The application of phenotypic microarray analysis to anti-fungal drug development

Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance

Line Strengths of Rovibrational and Rotational Transitions in the X2Π^2\Pi Ground State of OH

A new line list including positions and absolute intensities (in the form of Einstein $A$ values and oscillator strengths) has been produced for the OH ground X\DP\ state rovibrational (Meinel system) and pure rotational transitions. All possible transitions are included with v\primed and v\Dprimed up to 13, and $J$ up to between 9.5 and 59.5, depending on the band. An updated fit to determine molecular constants has been performed, which includes some new rotational data and a simultaneous fitting of all molecular constants. The absolute line intensities are based on a new dipole moment function, which is a combination of two high level ab initio calculations. The calculations show good agreement with an experimental v=1 lifetime, experimental $\mu_\mathrm{v}$ values, and $\Delta$v=2 line intensity ratios from an observed spectrum. To achieve this good agreement, an alteration in the method of converting matrix elements from Hund's case (b) to (a) was made. Partitions sums have been calculated using the new energy levels, for the temperature range 5-6000 K, which extends the previously available (in HITRAN) 70-3000 K range. The resulting absolute intensities have been used to calculate O abundances in the Sun, Arcturus, and two red giants in the Galactic open and globular clusters M67 and M71. Literature data based mainly on [O I] lines are available for the Sun and Arcturus, and excellent agreement is found.Comment: 17 pages, 8 figues. 7 supplementary files: dipole moment functions (OH-X-DMFs.txt), equilibrium constants (OH-X-Equilibrium_Constants.txt), partition function (OH-X-Q_5-6000K.dat), PGOPHER file with molecular constants and transition matric elements (OH-XX.pgo), vibrational Einstein A and f values (OH-XX-Avv_fvv.txt), line list (OH-XX-Line_list.txt), and OH-Transformation_Equation_Extra.doc

The Poisson-Boltzmann model for implicit solvation of electrolyte solutions: Quantum chemical implementation and assessment via Sechenov coefficients.

We present the theory and implementation of a Poisson-Boltzmann implicit solvation model for electrolyte solutions. This model can be combined with arbitrary electronic structure methods that provide an accurate charge density of the solute. A hierarchy of approximations for this model includes a linear approximation for weak electrostatic potentials, finite size of the mobile electrolyte ions, and a Stern-layer correction. Recasting the Poisson-Boltzmann equations into Euler-Lagrange equations then significantly simplifies the derivation of the free energy of solvation for these approximate models. The parameters of the model are either fit directly to experimental observables-e.g., the finite ion size-or optimized for agreement with experimental results. Experimental data for this optimization are available in the form of Sechenov coefficients that describe the linear dependence of the salting-out effect of solutes with respect to the electrolyte concentration. In the final part, we rationalize the qualitative disagreement of the finite ion size modification to the Poisson-Boltzmann model with experimental observations by taking into account the electrolyte concentration dependence of the Stern layer. A route toward a revised model that captures the experimental observations while including the finite ion size effects is then outlined. This implementation paves the way for the study of electrochemical and electrocatalytic processes of molecules and cluster models with accurate electronic structure methods

The anti-adhesive effect of curcumin on Candida albicans biofilms on denture materials

The use of natural compounds as an alternative source of antimicrobials has become a necessity given the growing concern over global antimicrobial resistance. Polyphenols, found in various edible plants, offers one potential solution to this. We aimed to investigate the possibility of using curcumin within the context of oral health as a way of inhibiting and preventing the harmful development of Candida albicans biofilms. We undertook a series of adsorption experiments with varying concentrations of curcumin, showing that 50 ug/ml could prevent adhesion. This effect could be further synergised by the curcumin pretreatment of yeast cells to obtain significantly greater inhibition (>90, p<0.001). Investigation of the biological impact of curcumin showed that it preferentially affected immature morphological forms (yeast and germlings), and actively promoted aggregation of the cells. Transcriptional analyses showed that key adhesins were down-regulated (ALS1 and ALS3), whereas aggregation related genes (ALS5 and AAF1) were up-regulated. Collectively, these data demonstrated that curcumin elicits anti-adhesive effects and that induces transcription of genes integrally involved in the processes related to biofilm formation. Curcumin and associated polyphenols therefore have the capacity to be developed for use in oral healthcare to augment existing preventative strategies for candidal biofilms on the denture surface

Examining the role of glycoside hydrolases in local rheology of Pseudomonas aeruginosa biofilms

Current research strategies in the treatment of biofilm infections have focused on dispersal, in which bacteria are made to vacate the extracellular polymeric substance (EPS) surrounding them and return to a planktonic state where antimicrobial treatments are more effective. Glycoside hydrolases (GHs), which cleave bonds in EPS polysaccharides, have been shown to promote dispersal in Pseudomonas aeruginosa biofilms. The dispersal mechanism is possibly due to GHs’ ability to directly release bacteria from the EPS, disrupt EPS’ ability to regulate the environment, or reduce overall mechanical stability. In this work, passive microrheology is used to examine the relevance of the last mechanism by exploring the effects of three GHs (α-amylase, cellulase, and xylanase) known to disperse P. aeruginosa on local biofilm viscoelasticity. Compared to control studies in wild-type strains, it is found that treatment with all three GHs results in statistically relatively less elastic and stiffer biofilms, indicating that changes to mechanical stability may be a factor in effective dispersal. Both cellulase and xylanase were observed to have the greatest impact in creating a less stiff and elastic biofilm; these GHs have been observed to be effective at dispersal in the published results. Each GH was further tested on biofilms grown with strains that produced EPS missing specific polysaccharide components. Cellulase specifically targeted Psl, which forms the major structural and mechanical backbone of the EPS, explaining its efficacy in dispersal. However, xylanase did not appear to exhibit any affinity to any polysaccharide within the EPS based on the microrheology results. Overall, these results suggest that the local microrheology of the biofilms is impacted by GHs and that may be one of the factors that is causing the ability of these therapeutics to enhance dispersal

Forecast Constraints on Inflation from Combined CMB and Gravitational Wave Direct Detection Experiments

We study how direct detection of the inflationary gravitational wave background constrains inflationary parameters and complements CMB polarization measurements. The error ellipsoids calculated using the Fisher information matrix approach with Planck and the direct detection experiment, BBO (Big Bang Observer), show different directions of parameter degeneracy, and the degeneracy is broken when they are combined. For a slow-roll parameterization, we show that BBO could significantly improve the constraints on the tensor-to-scalar ratio compared with Planck alone. We also look at a quadratic and a natural inflation model. In both cases, if the temperature of reheating is also treated as a free parameter, then the addition of BBO can significantly improve the error bars. In the case of natural inflation, we find that the addition of BBO could even partially improve the error bars of a cosmic variance-limited CMB experiment.Comment: 12 pages, 5 figures; matches version to appear in PRD; typos correcte

Biofilms formed by Candida albicans bloodstream isolates display phenotypic and transcriptional heterogeneity that are associated with resistance and pathogenicity

Background: Candida albicans infections have become increasingly recognised as being biofilm related. Recent studies have shown that there is a relationship between biofilm formation and poor clinical outcomes in patients infected with biofilm proficient strains. Here we have investigated a panel of clinical isolates in an attempt to evaluate their phenotypic and transcriptional properties in an attempt to differentiate and define levels of biofilm formation.<p></p> Results: Biofilm formation was shown to be heterogeneous; with isolates being defined as either high or low biofilm formers (LBF and HBF) based on different biomass quantification. These categories could also be differentiated using a cell surface hydrophobicity assay with 24 h biofilms. HBF isolates were more resistance to amphotericin B (AMB) treatment than LBF, but not voriconazole (VRZ). In a Galleria mellonella model of infection HBF mortality was significantly increased in comparison to LBF. Histological analysis of the HBF showed hyphal elements intertwined indicative of the biofilm phenotype. Transcriptional analysis of 23 genes implicated in biofilm formation showed no significant differential expression profiles between LBF and HBF, except for Cdr1 at 4 and 24 h. Cluster analysis showed similar patterns of expression for different functional classes of genes, though correlation analysis of the 4 h biofilms with overall biomass at 24 h showed that 7 genes were correlated with high levels of biofilm, including Als3, Eap1, Cph1, Sap5, Plb1, Cdr1 and Zap1.<p></p> Conclusions: Our findings show that biofilm formation is variable amongst C. albicans isolates, and categorising isolates depending on this can be used to predict how pathogenic the isolate will behave clinically. We have shown that looking at individual genes in less informative than looking at multiple genes when trying to categorise isolates at LBF or HBF. These findings are important when developing biofilm-specific diagnostics as these could be used to predict how best to treat patients infected with C. albicans. Further studies are required to evaluate this clinically.<p></p&gt

Constant Size Molecular Descriptors For Use With Machine Learning

A set of molecular descriptors whose length is independent of molecular size is developed for machine learning models that target thermodynamic and electronic properties of molecules. These features are evaluated by monitoring performance of kernel ridge regression models on well-studied data sets of small organic molecules. The features include connectivity counts, which require only the bonding pattern of the molecule, and encoded distances, which summarize distances between both bonded and non-bonded atoms and so require the full molecular geometry. In addition to having constant size, these features summarize information regarding the local environment of atoms and bonds, such that models can take advantage of similarities resulting from the presence of similar chemical fragments across molecules. Combining these two types of features leads to models whose performance is comparable to or better than the current state of the art. The features introduced here have the advantage of leading to models that may be trained on smaller molecules and then used successfully on larger molecules.Comment: 18 pages, 5 figure

Data compression using Chebyshev transform

The present invention is a method, system, and computer program product for implementation of a capable, general purpose compression algorithm that can be engaged on the fly. This invention has particular practical application with time-series data, and more particularly, time-series data obtained form a spacecraft, or similar situations where cost, size and/or power limitations are prevalent, although it is not limited to such applications. It is also particularly applicable to the compression of serial data streams and works in one, two, or three dimensions. The original input data is approximated by Chebyshev polynomials, achieving very high compression ratios on serial data streams with minimal loss of scientific information