Modal Analysis and Coupling in Metal-Insulator-Metal Waveguides

This paper shows how to analyze plasmonic metal-insulator-metal waveguides using the full modal structure of these guides. The analysis applies to all frequencies, particularly including the near infrared and visible spectrum, and to a wide range of sizes, including nanometallic structures. We use the approach here specifically to analyze waveguide junctions. We show that the full modal structure of the metal-insulator-metal (MIM) waveguides--which consists of real and complex discrete eigenvalue spectra, as well as the continuous spectrum--forms a complete basis set. We provide the derivation of these modes using the techniques developed for Sturm-Liouville and generalized eigenvalue equations. We demonstrate the need to include all parts of the spectrum to have a complete set of basis vectors to describe scattering within MIM waveguides with the mode-matching technique. We numerically compare the mode-matching formulation with finite-difference frequency-domain analysis and find very good agreement between the two for modal scattering at symmetric MIM waveguide junctions. We touch upon the similarities between the underlying mathematical structure of the MIM waveguide and the PT symmetric quantum mechanical pseudo-Hermitian Hamiltonians. The rich set of modes that the MIM waveguide supports forms a canonical example against which other more complicated geometries can be compared. Our work here encompasses the microwave results, but extends also to waveguides with real metals even at infrared and optical frequencies.Comment: 17 pages, 13 figures, 2 tables, references expanded, typos fixed, figures slightly modifie

Impacts of excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase, and epidermal growth factor receptor on the outcomes of patients with advanced gastric cancer

Using laser-captured microdissection and a real-time RT–PCR assay, we quantitatively evaluated mRNA levels of the following biomarkers in paraffin-embedded gastric cancer (GC) specimens obtained by surgical resection or biopsy: excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase (DPD), methylenetetrahydrofolate reductase (MTHFR), epidermal growth factor receptor (EGFR), and five other biomarkers related to anticancer drug sensitivity. The study group comprised 140 patients who received first-line chemotherapy for advanced GC. All cancer specimens were obtained before chemotherapy. In patients who received first-line S-1 monotherapy (69 patients), low MTHFR expression correlated with a higher response rate (low: 44.9% vs high: 6.3%; P=0.006). In patients given first-line cisplatin-based regimens (combined with S-1 or irinotecan) (43 patients), low ERCC1 correlated with a higher response rate (low: 55.6% vs high: 18.8%; P=0.008). Multivariate survival analysis of all patients demonstrated that high ERCC1 (hazard ratio (HR): 2.38 (95% CI: 1.55–3.67)), high DPD (HR: 2.04 (1.37–3.02)), low EGFR (HR: 0.34 (0.20–0.56)), and an elevated serum alkaline phosphatase level (HR: 1.00 (1.001–1.002)) were significant predictors of poor survival. Our results suggest that these biomarkers are useful predictors of clinical outcomes in patients with advanced GC

Multiple-input multiple-output causal strategies for gene selection

Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting.Journal ArticleResearch Support, N.I.H. ExtramuralResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12 155 patients

The Ki-67 antigen is used to evaluate the proliferative activity of breast cancer (BC); however, Ki-67's role as a prognostic marker in BC is still undefined. In order to better define the prognostic value of Ki-67/MIB-1, we performed a meta-analysis of studies that evaluated the impact of Ki-67/MIB-1 on disease-free survival (DFS) and/or on overall survival (OS) in early BC. Sixty-eight studies were identified and 46 studies including 12 155 patients were evaluable for our meta-analysis; 38 studies were evaluable for the aggregation of results for DFS, and 35 studies for OS. Patients were considered to present positive tumours for the expression of Ki-67/MIB-1 according to the cut-off points defined by the authors. Ki-67/MIB-1 positivity is associated with higher probability of relapse in all patients (HR=1.93 (95% confidence interval (CI): 1.74–2.14); P<0.001), in node-negative patients (HR=2.31 (95% CI: 1.83–2.92); P<0.001) and in node-positive patients (HR=1.59 (95% CI: 1.35–1.87); P<0.001). Furthermore, Ki-67/MIB-1 positivity is associated with worse survival in all patients (HR=1.95 (95% CI: 1.70–2.24; P<0.001)), node-negative patients (HR=2.54 (95% CI: 1.65–3.91); P<0.001) and node-positive patients (HR=2.33 (95% CI: 1.83–2.95); P<0.001). Our meta-analysis suggests that Ki-67/MIB-1 positivity confers a higher risk of relapse and a worse survival in patients with early BC

Aromatase inhibitor-associated bone and musculoskeletal effects: new evidence defining etiology and strategies for management

Aromatase inhibitors are widely used as adjuvant therapy in postmenopausal women with hormone receptor-positive breast cancer. While the agents are associated with slightly improved survival outcomes when compared to tamoxifen alone, bone and musculoskeletal side effects are substantial and often lead to discontinuation of therapy. Ideally, the symptoms should be prevented or adequately treated. This review will focus on bone and musculoskeletal side effects of aromatase inhibitors, including osteoporosis, fractures, and arthralgias. Recent advances have been made in identifying potential mechanisms underlying these effects. Adequate management of symptoms may enhance patient adherence to therapy, thereby improving breast cancer-related outcomes