The Characterization Of The Endoglucanase Cel12a From Gloeophyllum Trabeum Reveals An Enzyme Highly Active On β-glucan.

The basidiomycete fungus Gloeophyllum trabeum causes a typical brown rot and is known to use reactive oxygen species in the degradation of cellulose. The extracellular Cel12A is one of the few endo-1,4-β-glucanase produced by G. trabeum. Here we cloned cel12A and heterologously expressed it in Aspergillus niger. The identity of the resulting recombinant protein was confirmed by mass spectrometry. We used the purified GtCel12A to determine its substrate specificity and basic biochemical properties. The G. trabeum Cel12A showed highest activity on β-glucan, followed by lichenan, carboxymethylcellulose, phosphoric acid swollen cellulose, microcrystalline cellulose, and filter paper. The optimal pH and temperature for enzymatic activity were, respectively, 4.5 and 50 °C on β-glucan. Under these conditions specific activity was 239.2 ± 9.1 U mg(-1) and the half-life of the enzyme was 84.6 ± 3.5 hours. Thermofluor studies revealed that the enzyme was most thermal stable at pH 3. Using β-glucan as a substrate, the Km was 3.2 ± 0.5 mg mL(-1) and the Vmax was 0.41 ± 0.02 µmol min(-1). Analysis of the effects of GtCel12A on oat spelt and filter paper by scanning electron microscopy revealed the morphological changes taking place during the process.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Influence Of Substrate Steps On The Catalytic Properties Of Pt Layers: The Ethanol Electrooxidation Reaction.

The ethanol oxidation reaction (EOR) is investigated on Pt/Au(hkl) electrodes. The Au(hkl) single crystals used belong to the [n(111)x(110)] family of planes. Pt is deposited following the galvanic exchange of a previously deposited Cu monolayer using a Pt(2+) solution. Deposition is not epitaxial and the defects on the underlying Au(hkl) substrates are partially transferred to the Pt films. Moreover, an additional (100)-step-like defect is formed, probably as a result of the strain resulting from the Pt and Au lattice mismatch. Regarding the EOR, both vicinal Pt/Au(hkl) surfaces exhibit a behavior that differs from that expected for stepped Pt; for instance, the smaller the step density on the underlying Au substrate, the greater the ability to break the CC bond in the ethanol molecule, as determined by in situ Fourier transform infrared spectroscopy measurements. Also, we found that the acetic acid production is favored as the terrace width decreases, thus reflecting the inefficiency of the surface array to cleave the ethanol molecule.

Kinase Inhibitor Profile For Human Nek1, Nek6, And Nek7 And Analysis Of The Structural Basis For Inhibitor Specificity.

Human Neks are a conserved protein kinase family related to cell cycle progression and cell division and are considered potential drug targets for the treatment of cancer and other pathologies. We screened the activation loop mutant kinases hNek1 and hNek2, wild-type hNek7, and five hNek6 variants in different activation/phosphorylation statesand compared them against 85 compounds using thermal shift denaturation. We identified three compounds with significant Tm shifts: JNK Inhibitor II for hNek1(Δ262-1258)-(T162A), Isogranulatimide for hNek6(S206A), andGSK-3 Inhibitor XIII for hNek7wt. Each one of these compounds was also validated by reducing the kinases activity by at least 25%. The binding sites for these compounds were identified by in silico docking at the ATP-binding site of the respective hNeks. Potential inhibitors were first screened by thermal shift assays, had their efficiency tested by a kinase assay, and were finally analyzed by molecular docking. Our findings corroborate the idea of ATP-competitive inhibition for hNek1 and hNek6 and suggest a novel non-competitive inhibition for hNek7 in regard to GSK-3 Inhibitor XIII. Our results demonstrate that our approach is useful for finding promising general and specific hNekscandidate inhibitors, which may also function as scaffolds to design more potent and selective inhibitors.

Comparison between the 1% and 2% ibopamine provocative test in primary open-angle glaucoma patients: sensitivity, specificity and tolerability

PURPOSE: To compare intraocular pressure (IOP) rise in normal individuals and primary open-angle glaucoma patients and the safety and efficacy of ibopamine eye drops in different concentrations as a provocative test for glaucoma. METHODS: Glaucoma patients underwent (same eye) the ibopamine provocative test with two concentrations, 1% and 2%, in a random sequence at least 3 weeks apart, but not more than 3 months. The normal individuals were randomly submitted to one of the concentrations of ibopamine (1% and 2%). The test was considered positive if there was an IOP rise greater than 3 or 4 mmHg at 30 or 45 minutes to test which subset of the test has the best sensitivity (Se)/specificity (Sp). RESULTS: There was no statistically significant difference in any of the IOP measurements, comparing 1% with 2% ibopamine. The IOP was significantly higher at 30 and 45 minutes with both concentrations (p<0.001). The best sensitivity/specificity ratio was achieved with the cutoff point set as greater than 3 mmHg at 45 minutes with 2% ibopamine (area under the ROC curve: 0.864, Se: 84.6%; Sp:73.3%). All patients described a slight burning after ibopamine's instillation. CONCLUSION: 2% ibopamine is recommended as a provocative test for glaucoma. Because both concentrations have similar ability to rise IOP, 1% ibopamine may be used to treat ocular hypotony.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.