Abstract To promote the high quality development of school meal services, and to shape civilized and healthy eating habits for children and adolescents, the study analyzes Finnish school meal services. Finnish school meal services are not only free of charge, nutritionally balanced, safe and hygienic, but also carry the educational function of edutainment in meals. In order to ensure the high quality and efficient operation of the school meal service system, Finland has built a horizontal collaborative governance model, that is, the departments of education, finance, health and quality inspection have a clear division of labor and respective responsibilities. China can learn from the experience of Finnish schools in meal services, strengthen financial and legal guarantees, develop the educational functions of school meal services, and make full use of information technology such as the Internet, the Internet of things, and big data to promote the high quality development of school meal services.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Hypericum attenuatum Choisy.is dry whole grass of the genus Hypericum L.,is a kind of commonly used folk medicinal herbs more than 2400 years.And it is often used to treat heart disease,hemostasis,scald.Based on a review of domestic and international literature,the main chemical components of Hypericum attenuatum Choisy.include PPAPs,flavonoids,and volatile oil,of which PPAPs and xanthone have received the attention of a large number of scholars because of their complex and novel structures and unique pharmacological effects.Modern pharmacological studies have shown that Hypericum attenuatum Choisy.exerts various pharmacological activities,including anti-arrhythmia,reducing blood sugar,anti-tumor,anti-virus,anti-inflammation,as well as the treatment of depression.As a valuable folk medicine,there is relatively little related traditional Chinese medicine products,this review focus on its phytochemistry,and pharmacology,providing a comprehensive perspective and novel ideas for exploring its current and potential applications.

Diabetes, a metabolic disease stemming from impaired or defective insulin secretion, ranks among the most severe chronic illnesses globally. While several approved drugs exist for its treatment, they often come with multiple side effects. Therefore, there is a pressing need for safe and effective anti-diabetic medications. Traditional Chinese medicine has recognized Lycium barbarum (LB; goji berry) plant, commonly known as "wolfberry fruit" in China, for over 2,000 years. Natural compounds derived from LB show promise in reducing diabetes levels. Although research on the impact of LB on diabetes is still limited, our review aims to explore the potential of LB in reducing the risk of diabetes and examine the underlying mechanisms involved. LB can modulate diabetes through various pathways, such as inhibiting α-amylase and α-glucosidase activities, promoting β-cell proliferation, stimulating insulin secretion, inhibiting glucagon secretion, improving insulin resistance and glucose tolerance, and enhancing antioxidant and anti-inflammatory activities. Additionally, LB improves gut flora and immunomodulation, further aiding diabetes management. These findings highlight the potential clinical utility of LB in managing diabetes and its complications within the framework of evidence-based modern medicine.

BACKGROUND AND OBJECTIVE: Social anxiety arising from intensive social media usage (SMU) among adolescents and youth has gained extensive attention in recent years due to its negative influence on mental health and academic performance. In spite of that, there is a dearth regarding the etiology of SMU-related social anxiety. This study aims to further clarify the influence of introversion personality on SMU-related social anxiety and the mechanism underlying such an association and provide a new perspective for developing effective intervention strategies for the highly prevailing SMU-related anxiety among Chinese college students. METHODS: A cohort of 979 college students (266 males and 713 females) aged 20.90 ± 1.91 years was enrolled in this cross-sectional study. Four measures including the "extroversion" domain of Eysenck Personality Questionnaire Revised, Short Scale (EPQ-R-S E), Interaction Anxiousness Scale (IAS), Mobile Phone Addiction Index (MPAI), and Social Anxiety Scale for Social Media Users (SAS-SMU) were used to evaluate the influence of introversion personality on SMU-related social anxiety that was potentially mediated sequentially by interaction anxiousness and mobile phone addiction. Hayes PROCESS was used for correlation and mediation analysis. RESULTS: Interaction anxiousness (indirect effect = -1.331, 95% CI : -1.559 - -1.122) partially mediated the association between introversion personality and SMU-related social anxiety. Besides, a sequential mediation of interaction anxiousness and mobile phone addiction in the link between introversion personality and SMU-related social anxiety was revealed (indirect effect = -0.308, 95% CI : -0.404 - -0.220). No significant mediating effect was found with mobile phone addiction in the association between introversion personality and SMU-related social anxiety. CONCLUSION: Targeting interaction anxiousness and mobile phone addiction may represent an efficient strategy alleviating SMU-related social anxiety among Chinese college students with introversion personality.
Humans ; Male ; Female ; Social Media ; Students/psychology* ; Anxiety/psychology* ; Young Adult ; Cross-Sectional Studies ; Universities ; Behavior, Addictive/psychology* ; Cell Phone ; Adolescent ; Introversion, Psychological ; China ; Surveys and Questionnaires ; Internet Addiction Disorder/psychology*

Objective To analyze the value of abdominal CT images combined with serological indicators in predicting the ureteral involvement in idiopathic retroperitoneal fibrosis(IRF). Methods The CT images of 79 IRF patients were analyzed retrospectively,including the involved sites and enhancement characteristics of the lesions.According to the inclusion and exclusion criteria,43 patients with complete serological data were selected and assigned into a ureteral involvement group(n=29)and a non-ureteral involvement group(n=14) according to whether ureters were involved in IRF.Logistic regression analysis was performed to select independent risk factors for ureteral involvement in IRF.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of the CT arterial phase enhancement magnitude and serum cystatin C(CysC)for ureteral involvement in IRF. Results The CT images of IRF usually showed a soft tissue density lesion encompassing the abdominal aorta,iliac arteries,ureters,and retroperitoneal tissue,with a wide range of distribution.The ureteral involvement group and the non-ureteral involvement group showed differences in gender(P=0.031),CT arterial phase enhancement amplitude(P=0.014),CT venous phase enhancement amplitude(P=0.032),and serum CysC(P=0.036).Logistic regression analysis showed that gender(P=0.034),CT arterial phase enhancement amplitude(P=0.046),and serum CysC(P=0.041)were independent risk factors for ureteral involvement in IRF.The area under the curve for CT arterial phase enhancement combined with serum CysC to predict ureteral involvement in IRF was 0.776.Ten patients had lower levels of erythrocyte sedimentation rate(P<0.001),C-reactive protein(P=0.021),and IgG4(P<0.001)in the follow-up period than before treatment. Conclusion The combination of abdominal CT images with serological indicators demonstrates high accuracy in predicting the ureteral involvement in IRF,providing reference for early clinical diagnosis.
Humans ; Male ; Female ; Retroperitoneal Fibrosis/pathology* ; Middle Aged ; Retrospective Studies ; Tomography, X-Ray Computed ; Aged ; Adult ; Ureter/diagnostic imaging* ; Predictive Value of Tests ; Cystatin C/blood*

ObjectiveTo investigate the application value of a multimodal model integrating radiomics features， deep learning features， and clinical structured data in predicting severe acute pancreatitis （SAP）， and to provide more accurate tools for the early identification of SAP in clinical practice. MethodsThe patients with acute pancreatitis （AP） who attended The First Affiliated Hospital of Soochow University， Jintan Hospital Affiliated to Jiangsu University， and Suzhou Yongding Hospital from January 1， 2017 to December 31， 2023 were included. Related data were collected， including demographic information， previous medical history， etiology， laboratory test data， and systemic inflammatory response syndrome （SIRS） within 24 hours after admission， as well as imaging data within 72 hours after admission， while related scores were calculated， including Ranson score， modified CT severity index （MCTSI）， bedside index for severity in acute pancreatitis （BISAP）， and systemic inflammatory response syndrome， albumin， blood urea nitrogen and pleural effusion （SABP） score. The model was constructed in the following process： （1） three-dimensional CT images were used to extract and identify radiomics features， and a radiomics classification model was established based on the extreme gradient Boost （XGBoost） algorithm； （2） U-Net is used to perform semantic segmentation of three-dimensional CT images， and then the results of segmentation were imported into 3D ResNet50 to construct a deep learning classification model； （3） the predicted values of the above two models were integrated with clinical structured data to establish a multimodal model based on the XGBoost algorithm. The variable importance plot and local interpretability plot were used to perform visual interpretation of the model. The independent samples t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the chi-square test or Fisher’s exact test was used for comparison of categorical data between groups. The receiver operating characteristic （ROC） curve was plotted for each model and existing scoring systems， and the area under the ROC curve （AUC） was calculated to assess their performance； the Delong test was used for comparison of AUC. ResultsA total of 609 patients who met the criteria were included， among whom 114 （18.7%） developed SAP. In this study， the data of 426 patients from The First Affiliated Hospital of Soochow University was used as the training set， and the data of 183 patients from Jintan Hospital Affiliated to Jiangsu University and Suzhou Yongding Hospital were used as the independent test set. The multimodal model had an AUC of 0.914 in the test set， which was significantly higher than the AUC of traditional scoring systems such as MCTSI （AUC=0.827）， Ranson score （AUC=0.675）， BISAP （AUC=0.791）， and SABP score （AUC=0.648）； in addition， the multimodal model showed a significant improvement in performance compared with the radiomics classification model （AUC=0.739） and the deep learning classification model （AUC=0.685） （the Delong test： Z=-3.23， -4.83， -3.48， -4.92， -4.31， and -4.59， all P <0.01）. The top 10 variables in terms of importance in the multimodal model were pleural effusion， predicted value of the deep learning model， predicted value of the radiomics model， triglycerides， calcium ions， SIRS， white blood cell count， age， platelets， and C-reactive protein， suggesting that the above variables had significant contributions to the performance of the model in predicting SAP. ConclusionBased on structured data， radiomic features， and deep learning features， this study constructs a multicenter prediction model for SAP based on the XGBoost algorithm， which has a better predictive performance than existing traditional scoring systems and unimodal models.

Objective To investigate the expression of blood basophil activation markers in patients with allergic rhinitis (AR) and the effects of allergens on their expression. Methods The blood samples were collected from the following four groups: healthy control (HC), AR patients with negative skin prick test (nAR), seasonal AR patients (sAR) and perennial AR patients (pAR). Flow cytometry was employed to analyze the expression of basophil activation markers Immunoglobulin E receptor I alpha(FcepsilonRIα), CD63 and CD203c in AR patients. Plasma levels of interleukin 4 (IL-4) and IL-8 were measured by liquid-phase chip technology, and their correlations with the percentages of activated basophils were further analyzed. An ovalbumin-induced AR mouse model was established, and the expression levels of FcepsilonRIα and CD63 on blood basophils were detected. Results The expression of FcepsilonRIα, CD203c and CD63 on basophils were increased in nAR, sAR and pAR patients. Allergens enhanced the mean florescence intensity expression of CD63 and CD203c on basophils of sAR and pAR patients. The plasma levels of IL-4 and IL-8 were elevated in nAR, sAR and pAR patients, showing moderate to high correlations with the expression levels of basophil activation markers. The FcepsilonRIαand CD63 expression on basophils of AR mice were increased. Conclusion Allergens may contribute to AR pathogenesis by upregulating the expression of FcepsilonRIα, CD63 and CD203c, as well as promoting the secretion of IL-4 and IL-8.
Basophils/metabolism* ; Humans ; Allergens/immunology* ; Animals ; Rhinitis, Allergic/blood* ; Female ; Male ; Adult ; Mice ; Biomarkers/blood* ; Tetraspanin 30/blood* ; Interleukin-4/blood* ; Interleukin-8/blood* ; Receptors, IgE/blood* ; Phosphoric Diester Hydrolases ; Young Adult ; Pyrophosphatases ; Middle Aged ; Mice, Inbred BALB C