Measurement and modeling of metoclopramide hydrochloride (anti-emetic drug) solubility in supercritical carbon dioxide

Knowledge of drug solubility data in supercritical carbon dioxide (SC-CO₂) is a fundamental step in producing nano and microparticles through supercritical fluid technology. In this work, for the first time, the solubility of metoclopramide hydrochloride (MCP) in SC-CO₂ was measured in pressure and temperature range of 12 to 27 MPa and 308 to 338 K, respectively. The results represented a range mole fractions of 0.15 × 10^-5 to 5.56 × 10^-5. To expand the application of the obtained data, six semi-empirical models and three models based on the Peng-Robinson equation of state (PR + VDW, PR + WS + Wilson and PR + MHV1 + COSMOSAC) with different mixing rules and various ways to describe intermolecular interactions were investigated. Furthermore, total enthalpy, sublimation enthalpy and solvation enthalpy relevant to MCP solvating in SC-CO₂ were estimated.     

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.     

Metabolite Profiling and Characterization of LW6, a Novel HIF-1α Inhibitor,as an Antitumor Drug Candidate in Mice

A novel HIF (hypoxia-inducible factor)-1α inhibitor, the (aryloxyacetylamino)benzoic acid derivative LW6, is an anticancer agent that inhibits the accumulation of HIF-1α. The aim of this study was to characterize and determine the structures of the metabolites of LW6 in ICR mice. Metabolite identification was performed using a predictive multiple reaction monitoring-information dependent acquisition-enhanced product ion (pMRM-IDA-EPI) method in negative ion mode on a hybrid triple quadrupole-linear ion trap mass spectrometer (QTRAP). A total of 12 metabolites were characterized based on their MS/MS spectra, and the retention times were compared with those of the parent compound. The metabolites were divided into five structural classes based on biotransformation reactions: amide hydrolysis, ester hydrolysis, mono-oxidation, glucuronidation, and a combination of these reactions. From this study, 2-(4-((3r,5r,7r)-adamantan-1-yl)phenoxy)acetic acid (APA, M7), the metabolite produced via amide hydrolysis, was found to be a major circulating metabolite of LW6 in mice. The results of this study can be used to improve the pharmacokinetic profile by lowering the clearance and increasing the exposure relative to LW6.     

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.     

Fe(II) Spin Crossover/Polymer Hybrid Materials: Investigation of the SCO Behavior via Temperature-Dependent Raman Spectroscopy,Physicochemical Characterization and Migration Release Study

Polymeric composites constitute an appealing class of materials with applications in various fields. Spin crossover (SCO) coordination complexes are switchable materials with potential use in data storage and sensors. Their incorporation into polymers can be considered an effective method for their wider practical application. In this study, Fe(II) SCO/polylactic acid hybrid polymeric composites have been prepared by film casting. The mononuclear coordination complex [Fe{N(CN)₂}₂(abpt)₂] was incorporated into polylactic acid. The morphological, structural and thermoanalytical characterization of the composite films were performed via scanning electron microscopy (SEM), attenuated total reflectance (ATR/FTIR), Raman spectroscopy and differential scanning calorimetry (DSC). In addition, the migration release study (MRS) of the SCO compound from the polymeric matrix into the food simulant 50% v/v water/ethanol solution was also examined via UV/Vis absorption. Of particular interest was the investigation of the SCO behavior of the coordination complex after its incorporation into the polymer matrix; it was accomplished by temperature-dependent micro-Raman spectroscopy. The described attempt could be considered a preparatory step toward the development of SCO-based temperature sensors integrated into food packaging materials.     

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.     

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.