Phosphoproteomics by mass spectrometry and classical protein chemistry approaches

The general fields of biological sciences have seen phenomenal transformations in the past two decades at the level of data acquisition, understanding biological processes, and technological developments. Those advances have been made partly because of the advent of molecular biology techniques (which led to genomics) coupled to the advances made in mass spectrometry (MS) to provide the current capabilities and developments in proteomics. However, our current knowledge that approximately 30,000 human genes may code for up to 1 million or more proteins disengage the interface between the genome sequence database algorithms and MS to generate a major interest in independent de novo MS/MS sequence determination. Significant progress has been made in this area through procedures to covalently modify peptide N- and C-terminal amino-acids by sulfonation and guanidination to permit rapid de novo sequence determination by MS/MS analysis. A number of strategies that have been developed to perform qualitative and quantitative proteomics range from 2D-gel electrophoresis, affinity tag reagents, and stable-isotope labeling. Those procedures, combined with MS/MS peptide sequence analysis at the subpicomole level, permit the rapid and effective identification and quantification of a large number of proteins within a given biological sample. The identification of proteins per se, however, is not always sufficient to interpret biological function because many of the naturally occurring proteins are post-translationally modified. One such modification is protein phosphorylation, which regulates a large array of cellular biochemical pathways of the biological system. Traditionally, the study of phosphoprotein structure-function relationships involved classical protein chemistry approaches that required protein purification, peptide mapping, and the identification of the phosphorylated peptide regions and sites by N-terminal sequence analysis. Recent advances made in mass spectrometry have clearly revolutionized the studies of phosphoprotein biochemistry, and include the development of specific strategies to preferentially enrich phosphoproteins by covalent-modifications that incorporate affinity tags that use the physicochemical properties of phosphoaminoacids. The phosphoserine/phosphothreonine-containing proteins/peptides are derivatized under base-catalyzed conditions by thiol agents; mono- and di-thiol reagents both have been used in such studies. The thiol agent may have: (i) an affinity tag for protein enrichment; (ii) stable-isotopic variants for relative quantitation; or (iii) a combination of the moieties in (i) and (ii). These strategies and techniques, together with others, are reviewed, including their practical application to the study of phosphoprotein biochemistry and structure-function. The consensus of how classical protein chemistry and current MS technology overlap into special case of proteomics, namely "phosphoproteomics," will be discussed.     

A computationally efficient cohesive zone model for fatigue

A cohesive zone model has been developed for the simulation of both high and low cycle fatigue crack growth. The developed model provides an alternative approach that reflects the computational efficiency of the well‐established envelop‐load damage model yet can deliver the accuracy of the equally well‐established loading‐unloading hysteresis damage model. A feature included in the new cohesive zone model is a damage mechanism that accumulates as a result of cyclic plastic separation and material deterioration to capture a finite fatigue life. The accumulation of damage is reflected in the loading‐unloading hysteresis curve, but additionally, the model incorporates a fast‐track feature. This is achieved by “freezing in” a particular damage state for one loading cycle over a predefined number of cycles. The new model is used to simulate mode I fatigue crack growth in austenitic stainless steel 304 at significant reduction in the computational cost.     

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

     

Schiff bases and their complexes: Recent progress in thermal analysis

Schiff bases are versatile compounds synthesized from the condensation of primary amino compounds with aldehydes or ketones. The high thermal of many Schiff base and their complexes were useful attributes for their application as catalysts in reactions involving at high temperatures. This thermal behavior of Schiff bases and their complexes was evaluated by TGA/DTG and DTA curves with mass losses related to dehydration and decomposition. This review summarizes the developments in the last decade for thermal analysis of Schiff bases. Therefore, synthesis of Schiff bases and their complexes are reviewed.     

The influence of mineral admixtures on the short and long-term performance of concrete

This paper presents a laboratory study on the performance of concrete by adding mineral admixtures, silica fumes (SF) or/and fly ash (FA). Performance of the concrete mixes was determined with short and long-term tests, which include compressive strength, porosity, capillary absorption, wet–dry cycle and accelerated carbonation. The test results, in general, showed that mineral admixtures improved the performance of concretes. SF contributed to both short and long-term properties of concrete, whereas FA shows its beneficial effect in a relatively longer time. As far as the compressive strength is concerned, adding of both SF and FA slightly increased compressive strength, but contributed more to the improvement of transport properties of concretes.     

A newly synthesized single crystal zinc complex as molecular electrocatalyst for efficient hydrogen generation from neutral aqueous solutions

A new chlorobis(2-aminomethylbenzimidazole)zinc(II) perchlorate complex [Zn(AMB)₂Cl](ClO₄) 1 has been synthesized and characterized. Spectral and X-ray structural features led to the conclusion that the zinc(II) complex has a square-pyramidal environment around zinc(II) center with coordination chromophore ZnN₄Cl. Different amounts of complex 1 were supported on glassy carbon (GC) electrode yielding three GC-supported complex 1 electrodes with different loading densities (0.2, 0.4, and 0.8 mg cm^?2). These electrodes were tested as molecular electrocatalysts for the hydrogen evolution reaction (HER) in phosphate buffer aqueous solutions (pH 7), employing linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). Results showed that GC-complex 1 catalysts are highly active for the HER, and this catalytic activity enhances with the loading density. The one with the highest loading density (0.8 mg cm^?2) exhibited high HER catalytic activity with low onset potential of ?140 mV vs. RHE and a high exchange current density of 0.22 mA cm^?2. It required an overpotential of 240 mV to achieve a current density of 10 mA cm^?2. It also recorded a turnover frequency (TOF) of 1722 mol of hydrogen per mole of catalyst per hour at overpotential 500 mV, which is comparable with the most active molecular electrocatalysts reported in the literature for H₂ generation from aqueous neutral solutions. A catalytic cycle is proposed for the generation of hydrogen by complex 1 and the mechanism of the HER is discussed based on the measured Tafel slope (140 mV dec^?1).