Optimization of Gelatin Methacryloyl Hydrogel Properties through an Artificial Neural Network Model

Artificial Intelligence tool for prediction of ECM mimics hydrogel formulations via click chemistry

A user-friendly machine learning (ML) predictive tool is reported for designing extracellular matrix (ECM)-mimetic hydrogels with tailored rheological properties. Developed for regenerative medicine and 3D bioprinting, the model leverages click chemistry crosslinking to fine-tune the mechanical behaviour of gelatin- and hyaluronic acid-based hydrogels. Using both experimental rheological data and synthetic datasets, our supervised ML approach accurately predicts hydrogel compositions, significantly reducing the cost and time associated with trial-and-error approach. Despite advancements in the field, existing models remain limited in their ability to mimic the ECM due to the use of non-natural polymers, reliance on a single type of biologically active macromolecule, and physical crosslinking reactions with limited tuneability. Additionally, their lack of generalizability confines them to specific formulations and demands extensive experimental data for training. This predictive platform represents a major advancement in biomaterial design, improving reproducibility, scalability, and efficiency. By integrating rational design, it accelerates tissue engineering research and expands access to customized ECM-mimetic hydrogels with tailored viscoelastic properties for biomedical applications, enabling both experts and non-experts in materials design.

Advances of novel hydrogels in the healing process of alveolar sockets

Tooth extraction is a common oral surgical procedure that often leads to delayed alveolar socket healing due to the complexity of the oral microenvironment, which can hinder the patient's aesthetic and functional recovery. Effective alveolar socket healing requires a multidisciplinary approach. Recent advancements in materials science and bioengineering have facilitated the development of innovative strategies, with hydrogels emerging as ideal restorative materials for alveolar socket repair due to their superior properties. This review provides an overview of recent advances in hydrogels for alveolar socket healing, focusing on their classification, physical properties (e.g., mechanical strength, swelling behavior, degradation rate, and injectability), biological functions, and applications in relevant animal models. Specifically, the bone-regenerative and antimicrobial properties of hydrogels are highlighted. Furthermore, this review identifies future directions and addresses challenges associated with the clinical application of hydrogels in extraction socket healing.

An Endogenous Adenosine Triphosphate-Activated Hydrogel Prodrug System for Healing Multidrug-Resistant Bacteria Infected Diabetic Foot Ulcers

Current guidelines for addressing multidrug-resistant bacteria-infected diabetic foot ulcers (DFUs), a leading cause of disability and death among diabetes sufferers, still lack specificity. Such DFU lesions often experience delayed recovery, primarily due to the bacteria-induced inflammation in the adverse diabetic microenvironment. Here, an endogenous adenosine triphosphate (ATP)-responsive hydrogel prodrug platform (abbreviated as HSAQ3), which embeds hemoglobin@zeolitic imidazolate framework-8 (Hb@ZIF-8) nanoparticles in a prodrug (1-naphthylacetic acid, NAA)-loaded biopolymer matrix, targeting multidrug-resistant bacterial infections in DFUs is presented. Initially, using a simple local injection, an HSAQ3 adhesive barrier triggered by UV light is applied to the wound. Concurrently, HSAQ3's composition, enriched with quaternary ammonium salt and phenylboronic acid groups, exhibits strong bacterial trapping capabilities, effectively capturing bacteria at the wound location within the hydrogel. Following this, ATP secreted by bacteria initiates the degradation of Hb@ZIF-8, enabling the simultaneous interaction of the encapsulated NAA prodrug with Hb peroxidase. This process effectively produces reactive oxygen species (ROS) in situ, addressing their limited lifespan and diffusion range, thus guaranteeing a highly efficient bactericidal effect. This study unveils an innovative inorganic-organic hybrid prodrug system, leveraging endogenous ATP from bacteria for precise ROS generation, enhancing the healing of multidrug-resistant bacterial infections in DFUs.

DNA Hydrogels in Tissue Engineering: From Molecular Design to Next-Generation Biomedical Applications

DNA hydrogels have emerged as promising materials in tissue engineering due to their biocompatibility, programmability, and responsiveness to stimuli. Synthesized through physical and chemical crosslinking, these hydrogels can be categorized into functionalized types, such as those based on aptamers, and stimuli-responsive types that react to pH, temperature, and light. This review highlights their applications in tissue engineering, including drug delivery, cell culture, biosensing, and gene editing. DNA hydrogels can encapsulate therapeutic agents, support cell growth, and respond dynamically to environmental changes, making them ideal for tissue engineering. A comprehensive bibliometric analysis is included, identifying key research trends and emerging areas of interest in DNA hydrogel design, synthesis, and biomedical applications. The analysis provides a deeper understanding of the field's development and future research directions. Challenges such as mechanical strength, stability, and biosafety persist, but the integration of AI in hydrogel design shows promise for advancing their functionality in clinical applications.

Plant Polyphenol-Based Injectable Hydrogels: Advances and Biomedical Applications

Plant polyphenol-based hydrogels, known for their biocompatibility and adhesive properties, have emerged as promising materials in biomedical applications. These hydrogels leverage the catechol group's ability to form stable bonds in moist environments, similar to mussel adhesive proteins. This review provides a comprehensive overview of their synthesis, adhesion mechanisms, and applications, particularly in wound healing, tissue regeneration, and drug delivery. However, challenges related to in vivo stability and long-term biocompatibility remain critical barriers to clinical translation. Future research should focus on enhancing the bioactivity, biocompatibility, and scalability of these hydrogels, while addressing concerns related to toxicity, immune responses, and large-scale manufacturing. Advances in artificial intelligence-assisted screening and 3D/4D bioprinting are expected to accelerate their development and clinical translation. Furthermore, the integration of biomimetic designs and responsive functionalities, such as pH or temperature sensitivity, holds promise for further improving their therapeutic efficacy. In conclusion, the development of multifunctional plant polyphenol-based hydrogels represents a promising frontier in advancing personalized medicine and minimally invasive treatments.

AI-driven 3D bioprinting for regenerative medicine: From bench to bedside

In recent decades, 3D bioprinting has garnered significant research attention due to its ability to manipulate biomaterials and cells to create complex structures precisely. However, due to technological and cost constraints, the clinical translation of 3D bioprinted products (BPPs) from bench to bedside has been hindered by challenges in terms of personalization of design and scaling up of production. Recently, the emerging applications of artificial intelligence (AI) technologies have significantly improved the performance of 3D bioprinting. However, the existing literature remains deficient in a methodological exploration of AI technologies' potential to overcome these challenges in advancing 3D bioprinting toward clinical application. This paper aims to present a systematic methodology for AI-driven 3D bioprinting, structured within the theoretical framework of Quality by Design (QbD). This paper commences by introducing the QbD theory into 3D bioprinting, followed by summarizing the technology roadmap of AI integration in 3D bioprinting, including multi-scale and multi-modal sensing, data-driven design, and in-line process control. This paper further describes specific AI applications in 3D bioprinting's key elements, including bioink formulation, model structure, printing process, and function regulation. Finally, the paper discusses current prospects and challenges associated with AI technologies to further advance the clinical translation of 3D bioprinting.

Engineered Living Systems Based on Gelatin: Design, Manufacturing, and Applications

Engineered living systems (ELSs) represent purpose-driven assemblies of living components, encompassing cells, biomaterials, and active agents, intricately designed to fulfill diverse biomedical applications. Gelatin and its derivatives have been used extensively in ELSs owing to their mature translational pathways, favorable biological properties, and adjustable physicochemical characteristics. This review explores the intersection of gelatin and its derivatives with fabrication techniques, offering a comprehensive examination of their synergistic potential in creating ELSs for various applications in biomedicine. It offers a deep dive into gelatin, including its structures and production, sources, processing, and properties. Additionally, the review explores various fabrication techniques employing gelatin and its derivatives, including generic fabrication techniques, microfluidics, and various 3D printing methods. Furthermore, it discusses the applications of ELSs based on gelatin in regenerative engineering as well as in cell therapies, bioadhesives, biorobots, and biosensors. Future directions and challenges in gelatin fabrication are also examined, highlighting emerging trends and potential areas for improvements and innovations. In summary, this comprehensive review underscores the significance of gelatin-based ELSs in advancing biomedical engineering and lays the groundwork for guiding future research and developments within the field.

Progress of AI assisted synthesis of polysaccharides-based hydrogel and their applications in biomedical field

Polymeric hydrogels, characterized by their highly hydrophilic three-dimensional network structures, boast exceptional physical and chemical properties alongside high biocompatibility and biodegradability. These attributes make them indispensable in various biomedical applications such as drug delivery, tissue engineering, wound dressings and sensor technologies. With the integration of artificial intelligence (AI), hydrogels are undergoing significant transformations in design, leveraging human-machine interaction, machine learning, neural networks, and 3D/4D printing technology. This article provides a concise yet comprehensive overview of polysaccharide-based hydrogels, exploring their intrinsic properties, functionalities, preparation techniques, and classifications, alongside their progress in biomedical research. Special emphasis is placed on AI-enhanced hydrogels, underscoring their transformative potential in redefining hydrogel performance and functionality. By integrating AI technologies, these intelligent hydrogels open unprecedented opportunities in precision medicine, adaptive biomaterials, and smart healthcare systems, highlighting promising directions for future research.

A gelatin methacryloyl (GelMA) treated with gallic acid and coated with specially designed nanoparticles derived from ginseng enhances the healing of wounds in diabetic rats

Due to persistent inflammation and oxidative stress reactions, achieving drug absorption in diabetic wounds is challenging. To overcome this problem, our article presents a composite hydrogel, GelMA-GA/DMOG@GDNP, which consists of gelatin methacryloyl (GelMA) treated with gallic acid (GA) and encapsulating ginseng-derived nanoparticles (GDNPs) loaded with dimethyloxallyl glycine (DMOG). The composite hydrogel demonstrates excellent biocompatibility. In laboratory settings, the hydrogel inhibits the production of nitric oxide synthase 2 (iNOS) in mouse immune cells (RAW264.7 cells), enhances the growth and migration of mouse connective tissue cells (L929 cells) and human endothelial cells (HUVECs), and promotes tube formation in HUVECs. In a rat model of type 1 diabetes-induced wounds, the composite hydrogel attenuates inflammatory reactions, facilitates the formation of fibres and blood vessels, accelerates wound healing, and elucidates specific pathway mechanisms through transcriptome sequencing. Therefore, the GelMA-GA/DMOG@GDNP hydrogel can serve as a safe and efficient wound dressing to regulate the inflammatory response, promote collagen fiber and blood vessel formation, and accelerate wound healing. These findings suggest that utilizing this multifunctional engineered nanoparticle-loaded hydrogel in a clinical setting may be a promising strategy for diabetic wound healing.

AI energized hydrogel design, optimization and application in biomedicine

Traditional hydrogel design and optimization methods usually rely on repeated experiments, which is time-consuming and expensive, resulting in a slow-moving of advanced hydrogel development. With the rapid development of artificial intelligence (AI) technology and increasing material data, AI-energized design and optimization of hydrogels for biomedical applications has emerged as a revolutionary breakthrough in materials science. This review begins by outlining the history of AI and the potential advantages of using AI in the design and optimization of hydrogels, such as prediction and optimization of properties, multi-attribute optimization, high-throughput screening, automated material discovery, optimizing experimental design, and etc. Then, we focus on the various applications of hydrogels supported by AI technology in biomedicine, including drug delivery, bio-inks for advanced manufacturing, tissue repair, and biosensors, so as to provide a clear and comprehensive understanding of researchers in this field. Finally, we discuss the future directions and prospects, and provide a new perspective for the research and development of novel hydrogel materials for biomedical applications.

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Gelatin methacrylate (GelMA) hydrogels have gained significant traction in diverse tissue engineering applications through the utilization of 3D printing technology. As an artificial hydrogel possessing remarkable processability, GelMA has emerged as a pioneering material in the advancement of tissue engineering due to its exceptional biocompatibility and degradability. The integration of 3D printing technology facilitates the precise arrangement of cells and hydrogel materials, thereby enabling the creation of in vitro models that simulate artificial tissues suitable for transplantation. Consequently, the potential applications of GelMA in tissue engineering are further expanded. In tissue engineering applications, the mechanical properties of GelMA are often modified to overcome the hydrogel material's inherent mechanical strength limitations. This review provides a comprehensive overview of recent advancements in enhancing the mechanical properties of GelMA at the monomer, micron, and nano scales. Additionally, the diverse applications of GelMA in soft tissue engineering via 3D printing are emphasized. Furthermore, the potential opportunities and obstacles that GelMA may encounter in the field of tissue engineering are discussed. It is our contention that through ongoing technological progress, GelMA hydrogels with enhanced mechanical strength can be successfully fabricated, leading to the production of superior biological scaffolds with increased efficacy for tissue engineering purposes.