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A SERS instrument transformation framework based on the penalized functional regression model (SpectraFRM) is proposed for cross-instrument mapping with subsequent machine learning classification to compare transformed spectra with standard spectra. 

As a treatment for the widely spread cardiovascular diseases (CVD), bypass vascular grafts have room for improvement in terms of mechanical property match with native arteries. A 3D‐printed nozzle is presented, featuring unique internal structures, to extrude artificial vascular grafts with a flower‐mimicking geometry. The multilayer‐structured graft wall allows the inner and outer layers to interfere sequentially during lateral expansion, replicating the nonlinear elasticity of native vessels. Both experiment and simulation results verify the necessity and benefit of the flower‐mimicking structure in obtaining the self‐toughening behavior. The gelation study of natural polymers and the utilization of sacrificial phase enables the smooth extrusion of the multiphase conduit, where computer‐assisted image analysis is employed to quantify manufacturing fidelity. The cell viability tests demonstrate the cytocompatibility of the gelatin methacryloyl (GelMA)/sodium alginate grafts, suggesting potential for further clinical research with further developments. This study presents a feasible approach for fabricating bypass vascular grafts and inspires future treatments for CVD. 

Abstract During the operation of a localized surface plasmon resonance (LSPR) sensor made in the form of a core–shell nanoparticle with the shell acting as a sensing layer, the target molecules penetrate into the shell due to intrinsic diffusion or reaction mechanisms. As a result, these molecules or various reactants are nonuniformly distributed in the shell layer. Such sensing particles are termed composition graded plasmonic particles, and their LSPR characteristics may be quite different from those of the uniform core–shell particles. Here, under the quasi-static assumption, a perturbation theory is developed to predict the LSPR properties of composition graded plasmonic particles. The effects of the composition gradient on the LSPR properties due to a metal hydride, a dielectric, and an effective medium are either numerically calculated or analytically derived. Our results show that various configurations of the composition gradient can tune the location and the amplitude of the LSPR peak. The results are important for understanding the sensing performance of composition graded plasmonic particles, and the perturbative treatment presented here can also be used for other composition graded structures. 

Abstract 3D printing, also known as additive manufacturing, holds immense potential for rapid prototyping and customized production of functional health‐related devices. With advancements in polymer chemistry and biomedical engineering, polymeric biomaterials have become integral to 3D‐printed biomedical applications. However, there still exists a bottleneck in the compatibility of polymeric biomaterials with different 3D printing methods, as well as intrinsic challenges such as limited printing resolution and rates. Therefore, this review aims to introduce the current state‐of‐the‐art in 3D‐printed functional polymeric health‐related devices. It begins with an overview of the landscape of 3D printing techniques, followed by an examination of commonly used polymeric biomaterials. Subsequently, examples of 3D‐printed biomedical devices are provided and classified into categories such as biosensors, bioactuators, soft robotics, energy storage systems, self‐powered devices, and data science in bioplotting. The emphasis is on exploring the current capabilities of 3D printing in manufacturing polymeric biomaterials into desired geometries that facilitate device functionality and studying the reasons for material choice. Finally, an outlook with challenges and possible improvements in the near future is presented, projecting the contribution of general 3D printing and polymeric biomaterials in the field of healthcare.