Machine Learning-Aided Microdroplets Breakup Characteristic Prediction in Flow-Focusing Microdevices by Incorporating Variations of Cross-Flow Tilt Angles.

Controlling droplet breakup characteristics such as size, frequency, regime, and droplet quality within flow-focusing microfluidic devices is critical for different biomedical applications of droplet microfluidics such as drug delivery, biosensing, and nanomaterial preparation. The development of a prediction platform capable of forecasting droplet breakup characteristics can significantly improve the iterative design and fabrication processes required for achieving desired performance. The present study aims to develop a multipurpose platform capable of predicting the working conditions of user-specific droplet size and frequency and reporting the quality of the generated droplets, regime, and hydrodynamical breakup characteristics in flow-focusing microdevices with different cross-junction tilt angles. Four different neural network-based prediction platforms were compared to accurately estimate capsule size, generation rate, uniformity, and circle metric. The trained capsule size and frequency networks were optimized using the heuristic optimization approach for establishing the Pareto optimal solution plot. To investigate the transition of the droplet generation regime (i.e., squeezing, dripping, and jetting), two different classification models (LDA and MLP) were developed and compared in terms of their prediction accuracy. The MLP model outperformed the LDA model with a cross-validation measure evaluated as 97.85%, demonstrating that the droplet quality and regime prediction models can provide an engineering judgment for the decision maker to choose between the suggested solutions on the Pareto front. The study followed a comprehensive hydrodynamical analysis of the junction angle effect on the dispersed thread formation, pressure, and velocity domains in the orifice.

Composite Microgels for Imaging-Monitored Tracking of the Delivery of Vascular Endothelial Growth Factor to Ischemic Muscles.

Monitoring the supply of vascular endothelial growth factor (VEGF) to ischemic tissues provides information on its biodistribution and delivery to meet the requirements of therapeutic angiogenesis and tissue engineering applications. We herein report the use of microfluidically generated microgels containing VEGF-conjugated fluorescent carbon dots (CDs) (VEGF-CDs), a gelatin-phenol conjugate, and silk fibroin for imaging-monitored tracking of VEGF delivery to ischemic muscles. An in vitro release study and a bioactivity assay indicated that the VEGF-CDs were released in a sustained manner with high bioactivity. The microgels showed a high angiogenesis potential, along with a strong fluorescent signal, for the chicken chorioallantoic membrane and chick embryo. Imaging and studies of therapeutic modalities of the composite microgels indicated their effective localization in ischemic tissues and sustained VEGF release, which resulted in enhanced therapeutic angiogenesis of ischemic muscles. This work reveals the success of using VEGF-loaded composite polymer microgels for efficient and monitored VEGF delivery by intramuscular administration for ischemic disease treatment.

Preparation of microfluidic-based pectin microparticles loaded carbon dots conjugated with BMP-2 embedded in gelatin-elastin-hyaluronic acid hydrogel scaffold for bone tissue engineering application.

The controlled delivery of the bone morphogenetic protein-2 (BMP-2) with tracking ability would overcome most of the side effects linked to the burst release and uncontrolled delivery of this growth factor for bone regeneration. Herein, BMP-2-conjugated carbon dots (CDs) was used as noninvasive detection platforms to deliver BMP-2 for therapeutic applications where osteogenesis and bioimaging are both required. With this in mind, the present work aimed to develop a controlled BMP-2-CDs release system using composite scaffolds containing BMP-2-CDs loaded pectin microparticles, which had been optimized for bone regeneration. By using microfluidic approach, we encapsulated BMP-2-CDs in pectin microparticles with narrow size distribution and then incorporated into composite scaffolds composed of gelatin, elastin, and hyaluronic acid. The BMP-2-CDs was released from the composite scaffolds in a sustained fashion for up to 21 days exhibited a high controlled delivery capacity. When tested in vitro with MG-63 cells, these extraction mediums showed the intercellular uptake of BMP-2-CDs and enhanced biological properties and pro-osteogenic effect. By utilizing the pectin microparticles carrying BMP-2-CDs as promising bioimaging agents for growth factor delivery and by tuning the composition of the scaffolds, this platform has immense potential in the field of bone tissue regeneration.