Application of the phosphomannose-isomerase/mannose selection system in the Agrobacterium-mediated transformation of Lonicera hypoglauca Miq.

Journal of Plant Biochemistry and Biotechnology - The dried buds of Lonicera hypoglauca Miq. have antipyretic, antidotal and anti-inflammatory properties and as Flos lonicerae are widely used in...     

异质性荧光染色的巨噬细胞功能研究I．异质性荧光染色的巨噬细胞吞噬活性

利用淀粉多糖和免疫促进剂（白喉类毒素和卡介苗）诱导和活化小鼠腹腔巨噬细胞,观察了四种异质性荧光染色的巨噬细胞非特异性和特异性吞噬活性。实验证明,深蓝色和淡蓝色荧光的巨噬细胞是分化程度低的幼稚细胞,非特异性吞噬功能较弱,但在特异性吞噬过程中呈现了活跃的吞噬活性,特别是在免疫促进剂的活化下,它们的特异性吞噬功能显著增强、淡蓝绿色荧光的巨噬细胞是分化程度较高、非特异性和特异性吞噬功能最旺盛的巨噬细胞,而黄色荧光的巨噬细胞是分化程度最高、特异性吞噬功能较减退的巨噬细胞。     

Lifespan of long‐lived growth hormone receptor knockout mice was not normalized by housing at 30°C since weaning

Growth hormone receptor knockout (GHRKO) mice are remarkably long‐lived and have improved glucose homeostasis along with altered energy metabolism which manifests through decreased respiratory quotient (RQ) and increased oxygen consumption (VO₂). Short‐term exposure of these animals to increased environmental temperature (eT) at 30°C can normalize their VO₂ and RQ. We hypothesized that increased heat loss in the diminutive GHRKO mice housed at 23°C and the consequent metabolic adjustments to meet the increased energy demand for thermogenesis may promote extension of longevity, and preventing these adjustments by chronic exposure to increased eT will reduce or eliminate their longevity advantage. To test these hypotheses, GHRKO mice were housed at increased eT (30°C) since weaning. Here, we report that contrasting with the effects of short‐term exposure of adult GHRKO mice to 30°C, transferring juvenile GHRKO mice to chronic housing at 30°C did not normalize the examined parameters of energy metabolism and glucose homeostasis. Moreover, despite decreased expression levels of thermogenic genes in brown adipose tissue (BAT) and elevated core body temperature, the lifespan of male GHRKO mice was not reduced, while the lifespan of female GHRKO mice was increased, along with improved glucose homeostasis. The results indicate that GHRKO mice have intrinsic features that help maintain their delayed, healthy aging, and extended longevity at both 23°C and 30°C.     

Detecting Protein Candidate Fragments Using a Structural Alphabet Profile Comparison Approach

Predicting accurate fragments from sequence has recently become a critical step for protein structure modeling, as protein fragment assembly techniques are presently among the most efficient approaches for de novo prediction. A key step in these approaches is, given the sequence of a protein to model, the identification of relevant fragments - candidate fragments - from a collection of the available 3D structures. These fragments can then be assembled to produce a model of the complete structure of the protein of interest. The search for candidate fragments is classically achieved by considering local sequence similarity using profile comparison, or threading approaches. In the present study, we introduce a new profile comparison approach that, instead of using amino acid profiles, is based on the use of predicted structural alphabet profiles, where structural alphabet profiles contain information related to the 3D local shapes associated with the sequences. We show that structural alphabet profile-profile comparison can be used efficiently to retrieve accurate structural fragments, and we introduce a fully new protocol for the detection of candidate fragments. It identifies fragments specific of each position of the sequence and of size varying between 6 and 27 amino-acids. We find it outperforms present state of the art approaches in terms (i) of the accuracy of the fragments identified, (ii) the rate of true positives identified, while having a high coverage score. We illustrate the relevance of the approach on complete target sets of the two previous Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 9 and 10. A web server for the approach is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/SAFrag.     

Factors influencing wild boar damage in Taohongling National Nature Reserve in China: a model approach

Conflicts between humans and wildlife, especially wild boar (Sus scrofa), have caused serious problems across the world in recent years. It is necessary to effectively control wild boar agricultural damage that may be influenced by many factors. In this study, we collected data on agricultural damage caused by wild boars from November 2009 to October 2010 using field surveys and social interviews in Taohongling National Nature Reserve of Jiangxi Province, China. We constructed models using binary logistic regression analysis to predict damage risks and to identify the factors influencing damage risks. About 8.1 % of croplands were damaged by wild boars, and the damage to rice, cotton, and other crops were not distributed based on their respective availability as shown by the result of a chi-square goodness-of-fit test. Five factors (Japanese silvergrass, soil conditions, terrain, distances to settlements, and water sources) were explained in a model based on damage area (area-based model) with the prediction accuracy being 72.1 %. In addition to these five factors, one additional factor (i.e. distance to forest edge) was retained in a model based on damage frequency (frequency-based model) with the prediction accuracy being 83.1 %. Caution is needed when we apply these two models to predict boar damage to crops, and it is recommended that both models be used in combination to predict the damage probabilities more accurately.