A robust two-gene signature for glioblastoma survival prediction

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan-Meier analysis, t-distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two-gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2-RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64-0.98, vs median: 0.98, 95% CI: 0.65-1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70-1.18, vs median: 1.21, 95% CI: 0.95-2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86-1.24, vs median: 1.23, 95% CI: 1.04-1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two-gene signature was a robust prognostic model to predict GBM survival.     

尿激酶胸腔注入治疗结核包囊性胸腔积液

目的寻求治疗结核包囊性胸腔积液的新方法。方法胸膜活检确诊为结核性胸腔积液并经Ｂ超或胸部Ｘ线证实有粘连包囊的病人１５例,经胸腔内注入尿激酶每次１０万单位,用６０ｍｌ生理盐水稀释,每８～１２ｈ重复,连续５次,每次记录抽取胸水总量,并复查Ｂ超观察粘连包囊情况。对照组为单纯用抗结核治疗及间断抽胸水１５例。结果实验组１３例有效,总有效率８６．７％。对照组２例有效,有效率１３．３％,疗效明显优于对照组（Ｐ＜０．０５）。结论尿激酶胸腔内注入是治疗结核性粘连包囊性胸腔积液的一种安全可靠的新方法。     

A family-based approach to preventing excessive weight gain

Objective: Preventing weight gain in adults and excessive weight gain in children is a high priority. We evaluated the ability of a family‐based program aimed at increasing steps and cereal consumption (for breakfast and snacks) to reduce weight gain in children and adults. Research Methods and Procedures: Families (n = 105) with at least one 8‐ to 12‐year‐old child who was at‐risk‐for‐overweight or overweight (designated as the target child) were recruited for the study. Eighty‐two families were randomly assigned to receive the family‐based intervention and 23 families to the control condition. The 13‐week intervention consisted of specific increases in daily steps (an additional 2000 steps/d) and consumption of 2 servings/d of ready‐to‐eat cereal. Results: The intervention was successful in increasing walking (steps) and cereal consumption. The intervention had positive, significant effects on percentage BMI‐for‐age and percentage body fat for target children and weight, BMI, and percentage body fat for parents. On further analysis, the positive effects of the intervention were seen largely in target girls and moms, rather than in target boys and dads. Discussion: This family‐based weight gain prevention program based on small changes holds promise for reducing excessive weight gain in families and especially in growing overweight children.     

Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data

MOTIVATION: Because co-expressed genes are likely to share the same biological function, cluster analysis of gene expression profiles has been applied for gene function discovery. Most existing clustering methods ignore known gene functions in the process of clustering. RESULTS: To take advantage of accumulating gene functional annotations, we propose incorporating known gene functions into a new distance metric, which shrinks a gene expression-based distance towards 0 if and only if the two genes share a common gene function. A two-step procedure is used. First, the shrinkage distance metric is used in any distance-based clustering method, e.g. K-medoids or hierarchical clustering, to cluster the genes with known functions. Second, while keeping the clustering results from the first step for the genes with known functions, the expression-based distance metric is used to cluster the remaining genes of unknown function, assigning each of them to either one of the clusters obtained in the first step or some new clusters. A simulation study and an application to gene function prediction for the yeast demonstrate the advantage of our proposal over the standard method.     

脱氧核酶的研究进展

具有RNA裂解活性的DNA分子称为脱氧核酶。它是经过体外选择技术经多次筛选获得的。脱氧核酶在切割与其互补的RNA底物分子时具有极高的特异性和切割效率,有望成为新的RNA灭活工具。