Mechanisms of a Cyclobutane-Fused Lactone Hydrolysis in Alkaline and Acidic Conditions

Searching for functional polyesters with stability and degradability is important due to their potential applications in biomedical supplies, biomass fuel, and environmental protection. Recently, a cyclobutane-fused lactone (CBL) polymer was experimentally found to have superior stability and controllable degradability through hydrolysis reactions after activation by mechanical force. In order to provide a theoretical basis for developing new functional degradable polyesters, in this work, we performed a detailed quantum chemical study of the alkaline and acidic hydrolysis of CBL using dispersion-corrected density functional theory (DFT-D3) and mixed implicit/explicit solvent models. Various possible hydrolysis mechanisms were found: B_AC2 and B_AL2 in the alkaline condition and A_AC2, A_AL2, and A_AL1 in the acidic condition. Our calculations indicated that CBL favors the B_AC2 and A_AC2 mechanisms in alkaline and acidic conditions, respectively. In addition, we found that incorporating explicit water solvent molecules is highly necessary because of their strong hydrogen-bonding with reactant/intermediate/product molecules.     

Prediction of an outcome using NETwork Clusters (NET-C)

Birth weight is a key consequence of environmental exposures and metabolic alterations and can influence lifelong health. While a number of methods have been used to examine associations of trace element (including essential nutrients and toxic metals) concentrations or metabolite concentrations with a health outcome, birth weight, studies evaluating how the coexistence of these factors impacts birth weight are extremely limited. Here, we present a novel algorithm NETwork Clusters (NET-C), to improve the prediction of outcome by considering the interactions of features in the network and then apply this method to predict birth weight by jointly modelling trace element and cord blood metabolite data. Specifically, by using trace element and/or metabolite subnetworks as groups, we apply group lasso to estimate birth weight. We conducted statistical simulation studies to examine how both sample size and correlations between grouped features and the outcome affect prediction performance. We showed that in terms of prediction error, our proposed method outperformed other methods such as (a) group lasso with groups defined by hierarchical clustering, (b) random forest regression and (c) neural networks. We applied our method to data ascertained as part of the New Hampshire Birth Cohort Study on trace elements, metabolites and birth outcomes, adjusting for other covariates such as maternal body mass index (BMI) and enrollment age. Our proposed method can be applied to a variety of similarly structured high-dimensional datasets to predict health outcomes.     

A Theoretical Model for Release Dynamics of an Antifungal Agent Covalently Bonded to the Chitosan

The aim of the study was to create a mathematical model useful for monitoring the release of bioactive aldehydes covalently bonded to the chitosan by reversible imine linkage, considered as a polymer–drug system. For this purpose, two hydrogels were prepared by the acid condensation reaction of chitosan with the antifungal 2-formyl-phenyl-boronic acid and their particularities; influencing the release of the antifungal aldehyde by shifting the imination equilibrium to the reagents was considered, i.e., the supramolecular nature of the hydrogels was highlighted by polarized light microscopy, while scanning electron microscopy showed their microporous morphology. Furthermore, the in vitro fungicidal activity was investigated on two fungal strains and the in vitro release curves of the antifungal aldehyde triggered by the pH stimulus were drawn. The theoretical model was developed starting from the hypothesis that the imine-chitosan system, both structurally and functionally, can be assimilated, from a mathematical point of view, with a multifractal object, and its dynamics were analyzed in the framework of the Scale Relativity Theory. Thus, through Riccati-type gauges, two synchronous dynamics, one in the scale space, associated with the fungicidal activity, and the other in the usual space, associated with the antifungal aldehyde release, become operational. Their synchronicity, reducible to the isomorphism of two SL(2R)-type groups, implies, by means of its joint invariant functions, bioactive aldehyde compound release dynamics in the form of “kink–antikink pairs” dynamics of a multifractal type. Finally, the theoretical model was validated through the experimental data.     

Selection of the most effective kinetic model of lactase hydrolysis by immobilized Aspergillus niger and free β-galactosidase

The kinetic model of the hydrolysis of lactose by β-galactosidase from Aspergillus niger immobilized on a commercial ceramic monoliths was estimated in the attendance of lactose and its hydrolysis reaction products galactose and glucose. The aim of this work was to developing kinetic model of lactase hydrolysis by Aspergillus niger. The variables in this study are temperature, pH, enzyme concentration, substrate concentration and final product. The optimum temperature used to achieve the best hydrolysis performance in the kinetic model selection was 55 and 60 °C. The optimum pH used for enzyme activity was about 3.5 to 4. Five kinetic models were proposed to confirm experimental data the enzymatic reaction of the lactose hydrolysis by the β-galactosidase. The kinetics of lactose hydrolysis by both Immobilized and soluble lactases were scrutinized in a batch reactor system in the lack of any mass conduction restriction. In both instance the galactose inhibition kinetic models predicted the experimental data. The model is capable to fit the experimental data correctly in the extensive experimental span studied.     

Modeling of Solute-Solvent Interactions Using an External Electric Field—From Tautomeric Equilibrium in Nonpolar Solvents to the Dissociation of Alkali Metal Halides

An implicit account of the solvent effect can be carried out using traditional static quantum chemistry calculations by applying an external electric field to the studied molecular system. This approach allows one to distinguish between the effects of the macroscopic reaction field of the solvent and specific solute–solvent interactions. In this study, we report on the dependence of the simulation results on the use of the polarizable continuum approximation and on the importance of the solvent effect in nonpolar solvents. The latter was demonstrated using experimental data on tautomeric equilibria between the pyridone and hydroxypyridine forms of 2,6-di-tert-butyl-4-hydroxy-pyridine in cyclohexane and chloroform.     

An In Vitro Pilot Fermentation Study on the Impact of Chlorella pyrenoidosa on Gut Microbiome Composition and Metabolites in Healthy and Coeliac Subjects

The response of a coeliac and a healthy gut microbiota to the green algae Chlorella pyrenoidosa was evaluated using an in vitro continuous, pH controlled, gut model system, which simulated the human colon. The effect of C. pyrenoidosa on the microbial structure was determined by 16S rRNA gene sequencing and inferred metagenomics, whereas the metabolic activitywas determined by¹H-nuclear magnetic resonancespectroscopic analysis. The addition of C. pyrenoidosa significantly increased the abundance of the genera Prevotella, Ruminococcus and Faecalibacterium in the healthy donor, while an increase in Faecalibacterium, Bifidobacterium and Megasphaera and a decrease in Enterobacteriaceae were observed in the coeliac donor. C. pyrenoidosa also altered several microbial pathways including those involved in short-chain fatty acid (SCFA) production. At the metabolic level, a significant increase from baseline was seen in butyrate and propionate (p < 0.0001) in the healthy donor, especially in vessels 2 and 3. While acetate was significantly higher in the healthy donor at baseline in vessel 3 (p < 0.001) compared to the coeliac donor, this was markedly decreased after in vitro fermentation with C. pyrenoidosa. This is the first in vitro fermentation study of C. pyrenoidosa and human gut microbiota, however, further in vivo studies are needed to prove its efficacy.     

农林院校校外实验教学基地分类考评机制及考评指标改革研究——大学化学校外实践基地实证分析*

针对大学化学校外实践教学基地建设和运行过程中的基地与高校的协同管理机制,实践教学基地软硬条件建设和资源配置及实践教学与理论学习的连贯性等问题,在OBE理论指导下,探究分类考核机制,在实证中构建分层次考评模型及考评指标,并建立适合于农林高校的化学校外实践教学基地的分类考评指标体系。     

以模型认知素养为导向的电化学模拟题的命制*——以双极膜的应用为例

以双极膜发展进程为线索,以海水淡化、钠碱循环法脱除烟气中的SO₂等现实发展中真实问题为载体,结合中学生的认知能力水平,构建了电化学双极膜认识模型;命制了双极膜及其应用的电化学模拟题,以此测查学生模型认知素养的水平等级。阐述命题策略及过程,提供以模型认知素养为导向的试题命制思路;从模型建构的角度对2020年高考新课标Ⅰ卷第12题进行了评析。     

基于改进免疫遗传算法的近红外光谱变量选择方法

该文在免疫遗传算法（IGA）的基础上,提出一种改进免疫遗传算法（iIGA）用于近红外光谱波长变量的选择。该算法舍去了原算法中固定抗体相似度阈值的思想,取而代之的是抗体相似度阈值自适应,同时引入精英保留策略和贪心算法思想,使得算法朝着正确的方向进行局部性探优。将该算法在玉米的淀粉和蛋白质含量数据集上进行实验测试,建立偏最小二乘（PLS）分析模型,并与IGA、遗传算法（GA）以及全谱方法进行了对比。结果表明,在玉米淀粉含量的预测上,iIGA相较于原IGA算法,预测集均方根误差（RMSEP）从0.312 0降至0.298 0,预测集预测精度提升4.5%;在玉米蛋白质含量的预测上,RMSEP从0.124 4降至0.110 3,预测集预测精度提升11.3%。分别对预测淀粉和蛋白质模型的RMSEP值进行显著性检验,F值分别为165.22和182.05,P值分别为9.5 × 10－23和4.5 × 10－24,P值均小于0.05,因此,iIGA能显著提升模型预测精度。     

1,3,5-Triaza-7-Phosphaadamantane (PTA) as a 31P NMR Probe for Organometallic Transition Metal Complexes in Solution

Due to the rigid structure of 1,3,5-triaza-7-phosphaadamantane (PTA), its ³¹P chemical shift solely depends on non-covalent interactions in which the molecule is involved. The maximum range of change caused by the most common of these, hydrogen bonding, is only 6 ppm, because the active site is one of the PTA nitrogen atoms. In contrast, when the PTA phosphorus atom is coordinated to a metal, the range of change exceeds 100 ppm. This feature can be used to support or reject specific structural models of organometallic transition metal complexes in solution by comparing the experimental and Density Functional Theory (DFT) calculated values of this ³¹P chemical shift. This approach has been tested on a variety of the metals of groups 8–12 and molecular structures. General recommendations for appropriate basis sets are reported.