锁定加压钢板和动力加压钢板治疗肱骨中下段骨折的临床比较研究

目的:对比锁定加压钢板与动力加压钢板治疗肱骨中下段骨折患者的临床疗效。方法:抽取我院2010年8月~2013年12月收治的肱骨中下段骨折患者76例,按照随机数字表法分为锁定组(锁定加压钢板治疗)与动力组(动力加压钢板治疗),每组38例,随访1年。对比两组患者临床指标,治疗效果及并发症发生率。结果:锁定组患者手术时间、骨折愈合时间及住院时间均小于动力组,差异均有统计学意义(P0.05);锁定组患者优良率为89.47%,显著高于动力组的71.05%,差异有统计学意义(P0.05);锁定组的并发症发生率为10.53%,显著低于动力组的31.58%,差异有统计学意义(P0.05)。结论:锁定加压钢板应用于治疗肱骨中下段骨折患者疗效优于动力加压钢板治疗,它具有创伤小、恢复快的优点,且并发症发生率较低,值得推广。     

Mathematical modeling of cell growth in a 3D scaffold and validation of static and dynamic cultures

Tissue engineering, an immensely important field in contemporary clinical practices, aims at the repair or replacement of damaged tissues. The mathematical model proposed herein shows the distribution and growth of cells in their characteristic time in a 3D scaffold model. This study contributes to the progress of simulation techniques in static and dynamic cultures of bone tissue. Brinkman, nutrient transport, and cell growth equations are brought together to quantify the growth behavior of cells. However, when a static culture is being studied, the Brinkman equation is eliminated. The model was validated by experimental cell culture using 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay and scanning electron microscopy. Then, static and dynamic cultures were compared to assess the cell density and cell distribution in the scaffold. Cell counting after 21 days of cell culture showed that the number of cells increased 42‐fold in static and 53.5‐fold in dynamic cultures, which was in good agreement with our model estimations (37‐fold increase in the number of cells in static and 49‐fold increase in dynamic cultures). In conclusion, our mathematical model could predict cell distribution and growth in the scaffold.     

EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon–Mann–Whitney Test

In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney(WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program,the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease(COPD). We foundthat approximated P values were generally higher than the exact solution provided by EDISONWMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.     

Applying the Water Footprint and dynamic Structural Decomposition Analysis on the growing water use in China during 1997–2007

China has experienced rapid economic development during the recent years. In the meantime, the total water use in China has greatly increased, causing considerably severe water shortage. To quantify how the social-economic development drives the change of water use is of great importance for Chinese government. This study aims to quantitatively investigate the determinants of the growing water use in China during 1997–2007. China's water usages in 1997–2007 are indicated by the Internal Water Footprint (IWF), External Water Footprint (EWF), and Exported Virtual Water (ExVW) using an input–output based WF analysis. A dynamic Structural Decomposition Analysis (SDA) model is employed to decompose the changes in the total WFs (TWF) into five social-economic determinants. The dynamic SDA model, which uses a nonlinear path function to simulate the real paths followed by determinants, is a further development of a path-based SDA algorithm. To validate the dynamic SDA, a comparison study is carried out against the commonly used mean decomposition model. The results from the WF analysis show that, during 1997–2007, the increase of China's water use is dominated by the ExVW, which increases significantly due to the expansion of exports. While the changes in the IWF and EWF tend to help mitigating the water pressure. The dynamic decomposition results indicate that the consumption level is the dominant factor of China's water use growth, and the changes in water-saving technology and final demand pattern contribute largely to offsetting the water use growth. The model comparison shows that the dynamic SDA model is more advanced in obtaining reliable results and addressing the static issue of traditional SDA models. This study provides a robust framework for understanding the water use situation from the social-economic perspectives, which benefits sustainable water management.     

Investigating the environmental Kuznets curve hypothesis in seven regions: The role of renewable energy

The aim of this research is to investigate how renewable energy consumption effects pollution and whether the relationship between income and pollution formulates the inverted U-shaped relationship which signals the existence of the environmental Kuznets curve (EKC). To realize the aims of this study, non-stationary panel data techniques were utilized to examine the seven selected regions. According to Pedroni and Fisher type cointegration tests, the variables were cointegrated. Moreover, the dynamic ordinary least square (DOLS) and the vector error correction model Granger causality revealed that renewable energy consumption has a significant negative effect on pollution in Central and Eastern Europe, Western Europe, East Asia and the Pacific, South Asia, and the Americas. However, the tests revealed that renewable energy consumption has no significant effect on pollution in the Middle East and North Africa and Sub-Saharan Africa. In addition, the results in general indicated that the existence of the EKC hypothesis is determined by the significance of the renewable energy consumption. Therefore, the EKC hypothesis was only found in the regions where their renewable energy has a significant correlation with pollution in both the short run and the long run. Furthermore, a number of policy recommendations were provided for the investigated regions.     

Probing the geometric constraints of RNA binding via dynamic covalent chemistry

Dynamic Combinatorial Chemistry (DCC) has proven to be a reliable method for identifying hit compounds for target nucleic acid (DNA and RNA) sequences. Typically, these hit compounds are subjected to a lengthy process of optimization via traditional medicinal chemistry. Here, we examine the potential of DCC to also generate and test variations on a hit compound as a method for probing the binding site of an RNA-targeted compound. Specifically, we demonstrate that addition of linker dithiols to a disulfide library containing a known binder to the HIV-1 frameshift-stimulatory RNA (a critical regulator of the HIV life cycle) can yield a mixture of new bridged structures incorporating the dithiol, depending on dithiol structure. Equilibration of this library with the HIV FSS RNA resulted in selection of the original disulfide in preference to bridged structures, suggesting incorporation of the bridge is not compatible with this particular binding site. Application of this strategy to other RNA targets should allow for rapidly profiling the affinity of modified compounds.