Using Au nanoparticles, it is possible under certain experimental conditions to considerably enhance the sensitivity of a conventional surface plasmon resonance (SPR) device. In this report, we examine the mechanism of this enhancement and discuss the experimental factors that are crucial to the performance of such a nanoparticle based SPR device. Among these factors, the surface plasmon-supporting metal substrate plays a major role. We demonstrate this by comparing experimental SPR data for Au and Ag substrates. In both cases, ∼25-30 nm diameter Au particles are attached to the substrate metal via a sandwiched monolayer of 1,6-hexanedithiol. The width and the efficiency of SPR for both substrates are affected by the Au particles. However, the particle-induced shift in the SPR angle is observed only for the Au substrate. This observation is explained in terms of competitive effects of propagating surface plasmons in the substrate metal and localized surface plasmons in the Au nanoparticles.In recent years, the SPR imaging technique has been successfully employed for immunosensing and for thickness measurements of ultrathin (2-20 Å) films. [1][2][3] In a typical SPR device, the sample layer is adsorbed onto a metal film, and the total attenuated reflection (ATR) efficiency, R, of the metal is measured as a function of the incidence angle, θ, of a probe light beam. The behavior of R is determined by the propagating surface plasmon polariton (SPP) modes at the metal/sample interface. In the absence of the sample, the R-θ plot (SPR plot) exhibits a dip at the angle, θ p , where the condition for SPR (resonance in SPP oscillations) is satisfied. In the presence of the sample layer(s), θ p shifts to a new value, and this shift is analyzed to determine the thickness (amount) and/or the dielectric function (chemical properties) of the sample. 4,5 Usually, the width, position and height of the SPR plot, as well as the fractional reflectivity change, (∆R/R) p , at the SPR angle are also modified in the presence of the adsorbed sample. These latter changes can provide additional information about the sample. However, often the sensitivity of the SPR device is limited by small shifts in θ p and (∆R/R) p . An effort to overcome the limitations of conventional SPR imaging have been recently reported by Lyon et al. 6,7 The discussion of our present communication focuses on the SPR device proposed by these authors. They use a gold nanoparticle-modified device, where an organic self-assembled monolayer (SAM) is sandwiched between a gold film and a layer of colloidal gold particles (in the 10-60 nm diameter range). The experimental sample is adsorbed on top on to the Au nanoparticles. The Au particles enhance the magnitude of ∆θ p , and at the same time, introduce an additional change in (∆R/R) p . These particles have their own

No abstract

Choledochal cyst and anomalous pancreaticobiliary ductal union (APBDU) are considered to be embryologically related to each other, and their complications are clinically important. This article illustrates the key imaging features of choledochal cysts and APBDU and their various associated abnormalities and complications. Complications of common bile duct are more common in APBDU with choledochal cyst, and complications of gallbladder are more common in APBDU without choledochal cyst.

With advances in the design, synthesis and analysis of various metallic nanoparticles and substrates, surface‐enhanced Raman scattering (SERS) with plasmonic nanostructures has been extensively studied, and numerous SERS applications have been demonstrated in various applications including biomedical applications; however, the mechanism of SERS is not completely understood yet, and many challenges, including structural and spectral reproducibility, exist to achieve quantitative SERS analysis for practical and reliable use of SERS. Since SERS signal reproducibility mainly stems from structural reproducibility of targeted nanostructures, single‐particle SERS analysis is highly beneficial in understanding SERS signals generated from different plasmonic nanostructures and provides analytical insights that cannot be obtained with ensemble‐average spectrum‐based analysis. Single‐particle analysis is typically composed of single‐particle images and spectra, and the statistical results show the single‐particle SERS enhancement factor distribution of SERS signals and precise structure‐spectrum relationship. In particular, studying and evaluating single‐molecule SERS results require single‐particle analysis to fully understand how single‐particle images and spectra are correlated with how the position, orientation and resonance of a Raman dye affect single‐molecule SERS signals from individual nanoparticles, and this is often correlated with computational simulation results. In this mini‐review, we introduce key issues for quantitative SERS and present the fundamental SERS features obtained by single‐particle analysis, focused on plasmonic nanogap structures since these structures offer the very strong electromagnetic field‐based SERS signals with high controllability in structure and signal. We categorized the nanogap particle‐based SERS platforms into two different classes – plasmonic nanogap strctures with an intergap (the gap between two structures; intergap nanoparticles) and plasmonic nanogap structures with an intragap (the gap formed inside a single particle; intragap nanoparticles). Finally, we discuss the challenges and perspectives in designing and synthesizing nanogap structures that deliver strong, reproducible, and reliable SERS signals for the quantitative SERS analysis.

Surface-enhanced Raman scattering (SERS) provides significantly enhanced Raman scattering signals from molecules adsorbed on plasmonic nanostructures, as well as the molecules' vibrational fingerprints. Plasmonic nanoparticle systems are particularly powerful for SERS substrates as they provide a wide range of structural features and plasmonic couplings to boost the enhancement, often up to >10 8 −10 10 . Nevertheless, nanoparticle-based SERS is not widely utilized as a means for reliable quantitative measurement of molecules largely due to limited controllability, uniformity, and scalability of plasmonic nanoparticles, poor molecular modification chemistry, and a lack of widely used analytical protocols for SERS. Furthermore, multiscale issues with plasmonic nanoparticle systems that range from atomic and molecular scales to assembled nanostructure scale are difficult to simultaneously control, analyze, and address. In this perspective, we introduce and discuss the design principles and key issues in preparing SERS nanoparticle substrates and the recent studies on the uniform and controllable synthesis and newly emerging machine learning-based analysis of plasmonic nanoparticle systems for quantitative SERS. Specifically, the multiscale point of view with plasmonic nanoparticle systems toward quantitative SERS is provided throughout this perspective. Furthermore, issues with correctly estimating and comparing SERS enhancement factors are discussed, and newly emerging statistical and artificial intelligence approaches for analyzing complex SERS systems are introduced and scrutinized to address challenges that cannot be fully resolved through synthetic improvements.

No abstract

A I M :To d e t e r m i n e t h e a c c u r a c y o f c o m p u t e d tomography (CT) and magnetic resonance (MR) for presurgical characterization of paraaortic lymph nodes in patients with pancreatico-biliary carcinoma. METHODS:Two radiologists independently evaluated CT and MR imaging of 31 patients who had undergone lymphadenectomy (9 metastatic and 22 non-metastatic paraaortic nodes). Receiver operating characteristic (ROC) curve analysis was performed using a five point scale to compare CT with MRI. To re-define the morphologic features of metastatic nodes, we evaluated CT scans from 70 patients with 23 metastatic paraaortic nodes and 47 non-metastatic ones. The short axis diameter, ratio of the short to long axis, shape, and presence of necrosis were compared between metastatic and non-metastatic nodes by independent samples t -test and Fisher's exact test. P < 0.05 was considered statistically significant. RESULTS:The mean area under the ROC curve for CT (0.732 and 0.646, respectively) was slightly higher than that for MRI (0.725 and 0.598, respectively) without statistical significance (P = 0.940 and 0.716, respectively). The short axis diameter of the metastatic lymph nodes (mean = 9.2 mm) was significantly larger than that of non-metastatic ones (mean = 5.17 mm, P < 0.05). Metastatic nodes had more irregular margins (44.4%) and central necrosis (22.2%) than non-metastatic ones (9% and 0%, respectively), with statistical significance (P < 0.05). CONCLUSION:

Abstract--The optimal charging schemes for Electric vehicles (EV) generally differ from each other in the choice of charging periods and the possibility of performing vehicle-to-grid (V2G), and have different impacts on EV economics. Regarding these variations, this paper presents a numerical comparison of four different charging schemes, namely night charging, night charging with V2G, 24 hour charging and 24 hour charging with V2G, on the basis of real driving data and electricity price of Denmark in 2003. For all schemes, optimal charging plans with 5 minute resolution are derived through the solving of a mixed integer programming problem which aims to minimize the charging cost and meanwhile takes into account the users' driving needs and the practical limitations of the EV battery. In the post processing stage, the rainflow counting algorithm is implemented to assess the lifetime usage of a lithium-ion EV battery for the four charging schemes. The night charging scheme is found to be the cheapest solution after conducting an annual cost comparison.