Enhanced laccase stability through mediator partitioning into hydrophobic ionic liquids

Laccase-mediator systems have numerous potential uses for green oxidations, but their practical use may be limited because the reactive, oxidised mediators deactivate the enzyme. TEMPO, 4-hydroxybenzyl alcohol, phenothiazine and 2-hydroxybiphenyl caused almost complete deactivation of laccase from Trametes versicolor within 24-140 h. By contrast, 18% activity was retained after 188 h in controls without mediator, and 15% in the presence of ABTS. A biphasic reaction system was developed to protect the laccase, by partitioning the mediator into water-immiscible ionic liquids. In the presence of [C mim][AOT], laccase retained 54, 35, 35 and 41% activity after 188 h in the presence of 4-hydroxybenzyl alcohol, phenothiazine and 2-hydroxybiphenyl and ABTS, respectively, whilst 30% activity was retained in the presence of [N][Sac] and TEMPO. The protection against deactivation by the mediators correlated strongly with the distribution coefficients of the mediators between ionic liquids and water. © 2014 The Royal Society of Chemistry.

Chaotropic and hydrophobic stress mechanisms of antifungal substances

Growth and metabolism of fungi can be curtailed by chaotropic solutes and hydrophobic substances, both of which can weaken or inhibit non-covalent interactions within and between macromolecular systems. Here we explore the potential to utilize the fungistatic and fungicidal activities of such stressors as the basis for commercial formulations. A method was developed for the quantification of chaotropicity, which can be used for chemically diverse substances, in order elucidate roles of chaotropicity and hydrophobicity in microbial ecology (both of which are sufficiently potent to limit the Earth’s microbial biosphere). A large number of naturally occurring substances act as chaotropic or hydrophobic stressors including aliphatic alcohols, salts such as MgCl2, aromatics such as phenol, and hydrocarbons such as hexane and octene. We suggest that these stress parameters provide the (hitherto unidentified) modes-of-action for some extant antifungal products. The findings are discussed in relation to the development of a new generation of antifungals.

Properties of Super-Hydrophobic Copper and Stainless Steel Meshes: Applications in Controllable Water Permeation and Organic Solvents/Water Separation

The wettability and hydrophobicity of super-hydrophobic (SH) meshes is greatly influenced by their topographic structures, chemical composition and coating process. In this study, the properties of copper and stainless steel meshes, coated with super-hydrophobic electrolessly deposited silver were investigated. A new method to test the pressure resistance of super-hydrophobic mesh was applied to avoid any deformation of mesh. Results showed that SH copper mesh and SH stainless steel meshes with the same pore size have almost the same contact angle and the same hydrophobicity. SH copper mesh with a pore size of 122 μm can resist water pressure of 4900 Pa and a decrease of pore size of mesh can increase the pressure resistance of SH copper mesh. The SH copper mesh modified with 0.1 M HS(CH2)10COOH solution in ethanol has a controllable water permeation property by simply adjusting the pH of water solution. SH copper mesh shows super-oleophilicity with organic solvents and so with a water contact angle of 0° and it can be an effective tool for organic solvents/water separation. The separation efficiency of SH copper mesh for separating mixtures of organic solvent and water can be as high as 99.8%.

Improving antimicrobial release kinetics from hydrophobic polymer implants via ion pairing to combat biomedical-device related infection

Purpose The aim of this study is to improve the drug release properties of antimicrobial agents from hydrophobic biomaterials using using an ion pairing strategy. In so doing antimicrobial agents may be eluted and maintained over a sufficient time period thereby preventing bacterial colonisation and subsequent biofilm formation on medical devices. Methods The model antimicrobial agent was chlorhexidine and the selected fatty acid counter ions were capric acid, myristic acid and stearic acid. The polymethyl methacrylate films were loaded with 2% of fatty acid:antimicrobial agent at the following molar ratios; 0.5:1M, 1:1M and 2:1M and thermally polymerized using azobisisobutyronitrile initiator. Drug release experiments were subsequently performed over a 3-month period and the mass of drug released under sink conditions (pH 7.0, 37oC) quantified using a validated HPLC-UV method. Results In all platforms, a burst of chlorhexidine release was observed over the initial 24-hour period. Similar release kinetics were observed between the formulations during the initial 28 days. However, as time progressed, the chlorhexidine baseline plateaued after 56 days whereas formulations containing the counterions appeared to continuously elute linearly with time. As can be observed in figure 1, the rank order of total chlorhexidine release in the presence of 0.5M fatty acid was myristic acid (40%) > capric acid (35%) > stearic acid (30%)> chlorhexidine baseline (15%). Conclusion The incorporation of fatty acids within the formulation significantly improved chlorhexidine solubility within both the monomer and the polymer and enhanced the drug release kinetics over the period of study. This is attributed to the greater diffusivity of chlorhexidine through PMMA in the presence of fatty acids. In th absence of fatty acids, chlorhexidine release was facilitated by dissolution of surface associated drug particles. This study has illustrated the ability of fatty acids to modulate chlorhexidine release from a model biomaterial through enhanced diffusivity. This strategy may prove advantageous for improved medical devices with enhanced resistance to infection.

Quantitative structure-hydrophobicity relationships of molecular fragments and beyond

Quantitative structure-property relationship (QSPR) models were firstly established for the hydrophobic substituent constant (πX) using the theoretical descriptors derived solely from electrostatic potentials (EPSs) at the substituent atoms. The descriptors introduced are found to be related to hydrogen-bond basicity, hydrogen-bond acidity, cavity, or dipolarity/polarizability terms in linear solvation energy relationship, which endows the models good interpretability. The predictive capabilities of the models constructed were also verified by rigorous Monte Carlo cross-validation. Then, eight groups of meta- or para- disubstituted benzenes and one group of substituted pyridines were investigated. QSPR models for individual systems were achieved with the ESP-derived descriptors. Additionally, two QSPR models were also established for Rekker's fragment constants (foct), which is a secondary-treatment quantity and reflects average contribution of the fragment to logP. It has been demonstrated that the descriptors derived from ESPs at the fragments, can be well used to quantitatively express the relationship between fragment structures and their hydrophobic properties, regardless of the attached parent structure or the valence state. Finally, the relations of Hammett σ constant and ESP quantities were explored. It implies that σ and π, which are essential in classic QSAR and represent different type of contributions to biological activities, are also complementary in interaction site.

Towards a spectroscopically accurate set of potentials for heavy hydride laser cooling candidates: effective core potential calculations of BaH

BaH (and its isotopomers) is an attractive molecular candidate for laser cooling to ultracold temperatures and a potential precursor for the production of ultracold gases of hydrogen and deuterium. The theoretical challenge is to simulate the laser cooling cycle as reliably as possible and this paper addresses the generation of a highly accurate ab initio $^{2}\Sigma^+$ potential for such studies. The performance of various basis sets within the multi-reference configuration-interaction (MRCI) approximation with the Davidson correction (MRCI+Q)is tested and taken to the Complete Basis Set (CBS) limit. It is shown that the calculated molecular constants using a 46 electron Effective Core-Potential (ECP) and even-tempered augmented polarized core-valence basis sets (aug-pCV$n$Z-PP, n= 4 and 5) but only including three active electrons in the MRCI calculation are in excellent agreement with the available experimental values. The predicted dissociation energy De for the X$^2\Sigma^+$ state (extrapolated to the CBS limit) is 16895.12 cm$^{-1}$ (2.094 eV), which agrees within 0.1$\%$ of a revised experimental value of <16910.6 cm$^{-1}$, while the calculated re is within 0.03 pm of the experimental result.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.