Prevalence of adolescent idiopathic scoliosis in Shijiazhuang, Hebei, China: a cross-sectional study.

PURPOSE: This study is a large-scale screening supported by government departments to investigate the prevalence of scoliosis in Shijiazhuang. METHODS: In this cross-sectional study, all students underwent body posture evaluation and the Adam's forward flexure test to examine the back, and also underwent radiographic evaluation when scoliosis was suspected. RESULTS: In total, 181,935 students participated in the research, of which 289 students were diagnosed with scoliosis, with a prevalence of 2.5%, significantly higher in female (3.01%) than in male children (1.63%) (P < 0.001). Most of the patients (79.5%) had a Cobb angle from 10° to 19°.The mean Cobb angle of scoliosis was positively associated with age. The prevalence of a single curve (75.4%) was significantly higher than double curves (23.2%) and triple curves (1.38%). The percentage of scoliosis in which the thoracolumbar segment was involved (46.4%) was significantly higher than that of the single thoracic scoliosis (31.8%) and single lumbar scoliosis (21.8%). CONCLUSIONS: The prevalence of adolescent idiopathic scoliosis in XXX was high (2.50%). It is necessary to strengthen the education of adolescent scoliosis, and improve the awareness and attention of social to scoliosis. LEVEL OF EVIDENCE: IV.

Metagenomic analysis of gut microbiota modulatory effects of jujube (Ziziphus jujuba Mill.) polysaccharides in a colorectal cancer mouse model.

Accumulating evidence has reported that the gut microbiota could play important roles in the occurrence and progression of colorectal cancer. The nondigestible plant polysaccharides have always been fermented by the intestinal microbiota. Polysaccharides, the predominant functional composition found in jujube fruit, has been shown to inhibit carcinogenesis in animal models. However, the molecular mechanisms involved in polysaccharides preventing carcinogenesis are still uncharacterized. The aim of this study was to investigate the modulatory effects of jujube polysaccharides (JP) on intestinal microbiota, and the influence of JP on the gut flora structure was then analyzed using an AOM/DSS-induced colitis cancer mouse model, using high-throughput sequencing. Contrasted with control group, the addition of JP could ward off colon cancer by ameliorating colitis cancer-induced gut dysbiosis. In addition, there was a significant decrease in Firmicutes/Bacteroidetes post JP treatment. What's more, KEGG pathways of metabolic pathways, ATP-binding cassette (ABC) transporters and two-component system enriched the most differentially expressed genes after JP intervention for 13 weeks. These results suggested that JP showed prebiotic-like activities by positively modulating intestinal microbiota and affecting certain metabolic pathways contributing to host health. In conclusion, our results demonstrated an appreciable capability of JP to restore the gut microbiota profile altered by AOM/DSS, indicating the potential of jujube polysaccharides as promising prebiotic candidates for the prevention and treatment of colorectal cancer.

Efficient statistical tests to compare Youden index: accounting for contingency correlation.

Youden index is widely utilized in studies evaluating accuracy of diagnostic tests and performance of predictive, prognostic, or risk models. However, both one and two independent sample tests on Youden index have been derived ignoring the dependence (association) between sensitivity and specificity, resulting in potentially misleading findings. Besides, paired sample test on Youden index is currently unavailable. This article develops efficient statistical inference procedures for one sample, independent, and paired sample tests on Youden index by accounting for contingency correlation, namely associations between sensitivity and specificity and paired samples typically represented in contingency tables. For one and two independent sample tests, the variances are estimated by Delta method, and the statistical inference is based on the central limit theory, which are then verified by bootstrap estimates. For paired samples test, we show that the estimated covariance of the two sensitivities and specificities can be represented as a function of kappa statistic so the test can be readily carried out. We then show the remarkable accuracy of the estimated variance using a constrained optimization approach. Simulation is performed to evaluate the statistical properties of the derived tests. The proposed approaches yield more stable type I errors at the nominal level and substantially higher power (efficiency) than does the original Youden's approach. Therefore, the simple explicit large sample solution performs very well. Because we can readily implement the asymptotic and exact bootstrap computation with common software like R, the method is broadly applicable to the evaluation of diagnostic tests and model performance.