Objective: To explore the current status and influencing factors of eating behaviors in adolescents, so as to provide a theoretical foundation for health promotion education among adolescents. Methods: Based on the database from Survey of Chinese Family Health Index (2021), by a random number table method, 1 065 teenagers were selected from the provincial capitals of 22 provinces and 5 autonomous regions in China, as well as 4 municipalities directly under the central government. A general characteristic questionnaire, Patient Health Questionnaire-9 (PHQ-9), Short Form of the Family Health Scale (FHS-SF), 10-item Short Version of the Big Five Personality(BFP-10), Content-based Media Exposure Scale (CM-E) and Sakata Eating Behavior Scale Short Form(EBS-SF) were used to collect information. Multivariate stepwise linear regression analysis was employed to identify and analyze related factors of eating behaviors among adolescents. Receiver operating characteristic was used to validate the predictive ability of the EBS-SF score for overweight and obesity among adolescents. Results: The average scores of BFI-10,C-ME, FHS-SF, PHQ-9 and EBS-SF were (33.08±4.64)(19.20±4.55)(38.48±6.65)(6.09±5.63)(16.75±4.36), respectively. Multivariate linear regression showed that family type (other types), agreeableness, conscientiousness, family health and depression were the main related factors of EBS-SF scores among adolescents( B =2.61,-0.42,0.20,-0.11,0.23, P <0.05).The analysis of receiver operating characteristic curve showed that the EBS-SF scores had a good ability in predicting obesity among male adolescents ( AUC= 0.73, P <0.01). Conclusions Family type, big five personality, family health,depression are the related factors of eating behaviors among adolescents. EBS-SF scores are predictive of obesity in adolescents, which would provide a new perspective for promoting healthy eating habits among adolescents.

The study aims to explore the methods for preparing nanocomplexes of Prussian blue nanoparticles (PBNPs) with UNO peptide (UNO-PBNPs) and the functions of the nanocomplexes targeting M2-type macrophages in vitro. PBNPs were prepared by the hydrothermal synthesis method. Subsequently, the peptide UNO (CSPGAKVRC) targeting the mannose receptor was modified on their surface by a heterobifunctional coupling approach. The morphological characteristics of nanoparticles were observed by scanning and transmission electron microscopy. Additionally, their particle size, Zeta potential, and dispersion stability were assessed. The structural characteristics of nanoparticles were analyzed by X-ray diffraction and other techniques. The biological safety of the nanoparticles was evaluated by the CCK-8 assay and hemolysis experiments. Moreover, the targeting performance of UNO-PBNPs towards M2-type macrophages was assessed in vitro. The results showed that the synthesized UNO-PBNPs exhibited uniform cubic morphology, with an average particle size of (202.00±4.21) nm. They were negative charged, well dispersed, and stable. At concentrations ≤ 200 μg/mL, the synthesized UNO-PBNPs led to the hemolysis rate below 5%, demonstrating excellent biocompatibility. The laser confocal imaging results showed that after co-incubation with M2-type macrophages, the FITC-labeled UNO-PBNPs were effectively accumulated in the cells, presenting a distinct fluorescence signal. Quantitative analysis by flow cytometry showed that the intracellular mean fluorescence intensity (6 019.00±346.04) of UNO-PBNPs was higher than that (4 054.00±379.14) of unmodified PBNPs (P < 0.001). In summary, the UNO-PBNPs prepared in this study exhibited a targeting effect on M2-type macrophages, providing a potential method for targeted delivery of PBNPs in the tumor microenvironment and laying a foundation for the remodeling of the tumor immunosuppressive microenvironment.
Ferrocyanides/chemistry* ; Nanoparticles/chemistry* ; Macrophages/drug effects* ; Peptides/chemistry* ; Particle Size ; Animals ; Mannose Receptor ; Mice ; Lectins, C-Type ; Mannose-Binding Lectins ; Receptors, Cell Surface

Objective: To investigate the epidemiological characteristics of varicella outbreaks in primary and middle schools, and to establish a risk predictive model, so as to provide scientific guidance for the prevention of varicella outbreaks in schools. Methods: Based on a nested case-control study, primary and middle schools in 4 districts of Shanghai (Yangpu District and Jingan District) and Hangzhou (Xiaoshan District and Linping District) from January to December 2023 were selected to observe the status of varicella outbreaks. Associated factors of varicella outbreaks were investigated and used for establishing the predictive model, which was evaluated by the Hosmer-Lemeshow(H-L) goodness of fit test, receiver operating characteristic (ROC) curve, Calibration curve, decision curve analysis (DCA). Results: A total of 98 varicella outbreaks were included, with 195 schools without varicella outbreaks during the same period as controls. Eight factors, including the availability of warm water in restroom, availability of hand soap in restroom, average class size, duration of student attendance at school per day, presence of a fulltime school doctor, hesitancy of the school principal towards varicella vaccination, and rates of first and second doses of varicella vaccination, were identified as potential factors for school varicella outbreaks, with statistically significant differences (χ2/Z=10.01, 20.49, 17.43, 9.74, 32.17, 6.60, 2.20, 3.39, P<0.05). The 8 variables above were employed to construct a risk predictive model, and Hosmer-Lemeshow goodness of fit test yielded a χ2 value of 5.863 (P>0.05); the area under the ROC curve (AUC) was 0.846 (95%CI=0.799-0.893); Calibration curve analysis indicated good consistency between predicted and actual values of the model. DCA demonstrated favorable predictive performance of the model over a wide range. Conclusions The predictive model for school varicella outbreaks demonstrates satisfactory accuracy and efficacy. It suggested to make good use of this prediction model and take relevant measures to reduce the risk of varicella transmission in schools.

BACKGROUND:In clinical practice,the anterior superior iliac spine and posterior superior iliac spine are usually located by palpation,and the tilt of the pelvis is determined by visual observation method or photogrammetry.Among them,the visual observation method can only have qualitative conclusions,and its reliability is poor.The photogrammetry is not only more convenient and fast,but also can give more accurate quantitative data,which is one of the best clinical evaluation methods.However,there are no studies on the reliability of pelvic posture assessment using photogrammetry in China. OBJECTIVE:To evaluate the pelvic posture by visual observation method and photogrammetry,and to compare the reliability level of the two methods to guide clinical application. METHODS:Forty-five healthy subjects were selected and red marks were made at the bilateral anterior superior iliac spine and posterior superior iliac spine.Pelvic posture was photographed from the front,back(coronal plane),left,and right(sagittal plane).The left and right pelvic tilt angles(α,β angles)were selected from the front and back views,which represented the angle between the bilateral anterior superior iliac spine line or the bilateral posterior superior iliac spine line and the horizontal line.The anterior and posterior pelvic tilt angles(γ,θ angles)were selected from the side view,which represented the angle between the ipsilateral anterior superior iliac spine and posterior superior iliac spine line and the horizontal plane,indicating the sagittal plane pelvic tilt.Evaluation methods included visual observation method and photogrammetry.Two evaluators independently evaluated the pelvic α,β,γ,θ angles using the visual observation method first,and then recorded the pelvic α,β,γ,θ angles using the photogrammetry.After a one-month interval,the visual observation method and photogrammetry were performed again,and the pelvic α,β,γ,θ angles were recorded.The intraclass correlation coefficients were used to analyze the data obtained from the two evaluation methods and the before-and-after measurements:0.90-0.99 as an excellent correlation,0.80-0.89 as a good correlation,0.70-0.79 as a moderate correlation,and≤0.69 as a poor correlation.The standard error of measurement and the minimal detectable change with 95%confidence intervals were calculated to evaluate the inter-rater and intra-rater reliability. RESULTS AND CONCLUSION:(1)The interrater intraclass correlation coefficients of the visual observation method and photogrammetry were as follows:anterior view:0.682 and 0.718,posterior view:0.513 and 0.867,left view:0.739 and 0.960,and right view:0.756 and 0.971.The visual observation method showed poor correlation between the anterior and posterior views and moderate correlation between the left and right views,while the photogrammetry showed moderate correlation for the anterior view,good correlation for the posterior view,and excellent correlation for the left and right views.The standard error values of measurement were as follows:anterior view:3.266 and 1.625,posterior view:4.278 and 1.763,left view:5.935 and 1.787,and right view:5.723 and 1.698.The minimal detectable change values with 95%confidence intervals were as follows:anterior view:9.053 and 4.504,posterior view:11.858 and 4.887,left view:16.451 and 4.953,and right view:15.863 and 4.707.(2)The interrater intraclass correlation coefficients of the visual observation method and photogrammetry were as follows:anterior view:0.452 and 0.723,posterior view:0.483 and 0.904,left view:0.518 and 0.955,and right view:0.657 and 0.968.The visual observation method showed poor correlation in all four directions,while the photogrammetry showed moderate correlation for the anterior view and excellent correlation for the other three directions.The standard error values of measurement were as follows:anterior view:5.651 and 1.610,posterior view:4.237 and 1.523,left view:7.322 and 1.891,and right view:6.509 and 1.781.The minimal detectable change values with 95%confidence intervals were as follows:anterior view:15.664 and 4.463,posterior view:11.744 and 4.222,left view:20.296 and 5.242,and right view:18.042 and 4.937.(3)These results confirm that the sagittal and coronal plane photogrammetries have good intrarater and interrater reliability for evaluating pelvic posture,especially with the use of the photogrammetry,which has good data stability.This method is simple,fast,efficient,accurate,low-cost,and does not cause X-ray damage,and can qualitatively and quantitatively reflect the actual situation of the patient's pelvis,making it suitable for clinical use.

kidney deficiency and blood stasis are believed to be the key pathogenesis of recurrent implantation failure （RIF）， and therefore， it is proposed to take kidney-supplementing and blood-invigorating as the basic treatment method， and use it by stages to assist the controlled superovulation program of in vitro fertilization-embryo transfer （IVF-ET）. The focus should be put on nourishing kidney yin， soothing the liver and invigorating blood during down-regulation period， using kidney yin-nourishing medicinals and modified Qinghao Biejia Decoction （青蒿鳖甲汤）. During the ovulation induction period， the focus should be put on nourishing kidney yang， replenishing blood， and promoting blood circulation， with self-made Bushen Culuan Formula （补肾促卵方） in modifications. After transplantation， it is suggested to put focus on tonifying the kidneys and replenishing essence， and self-made Wuzi Yanzong Guchong Decoction （五子衍宗固冲汤） in modifications can be used. At the same time， fetal protection treatment should be carried out for pregnant women， and modified Shou Tai Pill （寿胎丸） can be used to tonify the kidneys and calm the fetus.

Objective To investigate the influencing factors for chronic pancreatitis(CP)complicated by pancreatogenic portal hypertension(PPH),and to establish a predictive model.Methods A retrospective analysis was performed for the clinical data of 99 patients with CP complicated by PPH who were hospitalized in The First Affiliated Hospital of Kunming Medical University,Chuxiong Yi Autonomous Prefecture People's Hospital,Wenshan People's Hospital,and Puer People's Hospital from January 2017 to December 2022,and these patients were enrolled as PPH group.The incidence density sampling method was used to select 198 CP patients from databases as control group.The independent-samples t test was used for comparison of normally distributed continuous data between two groups,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups;the chi-square test or the Fisher's exact test was used for comparison of categorical data between two groups.The Least Absolute Shrinkage and Selection Operator(LASSO)regression model was used to identify the potential predictive factors for CP complicated by PPH,and the predictive factors obtained were included in the multivariate Logistic regression analysis to obtain independent risk factors,which were used to establish a nomogram prediction model.The receiver operating characteristic(ROC)curve,the calibration curve,and the Hosmer-Lemeshow goodness-of-fit test were used to perform internal validation of the model,and the clinical decision curve was used to assess the clinical practicability of the model.Results There were significant differences between the two groups in sex,history of recurrent acute pancreatitis attacks,acute exacerbation of CP,bile duct stones,peripancreatic fluid accumulation,pseudocysts,pulmonary infection,elevated C-reactive protein(CRP),elevated procalcitonin,fibrinogen(FIB),neutrophil-lymphocyte ratio(NLR),gamma-glutamyl transpeptidase,total bilirubin,direct bilirubin,low-density lipoprotein(LDL),serum amylase,D-dimer,and serum albumin(all P<0.05).The predictive variables obtained by the LASSO regression analysis included sex,recurrent acute pancreatitis attacks,bile duct stones,peripancreatic fluid accumulation,pulmonary infection,pseudocysts,CRP,NLR,FIB,and LDL.The multivariate Logistic regression analysis showed that sex(odds ratio[OR]=2.716,P<0.05),recurrent acute pancreatitis attacks(OR=2.138,P<0.05),peripancreatic fluid accumulation(OR=2.297,P<0.05),pseudocysts(OR=2.805,P<0.05),and FIB(OR=1.313,P<0.05)were independent risk factors for CP complicated by PPH.The above factors were fitted into the model,and the Bootstrap internal validation showed that the nomogram model had an area under the ROC curve of 0.787(95%confidence interval:0.730—0.844),and the calibration curve was close to the reference curve.The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good degree of fitting(χ2=7.469,P=0.487).The clinical decision curve analysis showed that the prediction model had good clinical practicability.Conclusion Male sex,recurrent acute pancreatitis attacks,peripancreatic fluid accumulation,pseudocysts,and FIB are independent risk factors for CP complicated by PPH,and the nomogram model established has good discriminatory ability,calibration,and clinical practicability.

Objective Changes in relevant indexes in the mouse model of early-onset ovarian insufficiency caused by Tripterygium wilfordii polyglycoside were analyzed,and the optimal time point for intervention was determined.Methods Forty female ICR mice were randomly divided into control and A,B,C,and D model groups with eight mice in each group.The control group was gavaged with purified water for 14 days(0.01 mL/10 g),and the remaining groups were administered a Tripterygium wilfordii polyglycoside suspension(80 mg/kg,0.01 mL/10 g)for 1 day(A model group),3 days(B model group),7 days(C model group),or 14 days(D model group),and samples were collected.Body weight and wet weights of the uterus and bilateral ovaries of mice were determined in each group.Serum FSH,LH,E2,P,AMH,INH-B,and T contents were measured using enzyme-linked immunoassays.HE staining was used to observe the number and developmental status of follicles and corpus luteum at all levels in mice of each group.TUNEL staining was used to detect the apoptosis in the ovaries of mice in each group.IHC detected expression of VEGFA,CD34,and EPO proteins in the ovaries of mice in each group.mRNA expression of HIF-1α,SDF-1,and CXCR4 in each group of mice was detected by PCR.Results Compared with the control group,changes in indicators in model A mice did not meet the POI modeling standard.The ovarian index,uterine index,and body weight of mice in the B model group were decreased significantly(P＜0.01),the weight of the C model group was decreased significantly(P＜0.01),and the ovarian index of the D model group was decreased significantly(P＜0.05).Serum contents of FSH and LH in B,C,and D model groups were increased(P＜0.05,P＜0.01),the E2,PROG,AMH,INH-B,and T contents were decreased(P＜0.01).The numbers of basal follicles,pre-sinus follicles,sinusoidal follicles,antral follicles,preovulatory follicles,and corpus luteum were decreased significantly(P＜0.05,P＜0.01)and the number of atresia follicles was increased significantly(P＜0.01)in B,C,and D model groups.The apoptotic area of TUNEL staining in A,B,C,and D model groups was increased significantly(P＜0.05,P＜0.01).Expression of CD34,VEGFA,and EPO in B,C,and D model groups was decreased significantly(P＜0.05,P＜0.01).mRNA expression of HIF-1α,SDF-1,and CXCR4 in A and B model groups was significantly increased(P＜0.05,P＜0.01).Compared with the B model group,the relevant indexes of C and D model groups were changed significantly,indicating that C and D models were more serious and tended to develop POF.Conclusions The B model group is the turning point of ovarian function from impaired POI to irreversible POF,suggesting that 3 days of administrating Tripterygium wilfordii polyglycoside is optimal to induce a POI disease model for effective drug intervention.

Using big data and artificial intelligence to establish a multi-point monitoring, early warning, and disposal system to achieve early warning and intervention of infectious disease outbreaks is an important means of controlling the spread of the epidemic. Taking Xiaoshan district as an example, this study analyzes the monitoring contents, warning methods, and application effectiveness of the infectious disease monitoring, early warning and disposal system. Based on Xiaoshan′s health big data resources, the system starts with syndrome, disease diagnosis and etiology. Through advanced technologies such as artificial intelligence and block chain, it realizes early identification of infectious disease outbreaks, data fusion, multi-cross collaboration, and closed-loop management. It has improved the sensitivity of clustered outbreaks monitoring and the effectiveness of epidemic disposal and provided a reference for grassroots disease prevention and control departments to establish an infectious disease monitoring and early warning system.

Objective To standardize nursing management on postoperative patients with a left ventricular assist-ant device(LVAD).Methods The first draft of the Consensus was formed on the basis of literature review.2 rounds of expert consultations and a round of online meeting discussion were held for adjustments and modifications the draft of the Consensus.Results The recovery rate of the inquiry questionnaire was 93.75%.The authority coefficients of the 2 rounds of inquiry experts were 0.927 and 0.920.The concentration degree of expert opinions for each indicator was greater than 3.5 score,and the coefficient of variation was less than 0.25.The Kendall harmony coefficients for 2 rounds of correspondence were 0.402 and 0.407(P<0.01).The final Consensus formed through expert consultations and meetings includes 7 themes:hemodynamic monitoring,LVAD function monitoring,coagulation function monitoring,percutaneous cable and wound care,exercise rehabilitation care,health education and guidance,and pre-discharge assessment.Conclusion The Consensus is scientific,rigorous,and authoritative.The Consensus covers all aspects of postoperative care for patients with LVAD,and it will benefit to clinical practice.

Using big data and artificial intelligence to establish a multi-point monitoring, early warning, and disposal system to achieve early warning and intervention of infectious disease outbreaks is an important means of controlling the spread of the epidemic. Taking Xiaoshan district as an example, this study analyzes the monitoring contents, warning methods, and application effectiveness of the infectious disease monitoring, early warning and disposal system. Based on Xiaoshan′s health big data resources, the system starts with syndrome, disease diagnosis and etiology. Through advanced technologies such as artificial intelligence and block chain, it realizes early identification of infectious disease outbreaks, data fusion, multi-cross collaboration, and closed-loop management. It has improved the sensitivity of clustered outbreaks monitoring and the effectiveness of epidemic disposal and provided a reference for grassroots disease prevention and control departments to establish an infectious disease monitoring and early warning system.