Crystallization is an attractive alternative for protein-based therapeutic formulations since the crystalline form offers improved stability, longer storage lifetime, and enables controlled release of the active ingredient. 90% of the active drug ingredients are produced in the crystalline form within the biopharmaceutical industry. However, several problems have recently emerged related to the process manufacturing (i.e., handling and delivering) of these formulations. The occurrence of aggregation/ agglomeration events is frequent and may induce shear viscosity increases. Herein, a rheological characterization combined with the analysis of insulin behavior in solution is addressed in the presence of a precipitant solution: zinc-providing salt (zinc chloride) combined with a buffer (trisodium citrate) and a co-solvent (acetone). While the independent solutions (insulin and precipitant) exhibit a Newtonian behavior, their mixture results in a shear-thinning response within broad ranges of protein concentration and temperature. The transition to a Newtonian response is only captured at high temperature values. Rhombohedral crystals with variable size and number are produced for the studied working conditions, except at low precipitant concentrations, where aggregation/agglomeration events are observed, followed by sudden shear viscosity increases over time. Moreover, the critical shear rate to generate single large insulin crystals is optimized alongside the shear viscosity analysis. This has been observed for both single-and double-shearing experiments. During the double-shearing experiments, the protein solutions are exposed to sudden changes in shear rate, which might disturb the molecular arrangement. However, the crystallization outcome seems to be similar compared to the single-shearing experiments. Lastly, this work highlights a strategy to induce insulin crystallization under uniform shearing fields, which can be extended to other therapeutic proteins.

Opuntia species are well-known for their use in folk medicine and richness in many bioactive compounds. This study aims to realize a taxonomic study and to evaluate the polyphenols content and antioxidant potential of edible parts of cultivated and wild Opuntia sp. fruits, using different in-vitro bioassays. The phylogenetic analysis confirmed the assignment of the samples to Opuntia genera. The Opuntia fruit fractions (seeds, pulp, and entire fruit) exhibited different amounts of polyphenols, with the highest values recorded for the wild species, and particularly their pulp (1140.86 mg GAE/100 g DM, and 155.62 QE/100 g DM for total phenolic and flavonoid compounds, respectively). Among the antioxidant activities, wild pulp exhibited the greatest antioxidant potential with a high radical scavenging activity (72.34% and 92.12% for hydrogen peroxide and hydroxyl radicals, respectively). The best nitric oxide scavenging activity was found for cultivated fruit fraction, with 55.22%. The statistical analysis also confirmed a significant correlation between the antioxidant activities and the phenolic compounds and flavonoids (>0.90, p ≤ 0.001) in all Opuntia extracts. Finally, both Opuntia fruits demonstrated a good antioxidant potential, enhancing the interest of this species as a non-pharmacological approach in a wide variety of disorders and diseases associated with oxidative stress, and paving the way to Opuntia sp. economic valorization.

Bacterial biofilms are a source of infectious human diseases and are heavily linked to antibiotic resistance. Pseudomonas aeruginosa is a multidrug-resistant bacterium widely present and implicated in several hospital-acquired infections. Over the last years, the development of new drugs able to inhibit Pseudomonas aeruginosa by interfering with its ability to form biofilms has become a promising strategy in drug discovery. Identifying molecules able to interfere with biofilm formation is difficult, but further developing these molecules by rationally improving their activity is particularly challenging, as it requires knowledge of the specific protein target that is inhibited. This work describes the development of a machine learning multitechnique consensus workflow to predict the protein targets of molecules with confirmed inhibitory activity against biofilm formation by Pseudomonas aeruginosa. It uses a specialized database containing all the known targets implicated in biofilm formation by Pseudomonas aeruginosa. The experimentally confirmed inhibitors available on ChEMBL, together with chemical descriptors, were used as the input features for a combination of nine different classification models, yielding a consensus method to predict the most likely target of a ligand. The implemented algorithm is freely available at https://github.com/BioSIM-Research-Group/TargIDe under licence GNU General Public Licence (GPL) version 3 and can easily be improved as more data become available.

This study proposes an alternate method for the analysis of beams with solid cross‐section or built as a framed structure and subjected to transverse impact loads from an external striker. The procedure used in the analysis is a combination of two essential tools using pseudo‐dynamic techniques. The method reported here involves only one degree of freedom for the structure modelling and assumes an elastic contact between an external striker and the beam structure, which in reality does not happen. As only one degree of freedom is considered in the analysis, some important limitations are inherent to the method proposed here. Essentially, there is the difficulty of modelling the displacement field associated with the transient structure behaviour accurately, as a consequence of fast‐rate impact loads. Another difficulty faced by the method refers to a local structure behaviour associated with contact loads. The present method can deal with large displacements in transversely loaded beams associated to a collapse mechanism having a simple geometry and defined with precision from a single parameter. This ensures reasonable accuracy in the evaluation of the strain energy absorbing capacity of transversely impacted beam structures using a single degree of freedom model in a pseudo‐dynamic procedure.