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A demonstration of the presence of metal in salts due to reduction of metal cation is described. The heat coming from a Meeker burner leads to the decomposition of copper formate in a round-bottom flask. Nitric acid can be used for removing the bright copper mirror.

A simple lecture demonstration is described to show the latent presence of metal atoms in a metal salt. Copper(II) formate tetrahydrate is heated in a round-bottom flask forming a high-quality copper mirror.

The preparation of a large number of very stable metal-organic networks via aqueous reaction of CuCN with N-substituted piperazines and hexamethylenetetramine (HMTA) is described. The products have a very common structural network of hexagonally tiled (6,3) sheet composed of CuCN chains cross-linked by L giving rise to 2:1 CuCN/L (CuCN = N-phenylpiperazine and L = pip, [Me.sub.2]Pip, 1,4-butanediamine, and N,N,N',N'-tetramethylethylenediamine) stoichiometry.

The global media system during the mid - 19th century and the 1920s and the rise of globalization is studied. The era between 1907 and 1923, a second moment in long standing efforts to change the way the global media system of the time was owned, regulated and used is explored.

The hydrolysis of substrates representing cleavage sequences in the physiological substrates for Clr and Cls is examined. The importance of prime subsites in Cls for interaction with its cognate substrates in the complement pathway yielding greater understanding of the mechanism of interaction between the vital protease and its physiological substrates is highlighted.

A study conducted to map the preference of the gingipain-R enzymes for prime site amino acid residues in peptide substrates is presented. It was found that the gingipains were relatively nonspecific for these residues and that no marked difference in specificity could be found between different forms of the gingpains-R.

Results indicate that the Phe77 to Leu mutation in the shutter region of the serine proteinase inhibitor, antithrombin, results in conformational changes around the D-helix top of the inhibitor involving arginine 132 and 133 residues, which mediate antithrombin/heparin interactions.

Research has been conducted on serpin superfamily member hurpin, linked to human keratinocyte apoptosis. Results deminstrate that hurpin is an inhibitor of the archetypal lysosome cysteine proteinase cathepsin L.

The roles of proteolytic cleavage have been intensively investigated and discussed during the past two decades. This irreversible chemical process has been frequently reported to influence a number of crucial biological processes (BPs), such as cell cycle, protein regulation and inflammation. A number of advanced studies have been published aiming at deciphering the mechanisms of proteolytic cleavage. Given its significance and the large number of functionally enriched substrates targeted by specific proteases, many computational approaches have been established for accurate prediction of protease-specific substrates and their cleavage sites. Consequently, there is an urgent need to systematically assess the state-of-the-art computational approaches for protease-specific cleavage site prediction to further advance the existing methodologies and to improve the prediction performance. With this goal in mind, in this article, we carefully evaluated a total of 19 computational methods (including 8 scoring function-based methods and 11 machine learning-based methods) in terms of their underlying algorithm, calculated features, performance evaluation and software usability. Then, extensive independent tests were performed to assess the robustness and scalability of the reviewed methods using our carefully prepared independent test data sets with 3641 cleavage sites (specific to 10 proteases). The comparative experimental results demonstrate that PROSPERous is the most accurate generic method for predicting eight protease-specific cleavage sites, while GPS-CCD and LabCaS outperformed other predictors for calpain-specific cleavage sites. Based on our review, we then outlined some potential ways to improve the prediction performance and ease the computational burden by applying ensemble learning, deep learning, positive unlabeled learning and parallel and distributed computing techniques. We anticipate that our study will serve as a practical and useful guide for interested readers to further advance next-generation bioinformatics tools for protease-specific cleavage site prediction. [ABSTRACT FROM AUTHOR]