Preparation, structural characterisation and antibacterial properties of Ga-doped sol-gel phosphate-based glass

A sol-gel preparation of Ga-doped phosphate-based glass with potential application in antimicrobial devices has been developed. Samples of composition (CaO)(0.30)(Na2O)(0.20-x) (Ga2O3) (x) (P2O5)(0.50) where x = 0 and 0.03 were prepared, and the structure and properties of the gallium-doped sample compared with those of the sample containing no gallium. Analysis of the P-31 MAS NMR data demonstrated that addition of gallium to the sol-gel reaction increases the connectivity of the phosphate network at the expense of hydroxyl groups. This premise is supported by the results of the elemental analysis, which showed that the gallium-free sample contains significantly more hydrogen and by FTIR spectroscopy, which revealed a higher concentration of -OH groups in that sample. Ga K-edge extended X-ray absorption fine structure and X-ray absorption near-edge structure data revealed that the gallium ions are coordinated by six oxygen atoms. In agreement with the X-ray absorption data, the high-energy XRD results also suggest that the Ga3+ ions are octahedrally coordinated with respect to oxygen. Antimicrobial studies demonstrated that the sample containing Ga3+ ions had significant activity against Staphylococcus aureus compared to the control

Recent advances in electronic structure theory and their influence on the accuracy of ab initio potential energy surfaces

Recent advances in electronic structure theory and the availability of high speed vector processors have substantially increased the accuracy of ab initio potential energy surfaces. The recently developed atomic natural orbital approach for basis set contraction has reduced both the basis set incompleteness and superposition errors in molecular calculations. Furthermore, full CI calculations can often be used to calibrate a CASSCF/MRCI approach that quantitatively accounts for the valence correlation energy. These computational advances also provide a vehicle for systematically improving the calculations and for estimating the residual error in the calculations. Calculations on selected diatomic and triatomic systems will be used to illustrate the accuracy that currently can be achieved for molecular systems. In particular, the F+H2 yields HF+H potential energy hypersurface is used to illustrate the impact of these computational advances on the calculation of potential energy surfaces

Enteric Neurospheres Are Not Specific to Neural Crest Cultures: Implications for Neural Stem Cell Therapies

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited

Sparsest factor analysis for clustering variables: a matrix decomposition approach

We propose a new procedure for sparse factor analysis (FA) such that each variable loads only one common factor. Thus, the loading matrix has a single nonzero element in each row and zeros elsewhere. Such a loading matrix is the sparsest possible for certain number of variables and common factors. For this reason, the proposed method is named sparsest FA (SSFA). It may also be called FA-based variable clustering, since the variables loading the same common factor can be classified into a cluster. In SSFA, all model parts of FA (common factors, their correlations, loadings, unique factors, and unique variances) are treated as fixed unknown parameter matrices and their least squares function is minimized through specific data matrix decomposition. A useful feature of the algorithm is that the matrix of common factor scores is re-parameterized using QR decomposition in order to efficiently estimate factor correlations. A simulation study shows that the proposed procedure can exactly identify the true sparsest models. Real data examples demonstrate the usefulness of the variable clustering performed by SSFA

Multi-parallel qPCR provides increased sensitivity and diagnostic breadth for gastrointestinal parasites of humans: field-based inferences on the impact of mass deworming

BACKGROUND: Although chronic morbidity in humans from soil transmitted helminth (STH) infections can be reduced by anthelmintic treatment, inconsistent diagnostic tools make it difficult to reliably measure the impact of deworming programs and often miss light helminth infections. METHODS: Cryopreserved stool samples from 796 people (aged 2-81 years) in four villages in Bungoma County, western Kenya, were assessed using multi-parallel qPCR for 8 parasites and compared to point-of-contact assessments of the same stools by the 2-stool 2-slide Kato-Katz (KK) method. All subjects were treated with albendazole and all Ascaris lumbricoides expelled post-treatment were collected. Three months later, samples from 633 of these people were re-assessed by both qPCR and KK, re-treated with albendazole and the expelled worms collected. RESULTS: Baseline prevalence by qPCR (n = 796) was 17 % for A. lumbricoides, 18 % for Necator americanus, 41 % for Giardia lamblia and 15% for Entamoeba histolytica. The prevalence was <1% for Trichuris trichiura, Ancylostoma duodenale, Strongyloides stercoralis and Cryptosporidium parvum. The sensitivity of qPCR was 98% for A. lumbricoides and N. americanus, whereas KK sensitivity was 70% and 32%, respectively. Furthermore, qPCR detected infections with T. trichiura and S. stercoralis that were missed by KK, and infections with G. lamblia and E. histolytica that cannot be detected by KK. Infection intensities measured by qPCR and by KK were correlated for A. lumbricoides (r = 0.83, p < 0.0001) and N. americanus (r = 0.55, p < 0.0001). The number of A. lumbricoides worms expelled was correlated (p < 0.0001) with both the KK (r = 0.63) and qPCR intensity measurements (r = 0.60). CONCLUSIONS: KK may be an inadequate tool for stool-based surveillance in areas where hookworm or Strongyloides are common or where intensity of helminth infection is low after repeated rounds of chemotherapy. Because deworming programs need to distinguish between populations where parasitic infection is controlled and those where further treatment is required, multi-parallel qPCR (or similar high throughput molecular diagnostics) may provide new and important diagnostic information

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Self-assembled amyloid fibrils with controllable conformational heterogeneity

Amyloid fibrils are a hallmark of neurodegenerative diseases and exhibit a conformational diversity that governs their pathological functions. Despite recent findings concerning the pathological role of their conformational diversity, the way in which the heterogeneous conformations of amyloid fibrils can be formed has remained elusive. Here, we show that microwave-assisted chemistry affects the self-assembly process of amyloid fibril formation, which results in their conformational heterogeneity. In particular, microwave-assisted chemistry allows for delicate control of the thermodynamics of the self-assembly process, which enabled us to tune the molecular structure of ??-lactoglobulin amyloid fibrils. The heterogeneous conformations of amyloid fibrils, which can be tuned with microwave-assisted chemistry, are attributed to the microwave-driven thermal energy affecting the electrostatic interaction during the self-assembly process. Our study demonstrates how microwave-assisted chemistry can be used to gain insight into the origin of conformational heterogeneity of amyloid fibrils as well as the design principles showing how the molecular structures of amyloid fibrils can be controlledopen0

Nanodiamond preparation and surface characterization for biological applications

Nanodiamonds contain stable fluorescent emitters and hence can be used for molecular fluorescence imaging and precision sensing of electromagnetic fields. The physical properties of these emitters together with their low reported cytotoxicity make them attractive for biological imaging applications. The controlled application of nanodiamonds for cellular imaging requires detailed understanding of surface chemistry, size ranges and aggregation, as these can all influence cellular interactions. We compared these characteristics for graphitic and oxidized nanodiamonds. Oxidation is generally used for surface functionalization, and was optimized by Thermogravimetric Analysis, achieved by 445±5°C heating in air for 5 hours, then confirmed via Raman and Infrared spectroscopies. Size ranges and aggregation were assessed using Atomic Force Microscopy and Dynamic Light Scattering. Biocompatibility in breast cancer cell lines was measured using a proliferation assay. Heating at 445±5°C reduced the Raman signal of graphitic carbon (1575 cm-1) as compared to that of diamond (1332 cm-1) from 0.31±0.07 Raman intensity units to 0.07±0.04. This temperature was substantially below the onset of major mass loss (observed at 535±1°C) and therefore achieved cost efficiency, convenience and high yield. Graphitic and oxidized nanodiamonds formed aggregates in water, with a mean particle size of 192±4nm and 166±2nm at a concentration of 66μg/mL. We then applied the graphitic and oxidized nanodiamonds to cells in culture at 1μg/mL and found no significant change in the proliferation rate (-5±2% and -1±3% respectively). Nanodiamonds may therefore be suitable for development as a novel transformative tool in the life sciences

Synchronization modulation increases transepithelial potentials in MDCK monolayers through Na/K pumps

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