: To analyze the prevalence of anemia and iron deficiency among primary and secondary school students in Rural Nutrition Improvement Program areas of Guizhou Province in 2023, and to explore the related factors, so as to provide evidence for Rural Nutrition Improvement Program optimization. Methods: In September 2023, a stratified random cluster sampling strategy was used to select 40 rural compulsory education schools with rural nutrition improvement program in five counties of Guizhou Province. School level questionnaire was employed to collect information of basic characteristics and school meal implementation. A total of 7 826 primary and secondary school students aged 6-16 underwent anthropometry and hemoglobin (Hb) determination; serum ferritin (SF) was additionally measured in a random subsample of 1 795 pupils. Students in Grade 3 and above also completed a questionnaire covering demographic characteristics, dietary behaviours and nutrition knowledge. Group comparisons were conducted by Chi square test or Fisher s exact test, and multivariable Logistic regression models were constructed to identify factors associated with anemia and iron deficiency. Results: The overall Hb level was (133.21±12.95)g/L, with an anemia prevalence of 7.17%. The overall SF level was (69.58±59.01)μg/L, with an iron deficiency prevalence of 2.73%. Multivariable analysis showed that stunting ( OR =1.88), school menus without nutrient calculation ( OR =1.61) and absence of menu planning software in the current semester ( OR =2.34) independently increased anemia risk, whereas obesity reduced it ( OR =0.54) (all P <0.05). Girls ( OR =4.16) and Grades 7-9 ( OR =5.93) increased iron deficiency risk (both P <0.05). Compared with rarely eating fresh vegetables, students with consuming <3 kinds per day ( OR =0.08) or exactly 3 kinds per day ( OR =0.06) had lower iron deficiency risks (both P <0.05). Conclusions Anemia and iron deficiency are prevalent among primary and secondary school students in Guizhou. Targeted intervention measures should be implemented for key populations to enhance the effectiveness of nutrition improvement program.

ObjectiveTo explore the construction of a risk assessment indicator system for common infectious diseases in Shanghai’s childcare institutions, and to provide a reference standard for the prevention and control of infectious diseases, staff training and system construction in childcare institutions. MethodsBy combining the Delphi method with the literature review and expert consultation, the hierarchical dimensions and items at all levels of the risk assessment indicator system for common infectious diseases in Shanghai’s childcare institutions were constructed, and the weighting coefficients were determined by analytic hierarchy process. ResultsA total of 14 experts from the field of childcare institutions, infectious disease control, child healthcare and health supervision participated in the Delphi consultation. The system consisted of four core dimensions: organizational management, team building, hardware equipment, and infectious disease surveillance and disposal, with the weighting coefficients of 0.285 9, 0.261 6, 0.204 3 and 0.248 2, respectively. The evaluation indicator system consisted of 4 primary indicators, 15 secondary indicators and 45 tertiary items. The positivity coefficients of the two rounds of Delphi consultation were 0.93 and 1.00, the authority coefficients were both 0.81, and the Kendall’s coefficient of concordance were 0.44 and 0.49, respectively (P<0.01). ConclusionThe high expert engagement and coordination indicate that organizational management and team building remain the critical priorities for infectious disease prevention and control in Shanghai’s childcare institutions. It is recommended to strengthen financial investment, improve institutional mechanisms, and enhance personnel reserves and capacity building for healthcare teachers, thereby systematically upgrading the infectious disease control capabilities of childcare institutions.

Human milk is universally recognized as the optimal and most natural source of nutrition for newborns, offering benefits that extend far beyond basic energy and macronutrient provision. Among its complex constituents, human milk oligosaccharides (HMOs) represent the third most abundant solid component, surpassed only by lactose and lipids. HMOs are distinguished by their exceptionally high structural diversity—over 200 distinct structures have been identified to date. This structural complexity underlies the extensive biological functions HMOs perform within the infant’s body. HMOs play a pivotal role in promoting healthy growth, development, and overall well-being in infants and young children, functioning as indispensable bioactive molecules. Their key physiological activities include: immunomodulation and allergy prevention by promoting immune tolerance and reducing the risk of allergic diseases; potent anti-inflammatory and antioxidant effects that protect vulnerable infant tissues; support for brain development and cognitive enhancement through multiple mechanisms; anti-pathogenic properties, acting as soluble receptor analogs or “decoy” molecules to competitively block viral, bacterial, and other pathogen adhesion, thereby preventing colonization and infection in the gastrointestinal tract; and functioning as blood group substances. At the translational and application level, HMO research is actively driving cross-disciplinary innovation. Building on a deep understanding of their immunological and neurodevelopmental benefits, certain structurally defined HMOs have been successfully incorporated into infant formula. These HMO-supplemented formulas have received regulatory approval and are now commercially available worldwide, providing a nutritional alternative that more closely resembles human milk for infants who are not exclusively breastfed. This represents a significant step toward narrowing the compositional gap between formula and breast milk. Simultaneously, research into the symbiotic relationship between HMOs and the gut microbiota—particularly their role as selective prebiotic substrates promoting the growth of beneficial bacteria—has catalyzed the development of novel functional foods, dietary supplements, and microbiome-targeted therapies. These include advanced synbiotic formulations that combine specific probiotic strains with HMOs to synergistically optimize gut health and function. Furthermore, the intrinsic qualities of HMOs—including their natural origin, safety profile, biocompatibility, and proven antioxidant properties—have attracted growing interest in the emerging field of high-performance cosmetics. They are increasingly being explored as innovative functional ingredients in skincare products aimed at reducing oxidative stress and supporting skin health. This review aims to systematically synthesize recent advancements in HMO research, offering a comprehensive analysis centered on their complex composition and structural diversity; the molecular and cellular mechanisms underlying their diverse biological functions; their translational potential across sectors such as nutrition, medicine, and consumer care (including cosmetics); and the major challenges that persist in the field. It critically examines both foundational discoveries and recent breakthroughs. By integrating these interconnected themes, the review provides a holistic and up-to-date perspective on the scientific landscape of HMOs, highlighting their essential role in early-life nutrition and their expanding relevance across health and wellness applications. It also outlines promising directions for future research, with the goal of advancing evidence-based innovation in infant health and beyond.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

Objective To investigate indoor radon concentrations and environmental cumulative doses in residential and office units in Shenzhen, and estimate the average annual effective dose, and to provide data for assessing public health risks. Methods Within the 11 administrative districts of Shenzhen (including the Shenzhen-Shanwei Special Cooperation Zone), 17 residential units and 3 office units were randomly selected as monitoring sites in each district. The units selected represented buildings of different ages and various floors on which the units were located. Radon detectors and environmental cumulative dosimeters were deployed for monitoring. Results The indoor radon concentrations in Shenzhen during the two monitoring periods were (36.6 ± 16.5) Bq/m³ and (19.8 ± 15.3) Bq/m³, respectively. The environmental cumulative doses for the two monitoring periods were (0.33 ± 0.07) mSv and (0.25 ± 0.04) mSv, respectively. The estimated average annual effective dose due to indoor radon in Shenzhen was 0.92 mSv. Conclusion All monitored indoor radon concentrations in Shenzhen were below the national standard of China. The indoor radon concentrations exhibited significant regional variations, were higher in spring than in summer, and showed no statistically significant differences across buildings of different ages or units of various floors. The trends in indoor radon concentrations and environmental cumulative doses were highly consistent. The average indoor radon concentration in Shenzhen was lower than both the global and national levels, indicating a low risk of internal radiation exposure from radon.

Objective:To investigate the differences in clinical outcomes of septic children with varying serum zinc levels,and to analyze the relationship between reduced serum zinc levels and organ dysfunction as well as 28-day mortality in septic children.Methods:This study conducted a retrospective analysis of clinical data from pediatric patients diagnosed with sepsis or septic shock in the Department of critical care medicine of the children's Hospital of Soochow University between January 2017 and December 2022.Clinical characteristics,organ dysfunction,and prognosis were compared between two groups:children with low serum zinc levels and those with normal zinc levels.Results:The serum zinc level of septic children within 24 hours of admission was 9.60(5.52,13.80)μmol/L,with 50.54%(94/186)of the children exhibiting low serum zinc levels(<10.07 μmol/L).Compared to the normal serum zinc group,the low serum zinc group had a significantly lower Pediatric Critical Illness Score(PCIS)[(78.71±9.35)vs.(85.12±8.51),P=0.005]and higher 28-day mortality(46.80%vs.14.13%,P<0.001).The low serum zinc group also had a higher proportion of invasive mechanical ventilation(64.89%vs.47.82%,P=0.019),renal replacement therapy(15.59%vs.3.26%,P=0.003),and use of vasoactive drugs(56.38%vs.30.43%,P<0.001).The rate of underlying conditions in the low serum zinc group was significantly higher than that in the normal serum zinc group(57.44%vs.36.95%,P=0.005).Additionally,the low serum zinc group had a higher incidence of disseminated intravascular coagulation(DIC),respiratory failure,acute kidney injury,shock,and multiple organ dysfunction syndrome(MODS)compared to the normal serum zinc group(P<0.05).Serum zinc levels had predictive value for 28-day mortality in septic children(AUC=0.813;95%CI:0.725～0.902;P<0.001).A serum zinc level of less than 6.950 μmol/L predicted the death of septic children with a sensitivity of 0.618 and a specificity of 0.902.Conclusion:Sepsis in children is commonly associated with low serum zinc levels,especially in those with underlying conditions such as hematologic and oncologic disorders.Sepsis patients hypozincemia with a higher incidence of DIC,respiratory failure,acute kidney injury,shock,and MODS.A serum zinc level below 6.95 μmol/L serves as a significant predictor of 28-day mortality in children with severe sepsis.

Objective To investigate the effect of programmed death-1(PD-1)on cell infiltration in muscle tissue and immune response types in mice infected with Trichinella spiralis.Methods C57BL/6J wild-type(WT)and PD-1 deficient(PD-1-/-)mice were infected with T.spiralis(400 muscle larvae per mouse),and samples were collected on day 35 after infection.The proportions of infiltrating inflammatory cells and fibroblasts around encapsulated larvae were assessed by immunohistochemistry.The expression levels of interferon-γ(IFN-γ),interleukin(IL)-4,IL-5,IL-13,and eotaxin in muscle tissue were measured using enzyme-linked immunosorbent assay.Peripheral blood and spleen were collected at different time points after infection.The percentages of CD4+IFN-γ+Th1 and CD4+IL-4+Th2 within CD4+T cells population in peripheral blood and spleen of mice were analyzed using flow cytometry.Results The proportions of eosinophils and fibroblasts among total infiltrating cells around the encapsulated larvae in the muscle of PD-1-/-mice were significantly lower than those in WT mice after T.spiralis infection(P＜0.01).The infected PD-1-/-mice exhibited higher proportions of macrophages,T cells and B cells in total infiltrating cells than the infected WT mice(P＜0.01).The levels of IL-4,IL-5,IL-13,and eotaxin in the muscle tissue of infected PD-1-/-mice were significantly lower than those in infected WT mice(P＜0.05).However,IFN-γ levels were not significantly different between the infected WT and PD-1-/-mice.The proportions of Th2 cells in CD4+T cells from peripheral blood and spleen of infected PD-1-/-mice were significantly lower than those in infected WT mice,whereas the proportion of Th1 cells showed no difference among the infected groups.Conclusions PD-1 deletion results in decreased expression of key chemokines of eosinophils and key cytokines of fibroblast formation,and a corresponding decrease in inflammatory cells in muscle in T.spiralis-infected mice.This effect may be associated with a diminished Th2 immune response caused by PD-1 deletion.