ObjectiveTo investigate the trends in diabetes mortality and potential years of life lost (PYLL) among residents of Huangpu District, Shanghai from 1993 to 2021, to analyze the long-term trends of diabetic patients with different characteristics and to provide a reference for scientific prevention and control of diabetes in aging urban areas. MethodsDiabetes mortality data were obtained from the Huangpu District cause of death registration records in the Shanghai death cause registration system. Indicators such as crude mortality rate, standardized mortality rate, potential years of life lost (PYLL), average years of life lost (AYLL), annual percentage change (APC), and average annual percentage change (AAPC) were used to analyze diabetes-related mortality and life loss. Statistical analyses were performed using software SPSS 21.0 and Joinpoint 5.0.2. ResultsFrom 1993 to 2021, the average annual crude mortality rate of diabetes in Huangpu District was 46.56/100 000, and the average annual standardized mortality rate was 20.44/100 000. The crude mortality rate and standardized mortality rate of diabetes for female residents were higher than those for males. The crude mortality rate showed an overall increasing trend [AAPC=2.81% (95%CI: 0.20%‒5.49%), P<0.05], while the increase in standardized mortality rate significantly slowed [AAPC=0.15% (95%CI: -2.27%‒2.63%)], P<0.05]. The mortality rate rose rapidly in the 70‒74 years age group and peaked in the 85‒ years age group (607.69/100 000). Diabetes accounted for a cumulative PYLL of22 741 person-years, with an average annual AYLL of 1.88 years and an average annual potential years of life lost rate (PYLLR) of 0.82‰. Male residents had higher PYLL, AYLL, and PYLLR than females. ConclusionDiabetes mortality rates in Huangpu District have increased year by year, resulting in significant life loss. However, the age-standardized mortality rate increase has markedly slowed. Efforts should focus on elderly diabetic patients aged ≥70 years, by leveraging platforms such as community-based chronic disease health support centers, efforts should be made to enhance diabetes screening service for middle-aged and elderly residents. Consequently, elderly diabetic patients’ awareness of diabetes and responce to related complications is improved, which would be conducive to controling the progression of complications and reducing the mortolity risk of diabetes.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

OBJECTIVE: To analyze the factors related to spontaneous re-eruption after intruded injury in permanent anterior teeth in children and adolescents. METHODS: Clinical data from 5- to 17-year-old patients who sustained intrusive luxation of permanent anterior teeth and treated in the Department of Pedia-tric Dentistry of Peking University School and Hospital of Stomatology from June 2015 to August 2024 were reviewed. Information of age, gender, degree of intrusion, direction of intrusion, tooth development, concomitant injuries, luxation and post-osteoclastic eruption of the adjacent teeth were recorded. The patients were divided into two groups based on whether they showed spontaneous re-eruption during advised observation after intrusion. Univariate and multifactor analysis were performed using Logistic regression. RESULTS: Data from 170 teeth in 139 patients whose age ranging from 5.3-16.3 years [mean age (9.0± 2.1) years] were examined. A gender disparity was observed among the patients, with 84 being male and 55 being female. Among the 170 teeth, 112 were categorized as successfully spontaneous re-eruption during advised observation after intrusion, while 58 were not. In terms of the degree of intrusion, 45 teeth (26.47%) had intrusion less than 3 mm, 102 teeth (60.00%) experienced intrusion between 3-7 mm, and 23 teeth (13.53%) were faced with intrusion exceeding 7 mm. As for the direction of intrusion, 117 teeth (68.82%) were straight intrusion while mesial-distal and buccal-lingual intrusion respectively accounting for 17 (10.00%) and 23 (13.53%). Multivariate Logistic regression analysis showed that mesial-distal intrusion (OR=0.167, 95%CI: 0.031-0.9048, P=0.038), intrusion of >7 mm (OR=0.065, 95%CI: 0.014-0.299, P < 0.001) and luxation of adjacent teeth (OR=0.369, 95%CI: 0.144-0.944, P=0.037) were independent risk factors for spontaneous re-eruption of traumatically intruded permanent anterior teeth in children and adolescents during advised observation after intrusion, while intrusion of < 3 mm (OR=9.860, 95%CI: 2.430-40.009, P=0.001) and post-osteoclastic eruption of adjacent teeth (OR=4.712, 95%CI: 1.528-14.531, P=0.007) were independent protective factors. The possibility of spontaneous re-eruption in permanent anterior teeth during advised observation after intrusion was decreased by 61.1% with the increase of root development using Cvek' s classification (OR=0.611, 95%CI: 0.408-0.914, P=0.017). Age (OR=1.077, 95%CI: 0.763-1.521, P=0.673) and laceration of gingival (OR=0.865, 95%CI: 0.290-2.578, P=0.794) didn't significantly affect the spontaneous re-eruption during advised observation after intrusion. CONCLUSION In this study, mesial-distal intrusion, intrusion of >7 mm and luxation of adjacent teeth were independent risk factors for spontaneous re-eruption of traumatically intruded permanent anterior teeth in children and adolescents during advised observation, while intrusion of < 3 mm and post-osteoclastic eruption of adjacent teeth were served as independent protective factors.
Humans ; Adolescent ; Child ; Female ; Male ; Tooth Eruption/physiology* ; Child, Preschool ; Tooth Avulsion/therapy* ; Dentition, Permanent ; Incisor/injuries* ; Remission, Spontaneous

Cuproptosis, a recently discovered form of regulated cell death involving copper ion metabolism, has emerged as a promising approach for tumor therapy. This pathway not only directly eliminates tumor cells but also promotes immunogenic cell death (ICD), reshaping the tumor microenvironment (TME) and initiating robust anti-tumor immune responses. However, translating cuproptosis-based therapies into clinical applications is hindered by challenges, including complex metabolic regulation, TME heterogeneity, and the precision required for effective drug delivery. To address these limitations, nanoparticles offer transformative solutions by providing precise delivery of cuproptosis-inducing agents, controlled drug release, and enhanced therapeutic efficacy through simultaneous modulation of metabolic pathways and immune responses. This review systematically discusses recent advancements in nanoparticle-based cuproptosis delivery systems, highlighting nanoparticle design principles and their synergistic effects when integrated with other therapeutic modalities such as ICB, PTT, and CDT. Furthermore, we explore the potential of cuproptosis-based nanomedicine for personalized cancer treatment by emphasizing strategies for TME stratification and therapeutic optimization tailored to patient profiles. By integrating current insights from metabolic reprogramming, tumor immunotherapy, and nanotechnology, this review aims to facilitate the clinical translation of cuproptosis nanomedicine and significantly contribute to the advancement of precision oncology.

The research on the cardiovascular toxicity of air pollutants is in urgent need of collaborative innovation across multiple models. This paper systematically reviewed the advantages and limitations of four principal research models of cardiotoxicity, including epidemiological model, mammalian model, zebrafish model, and in vitro model. Epidemiological models have been used to demonstrate a significant correlation between exposure to PM_2.5 and both the incidence and mortality of cardiovascular diseases within populations; however, these models face challenges in establishing causal inferences and interpreting individual mechanisms. Mammalian models have been applied to elucidate the pathogenic mechanisms of PM_2.5 at both the systemic and organ-specific levels, yet they encounter difficulties related to interspecies differences and throughput constraints. Zebrafish models, with their transparent embryos and observable development, offer a distinctive opportunity for high-throughput screening and mechanistic investigation of PM_2.5-induced cardiac developmental toxicity. Nonetheless, their cardiac physiological structure diverges from that of mammals, limiting their capacity to accurately model chronic conditions such as coronary heart disease. In vitro models, particularly human heart organoids and chip technologies, have provided profound insights into the direct toxic mechanisms of PM_2.5, including disruptions in calcium homeostasis, cellular senescence, and electrophysiological irregularities at the cellular and molecular levels. Despite these advancements, the complexity and developmental maturity of these models present challenges to their broader application. This paper proposed that the key to overcoming the bottlenecks of single models lies in the construction of an integrated evaluation system that combines “epidemiological studies, mammalian models, zebrafish models, and in vitro models”. By focusing on three aspects, namely model integration, technological convergence, and policy support, it is intended to collaboratively address issues such as standardization of multi-model data, simulation of complex exposure scenarios and susceptible life stages, and transformation pathways. This will provide innovative methodological support for the analysis of the cardiotoxic mechanisms of air pollutants, the assessment of environmental health impacts, and the formulation of precise prevention and control strategies.

Objective:To investigate the distribution characteristics of skeletal muscle mass and strength in the older adults over 65 years old in 18 longevity areas in China.Methods:The subjects were selected from the Healthy Aging and Biomarkers Cohort Study conducted in 18 longevity areas of China. A total of 4 662 older adults over 65 years old from a cross- sectional survey in 2021 were included in the study. The information about their sociodemographic characteristics, lifestyle, nutrient intake and other factors were collected through questionnaire surveys and physical examinations. Grip strength was measured by using professional electronic grip dynamometer. Total skeletal muscle mass (TSM) was measured using bioelectrical impedance analysis, and TSM was adjusted by height squared and BMI to obtain TSM Ht2 and TSM BMI. The proportion of individuals with low muscle mass and strength was determined according to the recommended method by the Asian Working Group for Sarcopenia (AWGS). Descriptive analysis was conducted on the population and regional distribution characteristics of people with different muscle mass and grip strength. A generalized additive model was used to analyze the age-related trends of muscle mass and grip strength. Results:The age of 4 662 study subjects was (82.69±10.54) years, men accounted for 46.85% (2 184 cases) and Han Chinese accounted for 96.27% (4 488 cases). The M( Q1, Q3) of TSM, TSM Ht2 and TSM BMI in men were 23.30 (20.50, 26.20) kg, 9.02 (8.13, 9.89) kg/m 2, and 1.01 (0.90, 1.13) kg·(kg/m 2) -1, respectively, which were all higher than those in women [TSM: 18.20 (15.70, 20.70) kg, TSM Ht2: 8.18 (7.42, 9.07) kg/m 2 and TSM BMI: 0.79 (0.69, 0.90) kg·(kg/m 2) -1], the differences were significant (all P<0.001). The grip strength of men [ M( Q1, Q3): 24.50 (17.80, 30.80) kg] was higher than that of women [ M( Q1, Q3): 15.60 (11.10, 19.90) kg], the difference was significant ( P<0.001). Southern elderly men had lower TSM and TSM Ht2 compared with northern elderly men (all P<0.001), while there was no significant regional difference in TSM BMI ( P>0.05). Southern elderly women had higher TSM Ht2 and TSM BMI compared with northern elderly women (all P<0.001), while there was no significant regional difference in TSM ( P>0.05). Furthermore, according to the method recommended by AWGS, the elderly with low muscle mass and grip strength were characterized by older age, illiteracy, being unmarried/divorced/widowed, poor chewing ability, impaired activity of daily living and living in southern region. Conclusion:There were population and regional differences in muscle mass and grip strength in the older adults over 65 years in 18 longevity areas of China, and these differences showed decreasing trends with age.

Objective:To analyze the change in human resources within China′s Centers for Disease Control and Prevention (CDC) from 2010 to 2020.Methods:The self-reported information from provincial, prefectural (city), and county (district) levels of China′s CDC, covering employee counts, staff composition, professional qualifications, educational backgrounds, technical titles, and tenure, were extracted from the China Disease Prevention and Control Information System. The demographic context was provided by the annual population figures from the China Statistical Yearbook (2010-2020). The profile of CDC personnel was described, and the average annual percentage rate change (AAPC), average annual percentage rate change (APC), human resource agglomeration degree (HRAD) and the difference between HRAD and population agglomeration degree (PAD) were calculated. The Joinpoint regression model was used to analyze the time trend.Results:The decade under review witnessed a net increase of 17 300 active and 18 300 enrolled personnel in the CDC, surpassing the national population growth rate with AAPCs of 0.93% and 1.03%, respectively. This upward trajectory was statistically significant ( P<0.05). The ratio of disease control personnel per 10 000 population escalated from 1.14 to 1.21. An initial decline in active CDC workforce density (from 1.31 to 1.27 per 10 000 population between 2010 and 2017) was followed by an increase (from 1.28 to 1.37 between 2018 and 2020), with APCs of -0.40% and 3.73%, respectively. The proportion of professional and technical staff in 2019 was highest in the eastern region (86.01%), followed by the western (83.75%) and central regions (79.54%). The period also saw an enhancement in the average academic degree (from 1.91 to 2.43 points) and professional title scores (from 1.39 to 1.53 points) of CDC personnel. While the average tenure in the eastern and western regions showed a slight decline, the central region experienced an increase, with HRAD values indicating a higher concentration in the eastern and central regions compared to the western region. The HRAD-PAD discrepancy revealed a negative value in the eastern region, nearing zero in the central and western regions. Conclusion:Between 2010 and 2020, China′s CDC experienced notable growth in human resources and underwent structural optimization, albeit with significant regional disparities in concentration.