Bioprinting最新文献

The study focuses on the formulation of a hybrid hydrogel comprising alginate, carboxymethyl cellulose (CMC), and TEMPO-oxidized nano-fibrillated cellulose (TO-NFC) for bioprinting precise scaffold for tissue engineering applications. Even though controlling the capacity of porosity during scaffold fabrication can positively assist the encapsulated cell growth, the lack of the right material choice and percentage may make it difficult to 3D bioprint scaffold conforming user user-defined porosity, shape fidelity, and cell viability. In our earlier work, we have demonstrated that hybrid-hydrogel made of alginate, CMC, and TO-NFC has shown promising characteristics of bio-ink for tissue scaffold applications [1]. Carefully controlled material composition can help generate the required shear rate in the nozzle to flow the composition smoothly, confirming proper filament width and eventually, defined scaffold porosity. However, achieving the desired rheological property from the composition is an exhaustive process with a series of experiments. Due to their complex behavior after mixing, a predictive viscosity model is necessary. To address that challenge, we propose a multiple linear regression-based model with an adjusted-R² value of 89 % to estimate the viscosity of composition with respect to the weight percentage of alginate, CMC, TO-NFC, and various shear rates. There are 23 unique compositions prepared with various weight percent of Alginate, CMC, and TO-NFC, a comprehensive set of 483 viscosity measurements was obtained. These measurements were collected at 21 distinct shear rate levels, ranging from 0.1 to 100 s⁻¹. We observed while the same solid content can result in a wide range of viscosity by systematically varying the percentage of Alginate, CMC, TO-NFC, and shear rate, similar viscosity levels can also be attained across a range of compositions prepared with varying solid contents of them. After a 10-day incubation period, we assessed the morphology and viability of Porc1 cells encapsulated in one of the 23 compositions, revealing a significantly higher percentage of viability at 89 %. This fine-tuning of rheological properties by varying percentages and shear rates enhances the accuracy and fidelity of the printed scaffold, ensuring a realistic representation of the desired scaffold architecture. Such a predictive model can help prepare bio-ink with relative ease and a smaller number of experiments which can help expedite the development of new bio-ink for bio-printing applications.

Medical device-associated infections pose a threat to healthcare budgets in both developed and developing countries. Over the last decade, researchers have been looking for antimicrobial biomaterials using three-dimensional (3D) printing. This systematic review aims to understand the current state of the art in antimicrobial 3D-printed materials and their applications in healthcare. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to conduct this study. PubMed, Web of Science, Embase, and Scopus databases were searched for this review. According to the inclusion criteria, 269 relevant articles were retrieved for this study. Material extrusion was revealed to be the most commonly used 3D printing methodology for biomaterials and medical device production. Polylactic acid, polycaprolactone, chitosan, and alginate were the most explored materials for this application. Besides, vancomycin and gentamicin were the most prevalent antimicrobial substances loaded into 3D biomaterials. Further, Staphylococcus aureus and Escherichia coli are the most evaluated pathogens against 3D-printed materials. In conclusion, 3D printing is an excellent tool for designing functionalized biomaterials and developing alternatives for nosocomial infections. We hope this review provides helpful insights for scientists and innovation centers to understand the potential of the 3D-printed antimicrobial materials found in this study and the demands and opportunities for further research in this area.

Bioprinting of self-healing materials and nanostructures has gained significant attention in recent years due of its potential benefits in biomedical applications. Self-healing materials and nanostructures can enhance the mechanical stability of printed constructs by restoring their strength, stiffness, and elasticity following damage. Self-healing materials and nanostructures can improve the performance of printed constructs by preserving their viability, differentiation, and integration even when they are damaged. Self-healing materials and nanostructures possess the ability to offer supplementary capabilities, including medication delivery, biosensing, and bioimaging. This is achieved by their capacity to react to external stimuli, such as light, heat, or pH, and subsequently release pharmaceuticals, generate signals, or alter colors. This study presents a comprehensive summary of the latest progress in the field of bioprinting for the creation of self-healing materials and nanostructures. The emphasis is placed on the methods used for their production, analysis, and evaluation. Initially, we provide the fundamental concepts and methodologies of bioprinting, followed by an explanation of the primary categories and characteristics of self-healing materials and nanostructures. Here, we showcase a selection of illustrative instances where self-healing materials and nanostructures have been bio-printed for diverse biological purposes, including tissue engineering, organ transplantation, drug administration, and wound healing. In addition, we analyze the present constraints and potential future directions of this developing domain, including the capacity for expansion, compatibility with living organisms, and regulatory aspects of printing self-repairing substances and nanostructures. We anticipate that this review will serve as a catalyst for novel concepts and promote additional investigation in the field of bioprinting of self-repairing substances and nanostructures for biomedical purposes.

3D bioprinting, a vital tool in tissue engineering, drug testing, and disease modeling, is increasingly integrated with machine learning (ML) and artificial intelligence (AI). Although some existing reviews acknowledge this integration, a detailed examination of system and process challenges remains to be discussed. This review divides the topic into two main areas: the process view, which sees bioprinting as a standalone system and outlines data-driven solutions for challenges such as material selection, parameter optimization, and real-time monitoring, and the system view, which delves into the broader ecosystem of bioprinting and its interaction with other technologies. We first present the latest techniques in managing process-specific challenges using ML/AI, highlighting future opportunities. We then navigate through system-wide challenges, emphasizing data-driven solutions. This review also sheds light on potential regulatory frameworks and the need for skilled workforce development, advocating for an alignment between policy and technology progression.

Objective

A mechanical mismatch between a microprobe implanted in the brain and its surrounding soft tissue facilitates tissue damage and microprobe failure due to brain micromotion. Utilising soft intracortical microprobes with elastic moduli close to that of the brain may reduce tissue damage and enhance the longevity of the microprobes. Providing temporary stiffness for soft microprobes is a dominant method to prevent buckling during insertion. Nevertheless, the inability of these methods to efficiently control the stiffness results in inaccurate positioning or tissue damage.

Approach

This paper presents an engineered interface between the microprobe and an inserter/neural tissue to provide an instant switch between the stiff and soft modes of the microprobe.

Main results

The microprobe's equivalent elastic modulus increases to ≈4.2 GPa during insertion and positioning due to an applied compressive force by an inserter and instantly returns to ≈98 kPa after positioning. The 3D printed microprobe is experimentally tested and inserted into a lamb brain without buckling, confirming the feasibility of the design proposed in this study.

Significance

The cross-sectional area of the proposed microprobe is approximately 70 % smaller than that of the existing counterpart, resulting in less tissue damage during insertion and operation.

Alginate-based inks are widely used in 3D bioprinting. Its crosslinking by Ca²⁺ ions is extremely important to achieve scaffolds with optimal mechanical properties. Notably, despite previous studies on calcium diffusion in alginate systems, there have been no reported data regarding the effect of temperature on the diffusion and crosslinking dynamics of thermogelling alginate-based hydrogels. This study focuses on investigating the kinetics of the crosslinking front and Ca²⁺ diffusion within a matrix of Alginate-Gelatin-Hyaluronic acid ink, exploring the impact of temperature and Ca²⁺ concentration. The Ca²⁺ diffusion rate or ink crosslinking rate increase as the crosslinker concentration and ink temperature increase. Additionally, the mechanical properties of the scaffolds, assessed through compression, tension, and dynamic tests, were correlated with the crosslinking time.

The innovative aspect of this study lies in the development of a code that simulates the diffusion of Ca²⁺ ions from the exterior to the interior of a hydrogel structure. Specifically, the code facilitates the calculation of the crosslinking time for a cylindrical structure up to a specified thickness, providing valuable insights for the production of airways or blood vessels. Furthermore, the Python script, incorporating the numerical model, manages to simulate the crosslinking dynamics of scaffolds of any shape, and properly fits the rheological measurements of dynamic moduli during the crosslinking process. This represents a significant advance for the precise and controlled scaffold fabrication process using 3D bioprinting.

Middle ear ossicles transfer and amplify sound waves from the Tympanic Membrane (TM) to the inner ear and function as impedance transformers to overcome impedance mismatches between the outer air and cochlear fluid. Several factors, including trauma, otitis media, chronic middle ear disease, or cholesteatoma, can lead to ossicular erosion, causing conductive hearing loss (CHL). A common surgical approach to address ossicular erosion is Ossicular Chain Reconstruction (OCR), also known as ossiculoplasty, wherein a middle ear prosthesis is inserted in place of the damaged ossicle(s). Unfortunately, studies indicate poor long-term outcomes in OCR as current techniques fail to accurately reproduce the natural anatomy and function of the patients' middle ear, leading to excessive force transmission and prosthesis extrusion. One promising first-order approach is computational modelling paired with 3D printing, which allows multi-parametric control to optimise and fabricate ossicular implants customised to the patient's middle ear anatomy. This customisation approach holds the promise of enhancing hearing outcomes after prosthesis implantation, as it replicates the natural sound transmission mechanism and protective effect of the normal ossicles. There is a particular need for such an approach, given no clear standards exist for prosthesis optimisation, potentially affecting patient care and hearing outcomes. This paper provides a comprehensive review of various middle ear implants based on their materials and evaluates the feasibility of Finite Element Method (FEM)-based design and customisation of 3D printing for middle ear prostheses. To improve surgical outcomes, the optimisation of prosthesis design is crucial. Enhanced hearing restoration can be achieved through more efficient and personalised prosthesis designs, leveraging FE analysis and advanced additive manufacturing, notably 3D printing.

Bone injuries are increasing due to the ageing of the population, and the previous methods of treating bone injuries such as grafts face many limitations, especially in the treatment of large bone injuries. Recently, bone tissue engineering has been introduced as a substitute method for bone regeneration. Scaffolding is one of the most important stages of bone tissue engineering. One of the newest methods of creating scaffolds is using a 3D bioprinter. This method provides several advantages over the traditional methods of fabricating scaffolds, for example, personalization, scaffold designing before production and structure controlling, reproducibility, the possibility of simultaneous cell printing, etc. Here, bone injuries and bone diseases, especially large ones, have been discussed at first. In the following, the 3D printing method is introduced and different bio-ink compositions, and various effective fctors in the design of 3d printed scaffolds were summerized. Afterward, the use of 3D printining and 3D bioprinting has been discussed in previous studies and its current challenges and future perspectives for the treatment of lrage bone defects were mentioned. It is hoped that this review will be a guide for using 3D bioprinting to treat bone injuries in near future applications.

Bone tissue engineering (BTE) research has reached a significant level of maturity. This paper reviews the role of modeling and simulation in BTE, highlighting their exceptional utility in assessing and validating experiments conducted in vitro and in vivo. The study categorizes BTE simulations into three key areas: 1- Modeling Physical Phenomena: This includes simulations based on Computer-Aided Design (CAD), medical imaging, and the finite element method. 2- Structural Complexity and Scaffold Optimization: This involves exploring intricate scaffold structures and optimizing their design. 3- Diverse Simulation Conditions for Lattice structure: This category delves into simulations under varying conditions to understand scaffold behavior. The paper's focus is on CAD-based and medical image-based finite element analysis models of lattice structure, emphasizing their importance in BTE. Two significant findings emerge: 1- In silico experiments offer extraordinary possibilities and economic benefits in BTE research. They provide invaluable insights and reduce the need for resource-intensive physical experiments. 2- Collaborative practices are crucial for advancing BTE research. Collaboration among researchers strengthens the credibility and applicability of quantifiable and structurally sound methodologies within the field, fostering innovation and progress.

Bioreactors are essential tools in tissue engineering and drug delivery research, providing controlled environments for cell growth, tissue development, and optimization of manufacturing parameters. There are various types of bioreactors, including static, dynamic, perfusion, and rotating systems, each offering unique advantages depending on the application. Key design considerations for bioreactors include the size, geometry, components, materials, and operating conditions needed to support the cultured tissue or organ. Stimuli-responsive materials have emerged as essential components in the design of bioreactors and the fabrication of scaffolds for various applications in tissue engineering and drug delivery. These intelligent materials possess the ability to modulate their properties and functionalities in direct response to external stimuli such as temperature, pH, light, electric or magnetic fields, and biochemical signals. This inherent responsiveness affords precise control over the spatiotemporal manipulation of physical and chemical cues, thereby influencing cellular behavior and facilitating controlled release of therapeutic agents. Commonly employed stimuli-responsive polymers encompass thermoresponsive, pH-responsive, light-responsive, and redox-responsive materials.3D printing techniques allow fabrication of complex, customized scaffolds using digital designs and living cell-laden bio-inks. Bioprinting combined with stimuli-responsive materials enables 4D printing of dynamic scaffolds that transform over time when triggered. Ongoing research aims to optimize bioreactor design, develop novel smart biomaterials, achieve multi-material 4D printing, and enhance responsiveness to internal stimuli for advanced tissue engineering and drug delivery applications.