There are practical and cost-effective opportunities for the prevention and early intervention of periodontal disease, a common oral condition. Depression and anxiety represent major global mental health challenges, and they are characterized by high prevalence rates and an elevated suicide risk. Their clinical management is complicated by extended treatment timelines and substantial healthcare costs. Accumulating evidence demonstrates a statistically significant bidirectional association between periodontal disease and depression/anxiety disorders. However, established clinical pathways integrating these conditions remain lacking. This review presents a comprehensive analysis of current research examining the relationship between periodontal disease and mood disorders, specifically depression and anxiety. This study explored the bidirectional mechanisms within the microbiota-oral-brain axis, which includes both periodontal disease inducing neuroinflammation through pro-inflammatory factors, such as interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) activating the TLR-4/NF-κB signaling pathway, and depression and anxiety leading to “glucocorticoid resistance” through hypothalamic-pituitary-adrenal (HPA) axis dysregulation, thus causing dual immune dysfunction that exacerbates periodontal tissue destruction, as well as the mechanisms by which biological, psychological, and social factors contribute to the bidirectional association between periodontal disease and depression/anxiety. We propose implementing bidirectional referral protocols between dental and psychiatric services in clinical practice, incorporating mental health screening tools, such as Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7(GAD-7), for patients with moderate-to-severe periodontal disease, and incorporating periodontal examination into routine assessment during psychiatric services. This multidisciplinary approach aims to break the vicious circle between these conditions and provide clinicians with pragmatic intervention strategies.

Objective To explore the correlation and lag effect between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, and to provide a theoretical basis for the surveillance, early warning，and scientific prevention and control of scarlet fever. Methods Based on the daily scarlet fever incidence data and concurrent meteorological data in Xicheng District, Beijing from 2010 to 2019, the distributed lag non-linear model (DLNM) was used to analyze the impact of meteorological factors on the incidence of scarlet fever. Results The risk of scarlet fever was the highest when the daily average temperature was 34.2℃ with a lag of 0 days (RR=1.175, 95% CI:1.006-1.372). The risk was the second highest when the daily average temperature was 2.2℃ with a lag of 12 days (RR=1.123, 95% CI:1.044 -1.209). The cumulative relative risk of scarlet fever was statistically significant when the daily average temperature ranged from 27.2℃ to 34.2℃, with the highest cumulative relative risk at 34.2℃ (RR=1.906, 95%CI:1.215-2.989). When the daily average relative humidity was 19.5% with a lag of 6 days, the risk of scarlet fever incidence was the highest (RR=1.022, 95% CI: 1.005-1.040). The cumulative relative risk was statistically significant when the daily average relative humidity ranged from 24.7% to 40.2%, with the highest cumulative relative risk at 27.3% (RR=1.170, 95% CI: 1.020-1.343). The risk of scarlet fever was the highest when the daily average vapor pressure was 1.2 hPa with a lag of 5 days (RR=1.029, 95%CI:1.008-1.050). The cumulative relative risk of scarlet fever was statistically significant when the daily average vapor pressure was 1.2-7.4 hPa, and the highest cumulative risk was when the daily average vapor pressure was 1.2 hPa (RR=1.362, 95% CI:1.022-1.815). Conclusion There is a nonlinear relationship between meteorological factors and the incidence of scarlet fever in Xicheng District, Beijing, with a certain lag effect. Daily average temperature (27.2-34.2℃), daily average relative humidity (28.6~36.3%) and daily average vapor pressure (1.2-7.4 hPa) increase the risk of scarlet fever. These factors can be used as indicators for the prevention, control, surveillance, and early warning of scarlet fever.

Objective: To investigate the association between medium to long term PM 2.5 exposure around school areas and overweight/obesity among primary and secondary school students in Guangxi, providing data support and theoretical foundations for scientifically addressing overweight and obesity in primary and secondary school students. Methods: From September to November 2023, a stratified cluster random sampling method was employed to select 251 183 students aged 7-18 years (grade 1 to grade 12) from 14 prefecture level cities (111 districts and counties) in Guangxi. PM 2.5 mass concentration data were obtained from the Tracking Air Pollution in China (TAP) dataset. Preliminary comparative analysis was conducted using the Mann-Whitney U test, while binary Logistic regression models were applied to quantify the relationship between PM 2.5 exposure and overweight/obesity. Restricted cubic spline analysis was further utilized to examine the nonlinear association between PM 2.5 concentration and overweight/obesity risk. Results: The detection rate of overweight/obesity among Guangxi students in 2023 was 19.5%. The median PM 2.5 concentration in the year prior to the study was higher in the overweight/obesity group (23.22 μg/m 3) compared to the non overweight/obesity group (22.63 μg/m 3) ( Z=-15.66, P <0.01), and consistent trends were observed across gender (male/female) and educational stage (primary/junior/senior high school) subgroups (all P <0.01). Binary Logistic regression revealed that for every 10 μg/m 3 increase in the annual average PM 2.5 concentration, the risk of overweight/obesity increased by 12% ( OR=1.12, 95%CI=1.09- 1.15 , P <0.01). Restricted cubic spline analysis indicated a nonlinear relationship between monthly PM 2.5 levels and overweight/obesity risk ( P trend <0.01). Below 22.68 μg/m 3, PM 2.5 exposure showed no significant association with obesity risk; above the threshold, the risk increased with rising PM 2.5 levels. Conclusion Medium to long term PM 2.5 exposure around school environments is significantly associated with overweight/obesity among primary and secondary school students.

Objective: To investigate the prevalence and associated factors of spinal curvature abnormalities among primary and secondary school students in the Guangxi Zhuang Autonomous Region, so as to provide a scientific basis for the prevention and control of such abnormalities. Methods: From September to November 2023, adopting a stratified cluster random sampling method, spinal curvature screenings and questionnaire surveys were conducted among 168 931 students from grade 4 of primary school to grade 12 of high school in 111 districts and counties across 14 cities in Guangxi. Chi square tests and binary Logistic regression analysis were used to analyze influencing factors of spinal curvature abnormalities. Results: In 2023, the detection rate of poor posture among students above grade 4 in Guangxi was 4.24% , and the detection rate of spinal curvature abnormalities was 2.13%. The detection rate was higher among urban students (2.84%) than rural students (1.66%), boarding students (2.61%) than non-boarding students (1.60%), and high school students (3.16%) than junior high (2.45%) and primary school students (1.15%), and the differences were statistically significant ( χ 2=269.85, 221.44, 565.10, P <0.01). A trend of increasing detection rates with higher grade levels was observed ( χ 2 trend =617.63, P <0.01). Binary Logistic regression analysis indicated that students without boarding at school ( OR =0.82, 95% CI =0.75-0.90), engaging in high-intensity physical activity for over 60 min per day ≥5 days per week ( OR =0.90, 95% CI =0.82-0.98), and adequate sleep ( OR =0.87, 95% CI =0.81-0.94) had lower risks of detecting spinal curvature abnormalities ( P <0.05). Conclusions The prevalence of spinal curvature abnormalities increases with grade level among primary and secondary school students in Guangxi. Regular moderate-to-vigorous physical activity demonstrates protective effects against spinal abnormalities.

Objective This study aimed to explore the ability of ultrasonographic radiomics in predicting the occurrence of in-stent restenosis(ISR)after carotid artery stenting(CAS)by analyzing the correlation between radiomic features of responsible plaques in carotid artery stenosis and the incidence of ISR.Methods A retrospective collection was conducted on 206 cases that underwent CAS treatment at our hospital.The enrolled patients were randomly split into a training set(144 cases)and a test set(62 cases)at a 7∶3 ratio.We utilized the Darwin Intelligent Research Platform to extract radiomic features from each region of interest,and then screened 1125 ultrasonographic radiomic features.Different machine learning algorithms were employed to construct diagnostic models,and the best-performing classifier was selected.Various prediction models were established,including a clinical-ultrasonographic feature model,a radiomic model,and a combined clinical-ultrasonographic-radiomic model.Results Multivariate logistic regression analysis in the training set revealed that hypertension,hyperuricemia,triglycerides,and plaque location were independent risk factors for ISR after CAS.For the clinical-ultrasonographic model,the area under the curve(AUC)values for the training and validation sets were 0.896 and 0.644,respectively.The corresponding AUC values for the radiomic model were 0.961 and 0.715,while those for the combined model were 0.947 and 0.727.Conclusion The radiomic model demonstrates superior performance in predicting ISR compared to the traditional clinical-ultrasonographic model.The combined model exhibited an enhanced ability to predict ISR occurrence,thereby improving the diagnostic performance of traditional assessments.

Objective To construct a combined model integrating ultrasonic features and radiomics derived from ultrasound images,and to evaluate its diagnostic performance in re-assessing the benign or malignant nature of Bethesda Ⅲ nodules.Methods A retrospective study was carried out on 442 patients with thyroid nodules classified as Bethesda Ⅲ after fine-needle aspiration biopsy(FNAB)between January 2019 and September 2024.All patients had undergone surgical pathology.The patients were randomly allocated into a training set and a testing set at a ratio of 7∶3.Relevant clinical characteristics were gathered,and regions of interest(ROI)were outlined on the most suspicious slice of the lesion prior to biopsy.Ultrasound radiomics features were extracted,key radiomics features were selected,and radiomics scores(Rad-score)were computed.The ultrasound model,radiomics model,and combined model were constructed.Subsequently,the diagnostic efficacy and clinical application value of each model were evaluated using the area under the receiver operating characteristic curve(AUC)and decision curve analysis(DCA).Results Univariate analysis and multivariate logistic regression analysis findings indicated that microcalci-fication,irregular margin,and Rad-score were independent risk factors for the malignant transformation of BethesdaⅢ nodules.In the testing set,the AUC values of the ultrasound model,radiomics model,and combined model were 0.76,0.71,and 0.81,respectively.The calibration curve of the combined model revealed a good consistency between the predicted values and the actual outcomes.The DCA of the testing set demonstrated that the combined model exhibited high clinical utility.Conclusion The combined model,established based on ultrasonic features and ultrasound radiomics,provides a higher predictive value for evaluating the malignancy risk of Bethesda Ⅲ nodules.

Objective: To understand the changing trends and related factors of knowledge, attitude and practice (KAP) regarding the three major infectious diseases (acquired immunodeficiency syndrome, tuberculosis, hepatitis B) among freshmen in Jiangsu from 2019 to 2022, so as to provide a reference basis for the health education of infectious diseases in schools. Methods: From 2019 to 2022, a total of 33 944 freshmen from 20 universities in Jiangsu Province were randomly selected for four consecutive years to investigate their KAP levels online through self designed questionnaires on three major infectious diseases. The multiple linear regression model was used to analyze the changing trends of students KAP levels of the three major infectious diseases, and to explore the influencing factors of KAP. Results: From 2019 to 2022, the knowledge scores(18.0±3.1,18.4±3.2,18.7±3.2,18.8±3.2), related to the three major infectious diseases showed an upward trend ( F=436.50, P <0.01), and the positive attitude reporting rates were 81.77%, 81.46%, 82.68% and 81.74%, respectively. The reporting rates of positive practice were 80.11%, 79.25%, 79.08 % and 79.04%, respectively. Multiple linear regression showed that school type, parental education level, mother s occupation, average income per person in family and living arrangements during high school all had an impact on the knowledge ( β = -1.510 -0.559), attitudes ( β =-0.043-0.065) and practice ( β =-0.028-0.027) of the three major infectious diseases ( P < 0.05 ). The family residence areas only affected the reporting rate of positive attitude scores ( β =0.002-0.065), and whether only children or not affected the reporting rate of positive practice scores ( β =0.009)( P <0.05). The knowledge score showed an upward trend ( β= 0.297, P <0.01), the positive attitude reporting rate showed no statistically significant change ( β=0.001, P =0.22), and the positive practice reporting rate showed a downward trend ( β=-0.005, P <0.01). Conclusions Freshman in Jiangsu Province from 2019 to 2022 have shown a separation in KAP scores regarding the three major infectious diseases. Targeted measures should be taken to improve their health practice level.

A complete plant body consists of elements on different scales, including microscopic molecules, mesoscopic multicellular structures, and macroscopic tissues and organs, which are interconnected to form complex biological networks. The growth and development of plants involve the regulation of elements on different scales and their biological networks, which requires the coordinated operation of multiple molecules, cells, tissues, and organs. It is difficult to reveal the essence of multi-level life activities by a single method or technology. In recent years, the development of various novel imaging technologies has provided new approaches for revealing the complex life activities in plants. Using multi-modal imaging technologies to study the cross-scale network connections of plants from the microscopic, mesoscopic, and macroscopic levels is crucial for understanding the complex internal connections behind biological functions. This paper first summarizes multi-modal cross-scale imaging technologies, three-dimensional reconstruction, and image processing methods, outlines the basic framework of cross-scale network connection properties, and then summarizes the applications of multi-modal imaging technologies in elucidating plant multi-scale networks. Finally, this review systematically integrates the combined analysis of cross-scale 3D spatial structural data and single-cell omics, laying a theoretical foundation for the innovation of novel plant imaging technologies. Furthermore, it provides a new research paradigm for in-depth exploration of the interaction mechanisms among cross-scale elements and the principles of biological network connectivity in plant life activities.
Plants/metabolism* ; Imaging, Three-Dimensional/methods* ; Image Processing, Computer-Assisted/methods* ; Multimodal Imaging/methods* ; Plant Physiological Phenomena

Objective: To explore the association between physical activity, anxiety symptoms and academic performance among junior high school students, so as to provide data support for optimizing school physical education and health work and formulating physical activity guidelines. Methods: From September to December 2022, a convenience cluster sampling method was used to survey 2 800 junior high school students in a middle school from Anqing City, Anhui Province. Data were collected on the students anxiety symptoms, academic performance, 24 hour physical activity [moderate to vigorous intensity physical activity(MVPA), light intensity physical activity(LPA), sedentary behavior(SB), and sleep(SLP) duration] as well as demographic characteristics. Compositional data analysis was used to explore the associations between 24 hour physical activity, anxiety symptoms and academic performance among junior high school students, and to predict the optimal time use combination pattern. Results: Among the junior high school students, 16.0% (447 students) reported anxiety symptoms, and 42.0% (1 175 students) achieved excellent or good academic performance. Compositional data analysis showed that increased SLP duration was associated with both reduced anxiety symptoms ( β =-0.18) and decreased academic performance ( β =-0.03) among junior high school students; increased MVPA duration was correlated with fewer anxiety symptoms ( β =-0.02) and lower academic performance ( β =-0.13); in contrast, increased SB duration was linked to more anxiety symptoms ( β =0.09) and higher academic performance ( β =0.09) (all P <0.01). LPA duration exhibited a non linear relationship with anxiety symptoms and academic performance in junior high school students (all P >0.05). The time use combination pattern corresponding to the lowest anxiety symptoms and highest academic performance (top 5%) in adolescents was 611 (520-640) minutes of SLP, 258 (230-320) minutes of SB, 454 (280-610) minutes of LPA, and 117 (20-200) minutes of MVPA per day. Conclusions The 24 hour physical activity of junior high school students is associated with anxiety symptoms and academic performance. Therefore, it is recommended to increase the time spent on SB, MVPA, and LPA for junior high school students, while reducing SB.

Objective: To analyze the epidemiological characteristics of dengue fever outbreaks in schools from Guangzhou in 2024, so as to provide a reference for formulating targeted prevention and control policies and measures. Methods: By using the National Infectious Disease Surveillance Information Reporting Management System to obtain information on dengue fever cases in Guangzhou from January 1st to December 31st, 2024. Descriptive data analysis was conducted on the temporal distribution, regional distribution, and school distribution of dengue fever outbreaks in schools. A mediation effect model was used to analyze the mediating effect of the time between onset and reporting between the type of school and the occurrence of recurrent cases. Results: In 2024,12.41% (385 cases) of dengue fever cases in Guangzhou involved schools, with 300 schools affected. Among these, 16 schools (5.33%) reported cluster outbreaks, and 24 schools (8.00%) reported secondary cases. The first dengue case at the school was reported at 26 July and the last case was reported at 4 December, the peak reporting period for cases was October 7 to November 3. The incidence of secondary cases in schools in central urban areas (5.19%) was lower than that in suburban schools ( 17.39 %), and the difference was statistically significant ( χ 2=9.15, P <0.01). The time from onset to reporting partially mediated the relationship between school type and the occurrence of recurrent cases ( β=0.23, P <0.05), accounting for 21.50% of the total effect. Conclusions Dengue fever is a key infectious disease facing schools in Guangzhou during summer and autumn. Surveillance of dengue fever outbreaks in schools should be strengthened during the peak season to reduce the risk of cluster outbreaks and the occurrence of secondary cases.