A theory of finite tensile deformation of double-network hydrogels

A continuum damage model was developed to describe the finite tensile deformation of tough double-network (DN) hydrogels synthesized by polymerization of a water-soluble monomer inside a highly crosslinked rigid polyelectrolyte network. Damage evolution in DN hydrogels was characterized by performing loading-unloading tensile tests and oscillatory shear rheometry on DN hydrogels synthesized from 3-sulfopropyl acrylate potassium salt (SAPS) and acrylamide (AAm). The model can explain all the mechanical features of finite tensile deformation of DN hydrogels, including idealized Mullins effect and permanent set observed after unloading, qualitatively and quantitatively. The constitutive equation can describe the finite elasto-plastic tensile behavior of DN hydrogels without resorting to a yield function. It was showed that tensile mechanics of DN hydrogels in the model is controlled by two material parameters which are related to the elastic moduli of first and second networks. In effect, the ratio of these two parameters is a dimensionless number that controls the behavior of material. The model can capture the stable branch of material response during neck propagation where engineering stress becomes constant. Consistent with experimental data, by increasing the elastic modulus of the second network the finite tensile behavior of the DN hydrogel changes from necking to strain hardening.     

Influence of oxygen on soot formation during acetylene pyrolysis

Kinetic modeling of pyrolysis of acetylene diluted with argon showed a strong influence of small additives of oxygen on the routes of formation of soot nuclei. The influence of oxygen on various channels of formation and consumption of propargyl radicals C₃H₃, which are important precursors of soot formation, as well as the fundamental possibility of controlling the process of soot formation and its properties are considered.     

Salesforce contracting under model uncertainty

This paper considers a firm's salesforce contracting problem under model uncertainty. Based on the notion of multiplier preferences, we capture model uncertainty and explicitly characterize the structure of the optimal contract. Our findings provide guidelines on the design of salesforce compensation contracts in practical situations.     

数学建模对高中生构建数学底层思维的作用及其教学实施建议

数学底层思维即用数学的眼光观察世界、用数学的思维分析世界以及用数学的语言表达世界,是人们面对自然和社会中纷繁多样的现象和问题时,所展现的自发的、不依赖监督的、融汇数学学科核心素养的思维方式.作为国家高中新课程标准中数学六大核心素养之一的数学建模,是培养学生数学底层思维的良好载体,对人才培养和社会发展均起到良好的促进作用.本文主要阐述了数学建模对高中生构建数学底层思维的作用,并结合教学实例给出教学实施建议.     

Acetylcholinesterase inhibitory activities and bioguided fractionation of the Ocotea percoriacea extracts: HPLC-DAD-MS/MS characterization and molecular modeling of their alkaloids in the active fraction

In vitro acetylcholinesterase activities of the hexane, dichloromethane, ethyl acetate, n-butanol and aqueous extracts of leaves of Ocotea percoriacea Kosterm. (Lauraceae) were evaluated. The bioguided fractionation of the most active extract (dichloromethane) using silica gel open-column chromatography led to an active alkaloidal fraction composed of isocorydine N-oxide, isocorydine N-oxide derivative, palmatine, roemerine and roemerine N-Oxide. The identification of the chemical structure of these compounds was carried out with high-performance liquid chromatography coupled to electrospray ionization multiple-stage mass spectrometry (HPLC-ESI-MS/MS). Aiming to understand their inhibitory activities, these alkaloids were docked into a 3D model of Electrophorus electricus Acetylcholinesterase (EelAChE) built in the Modeller 9.18 employing homology modeling approach. The results suggest that the alkaloids had the same binding mode and, possibly, the inhibition mechanism of classic drugs (ex. tacrine and donepezil). The structural difference of these compounds opens a new opportunity for the optimization of leading compounds.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

Modeling of Anionic Polymerization of Isoprene in an Industrial Reactor

One of the most important reasons for modeling polymerization processes is to provide a tool for estimating the risks of runaway reactions in polymer industry. This is especially important for batch processes, such as anionic polymerization of isoprene or butadiene. This work presents a theoretical and experimental research of the anionic polymerization of isoprene using cyclohexane as solvent and n‐butyllithium as initiator. In the first part, a phenomenological kinetic expression is obtained that describes the anionic polymerization of isoprene initiated by n‐butyllithium in cyclohexane. In the second, the mass and energy balance equations are solved to model the anionic polymerization of isoprene in a quasi‐adiabatic batch reactor. Adjustment of reactor parameters is made using the data obtained from a laboratory reactor. The proposed model predicts adequately the obtained temperature, pressure, and conversion profiles from this set of experiments. Finally, a mathematical model is developed to predict the behavior for the anionic polymerization of isoprene in an industrial reactor.     

Controlled-advancement rigid-body optimization of nanosystems

In this study, we propose a novel optimization algorithm, with application to the refinement of molecular complexes. Particularly, we consider optimization problem as the calculation of quasi-static trajectories of rigid bodies influenced by the inverse-inertia-weighted energy gradient and introduce the concept of advancement region that guarantees displacement of a molecule strictly within a relevant region of conformational space. The advancement region helps to avoid typical energy minimization pitfalls, thus, the algorithm is suitable to work with arbitrary energy functions and arbitrary types of molecular complexes without necessary tuning of its hyper-parameters. Our method, called controlled-advancement rigid-body optimization of nanosystems (Carbon), is particularly useful for the large-scale molecular refinement, as for example, the putative binding candidates obtained with protein–protein docking pipelines. Implementation of Carbon with user-friendly interface is available in the SAMSON platform for molecular modeling at https://www.samson-connect.net . © 2019 Wiley Periodicals, Inc.     

Influence of weak groups on polyelectrolyte mobilities

The ionization of dissociable groups in weak polyelectrolytes does not occur in a homogenous fashion. Monomer connectivity imposes constraints on the localization of the dissociated (charged) monomers that affect the local electric potential. As a result, the mean bare charge along a weak polyelectrolyte can vary depending on the proximity to topological features (e.g. presence of crosslinks or dangling ends). Using reaction‐ensemble Monte‐Carlo simulations we calculate the dissociation inhomogeneities for a few selected PE configurations, linear, rod‐like, flexible four‐arm star, and a star with stiff arms. An ensemble preaverage is used to obtain the annealed bare charge profile for these different polymer configurations. Using molecular dynamics simulations within a Lattice‐Boltzman fluid, we investigate how the electrophoretic mobility is affected by the bare charge inhomogeneities arising from the annealed weak polyelectrolytes. Surprisingly, the mobility obtained for the situations corresponding to the predicted charge profile for annealed weak polyelectrolytes are not significantly different than the mobility obtained when all the monomers have an identical charge (under the constraint that the total polyelectrolyte bare charge is the same). This is also true for the stiff rod‐like variants where conformational changes induced from the localization of the monomer charges are negligible. In salty solutions, we find that counterions are affected by the electric potential modulations induced by the topological features. Since the counterions crowd in regions where the electric potential caused by the dissociated monomers is highest, they wash‐out the bare charge inhomogeneities and contribute to a more uniform effective backbone charge.     

In silico identification of natural products with anticancer activity using a chemo-structural database of Brazilian biodiversity

Cancer is one of the leading causes of death worldwide, and the number of patients has only increased each year, despite the considerable efforts and investments in scientific research. Since natural products (NPs) may serve as suitable sources for drug development, the cytotoxicity against cancer cells of 2221 compounds from the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE_DB) was predicted using CDRUG algorithm. Molecular modeling, chemoinformatics, and chemometric tools were then used to analyze the structural and physicochemical properties of these compounds. We compared the positive NPs with FDA-approved anticancer drugs and predicted the molecular targets involved in the anticancer activity. In the present study, 46 families comprising potential anticancer compounds and at least 19 molecular targets involved in oncogenesis. To the best of our knowledge, this is the first large-scale study conducted to evaluate the potentiality of NPs sourced from Brazilian biodiversity as anticancer agents, using in silico approaches. Our results provided interesting insights about the mechanism of action of these compounds, and also suggested that their structural diversity may aid structure-based optimization strategies for developing novel drugs for cancer therapy.