2022
DOI: 10.1016/j.isci.2022.104947
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3D bioprinting of nanoparticle-laden hydrogel scaffolds with enhanced antibacterial and imaging properties

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Cited by 17 publications
(18 citation statements)
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“…Compared to conventional scaffold fabrication methods, bioprinting enables creation of complex structural/functional designs, including both internal and external features such as vascular networks, [50] heterogenous pattering of cells and/or small molecules, [51] and patient-specific scaffold shape/geometry. [30,52] The integration of intrinsic and enhanced adhesive properties, together with complex structural/functional features in bioprinted ATES systems can provide robust implant solutions for a variety of regenerative medicine applications.…”
Section: Resultsmentioning
confidence: 99%
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“…Compared to conventional scaffold fabrication methods, bioprinting enables creation of complex structural/functional designs, including both internal and external features such as vascular networks, [50] heterogenous pattering of cells and/or small molecules, [51] and patient-specific scaffold shape/geometry. [30,52] The integration of intrinsic and enhanced adhesive properties, together with complex structural/functional features in bioprinted ATES systems can provide robust implant solutions for a variety of regenerative medicine applications.…”
Section: Resultsmentioning
confidence: 99%
“…Fidelity of bioprinted ATES constructs was evaluated at two different scales as previously reported. [ 23,30–32 ] First, strand‐level (micro) fidelity was examined [ 31 ] by printing a 2D network of bioink strands on the glass slide based on a lattice pattern designed by CAD software (Figure 1C). The diameter of the strands ( d strand ), the angle between two crossing strands ( α strands ), and the area between two pairs of parallel strands ( A strands ) were measured (ImageJ) and normalized by dividing to the corresponding values in the CAD design ( d strand in CAD , α strands in CAD , and A strands in CAD ) using the following equations: rd,strand=dstrand0.33emin0.33emprintdstrand0.33emin0.33emCAD×100$$\begin{eqnarray}{r}_{{\rm{d,strand}}} = \frac{{{d}_{{\rm{strand\ in\ print}}}}}{{{d}_{{\rm{strand\ in\ CAD}}}}}\ \times \ 100\end{eqnarray}$$ rα,strand=αstrands0.33emin0.33emprintαstrands0.33emin0.33emCAD×100$$\begin{eqnarray}{r}_{{\rm{\alpha ,strand}}} = \frac{{{\alpha }_{{\rm{strands\ in\ print}}}}}{{{\alpha }_{{\rm{strands\ in\ CAD}}}}}\ \times \ 100\end{eqnarray}$$ rA,strand=Astrands0.33emin0.33emprintAstrands0.33emin0.33emCAD×100$$\begin{eqnarray}{r}_{{\rm{A,strand}}} = \frac{{{A}_{{\rm{strands\ in\ print}}}}}{{{A}_{{\rm{strands\ in\ CAD}}}}}\ \times \ 100\end{eqnarray}$$…”
Section: Methodsmentioning
confidence: 99%
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“…A range of non‐invasive imaging modalities have been considered to monitor the performance of tissue engineering scaffolds. Magnetic resonance imaging (MRI) has been widely used to image scaffold constructs in vitro and in vivo due to exhibiting deep tissue penetration, soft tissue contrast, and high sensitivity; [ 8,18,19 ] MRI methods, however, require long acquisition times. [ 20 ] Other techniques, such as positron emission tomography (PET) and single positron emission computed tomography (SPECT), have been employed for in vivo molecular imaging of implanted scaffold structures.…”
Section: Introductionmentioning
confidence: 99%