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.

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.

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.

Objective To analyze the use of outcome indicators and evaluation tools in randomized controlled trial(RCT)of music interventions for lung cancer-related anxiety and depression.Methods Nine databases were searched,and the literature was screened according to inclusion and exclusion criteria,followed by a summary of outcome indicators,and statistical analysis of classification and frequency of use according to the attributes of the outcome indicators.Results A total of 243 articles were retrieved,and 18 RCTs were finally included.The outcome indicators were classified into 8 indicator categories according to their functional attributes:anxiety scale(24.19%),depression scale(16.13%),quality of life scale(14.52%),sleep quality scale(9.68%),pain scale(4.84%),blood biochemical indicators(14.52%),vital signs(11.29%),and pulmonary and exercise function indicators(FEV1%,6MWD,BODE index)(4.84%).The problems are as follows:First,the overall risk of bias is high in the included RCTs.Second,the timing of measurement is variable due to inconsistency in the length of treatment.Third,the forms of music intervention are diverse.Besides,the use of other rating scales and objective indicators is low and safety indicators were neglected.Finally,the method of evaluation tools was single and some RCTs did not specify grading criteria.Conclusion The use of outcome indicators and evaluation tools in music interventions for lung cancer-related anxiety and depression has certain shortcomings,which affects the credibility of the trials.It is recommended to standardize the use of outcome indicators and establish a core set of indicators for clinical studies of music intervention for lung cancer-related anxiety and depression.

Objective: To elucidate the association between biorhythm disorders and health risk behaviors in adolescence, so as to provide reference for appropriate interventions. Methods: From March to April 2023, 2 381 adolescents in Shanghai were selected as research objects using convenience sampling and stratified random cluster sampling methods. The Self rating Questionnaire of Biological Rhythm Disorders for Adolescents (SQBRDA) and the self report health risk behaviors questionnaire were used to investigate the status of adolescent biorhythm disorders and nine kinds of health risk behaviors, while a multivariate Logistic regression model was employed to analyze the association between the two variables. Results: The average SQBRDA score was (68.25±0.42) The incidence and detection rates of health risk behaviors in the groups with no co occurrence, mild co occurrence, moderate co occurrence, and severe co occurrence were 234(9.83%), 1 176(49.39%), 830(34.86%) and 141(5.92%), respectively. The total SQBRDA score was positively correlated with the risk of co occurrence of health risk behaviors. The risk of mild co occurrence, moderate co occurrence, and severe co occurrence of health risk behaviors was 9.05 times (95% CI =4.25-19.15, P <0.01), 44.55 times (95% CI =20.75-96.05, P <0.01) and 110.05 times (95% CI =40.65-297.95, P <0.01) higher, respectively, among adolescents with higher scores of biorhythm disorders compared to adolescents with lower scores of biorhythm disorders. Conclusions Health risk behaviors among adolescents in Shanghai draw attention to a serious phenomenon whereby biorhythm disorders are positively correlated with the risk of co occurrence. Comprehensive interventions aimed at addressing adolescent health risk behaviors should focus on regulating biorhythm disorders.

Objective: To explore the association between dietary behaviors and sleep duration among middle school students in Shanghai, so as to provide reference for interventions targeting insufficient sleep. Methods: From May to June 2021, a stratified cluster random sampling method was employed to select a sample of 10-17yearold middle school students for monitoring their healthrisk behaviors. A total of 5 538 valid questionnaires were collected. The survey included items such as daily sleep duration, weekly consumption of sugary beverages, freshly squeezed fruit juice, fresh fruits, fresh vegetables, fried foods, milk and yogurt, breakfast habits, and frequency of eating outside. Statistical analysis was conducted using Chisquare test, Wilcoxon ranksum test, and multivariable Logistic regression model. Results: About 73.7% of middle school students reported insufficient sleep in Shanghai. There was a positive correlation between the average daily consumption of fresh fruits and breakfast consumption with sleep duration. In other words, a higher frequency of consuming fresh fruits (OR=1.29) and eating breakfast (OR=1.07) were associated with a higher likelihood of sufficient sleep. Conversely, there was a negative correlation between the frequency of consuming desserts (OR=0.78) and fried foods (OR=0.88) and sleep duration (P<0.05). Conclusions Increasing the consumption of fresh fruits and maintaining regular breakfast habits while reducing the intake of fried foods can contribute to achieving sufficient sleep among middle school students. When implementing interventions to improve sleep among middle school students, promoting healthy and balanced diets can be considered as one of the intervention strategies.

Objective: To explore the current status and associated factors of bullying behavior among middle school students in Shanghai, so as to provide a reference basis for carrying out bullying intervention work. Methods: From May to June 2021, a stratified cluster sampling method was used to select 19 000 middle school students from 63 schools in 16 districts of Shanghai, and the Shanghai Youth Health Risk Behavior Survey Questionnaire was used to conduct an anonymous questionnaire survey of enrolled students. Chi square test and binary Logistic regression analysis were employed to investigate the associated factors of bullying among middle school students. Results: The prevalence of bullying behaviors in Shanghai was 15.5%, with males and junior high school students exhibiting the higher reporting rate(19.5%,17.2%). And malicious teasing or name calling had the highest reported rate at 9.4%. The results of binary Logistic regression analysis showed that fighting ( OR =5.02), attempting to smoke ( OR =3.22), having a feeling of sadness and hopelessness ( OR =2.50) and getting drunk( OR =1.72) were positively associated with bullying behavior among middle school students. Fighting ( OR =3.83-8.97), attempting to smoke ( OR =2.92-5.52), having a feeling of sadness and hopelessness ( OR =2.40-4.34), and getting drunk ( OR =1.66-2.34) were positively correlated with 6 forms of bullying (malicious teasing or name calling, intentionally damaging someone else s belongings, deliberately excluding someone from activities or isolating someone, threatening or intimidating others, hitting, kicking, or pushing someone, and verbally harassing or attacking someone online) ( P <0.05). Conclusions Bullying behavior of middle school students in Shanghai primarily presents as verbal harassment. In the future, greater attention should be directed towards bullies, and it should recognize potential hazards promptly and implement precise intervention measures.

Objective: To understand the relationship between stress and Internet addiction among middle school students in Shanghai, so as to provide a scientific basis for promoting students mental health and preventing Internet addiction. Methods: From May to June 2021, a stratified random cluster sampling method was used to select 6 123 middle and high school students in Shanghai for health risk behavior monitoring. Daily Stressors Evaluation Scale for Urban Secondary School Students was used to evaluate students' stress, and the Internet Addiction Test compiled by Young was used to evaluate students Internet addiction. The correlation between student stress and Internet addiction was analyzed by Kruskal-Wallis H test , Chi square test and multiple Logistic regression. Results: Total stress score of middle school students in Shanghai was 24 (12, 39), academic stress score was 8 (5, 13), physical and psychological stress score was 6 (2, 10), interpersonal stress score was 5 (1, 9), and family stress score was 4 (1, 8). The detection rate of Internet addiction was 4.7%. Multivariate Logistic regression analysis showed that the risk of Internet addiction among middle school students with high levels of stress was 8.05 times(95% CI =4.59-14.12) that of students with low levels of stress( P <0.05). The risk of Internet addiction among middle school students with high levels of academic stress, physical and psychological stress, interpersonal stress and family stress was 5.98(95% CI =3.69-9.70), 6.92(95% CI =4.03-11.88), 4.85(95% CI =3.11-7.55), and 4.18(95% CI =2.73-6.40) times that of students with low levels of stress, respectively( P <0.05). Conclusion The academic stress, physical and psychological stress, interpersonal stress, and family stress among middle school students can all lead to an increased risk of Internet addiction.