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.     

Bio-Acidification and Leaching of Metals,Nitrogen, and Phosphorus from Soil and Sludge Mixtures

Soil and wastewater treatment sludge are commonly brought together in mixtures for a variety of beneficial purposes. The mixtures contain bioacidifying (i.e., sulfur-oxidizing) microorganisms that can easily be activated through providing the appropriate substrate and environmental conditions. In this study, contaminated soil and sludge mixtures were subjected to controlled bio-acidification and the impacts of the process on the partitioning of heavy metals, nitrogen, and phosphorus were examined. Three successive bio-acidification cycles resulted in significant leaching of metals from sludge. The leaching results, expressed as fraction of total mass of metals in the sludge, averaged 67% for Cr, 96% for Ni, 24% for Zn; 16% for Cu; 23% for Cd; and 96% for Pb. Bio-acidification of the sludge also converted 28 to 45% of the organic nitrogen into ammonia and increased the soluble orthophosphates fraction of total phosphorus by approximately 18 to 20%. Bio-acidification also resulted in significant metals leaching from the contaminated soils in the soil/sludge mixtures. Soil/sludge mixtures were prepared using six soil particle sizes (less than 0.075?mm to 2.38?mm) contaminated with 22,500?mg/kg Zn, 14,000?mg/kg Pb, 1500?mg/kg Cr, 9500?mg/kg Cu, 1000?mg/kg Ni, and 1000?mg/kg Cd. The addition of metals to the soil inhibited the sulfur-oxidizing microorganisms, preventing bio-acidification in the mixtures containing 4 to 50?g soil in 130?ml sludge, and considerably slowing bio-acidification in the mixtures containing 1 to 3?g soil. Using a mixture that contained 2-g soil samples, three successive bio-acidification cycles resulted in significant cumulative metals leaching results. The leaching results, expressed as percentage of the mass of metals added to the soil, were in the range of 56 to 98% for Cr, 77 to 95% for Zn, 33 to 66% for Ni, 64 to 82% for Cu, and 10 to 33% for Pb, with the higher results in each range belonging to the larger size soil particles. On the other hand, only Cr was leached in neutralized soil samples. The results confirmed the potential for inhibition of the sulfur-oxidizing microorganisms and bio-acidification in contaminated soil/sludge mixtures, and the significant impacts of bio-acidification on the mobility of metals, nitrogen, and phosphorus. In addition, the results confirmed the potential for using controlled bioacidification for removing heavy metals from contaminated soil using the indigenous sulfur oxidizing microorganisms in sludge.     

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.     

Quercetin/β-Cyclodextrin Solid Complexes Prepared in Aqueous Solution Followed by Spray-drying or by Physical Mixture

The present study was designed to investigate the influence of operating conditions (temperature, stirring time, and excess amount of quercetin) on the complexation of quercetin with β-cyclodextrin using a 2³ factorial design. The highest aqueous solubility of quercetin was reached under the conditions 37°C/24 h/6 mM of quercetin. The stoichiometric ratio (1:1) and the apparent stability constant (Ks = 230 M⁻¹) of the quercetin/β-cyclodextrin complex were determined using phase-solubility diagrams. The semi-industrial production of a 1:1 quercetin/β-cyclodextrin solid complex was carried out in aqueous solution followed by spray-drying. Although the yield of the spray-drying process was adequate (77%), the solid complex presented low concentration of quercetin (0.14%, w/w) and, thus, low complexation efficiency. The enhancement of aqueous solubility of quercetin using this method was limited to 4.6-fold in the presence of 15 mM of β-cyclodextrin. Subsequently, an inclusion complex was prepared via physical mixture of quercetin with β-cyclodextrin (molar ratio of 1:1 and quercetin concentration of 23% (w/w)) and characterized using infrared spectroscopy, differential scanning calorimetry, nuclear magnetic resonance spectroscopy, and scanning electron microscopy analyses. The enhancement of aqueous solubility of quercetin using this method was 2.2-fold, similar to that found in the complex prepared in aqueous solution before the spray-drying process (2.5-fold at a molar ratio of 1:1, i.e., 6 mM of quercetin and 6 mM of β-cyclodextrin).     

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.

     

低剂量混合污染生态毒理与风险评价研究进展

环境中的化学品往往以低剂量混合形式存在.对单一化学品高剂量暴露下的生态毒性研究成果,难以适用于环境中低剂量混合物的生态毒理效应诊断及风险评价.文中概述了低剂量化学品混合污染生态毒理及风险评价方面的研究进展,主要包括低剂量化学品混合污染诊断的分子毒理研究方法、风险评价方法,并介绍了简单和复杂混合物的风险评价方案.对低剂量混合污染生态毒理与风险评价研究的发展动向提出了见解,指出低剂量化学混合物的研究需要寻找敏感终点,引入多学科手段,积累更多的数据,建立完善、统一的评价体系.     

基于MFCC和GMM的昆虫声音自动识别

昆虫的运动、 取食、 鸣叫都会发出声音, 这些声音存在种内相似性和种间差异性, 因此可用来识别昆虫的种类。基于昆虫声音的昆虫种类自动检测技术对协助农业和林业从业人员方便地识别昆虫种类非常有意义。本研究采用了语音识别领域里的声音参数化技术来实现昆虫的声音自动鉴别。声音样本经预处理后, 提取梅尔倒谱系数（Mel frequency cepstrum coefficient, MFCC）作为特征, 并用这些样本提取的MFCC特征集训练混合高斯模型（Gaussian mixture model, GMM）。最后用训练所得到的GMM对未知类别的昆虫声音样本进行分类。该方法在包含58种昆虫声音的样本库中进行了评估, 取得了较高的识别正确率（平均精度为98.95%）和较理想的时间性能。该测试结果证明了基于MFCC和GMM的语音参数化技术可以用来有效地识别昆虫种类。     

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.     

Bayesian variable selection for latent class models

In this article, we develop a latent class model with class probabilities that depend on subject-specific covariates. One of our major goals is to identify important predictors of latent classes. We consider methodology that allows estimation of latent classes while allowing for variable selection uncertainty. We propose a Bayesian variable selection approach and implement a stochastic search Gibbs sampler for posterior computation to obtain model-averaged estimates of quantities of interest such as marginal inclusion probabilities of predictors. Our methods are illustrated through simulation studies and application to data on weight gain during pregnancy, where it is of interest to identify important predictors of latent weight gain classes.