Malnutrition status among primary and middle school students in Yunfu City / 预防医学

Objective@#To investigate the nutritional status and its influencing factors among primary and middle school students in Yunfu City, Guangdong Province, so as to provide the basis for improving nutrition and health strategies for students.@*Methods@#Primary and middle school students from 26 schools in 5 counties (cities, districts) of Yunfu City were selected in 2022 through multi-stage stratified cluster random sampling method. Demographic information, dietary and exercise behaviors were collected using questionnaire surveys, and the prevalence of malnutrition were analyzed. Factors affecting malnutrition was evaluated using a multinomial logistic regression model.@*Results@#A total of 7 213 students were surveyed, including 3 881 boys (53.81%) and 3 332 girls (46.19%), and had a median age of 13.50 (interquartile range, 4.00) years. There were 2 667 primary school students (36.97%), 2 662 middle school students (36.91%) and 1 884 high school students (26.12%). There were 1 938 students suffered from malnutrition, with a detection rate of 26.87%. The detection rates for undernutrition, overweight and obesity were 11.66%, 9.75% and 5.46%, respectively. Multinomial logistic regression analysis showed that gender (boy, OR=2.227, 95%CI: 1.905-2.603), studying phase (primary school, OR=1.528, 95%CI: 1.239-1.884), ≥60 min/d of moderate/high-intensity exercise (0-1 d/week, OR=1.422, 95%CI: 1.153-1.753; 2-4 d/week, OR=1.280, 95%CI: 1.047-1.564) and frequency of having physical education (1-2 classes/week, OR=1.732, 95%CI: 1.084-2.767; 3-4 classes/week, OR=1.662, 95%CI: 1.026-2.693) were the influencing factors for undernutrition; gender (boy, OR=1.956, 95%CI: 1.656-2.311), frequency of sugary beverage intake (0 time/d, OR=0.721, 95%CI: 0.528-0.984) and frequency of having physical education (0 class/week, OR=2.087, 95%CI: 1.151-3.784; 1-2 classes/week, OR=1.644, 95%CI: 1.044-2.590; 3-4 classes/week, OR=1.685, 95%CI: 1.051-2.703) were the influencing factors for overweight; gender (boy, OR=2.459, 95%CI: 1.964-3.078) was the influencing factor for obesity among students.@*Conclusions@#Undernutrition, overweight and obesity coexist in primary and middle school students in Yunfu City. Gender, school phase, frequency of sugary beverage intake and frequency of having physical education are associated with malnutrition among primary and middle school students.

Identification and characterization of differentially expressed circRNA in 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced cleft palate.

Various circular RNAs (circRNAs) are novel class of non-coding RNAs, which are pervasively transcribed in the genome. CircRNAs play important roles in human, animals and plants. Up to now, there was no report regarding circRNAs of cleft palate by 2,3,7,8-tetrachlorodibenzo-pdioxin (TCDD) induce. The present study screened identification and characterization of differential expressed-circRNAs in TCDD-induced cleft palate. 6903 circRNAs candidates came from cleft palates. Among them, 3525 circRNAs are up-regulation, and 3378 circRNAs are down-regulation by TCDD induce. The cluster and GO analysis found that circRNAs involved in biological process, cellular component, and molecular function. Through the analysis of KEGG Pathway, circRNAs made functions via classical signaling pathway in cleft palate, such as TGF-beta signaling pathway, BMP signal pathway, MAPK signaling pathway. In addition, we found down-regulated circRNA224, circRNA3302 and up-regulated circRNA5021 targeted tgfbr3, but up-regulated circRNA4451 targeted tgfbr2. circRNA4451 may make functions through TGF-beta signaling pathway. These results suggested that many different circRNAs may make important role in TCDD-induced cleft palate, which provided a theoretical basis for further research.

Identification of a apoptosis-related LncRNA signature to improve prognosis prediction and immunotherapy response in lung adenocarcinoma patients.

Apoptosis is closely associated with the development of various cancers, including lung adenocarcinoma (LUAD). However, the prognostic value of apoptosis-related lncRNAs (ApoRLs) in LUAD has not been fully elucidated. In the present study, we screened 2, 960 ApoRLs by constructing a co-expression network of mRNAs-lncRNAs associated with apoptosis, and identified 421 ApoRLs that were differentially expressed between LUAD samples and normal lung samples. Sixteen differentially expressed apoptosis-related lncRNAs (DE-ApoRLs) with prognostic relevance to LUAD patients were screened using univariate Cox regression analysis. An apoptosis-related lncRNA signature (ApoRLSig ) containing 10 ApoRLs was constructed by applying the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression method, and all LUAD patients in the TCGA cohort were divided into high or low risk groups. Moreover, patients in the high-risk group had a worse prognosis (p < 0.05). When analyzed in conjunction with clinical features, we found ApoRLSig to be an independent predictor of LUAD patients and established a prognostic nomogram combining ApoRLSig and clinical features. Gene set enrichment analysis (GSEA) revealed that ApoRLSig is involved in many malignancy-associated immunomodulatory pathways. In addition, there were significant differences in the immune microenvironment and immune cells between the high-risk and low-risk groups. Further analysis revealed that the expression levels of most immune checkpoint genes (ICGs) were higher in the high-risk group, which suggested that the immunotherapy effect was better in the high-risk group than in the low-risk group. And we found that the high-risk group was also better than the low-risk group in terms of chemotherapy effect. In conclusion, we successfully constructed an ApoRLSig which could predict the prognosis of LUAD patients and provide a novel strategy for the antitumor treatment of LUAD patients.

Histomorphological and ultrastructural cadmium-induced kidney injuries and precancerous lesions in rats and screening for biomarkers.

Long-term exposure to cadmium (Cd) can severely damage the kidney, where orally absorbed Cd accumulates. However, the molecular mechanisms of Cd-induced kidney damage, especially the early biomarkers of Cd-induced renal carcinogenesis, are unclear. In the present study, we established a rat kidney injury model by intragastric administration of Cd to evaluate the morphological and biochemical aspects of kidney injury. We randomly divided Sprague-Dawley rats into control, low Cd (3 mg/kg), and high Cd (6 mg/kg) groups and measured biochemical indices associated with renal toxicity after 2, 4, and 8 weeks of treatment. The Cd-exposed mice had significantly higher Cd concentrations in blood and renal tissues as well as blood urea nitrogen (BUN), ß2-microglobulin (ß2-MG), urinary protein excretion, and tumor necrosis factor-α (TNF-α) levels. Furthermore, histopathological and transmission electron microscopy (TEM) observations revealed structural disruption of renal tubules and glomeruli after 8 weeks of exposure to the high Cd regimen. Besides, microarray technology experiments showed that Cd increased the expression of genes related to the chemical carcinogenesis pathway in kidney tissue. Finally, combining the protein-protein interaction (PPI) network of the Cd carcinogenesis pathway genes with the microarray and Comparative Toxicogenomics Database (CTD) results revealed two overlapping genes, CYP1B1 and UGT2B. Therefore, the combined molecular and bioinformatics experiments' results suggest that CYP1B1 and UGT2B are biomarkers of Cd-induced kidney injury with precancerous lesions.

Construction and evaluation of a nomogram for predicting survival in patients with lung cancer.

BACKGROUND: Lung cancer is a heterogeneous disease with a severe disease burden. Because the prognosis of patients with lung cancer varies, it is critical to identify effective biomarkers for prognosis prediction. METHODS: A total of 2325 lung cancer patients were integrated into four independent sets (training set, validation set I, II and III) after removing batch effects in our study. We applied the microarray data algorithm to screen the differentially expressed genes in the training set. The most robust markers for prognosis were identified using the LASSO-Cox regression model, which was then used to create a Cox model and nomogram. RESULTS: Through LASSO and multivariate Cox regression analysis, eight genes were identified as prognosis-associated hub genes, followed by the creation of prognosis-associated risk scores (PRS). The results of the Kaplan-Meier analysis in the three validation sets demonstrate the good predictive performance of PRS, with hazard ratios of 2.38 (95% confidence interval (CI), 1.61-3.53) in the validation set I, 1.35 (95% CI, 1.06-1.71) in the validation set II, and 2.71 (95% CI, 1.77-4.18) in the validation set III. Additionally, the PRS demonstrated superior survival prediction in subgroups by age, gender, p-stage, and histologic type (p < 0.0001). The complex model integrating PRS and clinical risk factors also have a good predictive performance for 3-year overall survival. CONCLUSIONS: In this study, we developed a PRS signature to help predict the survival of lung cancer. By combining it with clinical risk factors, a nomogram was established to quantify the individual risk assessments.