Photo-crosslinkable gelatin methacrylate (GelMA) has become an attractive ink in 3D printing due to its excellent biological performance. However, limited by low viscosity and long cross-linking time, it is still a challenge to directly print GelMA by extrusion-based 3D printing. Here, to balance the printability and biocompatibility, biomaterial ink composed of GelMA and nanoclay was specially designed. Using this ink, complex scaffolds with high shape fidelity can be easily printed based on the thixotropic property of nanoclay. In this study, we tried to answer some basic printing-required questions of this ink, including the printability window, general properties (porosity, mechanical strength, et al), and biocompatibility. We found that the GelMA/Nanoclay ink enabled printing complex 3D scaffolds, such as a bionic ear and a branched vessel. Furthermore, the addition of nanoclay improved the porosity, increased the mechanical strength, reduced the degradation ratio, and maintained a good biocompatibility of the printed scaffolds. Therefore, this method offers an easy way to print complex scaffolds with good shape fidelity and biological performance, and it might open up new potential applications for the customized therapy of tissue defects.

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Here, we constructs a whole vascular system, from arteries and capillaries to veins with a high resolution 3D printing. A bulk breast tumor tissue with a functional vascular network was built. The interaction between tumors and vessels is investigated.

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A rapid quantification method was developed and validated for simultaneous and nondestructive quantifying the constituent sugar concentrations of intact apples using Fourier transform near-infrared (FT-NIR) spectroscopy in diffuse reflectance mode. Multiplicative scatter correction (MSC), the second derivative of Savitsky-Golay, and mean centering were used as spectral preprocessing options. Calibration models were established by the partial least squares (PLS) regression analysis, and validation of the method was performed according to the high-performance liquid chromatography (HPLC) chromatographic method. Spectral range and the number of PLS factors were optimized for the lowest root-mean-square error of prediction (RMSEP) and correlation coefficient of determination (r). The best models showed satisfactory predictions as measured by the RMSEP and r values: glucose, 0.201 and 0.950; fructose, 0.298 and 0.968; sucrose, 0.335 and 0.969, respectively. FT-NIR analysis of constituent sugar concentrations in the intact apple form was found to be more flexible and much faster than performed with the HPLC method.