恶性疟原虫抗药性测定方法及其影响因素

本文就疟原虫抗药性测定方法近几年的研究进展及其在测定中的影响因素加以综述。对抗药性测定方法,如传统的微量测试法和同位素测定法,以及近几年发展起来的利用HRP Ⅱ和LDH酶联免疫法、利用SYBR Green I等标记的荧光法和流式细胞仪法进行了介绍。文内还分析了血清、红细胞压积和原虫起始密度、原虫时期和状态等因素对测定值的影响。

Leaf temperature of soybean grown under elevated CO2 increases Aphis glycines （Hemiptera＂ Aphididae） population growth

Plants grown under elevated carbon dioxide （CO2） experience physiological changes that influence their suitability as food for insects. To determine the effects of living on soybean （Glycine max Linnaeus） grown under elevated CO2, population growth of the soybean aphid （Aphis glycines Matsumura） was determined at the SoyFACE research site at the University of Illinois, Urbana-Champaign, Illinois, USA, grown under elevated （550μL/L） and ambient （370 μL/L） levels of CO2. Growth of aphid populations under elevated CO2 was significantly greater after 1 week, with populations attaining twice the size of those on plants grown under ambient levels of CO2. Soybean leaves grown under elevated levels of CO2 were previously demonstrated at SoyFACE to have increased leaf temperature caused by reduced stomatal conductance. To separate the increased leaf temperature from other effects of elevated CO2, air temperature was lowered while the CO2 level was increased, which lowered overall leaf temperatures to those measured for leaves grown under ambient levels of CO2. Aphid population growth on plants grown under elevated CO2 and reduced air temperature was not significantly greater than on plants grown under ambient levels of CO2. By increasing Glycine max leaf temperature, elevated CO2 may increase populations of Aphis glycines and their impact on crop productivity.

Identification of MicroRNA Precursors with Support Vector Machine and String Kernel

MicroRNAs （miRNAs） are one family of short （21-23 nt） regulatory non-coding RNAs processed from long （70-110 nt） miRNA precursors （pre-miRNAs）. Identifying true and false precursors plays an important role in computational identification of miRNAs. Some numerical features have been extracted from precursor sequences and their secondary structures to suit some classification methods; however, they may lose some usefully discriminative information hidden in sequences and structures. In this study, pre-miRNA sequences and their secondary structures are directly used to construct an exponential kernel based on weighted Levenshtein distance between two sequences. This string kernel is then combined with support vector machine （SVM） for detecting true and false pre-miRNAs. Based on 331 training samples of true and false human pre-miRNAs, 2 key parameters in SVM are selected by 5-fold cross validation and grid search, and 5 realizations with different 5-fold partitions are executed. Among 16 independent test sets from 3 human, 8 animal, 2 plant, 1 virus, and 2 artificially false human pre-miRNAs, our method statistically outperforms the previous SVM-based technique on 11 sets, including 3 human, 7 animal, and 1 false human pre-miRNAs. In particular, premiRNAs with multiple loops that were usually excluded in the previous work are correctly identified in this study with an accuracy of 92.66%.

中国古眼蝶的鉴别(鳞翅目,蛱蝶科)(英文)

Identity of the Chinese satyrine butterfly Palaeonympha avinoffi Schaus, 1927 has been uncertain since its description. The holotype is illustrated, and reasons are presented for considering it to represent the same species as Sinonympha amoena Lee, 1974, new synonym. Sinonympha avinoffi is a new combination. The systematic placement of Sinonympha is yet uncertain.