Templated Nucleation of Clotrimazole and Ketoprofen on Polymer Substrates.

The use of different template surfaces in crystallization experiments can directly influence the nucleation kinetics, crystal growth, and morphology of active pharmaceutical ingredients (APIs). Consequently, templated nucleation is an attractive approach to enhance crystal nucleation kinetics and preferentially nucleate desired crystal polymorphs for solid-form drug molecules, particularly large and flexible molecules that are difficult to crystallize. Herein, we investigate the effect of polymer templates on the crystal nucleation of clotrimazole and ketoprofen with both experiments and computational methods. Crystallization was carried out in toluene solvent for both APIs with a template library consisting of 12 different polymers. In complement to the experimental studies, we developed a computational workflow based on molecular dynamics (MD) and derived descriptors from the simulations to score and rank API-polymer interactions. The descriptors were used to measure the energy of interaction (EOI), hydrogen bonding, and rugosity (surface roughness) similarity between the APIs and polymer templates. We used a variety of machine learning models (14 in total) along with these descriptors to predict the crystallization outcome of the polymer templates. We found that simply rank-ordering the polymers by their API-polymer interaction energy descriptors yielded 92% accuracy in predicting the experimental outcome for clotrimazole and ketoprofen. The most accurate machine learning model for both APIs was found to be a random forest model. Using these models, we were able to predict the crystallization outcomes for all polymers. Additionally, we have performed a feature importance analysis using the trained models and found that the most predictive features are the energy descriptors. These results demonstrate that API-polymer interaction energies are correlated with heterogeneous crystallization outcomes.

A Fruit-Expressed MYB Transcription Factor Regulates Anthocyanin Biosynthesis in Atropa belladonna.

Anthocyanins are water-soluble flavonoid pigments that play a crucial role in plant growth and metabolism. They serve as attractants for animals by providing plants with red, blue, and purple pigments, facilitating pollination and seed dispersal. The fruits of solanaceous plants, tomato (Solanum lycopersicum) and eggplant (Solanum melongena), primarily accumulate anthocyanins in the fruit peels, while the ripe fruits of Atropa belladonna (Ab) have a dark purple flesh due to anthocyanin accumulation. In this study, an R2R3-MYB transcription factor (TF), AbMYB1, was identified through association analysis of gene expression and anthocyanin accumulation in different tissues of A. belladonna. Its role in regulating anthocyanin biosynthesis was investigated through gene overexpression and RNA interference (RNAi). Overexpression of AbMYB1 significantly enhanced the expression of anthocyanin biosynthesis genes, such as AbF3H, AbF3'5'H, AbDFR, AbANS, and Ab3GT, leading to increased anthocyanin production. Conversely, RNAi-mediated suppression of AbMYB1 resulted in decreased expression of most anthocyanin biosynthesis genes, as well as reduced anthocyanin contents in A. belladonna. Overall, AbMYB1 was identified as a fruit-expressed R2R3-MYB TF that positively regulated anthocyanin biosynthesis in A. belladonna. This study provides valuable insights into the regulation of anthocyanin biosynthesis in Solanaceae plants, laying the foundation for understanding anthocyanin accumulation especially in the whole fruits of solanaceous plants.

Cleaning Oil-Based Drilling Cuttings with Synthetic Gemini Surfactants.

The chemical cleaning method is the simplest approach for degreasing oil-based drilling cuttings (ODCs), with the effectiveness of the treatment relying mainly on the selection of the surfactant and the cleaning conditions. However, achieving the standard treatment of ODCs directly using conventional surfactants proves challenging. In light of this, this study introduces a synthesized and purified Gemini surfactant named DCY-1. The structure of DCY-1 was confirmed through Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) analyses. The characterization in this article encompasses the use of an interface tension meter, nanoparticle size analysis, scanning electron microscopy, and infrared oil measurement. The critical micelle concentration (CMC) of DCY-1 was determined to be 3.37 × 10-3 mol/L, with a corresponding γcmc value of 37.97 mN/m. In comparison to conventional surfactants, DCY-1 exhibited a larger micelle size of 4.52 nm, approximately 24.52% larger than that of SDS. Moreover, the residual oil rate of 3.96% achieved by DCY-1 was the lowest among the chemical cleaning experimental results. Through a single-factor experiment, the optimal cleaning ability of DCY-1 for ODCs was determined as follows: a surfactant concentration of 3 mmol/L, a temperature of 60 °C, an ODC/liquid mass ratio of 1:4, a cleaning duration of 40 min, and a stirring speed of 1000 rad/min. Under these optimal conditions and after merely two cleaning procedures, the residual oil content of ODCs was reduced to 1.64%, accompanied by a smooth and loose surface structure.