AutoPPI: An Ensemble of Deep Autoencoders for Protein–Protein Interaction Prediction

Proteins are essential molecules, that must correctly perform their roles for the good health of living organisms. The majority of proteins operate in complexes and the way they interact has pivotal influence on the proper functioning of such organisms. In this study we address the problem of protein–protein interaction and we propose and investigate a method based on the use of an ensemble of autoencoders. Our approach, entitled AutoPPI, adopts a strategy based on two autoencoders, one for each type of interactions (positive and negative) and we advance three types of neural network architectures for the autoencoders. Experiments were performed on several data sets comprising proteins from four different species. The results indicate good performances of our proposed model, with accuracy and AUC values of over 0.97 in all cases. The best performing model relies on a Siamese architecture in both the encoder and the decoder, which advantageously captures common features in protein pairs. Comparisons with other machine learning techniques applied for the same problem prove that AutoPPI outperforms most of its contenders, for the considered data sets.     

Microstructures and growth characteristics of polyelectrolytes on silicon using layer-by-layer assembly

Growth processes of nanocomposite layers obtained by polyelectrolytes, poly(sodium 4-styrenesulfonate) (PSS) and poly(diallyldimethylammonium chloride) (PDADMAC), self-assembled on silicon surface using layer-by-layer (LbL) technique were investigated, and theoretical and experimental data are herein reported. Complementary microstructural and compositional analyses techniques (scanning electron microscopy, ellipsometry, X-ray reflectivity, zeta (ξ) potential measurements and attenuated total reflection infrared spectroscopy) were used for deep characterization of the multilayer structure formation. Electrophoretic zeta (ξ) potential measurements indicated that the surface charge was either positive or negative, depending on the polyelectrolyte used (PDADMAC or PSS). ATR-IR spectra confirmed the successfully silanization process and then, the building up of the nanocomposite layer. Morphological investigation and X-ray reflectivity demonstrated the growth process and cross-section size of the bilayers. Ellipsometric measurements were in very good agreement with SEM and XRR, showing once again the successful deposition of polyelectrolyte multilayers.      

Microwave-assisted extraction of trichloroethylene from clay samples

A new method for volatile organic compounds (VOCs) extraction from low-permeability media, such as clay, has been developed and tested using trichloroethylene (TCE) as a model compound. The method is based on microwave-assisted extraction (MAE), which uses microwave energy to heat the extracting solvent and the sample. MAE allows the extraction process to be carried out at elevated temperatures and pressures, which dramatically reduces the time required to complete the process. A custom-made PTFE vessel was used for extraction investigations. TCE analysis was performed using gas chromatography with electron capture detection (GC-ECD). Three different solvents were tested: methanol, 1?:?1 hexane?:?acetone mixture, and 10?:?1 hexane?:?acetone mixture. A comparison of TCE recoveries from clay samples using the new method and the standard methanol extraction method was carried out. The newly developed method and the method currently in use were found to recover similar amounts of TCE. The major advantage of the MAE technique is the very short time needed to obtain complete analyte recovery (6–10?min), which makes it possible to analyse a large number of samples without the need for sample preservation or prolonged storage. Thus, the new method is much more efficient than the existing methods. The technique has a good potential for field application.     

A numerical approximation of parabolic stochastic partial differential equations driven by a Poisson random measure

The paper deals with SPDEs driven by Poisson random measures in Banach spaces and its numerical approximation. We investigate the accuracy of space and time approximation. As the space approximation we consider spectral methods and as time approximation the implicit Euler scheme and the explicit Euler scheme. AMS subject classification (2000) 60H15, 35R30     

Determination of the anchoring constant for a compensated binary cholesteric mixture

The optical transmission and the electric power was simultaneously recorded for the binary compensated cholesteric mixture cholesteryl chloride + cholesteryl nonanoate (70:30 molar). The values of the critical voltages U₁ and U₂ (at which the planar texture changes into a conic focal one, and the cholesteric-nematic transition take place) at different temperatures were obtained. The temperature dependence of the anchoring constant is determined.     

Biomarker Candidates of <Emphasis Type="Italic">Chlamydophila pneumoniae</Emphasis> Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.     

Modulating the acidity: highly acidic Brønsted acids in asymmetric catalysis

Recently, chiral highly acidic Brønsted acids have emerged as powerful catalysts for enantioselective C C and C X bond‐forming reactions. Their strong acidity renders them valuable tools for the activation of imines, carbonyl compounds, and other weakly basic substrates. As a result, new perspectives are opened and highly stereoselective transformations based on the concept of chiral contact‐ion‐pair catalysis can be realized. This Minireview gives an overview of the design and application of these new organocatalysts and presents recent results in this rapidly growing field.     

1,5,7-Triazabicyclo[4.4.0]dec-5-ene (TBD) an efficient homogeneous catalyst for aldol condensation reactions. Study of the catalyst recovery and reusability using CO2

In this work it was shown that TBD (1,5,7-triazabicyclo[4.4.0]dec-5-ene), a cheap and commercially available guanidine base, efficiently catalyzes aldol condensation reactions yielding interesting products for pharmacological and fragrance industries. This methodology works under solvent-less conditions and affords with very good conversions the corresponding products. Moreover, a simple and effective separation protocol using the CO₂ fixation was employed. The catalyst could be recovered and re-used for three consecutive runs without significant loss of activity.     

Thermal degradation of keratin waste

Thermal degradation of sheep wool, human hair and chicken feathers was studied by TG-MSD/FTIR and by pyrolysis followed by GC-MSD analysis in order to identify the degradation compounds and the temperature range in which they are formed. Only small differences were found between the studied keratin samples. They consist mainly in shift of characteristic temperatures of degradation and in relative amounts of compounds in degradation products, especially in aqueous phase. Degradation started with formation of ammonia and CO₂ (from 167 and 197 °C respectively and with maximum evolution at 273 and 287 °C respectively), continues with formation of sulphur-containing inorganic compounds (SCS, SCO, H₂S and SO₂ at 240, 248, 255 and 253-260 °C respectively) and of water (255 °C). Thiols are formed in two stages (257 and 320 °C) while the evolution of nitriles is maximum around 340 °C and continues up to about 480 °C. Phenol and 4-methylphenol are the most important degradation compounds, formed at 370 and 400 °C respectively. Nitrogen was present mainly in aliphatic/aromatic nitriles, pyrroles, pyridines and amides while sulphur was found mainly as sulphides, thiols, thiazoles and thiophenes.