Background Obesity is a global epidemic in the industrialized and developing world, and many children suffer from obesity-related complications. Gut microbiota dysbiosis might have significant effect on the development of obesity. The microbiota continues to develop through childhood and thus childhood may be the prime time for microbiota interventions to realize health promotion or disease prevention. Therefore, it is crucial to understand the structure and function of pediatric gut microbiota. Methods According to the inclusion criteria and exclusion criteria, twenty-three normal weight and twenty-eight obese children were recruited from Nanjing, China. Genomic DNA was extracted from fecal samples. The V4 region of the bacterial 16S rDNA was amplified by PCR, and sequencing was applied to analyze the gut microbiota diversity and composition using the Illumina HiSeq 2500 platform. Results The number of operational taxonomic units (OTUs) showed a decrease in the diversity of gut microbiota with increasing body weight. The alpha diversity indices showed that the normal weight group had higher abundance and observed species than the obese group (Chao1: P < 0.001; observed species: P < 0.001; PD whole tree: P < 0.001; Shannon index: P = 0.008). Principal coordinate analysis (PCoA) and Nonmetric multidimensional scaling (NMDS) revealed significant differences in gut microbial community structure between the normal weight group and the obese group. The liner discriminant analysis (LDA) effect size (LEfSe) analysis showed that fifty-five species of bacteria were abundant in the fecal samples of the normal weight group and forty-five species of bacteria were abundant in the obese group. In regard to phyla, the gut microbiota in the obese group had lower proportions of Bacteroidetes (51.35%) compared to the normal weight group (55.48%) (P = 0.030). There was no statistical difference in Firmicutes between the two groups (P = 0.436), and the Firmicutes/Bacteroidetes between the two groups had no statistical difference (P = 0.983). At the genus level, Faecalibacterium, Phascolarctobacterium, Lachnospira, Megamonas, and Haemophilus were significantly more abundant in the obese group than in the normal weight group (P = 0.048, P = 0.018, P < 0.001, P = 0.040, and P = 0.003, respectively). The fecal microbiota of children in the obese group had lower proportions of Oscillospira and Dialister compared to the normal weight group (P = 0.002 and P = 0.002, respectively). Conclusions Our results showed a decrease in gut microbiota abundance and diversity as the BMI increased. Variations in the bacterial community structure were associated with obesity. Gut microbiota dysbiosis might play a crucial part in the development of obesity in Chinese children.

Background With characteristic self-renewal and multipotent differentiation, cancer stem cells (CSCs) have a crucial influence on the metastasis, relapse and drug resistance of gastric cancer (GC). However, the genes that participates in the stemness of GC stem cells have not been identified. Methods The mRNA expression-based stemness index (mRNAsi) was analyzed with differential expressions in GC. The weighted gene co-expression network analysis (WGCNA) was utilized to build a co-expression network targeting differentially expressed genes (DEG) and discover mRNAsi-related modules and genes. We assessed the association between the key genes at both the transcription and protein level. Gene Expression Omnibus (GEO) database was used to validate the expression levels of the key genes. The risk model was established according to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Furthermore, we determined the prognostic value of the model by employing Kaplan-Meier (KM) plus multivariate Cox analysis. Results GC tissues exhibited a substantially higher mRNAsi relative to the healthy non-tumor tissues. Based on WGCNA, 17 key genes (ARHGAP11A, BUB1, BUB1B, C1orf112, CENPF, KIF14, KIF15, KIF18B, KIF4A, NCAPH, PLK4, RACGAP1, RAD54L, SGO2, TPX2, TTK, and XRCC2) were identified. These key genes were clearly overexpressed in GC and validated in the GEO database. The protein-protein interaction (PPI) network as assessed by STRING indicated that the key genes were tightly connected. After LASSO analysis, a nine-gene risk model (BUB1B, NCAPH, KIF15, RAD54L, KIF18B, KIF4A, TTK, SGO2, C1orf112) was constructed. The overall survival in the high-risk group was relatively poor. The area under curve (AUC) of risk score was higher compared to that of clinicopathological characteristics. According to the multivariate Cox analysis, the nine-gene risk model was a predictor of disease outcomes in GC patients (HR, 7.606; 95% CI, 3.037–19.051; P < 0.001). We constructed a prognostic nomogram with well−fitted calibration curve based on risk score and clinical data. Conclusion The 17 mRNAsi-related key genes identified in this study could be potential treatment targets in GC treatment, considering that they can inhibit the stemness properties. The nine-gene risk model can be employed to predict the disease outcomes of the patients.

BackgroundDue to the increase incidents of premarital sex and the lack of reproductive health services, college students are at high risk of HIV/AIDS infections in China. This study was designed to examine the predictors of consistency of condom use among college students based on the Information-Motivation-Behavioral Skills (IMB) model and to describe the relationships between the model constructs.MethodsA cross-sectional study was conducted to assess HIV/AIDS related information, motivation, behavioral skills and preventive behavior among college students in five colleges and universities in Nanjing, China. An anonymous questionnaire survey was conducted for data collection, and the structural equation model (SEM) was used to assess the IMB model.ResultsA total of 3183 participants completed this study. The average age was 19.90 years (SD = 1.43, range 16 to 25). 342 (10.7%) participants of them reported having had premarital sex, among whom 30.7% reported having had a consistent condom use, 13.7% with the experience of abortion (including the participants whose sex partner has the same experience), 32.7% of participants had experience of multiple sex partners. The final IMB model provided acceptable fit to the data (CFI = 0.992, RMSEA = 0.028). Preventive behavior was significantly predicted by behavioral skills (β = 0.754, P<0.001). Information (β = 0.138, P<0.001) and motivation (β = 0.363, P<0.001) were indirectly affected preventive behavior, and was mediated through behavioral skills.ConclusionsThe results of the study demonstrate the utility of the IMB model for consistent condom use among college students in China. The main influencing factor of preventive behavior among college students is behavioral skills. Both information and motivation could affect preventive behavior through behavioral skills. Further research could develop preventive interventions based on the IMB model to promote consistent condom use among college students in China.

Background: Lumican (LUM) is a member of the small leucine-rich proteoglycan family and plays dual roles as an oncogene and a tumor suppressor gene. The effect of LUM on tumors is still controversial. Methods: Gene expression profiles and clinical data of gastric cancer (GC) were downloaded from The Cancer Genome Atlas (TCGA) database. The expression difference of LUM in GC tissues and adjacent nontumor tissues was analyzed by R software and verified by quantitative real-time polymerase chain reaction (qRT-PCR) and comprehensive meta-analysis. The relationship between LUM expression and clinicopathological parameters was assessed by chi-square test and logistic regression. Kaplan-Meier survival analysis and Cox proportional hazards regression model were chosen to assess the effect of LUM expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways involved in GC between the low and the high LUM expression datasets. Results: The expression of LUM in GC tissues was significantly higher than that in adjacent nontumor tissues (P < 0.001) from the TCGA database. qRT-PCR (P = 0.022) and comprehensive meta-analysis (standard mean difference = 0.90, 95% CI: 0.34-1.46) demonstrated that LUM was upregulated in GC. The chi-square test showed that the high expression of LUM was correlated with tumor differentiation (P = 0.024) and T stage (P = 0.004). Logistic regression analysis showed that high LUM expression was significantly correlated with tumor differentiation (OR = 1.543 for poor vs. well or moderate, P = 0.043), pathological stage (OR = 3.149 for stage II vs. stage I, P = 0.001; OR = 2.505 for stage III vs. stage I, P = 0.007), and T classification (OR = 13.304 for T2 vs. T1, P = 0.014; OR = 18.434 for T3 vs. T1, P = 0.005; OR = 30.649 for T4 vs. T1, P = 0.001). The Kaplan-Meier curves suggested that patients with high LUM expression had a poor prognosis. Multivariate analysis showed that a high expression of LUM was an important independent predictor of poor overall survival (HR, 1.189; 95% CI, 1.011-1.400; P = 0.037). GSEA indicated that 14 signaling pathways were evidently enriched in samples with the high-LUM expression phenotype. Conclusions: LUM might act as an oncogene in the progression of GC and could be regarded as a potential prognostic indicator and therapeutic target for GC.

The interferon-inducible transmembrane protein 3 (IFITM3), as one of the key genes involved in the interferon pathway, is critical for defending the host against influenza virus, and the rs12252 T>C variant in IFITM3 might be associated with susceptibility to severe influenza. Owing to contradictory and inconclusive results, we performed a meta-analysis to assess the association between rs12252 T>C polymorphism and severe influenza risk. A comprehensive literature search up to 1 August 2014 was conducted in EMBASE, Pubmed, Web of Science, VIP, Wanfang and CNKI databases. Four eligible studies with a total of 445 influenza patients and 3396 controls were included in this meta-analysis. Overall, our results demonstrated a significant association between the IFITM3 rs12252 T>C polymorphism and influenza risk [C vs. T: odds ratio (OR) 1·68, 95% confidence interval (CI) 1·32-2·13; CC vs. CT+TT: OR 2·38, 95% CI 1·52-3·73; CC+CT vs. TT: OR 1·62, 95% CI 1·18-2·22]. Stratification by ethnicity indicated that the variant C allele was associated with an 88% increased risk of influenza in Asians (C vs. T: OR 1·88, 95% CI 1·34-2·62). Moreover, subjects carrying the variant C allele had an increased risk of developing severe illness upon influenza infection (C vs. T: OR 2·70, 95% CI 1·86-3·94). However, no significant association was observed in patients with mild infection (C vs. T: OR 1·26, 95% CI 0·93-1·71). Our meta-analysis suggests that IFITM3 rs12252 T>C polymorphism is significantly associated with increased risk of severe influenza but not with the chance of initial virus infection.