Constraint based Bayesian optimization of bioink precursor: a machine learning framework DOI
Yihao Xu,

Rokeya Sarah,

Ahasan Habib

et al.

Biofabrication, Journal Year: 2024, Volume and Issue: 16(4), P. 045031 - 045031

Published: Aug. 22, 2024

Abstract Current research practice for optimizing bioink involves exhaustive experimentation with multi-material composition determining the printability, shape fidelity and biocompatibility. Predicting properties can be beneficial to community but is a challenging task due non-Newtonian behavior in complex composition. Existing models such as Cross model become inadequate predicting viscosity heterogeneous of bioinks. In this paper, we utilize machine learning framework accurately predict compositions, aiming enhance extrusion-based bioprinting techniques. Utilizing Bayesian optimization (BO), our strategy leverages limited dataset inform model. This technique especially useful typically sparse data domain. Moreover, have also developed mask that handle constraints, informed by domain expertise, define feasible parameter space components their interactions. Our proposed method focused on intrinsic factor (e.g. viscosity) precursor which tied extrinsic property cell viability) through function. Through hyperparameter, strike balance between exploration new possibilities exploitation known data, crucial refining acquisition function then guides selection subsequent sampling points within defined viable process continues until convergence achieved, indicating has sufficiently explored identified optimal or near-optimal solutions. Employing AI-guided BO framework, developed, tested, validated surrogate compositions. data-driven approach significantly reduces experimental workload required identify compositions conducive functional tissue growth. It not only streamlines finding from vast array options offers promising avenue accelerating advancements engineering minimizing need extensive trials.

Language: Английский

Essential Guide to Hydrogel Rheology in Extrusion 3D Printing: How to Measure It and Why It Matters? DOI Creative Commons
Helena Herrada‐Manchón, M. Alejandro Fernández, Enrique Aguilar

et al.

Gels, Journal Year: 2023, Volume and Issue: 9(7), P. 517 - 517

Published: June 26, 2023

Rheology plays a crucial role in the field of extrusion-based three-dimensional (3D) printing, particularly context hydrogels. Hydrogels have gained popularity 3D printing due to their potential applications tissue engineering, regenerative medicine, and drug delivery. The rheological properties material significant impact on its behaviour throughout process, including extrudability, shape retention, response stress strain. Thus, understanding characteristics hydrogels, such as shear thinning behaviour, thixotropy, viscoelasticity, gelling mechanisms, is essential for optimising process achieving desired product quality accuracy. This review discusses theoretical foundations rheology, explores different types fluid properties, tests necessary characterising paper emphasises importance terminology, concepts, correct interpretation results evaluating hydrogel formulations. By presenting detailed rheology this aims assist researchers, engineers, practitioners hydrogel-based optimizing processes outcomes.

Language: Английский

Citations

75
Additively manufactured porous scaffolds by design for treatment of bone defects DOI Creative Commons

Shirin Toosi,

Mohammad Javad Javid‐Naderi,

Ali Tamayol

et al.

Frontiers in Bioengineering and Biotechnology, Journal Year: 2024, Volume and Issue: 11

Published: Jan. 19, 2024

There has been increasing attention to produce porous scaffolds that mimic human bone properties for enhancement of tissue ingrowth, regeneration, and integration. Additive manufacturing (AM) technologies, i.e., three dimensional (3D) printing, have played a substantial role in engineering clinical applications owing their high level design fabrication flexibility. To this end, review article attempts provide detailed overview on the main considerations such as permeability, adhesion, vascularisation, interfacial features interplay affect regeneration osseointegration. Physiology was initially explained followed by analysing impacts porosity, pore size, permeability surface chemistry defects. Importantly, major 3D printing methods employed substitutes were also discussed. Advancements MA technologies allowed production with complex geometries polymers, composites metals well-tailored architectural, mechanical, mass transport features. In way, particular devoted reviewing printed triply periodic minimal (TPMS) hierarchical structure bones. overall, enlighten pathway patient-specific 3D-printed substitutions osseointegration capacity repairing large

Language: Английский

Citations

21
Advancements of 3D bioprinting in regenerative medicine: Exploring cell sources for organ fabrication DOI Creative Commons
Yue Ma, Bo Deng,

Runbang He

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e24593 - e24593

Published: Jan. 17, 2024

3D bioprinting has unlocked new possibilities for generating complex and functional tissues organs. However, one of the greatest challenges lies in selecting appropriate seed cells constructing fully artificial Currently, there are no cell sources available that can fulfill all requirements technologies, each source possesses unique characteristics suitable specific applications. In this review, we explore impact different technologies bioink materials on cells, providing a comprehensive overview current landscape have been used or hold potential bioprinting. We also summarized key points to guide selection Moreover, offer insights into prospects bioprinted organs, highlighting their revolutionize fields tissue engineering regenerative medicine.

Language: Английский

Citations

20
Characterization of Biocompatibility of Functional Bioinks for 3D Bioprinting DOI Creative Commons
Jinku Kim

Bioengineering, Journal Year: 2023, Volume and Issue: 10(4), P. 457 - 457

Published: April 9, 2023

Three-dimensional (3D) bioprinting with suitable bioinks has become a critical tool for fabricating 3D biomimetic complex structures mimicking physiological functions. While enormous efforts have been devoted to developing functional bioprinting, widely accepted not yet developed because they fulfill stringent requirements such as biocompatibility and printability simultaneously. To further advance our knowledge of the bioinks, this review presents evolving concept standardization characterization. This work also briefly reviews recent methodological advances in image analyses characterize regard cell viability cell-material interactions within constructs. Finally, highlights number updated contemporary characterization technologies future perspectives understanding successful bioprinting.

Language: Английский

Citations

24
Polymer hydrogels: Classification and recent advances DOI

Mahua Dhara

Journal of Macromolecular Science Part A, Journal Year: 2024, Volume and Issue: 61(5), P. 265 - 288

Published: March 19, 2024

Hydrogels comprise of a group crosslinked hydrophilic polymeric materials which are capable absorbing and holding large quantities water in their three-dimensional network structure without undergoing dissolution. More importantly, the ability 'smart' hydrogels to respond certain environmental changes e.g. pH, heat, light, magnetic field, biomolecules have set them apart as unique class materials. A combination several such useful properties resulted tremendous progress toward development advanced hydrogel-based materials, is evident from an explosive amount research publications available this area over last few decades. Owing particularly biocompatibility biodegradability, become material prime importance context wide range applications starting simple contact lenses more complex ones tissue repair, drug delivery, sensors, 3D bioprinting, soft robotics agriculture. This review includes i) overview its classifications based on source, structure, crosslinking mechanism stimuli responsiveness, ii) detailed discussion some most works being carried out field years smart that need hour, domain biomedical applications.

Language: Английский

Citations

12
Tracheal Tissue Engineering: Principles and State of the Art DOI Creative Commons
Marco Mammana, Alessandro Bonis, Vincenzo Verzeletti

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(2), P. 198 - 198

Published: Feb. 19, 2024

Patients affected by long-segment tracheal defects or stenoses represent an unsolved surgical issue, since they cannot be treated with the conventional surgery of resection and consequent anastomosis. Hence, different strategies for replacement have been proposed (synthetic materials, aortic allografts, transplantation, autologous tissue composites, engineering), each advantages drawbacks. Tracheal engineering, on other hand, aims at recreating a fully functional substitute, without need patient to receive lifelong immunosuppression endotracheal stents. Tissue engineering approaches involve use scaffold, stem cells, humoral signals. This paper reviews main aspects TE, starting from choice scaffold type cells that can used seed methods their culture expansion, issue graft revascularization moment in vivo implantation, experimental models research. Moreover, critical insight state art is also presented.

Language: Английский

Citations

9
Artificial Intelligence-Driven Modeling for Hydrogel Three-Dimensional Printing: Computational and Experimental Cases of Study DOI Open Access
Harbil Bediaga, Isabel Moreno, Sonia Arrasate

et al.

Polymers, Journal Year: 2025, Volume and Issue: 17(1), P. 121 - 121

Published: Jan. 6, 2025

Determining the values of various properties for new bio-inks 3D printing is a very important task in design materials. For this purpose, large number experimental works have been consulted, and database with more than 1200 bioprinting tests has created. These cover different combinations conditions terms print pressure, temperature, needle values, example. data are difficult to deal determining optimize analyze options. The best model demonstrated specificity (Sp) 88.4% sensitivity (Sn) 86.2% training series while achieving an Sp 85.9% Sn 80.3% external validation series. This utilizes operators based on perturbation theory complexity data. comparative purposes, neural networks used, similar results obtained. developed tool could easily be applied predict assays silico. findings significantly improve efficiency accuracy predictive models without resorting trial-and-error tests, thereby saving time funds. Ultimately, may help pave way advances personalized medicine tissue engineering.

Language: Английский

Citations

1
Characterization and Machine Learning-Driven Property Prediction of a Novel Hybrid Hydrogel Bioink Considering Extrusion-Based 3D Bioprinting DOI Creative Commons

Rokeya Sarah,

Kory Schimmelpfennig,

Riley Rohauer

et al.

Gels, Journal Year: 2025, Volume and Issue: 11(1), P. 45 - 45

Published: Jan. 7, 2025

The field of tissue engineering has made significant advancements with extrusion-based bioprinting, which uses shear forces to create intricate structures. However, the success this method heavily relies on rheological properties bioinks. Most bioinks use shear-thinning. While a few component-based efforts have been reported predict viscosity bioinks, impact rate vastly ignored. To address gap, our research presents predictive models using machine learning (ML) algorithms, including polynomial fit (PF), decision tree (DT), and random forest (RF), estimate bioink based component weights rate. We utilized novel composed varying percentages alginate (2-5.25%), gelatin TEMPO-Nano fibrillated cellulose (0.5-1%) at rates from 0.1 100 s-1. Our study analyzed 169 measurements 80% training 20% validation data. results, coefficient determination (R2) mean absolute error (MAE), showed that RF algorithm-based model performed best: [(R2, MAE) = (0.99, 0.09), (R2, PF (0.95, 0.28), DT (0.98, 0.13)]. These serve as valuable tools for formulation optimization, allowing researchers determine effective viscosities without extensive experimental trials accelerate engineering.

Language: Английский

Citations

1
3D bioprinting: Advancing the future of food production layer by layer DOI Creative Commons

Nisansala Chandimali,

Seon-Gyeong Bak,

Eun Hyun Park

et al.

Food Chemistry, Journal Year: 2025, Volume and Issue: 471, P. 142828 - 142828

Published: Jan. 9, 2025

Language: Английский

Citations

1
Advances in Regenerative Medicine, Cell Therapy, and 3D Bioprinting for Glaucoma and Retinal Diseases DOI
Kevin Y. Wu, Rahma M Osman,

Obinna Esomchukwu

et al.

Advances in experimental medicine and biology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

1