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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. 

To sensitively detect multiple and cross-species disease-related targets from a single biological sample in a quick and reliable manner is of high importance in accurately diagnosing and monitoring diseases. Herein, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized multiple-armed tetrahedral DNA nanostructure (FMTDN) immobilized silver nanorod (AgNR) array substrate and Au nanoparticle (AuNP) SERS tags is constructed to achieve both multiplex detection and enhanced sensitivity using a sandwich strategy. The sensor can achieve single, dual, and triple biomarker detections of three lung cancer-related nucleic acid and protein biomarkers, i.e. , miRNA-21, miRNA-486 and carcinoembryonic antigen (CEA) in human serum. The enhanced SERS signals in multiplex detections are due to the DNA self-assembled AuNP clusters on the silver nanorod array during the assay, and the experimentally obtained relative enhancement factor ratios, 150 for AuNP dimers and 840 for AuNP trimers, qualitatively agree with the numerically calculated local electric field enhancements. The proposed FMTDN-functionalized AgNR SERS sensor is capable of multiplex and cross-species detection of nucleic acid and protein biomarkers with improved sensitivity, which has great potential for the screening and clinical diagnosis of cancer in the early stage.