Effect of Foreign Ion Substitution and Micropore Tuning in Robocasting Single-Phase Bioceramic Scaffolds on the Physicochemical Property and Vascularization

Biomaterials-Based Strategies to Enhance Angiogenesis in Diabetic Wound Healing

Amidst the present healthcare issues, diabetes is unique as an emerging class of affliction with chronicity in a majority of the population. To check and control its effects, there have been huge turnover and constant development of management strategies, and though a bigger part of the health care area is involved in achieving its control and the related issues such as the effect of diabetes on wound healing and care and many of the works have reached certain successful outcomes, still there is a huge lack in managing it, with maximum effect yet to be attained. Studying pathophysiology and involvement of various treatment options, such as tissue engineering, application of hydrogels, drug delivery methods, and enhancing angiogenesis, are at constantly developing stages either direct or indirect. In this review, we have gathered a wide field of information and different new therapeutic methods and targets for the scientific community, paving the way toward more settled ideas and research advances to cure diabetic wounds and manage their outcomes.

Exploration of the Underlying Space in Microscopic Images via Deep Learning for Additively Manufactured Piezoceramics

There has been a surge of interest in applying deep learning (DL) to microstructure generation and materials design. However, existing DL-based methods are generally limited in generating (1) microstructures with high resolution, (2) microstructures with high variability, (3) microstructures with guaranteed periodicity, and (4) highly controllable microstructures. In this study, a DL approach based on a stacked generative adversarial network (StackGAN-v2) is proposed to overcome these shortcomings. The presented modeling approach can reconstruct high-fidelity microstructures of additively manufactured piezoceramics with different resolutions, which are statistically equivalent to original microstructures either experimentally observed or numerically predicted. Advantages of the proposed modeling approach are also illustrated in terms of its capability in controlling the probability density function (PDF) of grain size, grain orientation, and micropore in a large space, which would have significant benefits in exploring the effects of these microstructure features on the piezoelectricity of piezoceramics. In the meantime, periodicity of the microstructures has been successfully introduced in the developed model, which can critically reduce the simulation volume to be considered as a representative volume element (RVE) during computational calculation of piezoelectric properties. Therefore, this DL approach can significantly accelerate the process of designing optimal microstructures when integrating with computational methods (e.g., fast Fourier spectral iterative perturbation (FSIPM)) to achieve desired piezoelectric properties. The proposed DL-based method is generally applicable to optimal design of a variety of periodic microstructures, allowing for maximum explorations of design spaces and fine manipulations of microstructural features.