Objective:To understand the characteristics of faculty in high-level public health schools in China, and analyze the differences in age, area and school level.Methods:Based on the internet information, the faculty information of 18 high-level public health schools was collected for a descriptive analysis on faculty characteristics.Results:There were 1 642 faculty members in the schools of public health in China, in whom 51.8% were women, 92.8% had doctorate, 32.4% had postdoctoral experience and 56.8% were former students staying to teach. The average age of the faculty members was (45.6±9.8) years. Meanwhile the top three study subjects were epidemiology and health statistics (31.0%), occupational health and environmental sanitation (16.5%), and health toxicology (16.3%). In the faculty members aged >40 years, 90.2% had doctorate, 62.6% were former students staying to teach, and 24.7% had no educational background of public health. The proportions of faculty members aged ≤40 years in the three groups mentioned above were 98.2%, 45.8% and 39.1% respectively. In terms of study subject, big data study were mainly conducted in the schools with top subject ranking and the schools in developed areas.Conclusions:The public health faculty was characterized by cross education background and high capability. The study subjects and sub-disciplines varied with schools and areas.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

Objective:To understand the characteristics of faculty in high-level public health schools in China, and analyze the differences in age, area and school level.Methods:Based on the internet information, the faculty information of 18 high-level public health schools was collected for a descriptive analysis on faculty characteristics.Results:There were 1 642 faculty members in the schools of public health in China, in whom 51.8% were women, 92.8% had doctorate, 32.4% had postdoctoral experience and 56.8% were former students staying to teach. The average age of the faculty members was (45.6±9.8) years. Meanwhile the top three study subjects were epidemiology and health statistics (31.0%), occupational health and environmental sanitation (16.5%), and health toxicology (16.3%). In the faculty members aged >40 years, 90.2% had doctorate, 62.6% were former students staying to teach, and 24.7% had no educational background of public health. The proportions of faculty members aged ≤40 years in the three groups mentioned above were 98.2%, 45.8% and 39.1% respectively. In terms of study subject, big data study were mainly conducted in the schools with top subject ranking and the schools in developed areas.Conclusions:The public health faculty was characterized by cross education background and high capability. The study subjects and sub-disciplines varied with schools and areas.

With the rapid development of medical big data and artificial intelligence,Clinical Prediction Models(CPMs)have become pivotal tools for disease prevention,diagnosis,and treatment.Current research predominantly focuses on the economic analysis of pharmacological or public health interventions,yet a comprehensive methodological framework for the economic evaluation of CPMs has been notably absent.The Guidelines for Economic Evaluation of Clinical Prediction Models(hereafter the Guidelines),jointly initiated by the Chinese Research Hospital Association and Peking University,Tsinghua University,and Capital Medical University,adheres to the WHO Handbook for Guideline Development and the Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards.A multidisciplinary collaboration,including a steering committee,expert panel,secretariat,and external review group,was established to develop the guideline following evidence-based principles and procedures.Consensus recommendations were formulated through the Delphi method.It describes the background,objectives,target group,and the development methodology and process,ensuring the entire compilation process of the Guidelines is transparent and standardized.Through comprehensive evidence retrieval,systematic evidence appraisal,and a scientific approach to forming recommendations,the scientific rigor and validity of the Guidelines were further enhanced.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

Multiple sclerosis (MS) is a neuroinflammatory demyelinating disease, mediated by pathogenic T helper 17 (Th17) cells. However, the therapeutic effect is accompanied by the fluctuation of the proportion and function of Th17 cells, which prompted us to find the key regulator of Th17 differentiation in MS. Here, we demonstrated that the triggering receptor expressed on myeloid cells 2 (TREM-2), a modulator of pattern recognition receptors on innate immune cells, was highly expressed on pathogenic CD4-positive T lymphocyte (CD4⁺ T) cells in both patients with MS and experimental autoimmune encephalomyelitis (EAE) mouse models. Conditional knockout of Trem-2 in CD4⁺ T cells significantly alleviated the disease activity and reduced Th17 cell infiltration, activation, differentiation, and inflammatory cytokine production and secretion in EAE mice. Furthermore, with Trem-2 knockout in vivo experiments and in vitro inhibitor assays, the TREM-2/zeta-chain associated protein kinase 70 (ZAP70)/signal transducer and activator of transcription 3 (STAT3) signal axis was essential for Th17 activation and differentiation in EAE progression. In conclusion, TREM-2 is a key regulator of pathogenic Th17 in EAE mice, and this sheds new light on the potential of this therapeutic target for MS.
Animals ; Humans ; Mice ; CD4-Positive T-Lymphocytes/pathology* ; Cell Differentiation ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Mice, Inbred C57BL ; Multiple Sclerosis ; Th1 Cells/pathology*