4% compared to 10.5% in the binary BHJ cell).Stress testing of active pharmaceutical ingredients (API) is an important tool used to gauge chemical stability and identify potential degradation products. While different flavors of API stress testing systems have been used in experimental investigations for decades, the detailed kinetics of such systems as well as the chemical composition of prominent reactive species, specifically reactive oxygen species, are unknown. As a first step toward understanding and modeling API oxidation in stress testing, we investigated a typical radical "soup" solution an API is subject to during stress testing. Here we applied ab initio electronic structure calculations to automatically generate and refine a detailed chemical kinetics model, taking a fresh look at API oxidation. We generated a detailed kinetic model for a representative azobis(isobutyronitrile) (AIBN)/H2O/CH3OH stress-testing system with a varied cosolvent ratio (50%/50%-99.5%/0.5% vol water/methanol) for 5.0 mM AIBN and representative pH values of 4-10 at 40 °C that was stirred and open to the atmosphere. https://www.selleckchem.com/Bcl-2.html At acidic conditions, hydroxymethyl alkoxyl is the dominant alkoxyl radical, and at basic conditions, for most studied initial methanol concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl radical, albeit at an overall lower concentration. At acidic conditions, the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl radicals are relatively high and comparable, while, at both neutral and basic pH conditions, superoxide becomes the prominent radical in the system. The present work reveals the prominent species in a common model API stress testing system at various cosolvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates the usage of novel software tools for automated chemical kinetic model generation and ab initio refinement.Ion-specific induced changes of the ζ-potential of phospholipid vesicles are commonly used to quantify the affinity of different ions to the lipid interface. The negative ζ-potential of zwitterionic net-neutral phospholipid vesicles in neat water, which changes sign and increases in solutions of NaCl or KCl, is a phenomenon consistently observed in experiments but not fully understood theoretically. Using atomistic molecular dynamics simulations in the presence of applied electric fields which drive electroosmotic flows, in combination with an electrostatic continuum model based on the modified Poisson-Boltzmann and Helmholtz-Smoluchowski equations, we study the electrokinetic and electrostatic properties as well as the specific ion affinities to the phospholipid-water interface, in order to resolve these puzzling observations. Our modified continuum equations account for the dielectric profile at the lipid-water interface, ion-specific interactions between ions and the lipid-water interface, and the interfacial viscosity profile, which are all extracted from our atomistic simulations and rather accurately predict ion-density and electrostatic-potential distributions as well as ζ-potentials in comparison with our atomistic simulations. Our continuum model can explain experimental ζ-potentials only when we assume minute amounts of surface-active anionic impurities in the aqueous solution. In fact, the amount of impurities needed to explain the experimental data increases linearly with the salt concentration, suggesting that surface-active species, which might be already present in the lab water or lipid samples, could further be introduced through the added salt.Chitosan-coated nanoparticles are a promising class of drug delivery vehicles that have been studied as tools for improving the gastrointestinal delivery of therapeutics. Here we present an analysis of chitosan-coated nanoparticles with an emphasis on characterizing the chitosan polymer properties. Cationic nanoparticles are produced by adsorbing a layer of chitosan HCl on an anionic (-40 mV ζ-potential) polyacrylic acid (PAA) coated primary nanoparticle. Commercially available chitosan (90% deacetylated) must be processed into a nearly completely deacetylated HCl salt form (99% deacetylation); otherwise, primary nanoparticle aggregation occurs. Deacetylated chitosan HCl produces stable, cationic (+35 mV ζ-potential) nanoparticles within 10% of the original anionic particle hydrodynamic diameter at a 12 molar ratio of chitosan glucosamine HCl monomers to PAA acrylic acid monomers.Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to predict only a specific type of residue-level attribute. In this work, we develop a new deep-learning method, named Membrane Association and Secondary Structure Predictor (MASSP), for accurately predicting both residue-level structural attributes (secondary structure, location, orientation, and topology) and protein-level structural classes (bitopic, α-helical, β-barrel, and soluble). MASSP integrates a multilayer two-dimensional convolutional neural network (2D-CNN) with a long short-term memory (LSTM) neural network into a multitasking framework. Our comparison shows that MASSP performs equally well or better than the state-of-the-art methods in predicting residue-level secondary structures, boundaries of transmembrane segments, and topology. Furthermore, it achieves outstanding accuracy in predicting protein-level structural classes. MASSP automatically distinguishes the structural classes of input sequences and identifies transmembrane segments and topologies if present, making it broadly applicable to different classes of proteins. In summary, MASSP's good performance and broad applicability make it well suited for annotating residue-level attributes and protein-level structural classes at the proteome scale.The shaping of metal-organic frameworks (MOFs), referring to the integration of small sub-millimeter MOF crystals into bulk samples of desired size and shape, is an important step in the practical use of this class of porous material in many applications. Herein, we demonstrate for the first time the fabrication of hierarchical 3D MOF monoliths in situ within an MOF particle-stabilized high internal phase emulsion (HIPE). In this approach, a subfamily MOF (ZIF-8) is selected as the sole Pickering emulsion stabilizer for an oil-in-water (O/W) HIPE. With 2-methylimidazole and zinc nitrate in the continuous phase, ZIF-8 is formed in the emulsion to "bond" the ZIF-8 particles fabricating a ZIF-8 monolith without the addition of a polymer or polymerization of monomers. Freeze-drying of the HIPE produces a 3D ZIF-8 monolith. The monolith is packed into a chromatography column to test its catalytic performance as a flow-through catalyst in the Knoevenagel reaction. The monolith catalyst exhibits very high catalytic efficiency.