Objective To systematically review international research on health communication, and to provide valuable insights and reference for China's health communication research and practice. Methods This study included 693 articles published from January 2023 to April 2024 in two authoritative academic journals in the field of health communication, ^“Health Communication^” and the ^“Journal of Health Communication^”. A systematic review was conducted on the themes, theoretical foundations, research methods, and populations of international health communication research. Results The findings in this study revealed that international health communication research topics were diverse, with hotspots including social media, health information behavior, health misinformation, stigmatization, trust, and risk perception. The results showed that 34% of the articles were based on theoretical foundations, and 93.3% employed research methods, focusing on adolescents, parents, women, and other key populations. Conclusion Domestic health communication research can expand its perspective from ^“information transmission^” to ^“social interaction^”, innovate theories and methods from ^“single paradigm" to ^“multi-integration^” and shift focus from a ^“mass perspective^” to ^“targeted care^” for the health of all populations. Domestic health communication practice can delve into the localization of social media health communication practices, the comprehensive management of health misinformation, and the critical application of new technologies.

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.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

The operation assistant work team of public hospitals is an important bridge and link to realize the integration of industry and finance,and an important practitioner to promote the realization of lean operation management.It examines the service model of the operation assistant team engaged in Similar Multi-disciplinary Treatment,focusing on organizational structure,job responsibilities,and service mechanisms.Build a four-tiered lean operational management system and set up an operation assistant work team that combines production,university and research.Based on specific management matters,establish an operation assistant service mechanism such as problem assessment and classification management mechanism,project standardization management mechanism,reward and punishment assessment mechanism,etc.,to promote the optimization and integration of hospital medical education,research,prevention and management and core elements such as human,talent,material and technology resources.Help public hospitals to continuously improve their lean operation management level.

Objective:To analyze the changing trend of cervical cancer epidemiological characteristics and disease burden in cancer registration areas of Guangxi Zhuang Autonomous Region (Guangxi) from 2010 to 2017, and to provide scientific basis for the development of cervical cancer prevention and control strategies in Guangxi.Methods:Using descriptive analysis method, based on the incidence and death data of cervical cancer in the tumor registration areas of Guangxi from 2010 to 2017, Crude morbidity, crude mortality, age-standardized morbidity and mortality (referred to as the winning rate), disability adjusted life years (DALYs) rate and the annual percentage change (APC) and average annual percentage change (AAPC) of the above indicators were calculated, and stratified analysis was conducted for urban and rural areas and different age groups.Results:From 2010 to 2017, the crude incidence rate of cervical cancer in Guangxi showed a significant upward trend, rising from 10.31/10 5 in 2010 to 19.94/10 5 in 2017, with an average annual growth rate of 7.9% ( P＜0.05). However, after age standardization, the trend of the age-standardized incidence rate of cervical cancer was not statistically significant ( P＞0.05). During the same period, the crude mortality rate of cervical cancer increased from 2.69/10 5 to 6.21/10 5, with an average annual growth rate of 13.1% ( P＜0.05), and the trend of the age-standardized mortality rate was basically consistent with that of the crude mortality rate. The analysis of urban-rural differences showed that the growth rates of the crude incidence rate and crude mortality rate of cervical cancer in rural areas were higher than those in urban areas from 2010 to 2017 (AAPC incidence rate: 21.3% vs. 2.3%; AAPC mortality rate: 20.1% vs. 8.4%). The analysis of age differences showed that the crude incidence rate and crude mortality rate of cervical cancer in all age groups increased to varying degrees, among which the growth rate of the incidence rate (AAPC=16.2%, P＜0.05) and mortality rate (AAPC=14.7%, P＜0.05) of cervical cancer in women aged 65 and above was the fastest. In addition, the DALYs rate of cervical cancer in Guangxi increased from 50.6/10 5 in 2010 to 111.0/10 5 in 2017, with an average annual increase of 11.9% ( P＜0.05). The growth rate of the DALYs rate in rural areas was higher than that in urban areas, and the growth rate of the DALYs rate in the 50-59 age group was higher than those in other age groups. Conclusions:From 2010 to 2017, the incidence rate, mortality rate and DALYs rate of cervical cancer in Guangxi showed an upward trend. Comprehensive prevention and control measures for cervical cancer, such as improving the early diagnosis and treatment system, promoting the popularization of HPV vaccination and strengthening health education, should be taken to reduce the disease burden of cervical cancer.

Current experimental and computational methods have limitations in accurately and efficiently classi-fying ion channels within vast protein spaces.Here we have developed a deep learning algorithm,GPT2 Ion Channel Classifier(GPT2-ICC),which effectively distinguishing ion channels from a test set con-taining approximately 239 times more non-ion-channel proteins.GPT2-ICC integrates representation learning with a large language model(LLM)-based classifier,enabling highly accurate identification of potential ion channels.Several potential ion channels were predicated from the unannotated human proteome,further demonstrating GPT2-ICC's generalization ability.This study marks a significant advancement in artificial-intelligence-driven ion channel research,highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data.Moreover,it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Objective: This study aims to investigate the therapeutic effects and underlying mechanisms of Xuanfei Baidu Decoction (XFBD) in a mouse model of dampness-heat toxin pneumonia. By exploring how XFBD exerts its effects, we seek to deepen our understanding of its role in treating pulmonary diseases and to address the current knowledge gap regarding its mechanisms of action, thereby supporting its clinical application. Methods: Ultra-high-performance liquid chromatography and high-resolution mass spectrometry (HRMS) were employed to analyze the chemical constituents of XFBD. The protective effects of XFBD were evaluated using a dampness-heat toxin-induced mouse model, established through dampness-heat exposure and HCoV-229E infection. XFBD was administered orally, followed by assessments including lung index measurement, micro-CT imaging, viral load quantification, cytokine analysis, and histological evaluation via hematoxylin-eosin staining. Proteomics and single-cell transcriptomic analyses were conducted to explore the potential mechanisms underlying XFBD’s pharmacological effects. A cellular model of HCoV-229E infection was developed to investigate changes in the cAMP/PKA signaling pathway. Molecular docking and surface plasmon resonance (SPR) experiments confirmed the strong binding affinity between key XFBD components and PKA. Finally, PKA activators and inhibitors were applied in vitro to validate these mechanistic findings. Results: In vivo studies demonstrated that XFBD significantly reduced the lung index, improved the structural integrity of lung and tongue tissues, and decreased levels of proinflammatory mediators, including IL-6, IL-8, and TNF-α. Proteomic and single-cell transcriptomic analyses showed that the differentially expressed proteins after XFBD treatment were primarily associated with inflammatory responses and immune regulation. The cAMP/PKA signaling pathway was identified as a key mechanism underlying these therapeutic effects. Notably, Western blot, ELISA, molecular docking, and SPR analyses confirmed that XFBD elevated cAMP levels and p-PKA expression, thereby activating the cAMP/PKA signaling pathway in vitro. Conclusion: This study demonstrated that XFBD significantly alleviates symptoms in mice with dampness-heat toxin pneumonia. Its therapeutic effects are mediated, at least in part, through activation of the cAMP/PKA signaling pathway. These findings provide compelling evidence that XFBD is an effective herbal remedy against HCoV-229E infection.

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

Notum, a negative feedback regulator of the Wnt signaling, has emerged as a promising target for treating glucocorticoid-induced osteoporosis (GIOP). This study showcases an efficient strategy for discovering the anti-Notum constituents from herbal medicines (HMs) as novel anti-GIOP agents. Firstly, a rapid-responding near-infrared fluorogenic substrate for Notum was rationally engineered for high-throughput identifying the anti-Notum HMs. The results showed that Bu-Gu-Zhi (BGZ), a known anti-osteoporosis herb, potently inhibited Notum in a competitive-inhibition manner. To uncover the key anti-Notum constituents in BGZ, an efficient strategy was adapted via integrating biochemical, phytochemical, computational, and pharmacological assays. Among all identified BGZ constituents, three furanocoumarins were validated as strong Notum inhibitors, while 5-methoxypsoralen (5-MP) showed the most potent anti-Notum activity and favorable safety profiles. Mechanistically, 5-MP acted as a competitive inhibitor of Notum via creating strong hydrophobic interactions with Trp128 and Phe268 in the catalytic cavity of Notum. Cellular assays showed that 5-MP remarkably promoted osteoblast differentiation and activated Wnt signaling in dexamethasone (DXMS)-challenged MC3T3-E1 osteoblasts. In dexamethasone-induced osteoporotic mice, 5-MP strongly elevated bone mineral density (BMD) and improved cancellous and cortical bone thickness. Collectively, this study constructs a high-efficient platform for discovering key anti-Notum constituents from HMs, while 5-MP emerges as a promising anti-GIOP agent.

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