1,721,135 research outputs found
4D Printing: A Snapshot on an Evolving Field
No full textShape-changing, self-repairing, self-assembly, are some of the characteristics today associated with 4D printed objects, highlighting that these are no longer static objects but programmable active structures that accomplish their function thanks to their architecture and compositio
Degradable block polyurethanes from non toxic building blocks as scaffold materials to support cell growth and proliferation
No full textDispositivi Tubolari Biaortificiali e Biodegradabili per la rigenerazione della fibra nervosa
No full textExtrusion control strategy for robotic-based in situ bioprinting
No full textRobotic-based in situ bioprinting is a very promising technology to overcome the limitations of the traditional scaffold-based tissue engineering approach. One of the most used bioprinting technologies to deposit the biomaterial directly onto/into a damaged site of the patient is based on a pneumatic extrusion. During the printing phase, the robotic manipulator end-effector is subjected to continuous changes in speed and direction to follow complex anatomical surfaces. For this reason, in this work we describe the development of an extrusion control strategy to obtain a uniform biomaterial deposition during a robotic-based in situ bioprinting procedure. The proposed algorithm was tested onto IMAGObot, a 5-axes robotic platform optimized for in situ bioprinting applications
Endothelial cell adhesion on bioerodable polymers
No full textThis paper presents the results of a preliminary screening of a new class of bioerodable polymers, partial esters of alternating copolymers of maleic anhydride and monomethoxyoligoethyleneglycol vinyl ethers (PAM) for use in engineered vascular tissue. Different initial concentrations of PAM and human serum albumin (HSA) were spin-coated onto glass substrates and the surface properties of the resulting films and their relationship to endothelial cell adhesion was examined. An optimum PAM/HSA blend for use as the cell contact surface of a bioerodable scaffold was identified. © 2001 Kluwer Academic Publishers
Microfabricated and multilayered PLGA structure for the development of co-cultured in vitro liver models
Full text linkOne of the main advantages of having an in vitro model is the possibility of reducing toxic effects of drugs on human body and evaluate their response to pharmacological treatments to improve the efficacy of a patient-specific therapy. The limitation of such in vitro model is the use of monolayer hepatocytes cultures that show some problems of protein secretion and hepatic functionality. In order to overcome these drawbacks, we present two innovative multilayer structures based on micro-stamped poly(lactic-co-glycolic acid) (PLGA) structures and hepatocytes and fibroblast co-cultures. In particular, the first model consisted of 1 up to 5 layers of PLGA seeded with the previously cited co-culture, while the second model consisted of various sandwich structures of PLGA functionalised (or not) with collagen and seeded with hepatocytes and/or fibroblasts. A mechanical analysis, contact angle and surface charge density measurements were carried out. After these preliminary tests, a metabolic analysis was performed evaluating glucose consumption and urea and albumin production over a culture period of 11 days. Results showed promising application of these in vitro liver models, in particular considering the field of cirrhotic liver treatment
Enhancing quality control in bioprinting through machine learning
No full textBioprinting technologies have been extensively studied in literature to fabricate three-dimensional constructs for tissue engineering applications. However, very few examples are currently available on clinical trials using bioprinted products, due to a combination of technological challenges (i.e. difficulties in replicating the native tissue complexity, long printing times, limited choice of printable biomaterials) and regulatory barriers (i.e. no clear indication on the product classification in the current regulatory framework). In particular, quality control (QC) solutions are needed at different stages of the bioprinting workflow (including pre-process optimization, in-process monitoring, and post-process assessment) to guarantee a repeatable product which is functional and safe for the patient. In this context, machine learning (ML) algorithms can be envisioned as a promising solution for the automatization of the quality assessment, reducing the inter-batch variability and thus potentially accelerating the product clinical translation and commercialization. In this review, we comprehensively analyse the main solutions that are being developed in the bioprinting literature on QC enabled by ML, evaluating different models from a technical perspective, including the amount and type of data used, the algorithms, and performance measures. Finally, we give a perspective view on current challenges and future research directions on using these technologies to enhance the quality assessment in bioprinting
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