胎儿体重相关因素分析以及多元回归方程的建立

目的:寻找更为准确的预测胎儿体重的方法,并探讨腹围增加值在预测胎儿体重中的价值。方法:回顾性分析山东省烟台市芝罘区妇幼保健院2010年3月至12月期间出生的280例新生儿的临床资料,将孕妇身高、体重、孕期增重、宫高、足月腹围、孕期腹围增加值及胎儿的双顶径、股骨长等,与新生儿出生体重进行相关及回归分析,得出回归方程并检验其显著性和与实际出生体重的符合率,并与以往临床常用方法比较。结果:宫高、腹围增加值、双顶径和股骨长与胎儿体重显著相关,建立的多元回归方程计算胎儿体重预测值与实际胎儿体重符合率达70.71%,远高于其它方法。结论:采用宫高、腹围增加值、双顶径、股骨长建立的多元回归方程对胎儿体重预测符合率高,有较好的临床应用价值。     

基于GARP的加拿大一枝黄花在中国的分布区预测

加拿大一枝黄花（Solidago canadensis）原产北美,是在中国大陆危害最严重的入侵植物之一。本研究基于大量已有分布点数据,使用生态位模型（GARP）对其在中国的潜在扩散区域进行了预测,结果表明：极端低温、年均温对加拿大一枝黄花的分布限制较小,而坡度、坡向、年降雨量、雨日频率、汇流累积量、水流方向、极端高温和霜日频率对其分布影响显著。加拿大一枝黄花的潜在入侵区远大于目前的实际分布区,因此仍会继续在中国扩散;中国中南部和东北部是加拿大一枝黄花最易形成入侵的地区,应采取措施防止其入侵。     

Prediction of crop response by linearisation about control approximation

A new method for modelling genotype x environment interaction: APLAT. The yield predicted by a crop-simulation model is developed as a Taylor series in the neighbourhood of a parameter vector of a control genotype. With this local linearisation, these genotype parameters can be estimated by a linear regression of the observed yield on the derivatives of the crop-simulation model predictions with respect to its parameters.     

MicroRNA在胃癌中的作用及研究进展

MicroRNA(miRNA)是一类含有18-25个核苷酸的小分子非编码RNA,通过与与其靶基因mRNA 3’-非编码区的碱基互补配对,降解靶基因mRNA导致转录后沉默或者抑制靶基因mRNA的翻译过程,影响细胞的增殖、分化、衰老和凋亡.研究显示部分microRNA在胃癌组织中确实存在表达异常,且异常表达的microRNA通过对其靶基因表达的调控影响胃癌的发生、发展及转移等过程.外周血中microRNA检测技术的发展使得microRNA应用于胃癌的临床诊疗具有了一定的可行性.众多研究提示microRNA在胃癌的演进中的作用可能作为胃癌早期诊断和疗效预测的生物标记物,本文就microRNA在胃癌中的作用及研究进展作一综述.     

Phosphorylated-Akt overexpression is associated with a higher risk of brain metastasis in patients with non-small cell lung cancer

Brain metastasis (BM) of non-small cell lung cancer (NSCLC) is relatively common and has a poor prognosis. Moreover, identifying which patients are more likely to develop BM is challenging. Akt, a serine/threonine-specific protein kinase, can be activated in various tumors, including lung cancer, and may be associated with poor prognosis. Here, we used immunohistochemistry to evaluate phosphorylated-Akt (p-Akt) expression in tumor tissues of 99 NSCLC patients. We also analyzed the genotype of the patients for two single nucleotide polymorphisms (SNPs) of the AKT1 gene, rs2498804 and rs2494732. We found that p-Akt expression differs between NSCLC patients and correlates with the risk of BM. Indeed, patients exhibiting medium to high p-Akt expression had a higher incidence of BM than those exhibiting low to no p-Akt expression (39% vs 16%). Our data also show that patients with the rs2498804 GT/GG and rs2494732 CT/TT variant genotypes were more likely to exhibit higher levels of p-Akt expression than those with the rs2498804 TT and rs2494732 CC variant genotypes (35% vs. 24% and 37% vs. 25%, respectively). Our results suggest that the level of expression of p-Akt, which may be affected by the AKT1 genotype, is correlated with the risk of BM. However, further studies are needed to establish p-Akt as a predictive marker for BM in NSCLC patients.     

Use of mutual information arrays to predict coevolving sites in the full length HIV gp120 protein for subtypes B and C

It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protein structure, structure function analysis or sequence alignment. Mutual Information is a standard measure for coevolution between two sites but its application is limited by signal to noise ratio. In this work we report a preliminary study to investigate whether larger sequence sets could circumvent this problem by calculating mutual information arrays for two sets of drug naïve sequences from the HIV gp120 protein for the B and C subtypes. Our results suggest that while the larger sequences sets can improve the signal to noise ratio, the gain is offset by the high mutation rate of the HIV virus which makes it more difficult to achieve consistent alignments. Nevertheless, we were able to predict a number of coevolving sites that were supported by previous experimental studies as well as a region close to the C terminal of the protein that was highly variable in the C subtype but highly conserved in the B subtype.