The chemical constituents of sesquiterpenes from 95% ethanol extract of Aquilariae Lignum Resinatum were isolated and purified by various column chromatography techniques, including silica gel, Sephadex LH-20, octadecylsilyl(ODS), and semi-preparative high performance liquid chromatography(HPLC). Their planar structures and absolute configurations were elucidated by ultraviolet(UV) spectrometry, infrared(IR) spectroscopy, mass spectrometry(MS), nuclear magnetic resonance(NMR), electronic circular dichroism(ECD), and other techniques. Eight sesquiterpenoids were isolated and identified as(+)-(7R,10R)-selina-4,11-dien-12-dimethoxy-15-al(1),(+)-(7R,10R)-selina-4,11-diene-12,15-dial(2), agalleudesmanol B(3), aquisinenoid C(4), 12,15-dioxo-α-selinen(5), agarospiranic aldehyde B(6), neopetasane(7), and eremophila-7(11),9-dien-8-one(8). Compound 1 was a new compound, and it was the first time to find a dimethoxy substitution on the side chain of eudesmane-type sesquiterpene skeleton.
Sesquiterpenes/isolation & purification* ; Thymelaeaceae/chemistry* ; Molecular Structure ; Drugs, Chinese Herbal/isolation & purification* ; Magnetic Resonance Spectroscopy

Objective To assess the status of rodent infestation in commercial kitchens using data from the‘Bright Kitchen, Clean Stove' initiative. The potential use of artificial-intelligence(AI)-based surveillance systems to monitor rodent density was explored, thereby providing a scientific basis for rodent control strategies. Methods As a component of the ‘Bright Kitchen, Clean Stove' initiative, the Minhang District Market Supervision Administration in Shanghai has installed cameras in 297 kitchens. These systems incorporate an AIpowered rodent image recognition method that automatically captures and stores the first image captured in each kitchen each day when a rodent is detected. In 2023, the system collected and stored 736 screenshots of rodents. Following manual verification,720 of the images were confirmed to contain rodents. The images were analyzed by noting the time, location, and kitchen area, and the species were manually identified to assess the population density. Results Rodent activity was detected in 34 of the 297 monitored kitchens, with an overall infestation rate of 11.45%. Of the 720 confirmed images of rodents, Rattus norvegicus(brown rat)was the predominant species, present in 409(56.81 %)images. Rodents were primarily concentrated in hot food preparation spaces. The density fluctuation curve had a multimodal pattern peaking in spring and autumn. The peak of daily activity was between 22: 00 and 2: 00. There was a significant difference in the rodent detection frequency between weekends and weekdays during peak hours and during non-peak hours(χ2=7.18, P＜ 0.01). Conclusions The ‘Bright Kitchen, Clear Stove' smart monitoring system has been proven to be applicable to rodent density monitoring. To control rodents in commercial kitchens, greater efforts are required to address and identify the specific infesting conditions and the key points in the control process.

Objective:To analyze the individual and cumulative effects of unhealthy lifestyle on the prevalence of hypertension, diabetes and dyslipidemia in old adults in China, and find out the critical lifestyle in the network.Methods:Based on the baseline data of Yunnan Behavior and Disease Surveillance Cohort in 2021, a total of 16 763 older adults aged ≥60 years were included in our study. The unhealthy lifestyle factors including smoking, drinking, unhealthy eating habit, lower physical activity level, abnormal BMI and abnormal waist circumference. We calculated the unhealthy lifestyle score by using the cumulative exposures of each participant. Multiple logistic regression and mixed graphical models were used to describe the association between unhealthy lifestyle and the prevalence of hypertension, diabetes and dyslipidemia.Results:The prevalence of hypertension, diabetes and dyslipidemia were 57.0%, 11.5% and 37.0%, respectively. Most of the unhealthy lifestyles included in the study were risk factors for hypertension, diabetes and dyslipidemia, and the risks of disease increased with the increase of the unhealthy lifestyle score. The participants with the highest score (score: 6) had significantly higher prevalence of hypertension ( OR=3.99, 95% CI: 1.81-8.80), diabetes ( OR=4.64, 95% CI: 1.64-13.15) and dyslipidemia ( OR=4.26, 95% CI: 2.08-8.73) compared with those with lowest score (score: 0). In the network constructed by mixed graphical model, abnormal waist circumference (bridge strength=0.81) and hypertension (bridge strength=0.55) were vital bridge nodes connecting unhealthy lifestyle and hypertension, diabetes and dyslipidemia. Conclusions:The unhealthy lifestyle score was associated with risks for hypertension, diabetes and dyslipidemia. Abnormal waist circumference was the key factor for chronic diseases in old adults.

In recent years, the research focus on health-related behavior and chronic non-communicable diseases has shifted from the analysis on independent effects of multiple causes on a single outcome to the evaluation the complex relationships between multiple causes and multiple effects. Complex network theory, an important branch of system science, considers the relationships among factors in a network and can reveal how health-related behaviors interact with chronic diseases through a series of complex network models and indicators. This paper summarizes the definition and development of complex network theory and its commonly used models, indicators, and case studies in the field of health-related behavior and chronic disease to promote the application of complex network theory in the field of health and provide reference and tools for future research of the relationship between health-related behavior and chronic disease.

Objective:To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses.Methods:A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity.Results:A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95% CI: 1.73-2.65) times, 8.80 (95% CI: 7.91-9.78) times, and 17.02 (95% CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions:Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Objective:To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia.Methods:Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism.Results:A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95% CI: 1.31-2.86) times and 2.37 (95% CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0; People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95% CI: 1.08-3.61) times, 2.87 (95% CI: 1.60-5.14) times and 3.95 (95% CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion:The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.

Objective In this study,a pictorial database of Aedes albopictus eggs was built to establish a model for the automatic recognition and counting of eggs of this mosquito species.Methods In total,449 images of Ae.albopictus eggs from field strains in three districts of Shanghai and laboratory strains were collected.The eggs were manually calibrated using the Python environment labeling library,and the faster region-based convolution neural network(Faster R-CNN)was used to train the model with the tile overlap method.Results The results of model validation evaluation using accuracy,recall,and F-measure showed that after 15 training sessions,the loss gradually decreased with increasing training frequency and ultimately decreased to 0.000119.The mean accuracy(mAP)increased from 0.968 to 0.980 with increasing training frequency.The final model had an accuracy of up to 0.90,a recall rate of 0.97,and an F-measure of 0.93.Conclusion The established model achieved its function of assisting in egg identification and counting.With further optimization of the model and refining of its classification and recognition capabilities,it will serve as a simple and efficient auxiliary monitoring tool.

Objective:To explore the potential action mechanism of Huotu Jiji Pellets(HJP)in the treatment of erectile dys-function(ED)based on network pharmacology and molecular docking.Methods:We identified the main effective compounds and active molecular targets of HJP from the database of Traditional Chinese Medicine Systems Pharmacology(TCMSP)and Integrative Pharmacology-Based Research Platform of Traditional Chinese Medicine(TCMIP)and the therapeutic target genes of ED from the data-bases of Genecards.Then we obtained the common targets of HJP and ED using the Venny software,constructed a protein-protein in-teraction(PPI)network of HJP acting on ED,and screened out the core targets with the Cytoscape software.Lastly we performed GO functional enrichment and KEGG pathway enrichment analyses of the core targets followed by molecular docking of HJP and the core targets using Chem3D and AutoDock Tools and QuickVina-W software.Results:A total of 64 effective compounds,822 drug-related targets,1 783 disease-related targets and 320 common targets were obtained in this study.PPI network analysis showed that the core targets of HJP for ED included ESR1,HSP90AA1,SRC,and STAT3.GO functional enrichment analysis indicated the involvement of the core targets in such biological processes as response to xenobiotic stimulus,positive regulation of kinase activity,and positive regu-lation of MAPK cascade.KEGG pathway enrichment analysis suggested that PI3K-Akt,apoptosis,MAPK,HIF-1,VEGF,autophagy and other signaling pathways may be related to the mechanism of HJP acting on ED.Molecular docking prediction exhibited a good doc-king activity of the key active molecules of HJP with the core targets.Conclusion:This study showed that HJP acted on ED through multi-components,multi-targets and multi-pathways,which has provided some evidence and reference for the clinical treatment and subsequent studies of the disease.

Objective: To analyze the trends of the age of menarche among Chinese Han girls aged 9 to 18 years from 2010 to 2019. Methods: Data were extracted from the Chinese National Surveys on Students' Constitution and Health in 2010, 2014 and 2019. A total of 253 037 Han girls aged 9 to 18 years with complete data on menarche were selected in this study. They were asked one-on-one about their menstrual status, age and residence information. The median age of menarche was estimated by probability regression. U tests were used to compare the difference in median age at menarche in different years. Results: The median age at menarche (95%CI) among Chinese Han girls was 12.47 (12.09-12.83) years in 2010, 12.17 (11.95-12.38) years in 2014 and 12.05 (10.82-13.08) years in 2019, respectively. Compared with that in 2010, the median age at menarche in 2019 decreased by 0.42 years (U=-77.27, P<0.001). The annual average changes were-0.076 years from 2010 to 2014 (U=-57.19, P<0.001) and-0.023 years from 2014 to 2019 (U=-21.41, P<0.001), respectively. The average annual changes in urban areas in the periods of 2010 to 2014 and 2014 to 2019 were-0.071 years and 0.006 years, respectively, while those in rural areas were-0.082 years and-0.053 years, respectively. The average annual changes in the regions of north, northeast, east, south central, southwest and northwest were-0.064, -0.099, -0.091, -0.080, -0.096 and-0.041 years in the period of 2010 to 2014 and 0.001, -0.040, -0.002, -0.005, -0.043 and-0.081 years in the period of 2014 to 2019. Conclusion: The age of menarche among Chinese Han girls aged 9 to 18 years shows an advanced trend from 2010 to 2019, and the trends in urban and rural areas and different regions have different characteristics.

Objective: To analyze the trend of the detection rate of myopia among Chinese Han children and adolescents aged 7-18 years from 2010 to 2019. Methods: Data from the Chinese National Survey on Students' Constitution and Health in 2010, 2014 and 2019 were used, and about 213 833, 212 742 and 209 942 Han students aged 7-18 years were included in this study. The χ² test was used to compare the differences in the prevalence of myopia among the subgroups in the survey year, and logistic regression was used to compare the differences in the prevalence of myopia between different years. A curve-fitting method was used to obtain the growth rate of myopia among Han Chinese students from 2010 to 2019, and the differences in the change of myopia between different age groups were analyzed. Results: In 2019, the overall detection rate of myopia among Chinese Han children and adolescents aged 7-18 was 60.1%. The detection rate of urban students (62.7%) was higher than that of rural students (57.4%) and the detection rate of girls (63.5%) was higher than that of boys (56.7%). In 2019, the regional disparities were large in the detection rate of myopia in various provinces, with the lowest in Guizhou (49.6%) and the highest in Zhejiang (71.3%). The detection rate of myopia showed an upward trend from 2010 to 2019, from 55.5% in 2010 to 57.1% in 2014, and finally to 60.1% in 2019. The gap in the detection rate of myopia between urban and rural children and adolescents gradually shrank. The average annual growth rate of myopia detection rate from 2014 to 2019 was 0.6 percentage points per year, higher than that from 2010 to 2014 about 0.4 percentage points per year. The peak age of the growth rate of myopia detection rate decreased from 12 years in 2010 to 10 years in 2014, and finally to 7 years in 2019. Conclusions: The detection rate of myopia among Chinese Han children and adolescents is still at a high level, and the peak age of the growth rate of myopia detection rate continues to advance.