly higher concentration of 59.4 μg/m³ (p=0.0001). However, there was no statistically significant difference between traditional and improved stoves. Among study participants, 21.4% reported that someone in their household smoked indoors. Additionally, 86.5% regularly burned incense, candles, or herbs, while 99.2% did not use an air purifier. Conclusion The indoor particulate matter concentration in houses and gers in Darkhan was 59.4μг/m3. Variations in stove types, poor chimney sealing limited space, and frequent gaps and cracks contribute to increased spread of indoor air pollutants.

Objective: To explore relationship of sleep quality with overweight and obesity among middle school students, so as to provide a reference basis for improving adolescent sleep health. Methods: From September to December 2023, 5 713 middle school students aged 13 to 18 were selected by stratified cluster random sampling method in six regions, including Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi and Urumqi. Sleep quality survey was conducted on middle school students by Pittsburgh Sleep Quality Index. Height and weight were measured, and World Health Organization s standards for growth and development of children and adolescents was used to evaluate their nutritional status. Both χ 2 test and Logistic regression analysis were used to analyze the association between sleep quality and nutritional status of middle school students. Results: The non compliance detection rate of sleep quality was 38.4% among girls, but 29.2% among boys, and the difference was of statistical significance( χ 2=54.08, P < 0.01 ). The detection rate of substandard sleep quality was 34.2% in the group with normal nutritional status, 38.3% in the group with overweight, 43.7% in the group with obesity and 26.0% in the group with emaciation, and the difference in the rates of substandard sleep quality among middle school students of different nutritional status was statistically significant ( χ 2=68.15, P <0.01). Logistic regression analysis showed that, after controlling for mental health and physical activity, the detection rate of substandard sleep quality in the obese groups was 1.30 times higher than that in the normal group, respectively( OR =1.30, 95% CI =1.06- 1.59 , P <0.01). Conclusions Sleep quality is correlated with overweight and obesity among middle school students, and there are gender differences. Intervention policies should be formulated according to the characteristics of different genders.

The immunomodulatory， repair， and regeneration-promoting functions of mesenchymal stem cells make them one of the potential treatment methods for liver diseases. At present， viral and non-viral delivery methods have been developed to genetically modify mesenchymal stem cells， and gene modification can promote the survival， homing， and cytokine secretion of mesenchymal stem cells， thereby enhancing the ability of mesenchymal stem cells to treat liver diseases. This article mainly summarizes the research advances in gene-modified mesenchymal stem cells in the treatment of liver diseases， in order to provide new insights and strategies for the clinical treatment of liver diseases.

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

Objective: To explore the potential category patterns of risk prevention and control behaviors of HIV infection among young students who have sex with men (MSM) and their impact on HIV infection and late detection, aiming to optimize intervention strategies. Methods: From September 2017 to December 2024, a total of 1 637 MSM young students in Tianjin were recruited through both online and offline channels. Latent class analysis was applied to classify 11 HIV risk prevention and control behaviors [condom use during the most recent anal sex in the past 6 months, consistent condom use, use of water based lubricants, abstinence from recreational drugs, regular on site professional testing, fixed sexual partners, partner testing, awareness of partner s HIV testing results, testing before sexual activity, nucleic acid testing, and use of pre exposure prophylaxis (PrEP) or post exposure prophylaxis (PEP)]. Multivariate Logistic regression analyzed associations between demographic characteristics/intervention services factors and latent classes. Differences in HIV infection and late detection across behavior patterns were compared. Results: HIV risk prevention and control behaviors among MSM students were classified into three latent classes:condom dependent group (38.42%), low prevention group (27.73%), and comprehensive prevention group (33.85%). Students who received condom promotion/testing services were more likely to belong to the comprehensive prevention group ( OR =5.58), while those who received peer education were less likely to the comprehensive prevention group ( OR =0.43) (both P <0.01). Among the MSM student population, the HIV infection rate was 4.83%, with 2.26% of cases detected late. The HIV infection rate (1.45%) and late detection proportion (0.82%) in the comprehensive prevention group were lower than those in the low prevention group (7.89% and 3.83%, respectively) ( χ 2=16.20, 7.31, both P <0.01). Conclusions HIV risk prevention and control behaviors among MSM young students exhibit significant heterogeneity. Comprehensive prevention strategies can effectively reduce HIV infection and late detection risks. It is necessary to optimize peer education content and improve the accessibility of diversified prevention measures such as PrEP/PEP to enhance HIV prevention and control.

Backgroun: Air pollution is a major global public health concern that poses serious risks to human health regardless of a country’s level of economic or technological development. According to the World Health Organization (WHO, 2021), nine out of ten people worldwide breathe polluted air, and air pollution is responsible for the deaths of approximately 800 people every hour and 13 people every minute. Prolonged exposure to polluted air has been linked to a wide range of chronic illnesses, including chronic obstructive pulmonary disease (COPD), lung and bronchial cancers, asthma, and stroke. In Mongolia, air pollution reaches its highest levels during the winter months, particularly in Ulaanbaatar, where the majority of the country’s population resides. A study conducted by Enkhjargal G. (2012) reported that the concentrations of PM10 and PM2.5 in Ulaanbaatar were 7–8 times higher than the WHO recommended guidelines. In response to such challenges, many countries have increasingly adopted low-cost, direct measurement devices such as PurpleAir to monitor air quality. These devices are valued for their accessibility, network connectivity, and potential role in smart city pollution management systems. Despite their global application, there remains a lack of research in Mongolia on the use of PurpleAir sensors to measure PM2.5 concentrations and compare the results with official monitoring station data. Addressing this gap is essential for improving local air quality monitoring capacity and informing effective public health and environmental policies. Aim: Determination of PM2.5 particulate matter pollution in the outdoor environment of Ulaanbaatar city using a direct measurement device (Purple Air). Materials and Methods: A cross-sectional study design was employed. Direct measurement devices (Purple Air) were installed in selected districts of central Ulaanbaatar between December 2024 and February 2025, measuring PM2.5 concentrations at two-minute intervals over 24-hour periods. All data were statistically processed and analyzed using the SPSS-26 software package. Results: The average concentration of PM2.5 particles in the air of Ulaanbaatar city in winter is 66.68 μg/m3. Compared to the districts, the highest concentration was determined in SKHD (118.58±90.22 μg/m3), while the lowest concentration was determined in KHUD (42.37±43.51 μg/m3). Compared to the days of the week, the highest concentrations were measured on Monday (76.68±71.98 μg/m³), Saturday (77.50±71.63 μg/m³), and Sunday (80.34±74.45 μg/m³). The highest concentration of PM2.5 particles occurred from 6 pm to 1 am, and the lowest concentration was measured during the day (between 2 pm and 4 pm). The highest concentration of PM2.5 was measured in December (74.22±73.45 μg/m3), while the lowest concentration was measured in February (50.25±57.44 μg/m3). Conclusion The concentration of PM2.5 in the air of Ulaanbaatar city is 1.7 times higher than the general standard and technical requirements of Mongolia in winter, and the highest concentration is in the SKHD. The highest concentration of PM2.5 occurs more often in December and at night than in the winter months.

Background: Particulate matter with an aerodynamic diameter of 2.5 micrometers or smaller (PM2.5) penetrates deep into the alveoli through the respiratory tract and is characterized by its ability to induce oxidative stress, systemic inflammation, and vascular inflammation. Mongolia ranks among the countries with the highest levels of air pollution. In Ulaanbaatar, where more than half of the country’s population resides, wintertime PM2.5 concentrations often exceed 200 μg/m³, which is about eight times higher than the World Health Organization (WHO) guideline value. A study involving 1,200 adults in Ulaanbaatar showed that quality of life deteriorated sharply during periods of high air pollution, with effects more pronounced among individuals who already had impaired respiratory function. Aim: To examine the relationship between indoor household PM2.5 concentrations and lung function indicators among adults in Ulaanbaatar and Darkhan. Materials and Methods: This analytical cross-sectional study recruited adult participants from Ulaanbaatar and Darkhan through targeted sampling. Household air quality was measured using PurpleAir sensors, which were installed in participants’ homes for one month. After exposure measurement, lung function was assessed via spirometry. Statistical analyses were conducted using SPSS version 25.0. Results: A total of 236 participants were included: 114 (48.3%) from Ulaanbaatar and 122 (51.7%) from Darkhan. The sample consisted of 111 men (47.0%) and 125 women (53.0%). The mean indoor PM2.5 concentration was 66.24 μg/m³ (SD 44.87 μg/m³), ranging from a minimum of 7.79 μg/m³ to a maximum of 264.55 μg/m³. Stratification by housing type showed the highest PM2.5 levels in gers (82.34 μg/m³), followed by detached houses (67.34 μg/m³), while apartments had the lowest concentrations (32.24 μg/m³). Correlation analysis revealed statistically significant negative associations between PM2.5 levels and measures of expiratory function, including the FEV1/FVC ratio, peak expiratory flow (PEF), and mid-expiratory flow (FEF25–75). Reduced forced vital capacity (FVC) was observed in 9.4% of participants, reduced forced expiratory volume in one second (FEV1) in 15.3%, and a decreased FEV1/FVC ratio in 3.8%. Conclusion Indoor household PM2.5 concentrations were highest in gers, and expiratory flow-related lung function parameters showed significant negative associations with particulate exposure. This suggests that indoor PM2.5 primarily affects airflow limitation rather than overall lung volumes in this population.