Evaluation of reproducible cryogel preparation based on automated image analysis using deep learning

Construction of foam-templated Antarctic krill oil oleogel based on pea protein fibril and ι-carrageenan

Edible plant-based oleogels with zero trans-fat are promising solid fat substitutes. In this study, Antarctic krill oil (AKO) oleogels prepared from pea protein fibril (PPF) and ι-carrageenan (CG) by foam-templated method were developed for the first time. The modulation of the ratio of PPF and CG concentration on the structure and properties of foam, cryogel and oleogel was investigated and the potential formation mechanism of the foam-templated oleogel was explained. The results demonstrated that the addition of CG significantly decreased the foam size and enhanced the foam stability. The oil absorption and oil holding ability of the dense and reticular porous structure of the cryogel was demonstrated. Fourier infrared spectroscopy confirmed the interaction between PPF and CG involved in the formation of cryogels. With the addition of CG, the network structure and mechanical strength of the cryogel were reinforced, leading to more compact pores and higher capillary suction, which was appropriate for the establishment of good viscoelastic semi-solid oleogels. In addition, the oleogel was effective in masking the fishy odor of AKO. The significance of this study lies in its provision of a novel approach to the preparation of the foam-templated oleogel with PPF and CG as the oleogelators.

Macroporous PEG-Alginate Hybrid Double-Network Cryogels with Tunable Degradation Rates Prepared via Radical-Free Cross-Linking for Cartilage Tissue Engineering

Trauma or repeated damage to joints can result in focal cartilage defects, significantly elevating the risk of osteoarthritis. Damaged cartilage has an inherently limited self-healing capacity and remains an urgent unmet clinical need. Consequently, there is growing interest in biodegradable hydrogels as potential scaffolds for the repair or reconstruction of cartilage defects. Here, we developed a biodegradable and macroporous hybrid double-network (DN) cryogel by combining two independently cross-linked networks of multiarm polyethylene glycol (PEG) acrylate and alginate.Hybrid DN cryogels are formed using highly biocompatible click reactions for the PEG network and ionic bonding for the alginate network. By judicious selection of various structurally similar cross-linkers to form the PEG network, we can generate hybrid DN cryogels with customizable degradation kinetics. The resulting PEG-alginate hybrid DN cryogels have an interconnected macroporous structure, high mechanical strength, and rapid swelling kinetics. The interconnected macropores in the cryogels support efficient mesenchymal stem cell infiltration at a high density. Finally, we demonstrate that PEG-alginate hybrid DN cryogels allow sustained release of chondrogenic growth factors and support chondrogenic differentiation of mouse mesenchymal stem cells. This study provides a novel method to generate macroporous hybrid DN cryogels with customizable degradation rates and a potential scaffold for cartilage tissue engineering.

Hybrid machine learning model based predictions for properties of poly(2-hydroxyethyl methacrylate)-poly(vinyl alcohol) composite cryogels embedded with bacterial cellulose

Supermacroporous composite cryogels with enhanced adjustable functionality have received extensive interest in bioseparation, tissue engineering, and drug delivery. However, the variations in their components significantly impactfinal properties. This study presents a two-step hybrid machine learning approach for predicting the properties of innovative poly(2-hydroxyethyl methacrylate)-poly(vinyl alcohol) composite cryogels embedded with bacterial cellulose (pHEMA-PVA-BC) based on their compositions. By considering the ratios of HEMA (1.0-22.0 wt%), PVA (0.2-4.0 wt%), poly(ethylene glycol) diacrylate (1.0-4.5 wt%), BC (0.1-1.5 wt%), and water (68.0-96.0 wt%) as investigational variables, overlay sampling uniform design (OSUD) was employed to construct a high-quality dataset for model development. The random forest (RF) model was used to classify the preparation conditions. Then four models of artificial neural network, RF, gradient boosted regression trees (GBRT), and XGBoost were developed to predict the basic properties of the composite cryogels. The results showed that the RF model achieved an accurate three-class classification of preparation conditions. Among the four models, the GBRT model exhibited the best predictive performance of the basic properties, with the mean absolute percentage error of 16.04 %, 0.85 %, and 2.44 % for permeability, effective porosity, and height of theoretical plate (1.0 cm/min), respectively. Characterization results of the representative pHEMA-PVA-BC composite cryogel showed an effective porosity of 81.01 %, a permeability of 1.20 × 10-12 m2, and a range of height of theoretical plate between 0.40-0.49 cm at flow velocities of 0.5-3.0 cm/min. These indicate that the pHEMA-PVA-BC cryogel was an excellent material with supermacropores, low flow resistance and high mass transfer efficiency. Furthermore, the model output demonstrates that the alteration of the proportions of PVA (0.2-3.5 wt%) and BC (0.1-1.5 wt%) components in composite cryogels resulted in significant changes in the material basic properties. This work represents an attempt to efficiently design and prepare target composite cryogels using machine learning and providing valuable insights for the efficient development of polymers.

Cryogels Based on Poly(2-oxazoline)s through Development of Bi- and Trifunctional Cross-Linkers Incorporating End Groups with Adjustable Stability

1,4-Bis(iodomethyl)benzene and 1,3,5-tris(iodomethyl)benzene were used as initiators for the cationic ring-opening polymerization (CROP) of 2-ethyl-2-oxazoline (EtOx) and its copolymerization with tert-butyl (3-(4,5-dihydrooxazol-2-yl)propyl)carbamate (BocOx) or methyl 3-(4,5-dihydrooxazol-2-yl)propanoate (MestOx). Kinetic studies confirmed the applicability of these initiators. Termination with suitable nucleophiles resulted in two- and three-armed cross-linkers featuring acrylate, methacrylate, piperazine-acrylamide, and piperazine-methacrylamide as polymerizable ω-end groups. Matrix-assisted laser desorption/ionization mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy confirmed the successful attachment of the respective ω-end groups at all initiation sites for every prepared cross-linkers. Except for acrylate, each ω-end group remained stable during deprotection of BocOx containing cross-linkers. The cryogels were prepared using EtOx-based cross-linkers, as confirmed by solid-state NMR spectroscopy, scanning electron microscopy, and thermogravimetric analysis. Stability tests revealed a complete dissolution of the acrylate-containing gels at pH = 14, whereas the piperazine-acrylamide-based cryogels featured excellent hydrolytic stability.