The COVID-19 pandemic, which emerged in 2019, presents significant challenges to human health, well-being,and global economic progress. Vaccines are crucial in curbing the spread of viral diseases. This paper provided an overview of scientific research and technological advancements in coronavirus vaccine development, drawing upon literature and patent quantitative analysis approaches to establish a theoretical foundation for future research.

Implementation Science is an interdisciplinary field dedicated to systematically studying how to effectively translate evidence-based research findings into practical application and implementation. In the health-related context, it focuses on enhancing the efficiency and quality of healthcare services, thereby facilitating the transition from scientific evidence to real-world practice. This article elaborates on Theories, Models, and Frameworks (TMF) within health-related Implementation Science, clarifying their basic concepts and classifications, and discussing their roles in guiding implementation processes. Furthermore, it reviews and prospects current research from three aspects: the constituent elements of TMF, their practical applications, and future directions. Five representative frameworks are emphasized, including the Consolidated Framework for Implementation Research (CFIR), the Practical Robust Implementation and Sustainability Model (PRISM), the Exploration, Preparation, Implementation, Sustainment (EPIS)framework, the Behavior Change Wheel (BCW), and the Normalization Process Theory (NPT). Additionally, resources such as the Dissemination & Implementation Models Webtool and the T-CaST tool are introduced to assist researchers in selecting appropriate TMFs based on project-specific needs.

Probiotics are natural systems bridging synthetic biology, physical biotechnology, and immunology, initiating innate and adaptive anti-tumor immune activity. We previously constructed an all-in-one engineered food-grade probiotic Lactococcus lactis (FOLactis) which could boost the crosstalk among different immune cells such as dendritic cells (DCs), natural killer cells, and T cells. Herein, considering the limited clinical efficacy of naked personalized neoantigen peptide vaccines, we decorate FOLactis with tumor antigens by employing a Plug-and-Display system comprising membrane-inserted peptides. Intranodal injection of FOLactis coated with neoantigen peptides (Ag-FOLactis) induces robust DCs presentation and neoantigen-specific cellular immunity. Notably, Ag-FOLactis not only triggers a 45-fold rise in the quantity of locally reactive neoantigen-specific T cells but also induces epitope spreading in both subcutaneous and metastatic tumor-bearing models, leading to potent inhibition of tumor growth. These findings imply that Ag-FOLactis represents a powerful platform to rapidly and easily display antigens, facilitating the development of a bio-activated platform for personalized therapy.

Root caries is a prevalent chronic oral disease with an average global prevalence of 41.5%, characterized by high incidence, low rate of treatment, and high rate of retreatment. Root caries is primarily caused by core microbiome-induced dysbiosis and has multiple risk factors, including gingival recession, root surface exposure, and salivary dysfunction. The traditional preventive measures and treatments such as fluoride, mineralizing agents, and restorative materials, are unable to restore or maintain oral microecological homeostasis. Recent studies have demonstrated that probiotics, prebiotics, synbiotics, and antimicrobial peptides may prevent and treat root caries by reversing dysbiosis. In addition, these biotherapeutics can reduce acid production by acidiferous bacteria, promote alkali production (hydrogen peroxide and ammonia) by alkali-producing bacteria, inhibit biofilm formation, decrease extracellular polysaccharide production, and suppress microbial adhesion and aggregation. It is expected to play an important role in the prevention and control of root caries. This article aims to review oral probiotics (Streptococcus oligofermentans, Streptococcus oralis subsp. dentisani, and Streptococcus salivarius), prebiotics (arginine, nitrates, and synthetic compounds), synbiotics, and antimicrobial peptides (gallic acid-polyphemusin I and LH12) to provide evidence and guidance for root caries management through microecological modulation.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

Objective To analyze the academic literature on sepsis-related microRNA(miRNA)at worldwide,and to dentify thematic hotspots and future research trends.Methods A bibliometric analysis was employed to retrieve the literature on sepsis-related miRNA published in the core collection of China National Knowledge Infrastructure(CNKI),and Web of Science(WOS)databases from January 1,2010,to January 1,2025,which met the article inclusion criteria,and used CiteSpace 6.3.1 software to perform the co-occurrence analysis of keywords,keyword emergence analysis,and cluster analysison;on the basis of these analyses,the keywords were sorted according to time to generate clustering time line figure to explore the current status and hotspot evolution process of sepsis-related miRNA.Results A total of 135 and 1 278 articles were retrieved from CNKI and the core collection of WOS databases,respectively.The frequency and centrality of keywords such as sepsis,prognosis,microRNA,acute lung injury,acute kidney injury,etc.were high in 135 documents in CNKI;in 1 278 documents in WOS core collection,the frequency and centrality of keywords such as expression,sepsis,inflammation,cells,micrornas,etc.were high;The top 10 keywords in the CNKI database in terms of burst intensity were:microRNA,inflammatory response,inflammatory factor,interleukin-10,tumor necrosis factor-α,acute respiratory distress syndrome,interleukin-35,septic shock,rat,tiny microRNA-155(miR-155);the top 10 keywords in the core collection of the WOS database in terms of burst intensity were:expression,NF-κB,microRNA,cells,induction,pathway,mechanisms,septic shock,mortality,cancer.Representative clustering tags in the CNKI are#0 prognosis,#1 miRNA,#2 septic shock;The representative clustering labels in the core collection of WOS database are#0 acute lung injury,#1 cancer,#2 septic shock,and so on.In CNKI and WOS core databases,the early keywords mainly revolve around the study of inflammatory factors and related mechanisms of sepsis,and the research center gradually shifts to the clinical physiological injuries as well as complications and mortality in the later stage,miRNA-126,AMP-activated protein kinase,interleukin-35 and other keywords have emerged.Among the top 10 most-cited English literature,researchers have paid particular attention to studying various miRNA as potential biomarkers of sepsis,including miR-146a,miR-223 and miR-146.Conclusions There are similarities and differences in the direction and hotspots of sepsis-related miRNA research in China and abroad.The research paradigm of sepsis has gradually shifted from the early clinical observation focusing on the overall complications and prognosis of patients to the basic research centered on the molecular mechanisms of inflammatory factors and signaling pathways.In this context,the study of miRNA as novel biomarkers for sepsis has been increasingly emphasized,and miRNA represent a promising direction for sepsis research,with potential applications both in basic research and clinical treatment.

Objective:To analyze the association between moderate-to-vigorous-physical activity (MVPA) and obesity, poor sleep quality, as well as multimorbidity in 7- to 8-year-old children in Shanghai City.Methods:From September to November 2023, a cluster sampling method was used to select second-grade students from four primary schools in Jinshan District, Shanghai. Three-axis acceleration motion sensors (GT3X+, Acti-graph) were used to monitor daily physical activity for seven consecutive days. A multivariate logistic regression model was used to analyze the association between MVPA duration characteristics and obesity, poor sleep quality and multimorbidity in school-age children.Results:Of the 937 study participants, 512 (54.64%) were boys and 425 (45.36%) were girls. Among them, 89 (9.50%) were obese and 782 (83.46%) had poor sleep quality. A total of 77 cases (8.22%) were affected by obesity and poor sleep quality. The average daily MVPA time was (45.97±15.87) minutes, and the MVPA attainment rate was 17.18%. The multivariate logistic regression model analysis showed that, after adjusting for covariates, the daily average MVPA time was negatively associated with the risk of obesity ( OR=0.982, 95% CI: 0.968-0.997), as well as multimorbidity ( OR=0.981, 95% CI: 0.965-0.997). The risk of obesity, poor sleep quality and multimorbidity in <1 d was 2.228 ( OR=2.228, 95% CI: 1.398-3.549), 1.702 ( OR=1.702, 95% CI: 1.141-2.540) and 2.150 ( OR=2.150, 95% CI: 1.310-3.528) times higher than that in ≥1 d. Conclusion:Obesity, poor sleep quality and multimorbidity of school-age children are closely related to the level of moderate-to-vigorous physical activity.

Objective:To compare the accuracy of two-dimensional (2D) ultrasound with three-dimensional (3D) reconstruction and conventional 2D ultrasound in measuring bladder volume in pelvic tumor patients, using computed tomography (CT) as the reference.Methods:A set of bladder phantoms were constructed to compare CT and ultrasound measurements with actual injected volumes. Clinical data of 104 pelvic tumor patients who received radiotherapy at the Cancer Hospital, Chinese Academy of Medical Sciences between August and December 2023 were retrospectively analyzed. Portable transabdominal ultrasound was used to obtain the largest bladder cross-section, and the maximum diameters in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions (D LR, D AP, D SI) were measured. The 2D ultrasound volume was calculated as V=0.523 × D LR × D AP × D SI. Full-bladder transverse videos were recorded and processed in Matlab R2016a through frame extraction(60 images), followed by contrast enhancement, edge detection segmentation, cubic spline interpolation, and image smoothing to achieve 3D reconstruction. Paired t-tests, intraclass correlation coefficients (ICC), and Bland-Altman analyses were performed to assess systematic bias and consistency between ultrasound methods and CT. Multivariate linear regression was applied to evaluate the effects of slice thickness, posture, age, and other factors on CT measurements. Results:In the phantom study, deviations of 2D ultrasound and CT from actual injected volumes were (0.73±3.05) ml ( t=-0.48, P=0.667) and (1.52±11.27) ml ( t=0.17, P=0.875), with ICC values>0.999. In the clinical study, mean bladder volumes measured by 3D-reconstructed ultrasound, conventional 2D ultrasound, and CT were (373.5±153.31), (314.89±135.28), (382.82±157.57) ml, respectively. The 3D-reconstructed method showed excellent agreement with CT (ICC=0.98; Bland-Altman mean bias=-9.32 ml, P=0.096), while 2D ultrasound also showed good consistency (ICC=0.91), but significantly underestimated bladder volume (mean bias=-67.93 ml, P<0.001). Subgroup analysis revealed that 2D ultrasound had the best agreement with CT in the medium-volume group (200-500 ml, ICC=0.902), whereas agreement decreased in the small-volume (<200 ml, ICC=0.884) and large-volume (>500 ml, ICC=0.840) groups (all P<0.001). The 3D-reconstructed ultrasound maintained excellent consistency with CT across all subgroups (all ICC>0.95), and the measured bladder volume was not statistically significant. Multivariate regression showed that slice thickness, posture, age, sex, and surgical status had no significant effects on CT measurements. Conclusions:Ultrasound with 3D reconstruction enables accurate bladder volume monitoring through true 3D contour reconstruction, while conventional 2D ultrasound systematically underestimates bladder volume and requires correction.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.