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Municipal solid waste (MSW) is one of the issues associated with the growth of economic and urban population. The aim of this study is to develop an integrated design of waste management systems in support of a Circular Economy by P-graph (a bipartite graphical optimisation tool) as an effective decision support tool. The case study considers four MSW compositions based on different country income levels. Solving the P-graph model identifies the most suitable treatment approaches, considering the economic balance between the main operating cost, type, yield, quality of products, as well as the GHG emission (externality cost). The identification of near-optimal solutions by P-graph is useful in dealing with the trade-offs between conflicting objectives, e.g. local policy and practical implementation, that are difficult to monetise. For a lower-income country, the optimal solution includes a combination of at source separation, recycling, incineration (heat, electricity), anaerobic digestion (biofuel, digestate) and the landfill. It avoids an estimated 411 kg CO 2eq /t of processed MSW and achieves a potential profit of 42 €/t of processed MSW. The optimisation generally favours mechanical biological treatment as the country income level rises, which affects the composition of the MSW. The relative prices of biofuel, electricity and heat (>20%) cause a significant impact on the highest-ranking treatment structure and overall profit. This study shows that the developed framework by P-graph is an effective tool for MSW systems planning. For future study, localised data inputs can be fed into the proposed framework for a customised solution and economic feasibility assessment., (Copyright © 2019 Elsevier B.V. All rights reserved.)

A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided.

Cell robustness and complexity have been recognized as unique features of biological systems. Such robustness and complexity of metabolic-reaction systems can be explored by discovering, or identifying, the multiple flux distributions (MFD) and redundant pathways that lead to a given external state; however, this is exceedingly cumbersome to accomplish. It is, therefore, highly desirable to establish an effective computational method for their identification, which, in turn, gives rise to a novel insight into the cellular function. An effective approach is proposed for complementarily identifying MFD in metabolic flux analysis and multiple metabolic pathways (MMP) in structural pathway analysis. This approach judiciously integrates flux balance analysis (FBA) based on linear programming and the graph-theoretic method for determining reaction pathways. A single metabolic pathway, with the concomitant flux distribution and the overall reaction manifesting itself as the desired phenotype under some environmental conditions, is determined by FBA from the initial candidate sequence of metabolic reactions. Subsequently, the graph-theoretic method recovers all feasible MMP and the corresponding MFD. The approach's efficacy is demonstrated by applying it to the in silico Escherichia coli model under various culture conditions. The resultant MMP and MFD attaining a unique external state reveal the surprising adaptability and robustness of the intricate cellular network as a key to cell survival against environmental or genetic changes. These results indicate that the proposed approach would be useful in facilitating drug discovery.

Structure-activity relationships of aryl alkynyl synergists of the general formula of Ar-Q-R, where Q represents a bridging structure, were studied using a standardised testing system and Relative Potency values. Ethers, esters, oxime ethers, amides and amines were prepared and evaluated. The length of the R-alkynyl chain, the role of the bridge and the substitution of the aromatic ring were examined systematically. The most potent compounds possessed an aromatic ring connected via a bridge of three atoms to an alkynyl chain, forming together a linear side-chain of six atoms. Several highly potent compounds were synthesised of which one (MB-599; proposed common name verbutin) was selected for development as a selective insecticide synergist in crop protection. Its high potential at practical insecticide:synergist ratios makes possible the reduction of the total amount of insect-control chemicals applied, and its use as an additive to produce new formulations of existing insecticides makes it highly advantageous in resistance management, giving a new tool to sustain the effectiveness of a wide range of insecticides. A product containing a (1+1) mixture of verbutin and beta-cypermethrin was launched in Hungary in 2002.

Cross-substituted derivatives of piperonyl butoxide (PBO) and MB-599 (proposed common name: verbutin) were synthesized and investigated as carbofuran and permethrin synergists against housefly, Musca domestica L. The majority of PBO and MB-599 derivatives were significantly more potent synergists for carbofuran than for permethrin. PBO, the most important representative of this series was not the most potent synergist for carbofuran or for permethrin. Cleavage of the methylenedioxy ring of methylenedioxyphenyl (MDP) polyether compounds resulted in complete loss of synergistic activity with both insecticides, but it could be restored or even improved by incorporating an alkynyl ether moiety into the molecule. The improved synergistic activity was found to be closely associated with the 2-butynyloxymethyl side-chain, suggesting that this can be regarded as a characteristic synergophore group. MB-599, one of the most promising compounds bearing this group showed considerably higher activity with carbofuran (synergist ratio, SR = 37.8) than with PBO (SR = 6.4). There was no significant difference between synergistic activities of MB-599 (SR = 4.6) and PBO (SR = 4) for permethrin.

Cytochrome P450 (CP450) catalyzed oxidative metabolism of carbofuran (1), carbaryl (2), and pirimicarb (3) has been modeled using biomimetic oxidations catalyzed by iron(III) tetraarylporphyrins. Oxidation products of 1 were identified by comparison of HPLC retention times measured under standardized conditions for metabolites synthesized and characterized by (1)H and (13)C NMR spectroscopy. Comparison of product distributions to in vivo metabolic profiles revealed that the H(2)O(2)/meso-tetrakis(pentafluorophenyl)porphyrin iron(III) chloride [Fe(TF(20)PP)] system mimics the action of insect CP450s against carbofuran. The effectiveness of this system was further demonstrated by the biomimetic oxidation of other carbamate insecticides (2 and 3) monitored by HPLC/electrospray MS. The predictive power of this biomimetic model was compared to that of knowledge-based expert systems. Although similar models were recently applied in pharmaceutical research, the usefulness of this approach has first been demonstrated for the prediction of metabolic profiles of agrochemicals.

Serum contains a factor that can normalize streptozotocin induced blood sugar elevation. This normalization can last for a long period. Thus an elimination of elevated diabetic blood sugar values takes place. This means that an euglycemic factor may have the ability to an eventual curing of diabetes. Normal, starving rats are not influenced by the euglycemic factor. An other factor even aggravates diabetic blood sugar level.