Optimizing microfluidic preparation parameters of nanosuspension to evaluate stability in nanoprecipitation of stable-iodine (127I)

Controlled preparation of curcumin nanocrystals by detachable stainless steel microfluidic chip

Microfluidic technology has not been extensively utilized in nanocrystals manufacture, although it has been used in the production of liposomes and LNPs. This is mainly due to concerns including blockage of narrow pipes and corrosion of organic solvents on chips. In this study, a detachable stainless steel microfluidic chip with split-and-recombine (SAR) structure was engraved and used to prepare curcumin nanocrystal suspensions by a microfluidic-antisolvent precipitation method. A simulation study of the mixing activities of three chip structures was conducted by COMSOL Multiphysics software. Then the curcumin nanocrystals preparation was optimized by Box-Behnken design to screen different stabilizers and solvents. Two curcumin nanocrystals formulations with an average particle size of 59.29 nm and 168.40 nm were obtained with PDIs of 0.131 and 0.058, respectively. Compared to curcumin powder, the formulation showed an increase in dissolution rate in 0.1 M HCL while pharmacokinetic study indicated that Cmax was increased by 4.47 and 3.14 times and AUC0-∞ were 4.26 and 3.14 times greater. No clogging or deformation of the chip was observed after long usage. The results demonstrate that the stainless steel microfluidic chips with SAR structure have excellent robustness and controllability. It has the potential to be applied in GMP manufacturing of nanocrystals.

Artificial neural network modelling hydrodenticity for optimal design by microfluidics of polymer nanoparticles to apply in magnetic resonance imaging

The engineering of nanoparticles impacts the control of their nano-bio interactions at each level of the delivery pathway. Therefore, optimal nanoparticle physicochemical properties should be identified to favour on-target interactions and deliver efficiently active compounds to a specific target. To date, traditional batch processes do not guarantee the reproducibility of results and low polydispersity index of the nanostructures, while microfluidics has emerged as cost effectiveness, short-production time approach to control the nanoparticle size and size distribution. Several thermodynamic processes have been implemented in microfluidics, such as nanoprecipitation, ionotropic gelation, self-assembly, etc., to produce nanoparticles in a continuous mode and high throughput way.   In this work, we show how the Artificial Neural Network (ANN) can be adopted to model the impact of microfluidic parameters (namely, flow rates and polymer concentrations) on the size of the nanoparticles. Promising results have been obtained, with the highest model accuracy reaching 98.9 %, thus confirming the proposed approach's potential applicability for an ANN-guided biopolymer nanoparticle design for biomedical applications. Nanostructures with different degrees of complexity are analysed, and a proof-of-concept machine learning approach is proposed to evaluate Hydrodenticity in biopolymer matrices. STATEMENT OF SIGNIFICANCE: Size, shape and surface charge determine nano-bio interactions of nanoparticles and their ability to target diseases. The ideal nanoparticle design avoids off-target interactions and favours on-target interactions. So, tools enabling the identification of the optimal nanoparticle physicochemical properties for delivery to a specific target are required. In this work, we evaluate the use of Artificial Neural Network (ANN) to analyse the role of microfluidic parameters in predicting the optimal size of the different hydrogel nanoparticles and their ability to trigger Hydrodenticity.

Bioactivity and safety evaluations of Cupressus sempervirens essential oil, its nanoemulsion and main terpenes against Culex quinquefasciatus Say

The essential oil (EO) of Cupressus sempervirens was obtained by hydrodistillation and analysed using gas chromatography-flame ionization detection (GC-FID) and gas chromatography-mass spectrometry (GC-MS). Two monoterpenes, α-pinene (49.1%) and δ-3-carene (21.4%), and one sesquiterpene hydrocarbon, α-cedrol (5.1%), were isolated as the EO major terpenes. An oil-in-water nanoemulsion (particle size 71.2 nm) was produced from the EO through a low-energy method. The EO, its nanoemulsion and its main constituents showed mosquitocidal and biochemical effects against Culex quinquefasciatus Say, the common vector of lymphatic filariasis parasites. All treatments showed dose-dependent bioactivity, and adults were more susceptible to the EO products than the larvae. The nanoemulsion showed superior activity, followed by the crude EO and α-cedrol. At 40 μg/ml, the nanoemulsion caused 100% larval mortality, while the EO and α-cedrol required twice this concentration to achieve the same larval mortality. The LC₅₀ values were 8.4, 16.1, 15.1, 30.7 and 53.4 μg/ml at 24 h after exposure for the nanoemulsion, crude oil, α-cedrol, δ-3-carene and α-pinene, respectively. For adults, 20.0 μl/l nanoemulsion caused 100% mortality, while twice this concentration of the EO was required to achieve the same effect. The LC₅₀'s against adults ranged between 6.2 and 40.4 μl/l. EO products prominently repelled mosquitoes at concentrations between 0.75 and 6.0 μl/cm². The EO products caused remarkable inhibition of Cx. quinquefasciatus acetylcholinesterase activity but were safer towards the non-target aquatic species Gambusia affinis. These results recommend the use of C. sempervirens EO, its nanoemulsion and main terpenes as natural tools to control Cx. quinquefasciatus.