Deconvoluting Kinetic Rate Constants of Catalytic Substrates from Scanning Electrochemical Approach Curves with Artificial Neural Networks.

Extracting information from experimental measurements in the chemical sciences typically requires curve fitting, deconvolution, and/or solving the governing partial differential equations via numerical (e.g., finite element analysis) or analytical methods.

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides.

Background: Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational outcomes is a major concern for their implementation. With the rising antibiotic resistance, antimicrobial peptides (AMPs) have increasingly gained attention as novel therapeutic agents.

Antimicrobial peptide similarity and classification through rough set theory using physicochemical boundaries.

Background: Antimicrobial peptides attract considerable interest as novel agents to combat infections. Their long-time potency across bacteria, viruses and fungi as part of diverse innate immune systems offers a solution to overcome the rising concerns from antibiotic resistance. With the rapid increase of antimicrobial peptides reported in the databases, peptide selection becomes a challenge.

Computer-aided Molecular Design of Water Compatible Visible Light Photosensitizers for Dental Adhesive.

Dental adhesive resin undergoes phase separation during its infiltration through the wet demineralized dentin and it has been observed previously that the hydrophilic-rich phase is a vulnerable region for failure due to the lack of photo-polymerization and crosslinking density. The lack of photo-polymerization is mostly due to the partitioning of photo-initiators in low concentrations within this phase. Here, a computational approach has been employed to design candidate water compatible visible light photosensitizers which could improve the photo-polymerization of the hydrophilic-rich phase.

Impact of light intensity on the polymerization kinetics and network structure of model hydrophobic and hydrophilic methacrylate based dental adhesive resin.

The impact of light intensity on the degree of conversion (DC), rate of polymerization and network structure was investigated for hydrophobic and hydrophilic dental adhesive resins. Two and three component photoinitiating (PI) systems were used in this study. Low light intensities had a negative impact on the polymerization efficiency for the hydrophilic resin with 2 component PI system.

Effect of Partition of Photo-initiator Components and Addition of Iodonium Salt on the Photopolymerization of Phase-Separated Dental Adhesive.

The polymerization kinetics of physically separated hydrophobic- and hydrophilic-rich phases of a model dental adhesive have been investigated. The two phases were prepared from neat resin containing 2-hydroxyethyl methacrylate (HEMA) and bisphenol A glycerolate dimethacrylate (BisGMA) in the ratio of 45:55 (wt/wt). Neat resins containing various combinations of popular photo-initiating compounds, e.

Mathematical model of microbicidal flow dynamics and optimization of rheological properties for intra-vaginal drug delivery: Role of tissue mechanics and fluid rheology.

Topically applied microbicide gels can provide a self-administered and effective strategy to prevent sexually transmitted infections (STIs). We have investigated the interplay between vaginal tissue elasticity and the yield-stress of non-Newtonian fluids during microbicide deployment. We have developed a mathematical model of tissue deformation driven spreading of microbicidal gels based on thin film lubrication approximation and demonstrated the effect of tissue elasticity and fluid yield-stress on the spreading dynamics.

Protein aggregation and lyophilization: Protein structural descriptors as predictors of aggregation propensity.

Lyophilization can induce aggregation in therapeutic proteins, but the relative importance of protein structure, formulation and processing conditions are poorly understood. To evaluate the contribution of protein structure to lyophilization-induced aggregation, fifteen proteins were co-lyophilized with each of five excipients. Extent of aggregation following lyophilization, measured using size-exclusion chromatography, was correlated with computational and biophysical protein structural descriptors via multiple linear regression.

Use of glass transitions in carbohydrate excipient design for lyophilized protein formulations.

This work describes an effort to apply methods from process systems engineering to a pharmaceutical product design problem, with a novel application of statistical approaches to comparing solutions. A computational molecular design framework was employed to design carbohydrate molecules with high glass transition temperatures and low water content in the maximally freeze-concentrated matrix, with the objective of stabilizing lyophilized protein formulations. Quantitative structure-property relationships were developed for glass transition temperature of the anhydrous solute, glass transition temperature of the maximally concentrated solute, melting point of ice and Gordon-Taylor constant for carbohydrates.

Adhesive/Dentin interface: the weak link in the composite restoration.

Results from clinical studies suggest that more than half of the 166 million dental restorations that were placed in the United States in 2005 were replacements for failed restorations. This emphasis on replacement therapy is expected to grow as dentists use composite as opposed to dental amalgam to restore moderate to large posterior lesions. Composite restorations have higher failure rates, more recurrent caries, and increased frequency of replacement as compared to amalgam.