Objective: To explore the association of vegetables and fruits intake with depressive symptoms among multi ethnic first year junior high school students in Yunnan Province, so as to provide data support for preventing and reducing depressive symptoms among first year junior high school students. Methods: From October to December 2022, a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas in Yunnan Province (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County), to investigate with a questionnaire. The Dietary Frequency Questionnaire was used to collect dietary behavior datas, and the Chinese version of Depression Anxiety Stress Scale-21 (DASS-21) was used to assess depressive symptoms. The generalized linear model was used to analyze the association of vegetable and fruit intake with depressive symptoms in students, and stratified analysis was performed according to ethnicity. Results: The detection rate of depressive symptoms among first year junior high school students in Yunnan Province was 29.5%. The detection rates of depressive symptoms in Han and minority first year junior high school students were 26.9% and 31.6%. After controlling for demographic variables such as gender, age, family residence and other confounding factors, the generalized linear model analysis results showed that the intake of leafy vegetables ( β= -0.07 , 95%CI =-0.12 to -0.01), flat fruits ( β=-0.06, 95%CI =-0.12 to -0.00) and hot natured fruits ( β=0.11, 95%CI = 0.04- 0.17) were associated with depressive symptoms in Han first year junior high school students (all P <0.05). The intake of melon and fruit vegetables ( β=-0.06, 95%CI =-0.11 to -0.01) and hot natured fruits ( β=0.06, 95%CI =0.01-0.12) were associated with depressive symptoms in ethnic minority first year junior high school students (both P <0.05). Conclusions The intake of vegetables and fruits among multi ethnic first year junior high school students in Yunnan Province is related to the risk of depressive symptoms. It is suggested to strengthen the consumption guidance and education of vegetables and fruits to prevent depressive symptoms among first year junior high school students.

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

Objective:To explore the current implementation status and challenges of family doctor contract services (FDCS) from the perspective of contracted residents.Methods:This qualitative study used purposive sampling to select contracted residents from 11 primary healthcare institutions across five cities in China. Semi-structured interviews were conducted from March to December 2024, covering topics such as awareness of contracting, service experience, health needs, service continuity, and policy recommendations. Thematic framework analysis was applied to organize, code, and summarize the data.Results:A total of 25 contracted residents were interviewed (6 men, 19 women; 11 from central urban areas, 14 from suburban or rural towns; 8 with chronic diseases). Three main themes and ten sub-themes emerged: Theme Ⅰ: Pathways to improved service accessibility (optimized chronic disease management, more efficient referrals, and improved health education). Theme Ⅱ: Structural misalignment between supply and demand (limited specialty services despite patient needs, insufficient coverage and public awareness of home-based medical care, imbalanced human resources, and service disruption due to clinician turnover). Theme Ⅲ: Challenges in service awareness and communication mechanisms (information asymmetry and public misperception regarding FDCS, perverse incentives in administrative performance evaluation, and communication barriers in building patient-doctor trust).Conclusions:While FDCS has shown progress in chronic disease management, referral coordination, and health education, structural supply-demand gaps and communication challenges continue to hinder service quality. Improvements in resource allocation and service models are needed to support high-quality development.

ObjectiveTo investigate the possible mechanism of Shufeng Jiedu capsules （SFJD） in alleviating influenza A （H1N1） virus pneumonia and focus on its effect on Toll-like receptor （TLR） signaling pathway in respiratory epithelial cells. MethodsA mouse model of viral pneumonia was established via the A/PR/8/34 （PR8） strain of influenza A virus. Mice were randomly divided into a normal group， a PR8 infection （PR8） group， and an SFJD group （8.4 g·kg^-1）， with 10 mice in each group. The day of infection was designated as day 1. The SFJD group was administered intragastrically at a volume of 20 mL·kg^-1 daily， while the normal and PR8 groups were given an equal volume of deionized water. Micro-computed tomography （Micro-CT） was performed on day 5， and the mice were dissected to collect their lungs， after which the lung index was calculated to verify the therapeutic effect of SFJD. Single-cell sequencing was used to analyze the differentially expressed genes in respiratory epithelial cells. Multiplex fluorescence immunohistochemistry was employed to detect the expression of TLR， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） proteins in epithelial cell adhesion molecule （EpCAM）-positive cells， and the proportion of respiratory epithelial cells expressing TLR pathway proteins was calculated. Respiratory epithelial cells were then sorted by flow cytometry， and Western blot was used to detect the expression of TLR， MyD88， TRAF6， Toll-interleukin receptor domain-containing adaptor inducing interferon-β （TRIF）， inhibitor of κB kinase α （IKKα）， and nuclear factor-κB （NF-κB） in the sorted epithelial cells. Enzyme-linked immunosorbent assay （ELISA） was used to measure the levels of interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α） in lung tissue. ResultsAt the transcriptional level， SFJD reversed the expression of TLR signaling pathway genes in respiratory epithelial cells， downregulating multiple TLR signaling pathway-related genes （P<0.01）. At the protein level， SFJD significantly reduced the proportion of respiratory epithelial cells expressing TLR3 （P<0.05）， the expression levels of TLR2， TLR3， TLR4， TRIF， TRAF6， IKKα， and NF-κB in epithelial cells（P<0.05， P<0.01）， as well as the levels of pro-inflammatory cytokines IL-1β and TNF-α in lung tissue （P<0.01）. ConclusionSFJD may alleviate viral pneumonia by suppressing the expression of TLR in respiratory epithelial cells and their subsequent signaling cascades.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Objective:To explore the current implementation status and challenges of family doctor contract services (FDCS) from the perspective of contracted residents.Methods:This qualitative study used purposive sampling to select contracted residents from 11 primary healthcare institutions across five cities in China. Semi-structured interviews were conducted from March to December 2024, covering topics such as awareness of contracting, service experience, health needs, service continuity, and policy recommendations. Thematic framework analysis was applied to organize, code, and summarize the data.Results:A total of 25 contracted residents were interviewed (6 men, 19 women; 11 from central urban areas, 14 from suburban or rural towns; 8 with chronic diseases). Three main themes and ten sub-themes emerged: Theme Ⅰ: Pathways to improved service accessibility (optimized chronic disease management, more efficient referrals, and improved health education). Theme Ⅱ: Structural misalignment between supply and demand (limited specialty services despite patient needs, insufficient coverage and public awareness of home-based medical care, imbalanced human resources, and service disruption due to clinician turnover). Theme Ⅲ: Challenges in service awareness and communication mechanisms (information asymmetry and public misperception regarding FDCS, perverse incentives in administrative performance evaluation, and communication barriers in building patient-doctor trust).Conclusions:While FDCS has shown progress in chronic disease management, referral coordination, and health education, structural supply-demand gaps and communication challenges continue to hinder service quality. Improvements in resource allocation and service models are needed to support high-quality development.

[Objective]To explore data on traditional Chinese medicine formulas for the treatment of rheumatoid arthritis(RA),analyze medication patterns and provide ideas for the clinical staging treatment of RA.[Methods]Using the China Patent Publication Platform of the State Intellectual Property Office,the patent data of traditional Chinese medicine compounds for RA published from the establishment date of the database to November 2023 were systematically collected,and the frequency of drug application,nature and taste,and efficacy of the included traditional Chinese medicine formulas were analyzed.Correlation analysis,cluster analysis and latent structure analysis were used to explore the core prescriptions of traditional Chinese medicine in the treatment of different stages of RA.[Results]Two hundred and ninety-nine traditional Chinese medicine formulas were included,including 537 traditional Chinese medicines,with a total frequency of 3 739 times.The nature and flavor of the medicines are primarily categorized as warm,neutral,and cold.The channel tropism of the medicines is generally classified into the liver,spleen,kidney,and heart meridians.High-frequency traditional Chinese medicine can be classified into six primary categories and nine secondary subcategories.The high-frequency drug combinations used in association analysis included"Huangqi → Guizhi"and"Ruxiang → Myrrh".The cluster analysis of 58 high-frequency traditional Chinese medicines with frequency≥20 times was carried out,and the results showed that 6 clusters were formed.Among them,wind and dampness obstruction and deficiency of Qi and blood belonged to the pre-RA state,damp-heat obstruction belonged to the acute phase,cold dampness obstruction belonged to the chronic phase,phlegm stasis obstruction and liver and kidney deficiency belonged to the remission phase.[Conclusion]Traditional Chinese medicine formulas therapy for RA often starts from the three major causes of deficiency,evil and blood stasis,by using drugs that dispel wind and dampness,promote blood circulation and remove blood stasis,and nourish deficiency.It follows the principle of"treating the same disease differently"and emphasizes staged treatment,Which providing a certain reference for clinical treatment.

After the full implementation of Diagnosis-Intervention Packet(DIP)payment,driven by the dual mode of public welfare and economy,disease cost accounting,as a key link,promotes the transformation of hospitals from extensive income-driven development mode to refined operation management.Through literature analysis,it compares the characteristics,advantages and limitations of various methods of disease cost accounting.Combined with the current situation of case hospital cost accounting and the dilemma of disease cost accounting,the parameter distribution method combined with the service unit superposition method is used to realize the medical business cost and medical total cost accounting of the DIP disease in the case hospital.In addition,how to better implement DIP disease cost accounting in county-level public hospitals is discussed and suggested,in order to further improve the same type of hospitals and speed up the application of disease cost accounting results.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

After the full implementation of Diagnosis-Intervention Packet(DIP)payment,driven by the dual mode of public welfare and economy,disease cost accounting,as a key link,promotes the transformation of hospitals from extensive income-driven development mode to refined operation management.Through literature analysis,it compares the characteristics,advantages and limitations of various methods of disease cost accounting.Combined with the current situation of case hospital cost accounting and the dilemma of disease cost accounting,the parameter distribution method combined with the service unit superposition method is used to realize the medical business cost and medical total cost accounting of the DIP disease in the case hospital.In addition,how to better implement DIP disease cost accounting in county-level public hospitals is discussed and suggested,in order to further improve the same type of hospitals and speed up the application of disease cost accounting results.