Objective: To investigate the impact of disposable plastic food container usage on the executive function among primary school students, so as to provide the evidence for the formulation of relevant health policies. Methods: From November 2023 to May 2024, a convenience sampling method was employed to select 1 118 grade 1-3 students from three primary schools in a central district of Chongqing. A self developed questionnaire was used to collect demographic characteristics and data on disposable plastic food container usage. Executive function of primary school students was assessed using the Childhood Executive Functioning Inventory (CHEXI). Multivariate linear regression analysis was conducted to explore the associations between disposable plastic food container usage and heating with executive function among primary school students. Results: Median scores for working memory, inhibition and total executive function among primary school students were 32 (26, 39), 33 (28, 38), and 66 (54, 75), respectively. Multivariate linear regression analysis showed that among girls, higher frequencies of eating meals from plastic lunchboxes were associated with higher CHEXI working memory scores ( β =1.29), inhibition scores ( β =1.57), and total executive function scores ( β =2.85) ( P <0.05). Compared to girls who did not use plastic cups or drank bottled water, those who used plastic cups for drinking or drank bottled water had higher scores in working memory ( β =2.63), inhibition ( β =2.10), and total executive function ( β =4.73); compared to girls who did not eat canned food from metal cans, those who ate such food had higher scores in working memory ( β =3.62), inhibition ( β =1.89), and total executive function ( β =5.50) ( P <0.05).Among boys, higher frequencies of eating meals from plastic lunchboxes were associated with higher inhibition scores ( β =1.13) ( P <0.05). Compared to girls who ate with a plastic lunch box and did not heat it when they ate,girls who more frequent heating plastic lunchboxes with food inside had higher working memory scores ( β = 5.39), inhibition scores ( β =4.29), and total executive function scores ( β = 9.68) ( P <0.05). Conclusions The use of disposable plastic food containers may adversely affect executive function of primary school students, with a more pronounced effect observed in girls. Strengthened regulation of disposable plastic products and health education are urgently needed.

Mitochondrial dysfunction in chondrocytes is a key pathogenic factor in osteoarthritis (OA), but directly modulating mitochondria in vivo remains a significant challenge. This study is the first to verify a correlation between mitochondrial dysfunction and the downregulation of the FOXO3 gene in the cartilage of OA patients, highlighting the potential for regulating mitophagy via FOXO3 gene modulation to alleviate OA. Consequently, we developed a chondrocyte-targeting CRISPR/Cas9-based FOXO3 gene-editing tool (FoxO3) and integrated it within a nanoengineered 'truck' (NETT, FoxO3-NETT). This was further encapsulated in injectable hydrogel microspheres (FoxO3-NETT@SMs) to harness the antioxidant properties of sodium alginate and the enhanced lubrication of hybrid exosomes. Collectively, these FoxO3-NETT@SMs successfully activate mitophagy and rebalance mitochondrial function in OA chondrocytes through the Foxo3 gene-modulated PINK1/Parkin pathway. As a result, FoxO3-NETT@SMs stimulate chondrocytes proliferation, migration, and ECM production in vitro, and effectively alleviate OA progression in vivo, demonstrating significant potential for clinical applications.

Over the past few decades, tumor immunotherapy has revolutionized the landscape of cancer clinical treatment. There is a flourishing development of combination strategies to improve the anti-tumor efficacy of mono-immunotherapy. However, instead of a straightforward combination of multiple therapeutics, it is more preferable to pursue a synergistic effect by designing rational combinations as well as administration strategies, which are based on a comprehensive understanding of the physiological and pathological features. In this case, the timing and spatial distribution of the combination drugs become essential factors in achieving improved therapeutic outcomes. Therefore, the concept of Sequential Drug Delivery System (SDDS) is proposed to define the spatiotemporally programmed drug delivery/release through triggers of internal conditions and/or external interventions, thus complying with the dynamic disease evolution and the human immunity. This review summarizes the recent advancements in biomaterial-based SDDSs used for spatiotemporally-tuned combination tumor immunotherapy. Furthermore, the rationales behind various engineering strategies are discussed. Finally, an overview of potential synergistic mechanisms as well as their prospects for combination immunotherapy is presented.

This paper briefly introduces the definition, classification and significance of effect modification in epidemiological studies, summarizes the difference between effect modifier and confounders, and analyze the influence as well as the role of effect modification in epidemiological studies and Meta-analysis. In this paper, the possible scenarios of effect modification and related analysis strategy in Meta-analysis are indicated by graphics, aiming to arouse researchers' attention to effect modification. This paper also demonstrates how to identify and deal with effect modification in Meta-analysis through a study case of "Efficacy of sodium-glucose cotransporter 2 inhibitors in patients with type 2 diabetes", and shows the analysis process and interpretation of results of subgroup analysis and Meta-regression methods respectively. The advantages and disadvantages of these two methods are summarized to provide reference for the method selection of future research.

This paper briefly introduces the characteristics, research significance, and global reporting status of effect modification in network Meta-analysis, demonstrates the heterogeneity caused by effect modification in network Meta-analysis, and emphasizes the importance of exploring effect modification in network Meta-analysis. This paper also summarizes the normalized description and analysis strategies of effect modification in network Meta-analysis. Finally, by the case of "comparison of efficacy of three new hypoglycemic drugs in reducing body weight in type 2 diabetes patients", this paper demonstrates the realization of subgroup analysis and network Meta-regression in exploring effect modification, summarizes the advantages and disadvantages of the two methods, to provide references for future researchers.

Objective:Differences between randomized controlled trial (RCT) results and real world study (RWS) results may not represent a true efficacy-effectiveness gap because efficacy-effectiveness gap estimates may be biased when RWS and RCT differ significantly in study design or when there is bias in RWS result estimation. Secondly, when there is an efficacy- effectiveness gap, it should not treat every patient the same way but assess the real-world factors influencing the intervention's effectiveness and identify the subgroup likely to achieve the desired effect.Methods:Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31 st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results:Ten articles were included to discuss how to use the RCT research protocol as a template to develop the corresponding RWS research protocol. Moreover, based on correctly estimating the efficacy-effectiveness gap, evaluate the intervention effect in the patient subgroup to confirm the subgroup that can achieve the expected benefit-risk ratio to bridge the efficacy-effectiveness gap.Conclusion:Using real-world data to simulate key features of randomized controlled clinical trial study design can improve the authenticity and effectiveness of study results and bridge the efficacy-effectiveness gap.

This paper briefly introduces the unique advantages, overall analysis ideas and existing analysis methods of individual patient data Meta-analysis in terms of effect modification. In addition to Meta-regression and subgroup analysis, this paper also introduces the analysis methods based on part of individual patient data integrated with aggregated data and summarizes the current reporting of the above mentioned methods. In addition, the application and results interpretation of the above mentioned methods in individual patient data Meta-analysis are presented in this paper by taking "Effects of sodium-glucose cotransporter 2 inhibitors on SBP in patients with type 2 diabetes" as an example and by introducing their advantages and limitations.

Objective:Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings.Methods:Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31 st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results:A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics.Conclusions:Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted.

This study aims at examining the application and development of digital teaching materials in the field of epidemiology, encompassing both China and international contexts. The research involved conducting search on websites and literature databases to assess the status of digital teaching materials in epidemiology, nationally and internationally. At present, in China, digital teaching materials used in epidemiology are primarily presented in the form of printed books with added QR codes, providing teaching resources such as videos and exercises. However, issues with the level of interactivity have been identified. In foreign countries, with stronger emphasis placed on personalization, interactivity, and the use of rich media technologies in the digital teaching materials, epidemiologically. Enhanced digitization regarding materials and learning outcomes is achieved through features such as real-time notes, interactive animations, and quizzes. These approaches are considered worth considering for adoption. This study provides valuable insights for the digital transformation of epidemiology education.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.