杀虫剂轮用和混用对害虫种群抗性演化的影响

杀虫剂轮用和混用是当前害虫抗药性治理中最常采用的两种用药策略。该文用抗性模型和室内试验对轮用和混用延缓害虫抗性演化的效果及轮用最佳间隔期问题作了研究。模型模拟结果表明,在延缓害虫抗性演化方面轮用和混用对抗性演化的影响主要取决于杀虫剂作用强度、抗性基因型个体的适合度大小和杀虫剂混用后的毒理效应类型。两种杀虫剂轮用时,轮用间隔期以1(即两种杀虫剂隔次施用)为佳。以模型昆虫小菜蛾Plutella xylostella在室内试验结果表明,氰戊菊酯单用(I)及与杀虫单轮用(II)和混用(1∶1)(III)连续处理8代后,抗性个体频率为0.01的小菜蛾种群其3龄幼虫对氰戊菊酯的抗性分别上升了75.87(I)、28.67(II)和58.72(III)倍,与模型模拟结果表现出较好的一致性。据此,作者认为抗性模型可用于预测害虫抗性演化和评价抗性治理策略。     

Individual Learning Ability and Complex Odor Recognition in the Honey Bee, Apis mellifera L.

Individually restrained worker bees were trained to recognize complex odors in a conditioned proboscis extension assay. Three groups of bees were considered, based on the responses recorded during the experimental procedure: selective learners, nonselective learners, and nonlearners. For conditioning, three concentrations of two synthetic mixtures were used. The distribution of bees between groups was not significantly affected by the nature or by the concentration of the conditioning mixture. After conditioning, bees were tested with the individual compounds, and the responses were analyzed with respect to the three groups. Selective learners showed discriminative responses to a few key compounds, while nonselective learners responded to all the compounds, and nonlearners to none. These results showed that complex odor recognition is based on the recognition of key components and relies on the ability of bees to learn.     

Identifying mismatches between conservation area networks and vulnerable populations using spatial randomization

Grassland birds are among the most globally threatened bird groups due to substantial degradation of native grassland habitats. However, the current network of grassland conservation areas may not be adequate for halting population declines and biodiversity loss. Here, we evaluate a network of grassland conservation areas within Wisconsin, U.S.A., that includes both large Focal Landscapes and smaller targeted conservation areas (e.g., Grassland Bird Conservation Areas, GBCAs) established within them. To date, this conservation network has lacked baseline information to assess whether the current placement of these conservation areas aligns with population hot spots of grassland‐dependent taxa. To do so, we fitted data from thousands of avian point‐count surveys collected by citizen scientists as part of Wisconsin''s Breeding Bird Atlas II with multinomial N‐mixture models to estimate habitat–abundance relationships, develop spatially explicit predictions of abundance, and establish ecological baselines within priority conservation areas for a suite of obligate grassland songbirds. Next, we developed spatial randomization tests to evaluate the placement of this conservation network relative to randomly placed conservation networks. Overall, less than 20% of species statewide populations were found within the current grassland conservation network. Spatial tests demonstrated a high representation of this bird assemblage within the entire conservation network, but with a bias toward birds associated with moderately tallgrasses relative to those associated with shortgrasses or tallgrasses. We also found that GBCAs had higher representation at Focal Landscape rather than statewide scales. Here, we demonstrated how combining citizen science data with hierarchical modeling is a powerful tool for estimating ecological baselines and conducting large‐scale evaluations of an existing conservation network for multiple grassland birds. Our flexible spatial randomization approach offers the potential to be applied to other protected area networks and serves as a complementary tool for conservation planning efforts globally.     

Hierarchical Bayesian Estimation for the Number of Species

This paper is concerned with the estimation of the number of species in a population through a fully hierarchical Bayesian model using the Metropolis algorithm. The proposed Bayesian estimator is based on Poisson random variables with means that are distributed according to some prior distributions with unknown hyperparameters. An empirical Bayes approach is considered and compared with the fully Bayesian approach based on biological data.     

Anti-aging and antioxidant of four traditional malaysian plants using simplex centroid mixture design approach

Aging is a naturally biological process with adverse effects. The continuous accumulation of reactive oxygen species (ROS) trigger cellular and tissue damage by activating several aging enzymes. The antioxidant properties of traditional medicinal plants used by Jakun aborigine’s community are a promising approach to alleviate aging process and prevent Alzheimer. The aim of the current investigation was to optimize a novel anti-aging formulation from traditional plants (Cnestis palala stem, Urceola micrantha stem, Marantodes pumilum stem and Microporus xanthopus fruiting bodies) using simplex centroid mixture design (SCMD). After selecting the optimal formulations based on desirability function of antioxidant activity (DPPḢ, ABTS^̇+ and FRAP), they were further examined against the activity of aging-related-enzymes (collagenase, tyrosinase, acetyl- and butyrylcholinesterase). The single extracts of C. palala, U. micrantha and the binary mixture of C. palala and U. micrantha were the optimal formulations with high antioxidant activities. Single extract of U. micrantha showed the highest inhibition towards matrix metalloproteinase-1 (49.44 ± 4.11 %), while C. palala water extract showed highest inhibitions towards tyrosinase (14.06 ± 0.31%), acetylcholinesterase (32.92 ± 2.13%) and butyrylcholinesterase (34.89 ± 2.84%) enzymes. The single extracts of C. palala and U. micrantha displayed better activity as compared to the binary mixture formulation. In conclusion, these findings could be a baseline for further exploration of novel anti-aging agents from natural resources.     

Improvement in lipase-catalyzed methanolysis of triacylglycerols for biodiesel production using a solvent engineering method

A solvent engineering strategy was applied to the lipase-catalyzed methanolysis of triacylglycerols for biodiesel production. The effect of different pure organic solvents and co-solvent mixtures on the methanolysis was compared. The substrate conversions in the co-solvent mixtures were all higher than those of the corresponding pure organic solvents. Further study showed that addition of co-solvent decreased the values of |log P_interface − log P_substrate| and thus led to a faster reaction. The more the values of |log P_interface − log P_substrate| decreased, the faster the reaction proceeded and the higher the conversion attained. Different co-solvent ratio was further investigated. The co-solvent mixture of 25% t-pentanol:75% isooctane (v/v) was optimal, with which both the negative effects caused by excessive methanol and by-product glycerol could be eliminated. There was no obvious loss in lipase activity even after being repeatedly used for 60 cycles (720 h) with this co-solvent mixture as reaction medium. Other lipases and lipase combinations can also catalyze methanolysis in this co-solvent mixture. Furthermore, other vegetable oils were also explored for biodiesel production in this co-solvent mixture and it had been found that this co-solvent mixture media has extensive applicability.     

A chip‐based amide‐HILIC LC/MS platform for glycosaminoglycan glycomics profiling

A key challenge to investigations into the functional roles of glycosaminoglycans (GAGs) in biological systems is the difficulty in achieving sensitive, stable, and reproducible mass spectrometric analysis. GAGs are linear carbohydrates with domains that vary in the extent of sulfation, acetylation, and uronic acid epimerization. It is of particular importance to determine spatial and temporal variations of GAG domain structures in biological tissues. In order to analyze GAGs from tissue, it is useful to couple MS with an on‐line separation system. The purposes of the separation system are both to remove components that inhibit GAG ionization and to enable the analysis of very complex mixtures. This contribution presents amide–silica hydrophilic interaction chromatography (HILIC) in a chip‐based format for LC/MS of heparin, heparan sulfate (HS) GAGs. The chip interface yields robust performance in the negative ion mode that is essential for GAGs and other acidic glycan classes while the built‐in trapping cartridge reduces background from the biological tissue matrix. The HILIC chromatographic separation is based on a combination of the glycan chain lengths and the numbers of hydrophobic acetate (Ac) groups and acidic sulfate groups. In summary, chip based amide‐HILIC LC/MS is an enabling technology for GAG glycomics profiling.     

Dimethoate,fenvalerate and their mixture affects Hylyphantes graminicola (Araneae: Linyphiidae) adults and their unexposed offspring

• 1 Mixtures of organophosphorus and pyrethroid insecticides are widely used to combat resistance in agricultural pests, although few studies have been conducted on the effects of pesticide mixtures on beneficial nontarget organisms.
• 2 In the present study, we exposed adult females (F₀) of Hylyphantes graminicola (Araneae: Linyphiidae) to fenvalerate, dimethoate and their commercially available 1 : 1 mixture (by mass). We investigated the acute toxicity of these pesticides to the exposed adults, as well as sublethal effects on reproduction and acetylcholinesterase and carboxylesterase activity. We also studied the effects of parental exposure on the size, development and enzyme activity of unexposed offspring.
• 3 All three formulations were acutely toxic to H. graminicola, with synergism between dimethoate and fenvalerate leading to greater toxicity in the 1 : 1 mixture than for the two insecticides alone. The sublethal effects of direct pesticide exposure were a reduction in acetylcholinesterase and carboxylesterase activity and a reduction in the number of egg sacs produced by exposed spiders relative to the control spiders. The unexposed offspring of the fenvalerate and mixture exposed spiders were smaller and took longer to mature than the control spiders. Offspring of all exposed spiders also had significantly reduced carboxylesterase activity relative to control spiders.
• 4 We concluded that the effects of parental exposure on the offspring were likely to increase their susceptibility to future pesticide exposures, and reduce the capacity of this spider to serve as a pest control agent.

     

Estimating effect sizes of differentially expressed genes for power and sample-size assessments in microarray experiments

Summary In microarray screening for differentially expressed genes using multiple testing, assessment of power or sample size is of particular importance to ensure that few relevant genes are removed from further consideration prematurely. In this assessment, adequate estimation of the effect sizes of differentially expressed genes is crucial because of its substantial impact on power and sample‐size estimates. However, conventional methods using top genes with largest observed effect sizes would be subject to overestimation due to random variation. In this article, we propose a simple estimation method based on hierarchical mixture models with a nonparametric prior distribution to accommodate random variation and possible large diversity of effect sizes across differential genes, separated from nuisance, nondifferential genes. Based on empirical Bayes estimates of effect sizes, the power and false discovery rate (FDR) can be estimated to monitor them simultaneously in gene screening. We also propose a power index that concerns selection of top genes with largest effect sizes, called partial power. This new power index could provide a practical compromise for the difficulty in achieving high levels of usual overall power as confronted in many microarray experiments. Applications to two real datasets from cancer clinical studies are provided.