Engineering of Vis-NIR Metamaterials towards Revolutionary Ultrasensitive and Versatile Plasmonic Biosensors

By enabling subwavelength light localization and strong electromagnetic field enhancement, plasmonic biosensors have opened up a new realm of possibilities for a broad range of chemical and biological sensing applications owing to their label-free and real-time attributes. Although significant progress has been made, many fundamental and practical challenges still remain to be addressed. For instance, the plasmonic biosensors are nonselective sensing platforms; they are not well-suited to provide information regarding conformation or chemical fingerprint of unknown biomolecules. Furthermore, tunability of the plasmonic resonance in visible frequency regime is still limited; this will prevent their efficient and reproducible exploitation in single-molecule sensitivity. Here, we show that by engineering geometry of plasmonic metamaterials,1 consisting of periodic arrays of artificial split-ring resonators (SRRs), the plasmonic resonance of metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that it allows parallel acquisition of optical transmission and highly surface-enhanced Raman (SERS) spectra from large functionalized SRR arrays. The Au SRRs were designed in form of alphabet letters (U, V, S, H, Y) with various line width (from 80 to 30 nm). By tailoring their size and shape, plasmonic resonance wavelength of the SRRs could be actively tuned so that it gives the strongest SERS effect under given excitation energy and polarization for biological and organic molecules. On the other hand, the plasmonic tunability was also achieved for a given SRR pattern by tuning the laser wavelength to obtain the highest electromagnetic field enhancement. The geometry- and laser-tunable channels typically provide an electromagnetic field enhancement as high as 20 times. This will provide the basis of versatile and multichannel devices for identification of different conformational states of Guanine-rich DNA, detection of a cancer biomarker nucleolin, and femtomolar sensitivity detection of food and drink additives. These results show that the tunable Vis-IR metamaterials are very versatile biosensing platforms and suggest considerable promise in genomic research, disease diagnosis, and food safety analysis.

Label-free Analysis of Conformational Dynamics and Molecular Interaction of Biomolecules by Vis-NIR Metasensor

Analysis of binding recognition and conformation of biomolecules is of paramount important in understanding of their vital functions in complex biological systems. By enabling sub-wavelength light localization and strong local field enhancement, plasmonic biosensors have become dominant tools used for such analysis owing to their label-free and real-time attributes1,2. However, the plasmonic biosensors are not well-suited to provide information regarding conformation or chemical fingerprint of biomolecules. Here, we show that plasmonic metamaterials, consisting of periodic arrays of artificial split-ring resonators (SRRs)3, can enable capabilities of both sensing and fingerprinting of biomolecules. We demonstrate that by engineering geometry of individual SRRs, localized surface plasmon resonance (LSPR) frequency of the metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that they possess high local field enhancement for surface-enhanced Raman scattering spectroscopy (SERS). This will provide the basis for the development of a dual mode label-free conformational-resolving and quantitative detection platform. We present here the ability of each sensing mode to independently detect binding adsorption and to identify different conformational states of Guanine (G)-rich DNA monolayers in different environment milieu. Also shown is the use of the nanosensor for fingerprinting and detection of Arginine-Glycine-Glycine (RGG) peptide binding to the G-quadruplex aptamer. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays that the conventional, population-averaged plasmonic biosensors cannot achieve.

3-Deoxyfructose concentrations are increased in human plasma and urine in diabetes

3-Deoxyglucosone (3-DG) is a reactive dicarbonyl sugar thought to be a key intermediate in the nonenzymatic polymerization and browning of proteins by glucose. 3-DG may be formed in vivo from fructose, fructose 3-phosphate, or Amadori adducts to protein, such as N epsilon-fructoselysine (FL), all of which are known to be elevated in body fluids or tissues in diabetes. Modification of proteins by 3-DG formed in vivo is thought to be limited by enzymatic reduction of 3-DG to less reactive species, such as 3-deoxyfructose (3-DF). In this study, we have measured 3-DF, as a metabolic fingerprint of 3-DG, in plasma and urine from a group of diabetic patients and control subjects. Plasma and urinary 3-DF concentrations were significantly increased in the diabetic compared with the control population (0.853 +/- 0.189 vs. 0.494 +/- 0.072 microM, P <0.001, and 69.9 +/- 44.2 vs. 38.7 +/- 16.1 nmol/mg creatinine, P <0.001, respectively). Plasma and urinary 3-DF concentrations correlated strongly with one another, with HbA1c (P <0.005 in all cases), and with urinary FL (P <0.02 and P = 0.005, respectively). The overall increase in 3-DF concentrations in plasma and urine in diabetes and their correlation with other indexes of glycemic control suggest that increased amounts of 3-DG are formed in the body during hyperglycemia in diabetes and then metabolized to 3-DF. These observations are consistent with a role for increased formation of the dicarbonyl sugar 3-DG in the accelerated browning of tissue proteins in diabetes.

The Potency of Pastoral in Hispanic Baroque poetry

This monograph demonstrates that aesthetic and ontological anxieties continue to find diverse expression within the contrived textual artifice of the bucolic space. Drawing upon expansive definitions of the Hispanic literary Baroque, (Beverley, 1980, 2008, Echevarría 1993, Ross 1993, Chemris 2008 , Egido 2009 ) the study analyses the pastoral verse of representative poets of the period to demonstrate that they re-enter an Arcadia that has been defamiliarized but is nonetheless inexorably connected to the classical origins of the mode. Pastoral, in common with other literary forms, is subject to a process of re-evaluation which was latent in its classical legacy. Within the intricacies of this literary construct, surface artistry sustains an effect of artless innocence that is vibrantly contested across the secular, sacred, parodic and colonial text.

It's not that I don't care, I just don't care very much: confounding between attribute non-attendance and taste heterogeneity

With the growing interest in the topic of attribute non-attendance, there is now widespread use of latent class (LC) structures aimed at capturing such behaviour, across a number of different fields. Specifically, these studies rely on a confirmatory LC model, using two separate values for each coefficient, one of which is fixed to zero while the other is estimated, and then use the obtained class probabilities as an indication of the degree of attribute non-attendance. In the present paper, we argue that this approach is in fact misguided, and that the results are likely to be affected by confounding with regular taste heterogeneity. We contrast the confirmatory model with an exploratory LC structure in which the values in both classes are estimated. We also put forward a combined latent class mixed logit model (LC-MMNL) which allows jointly for attribute non-attendance and for continuous taste heterogeneity. Across three separate case studies, the exploratory LC model clearly rejects the confirmatory LC approach and suggests that rates of non-attendance may be much lower than what is suggested by the standard model, or even zero. The combined LC-MMNL model similarly produces significant improvements in model fit, along with substantial reductions in the implied rate of attribute non-attendance, in some cases even eliminating the phenomena across the sample population. Our results thus call for a reappraisal of the large body of recent work that has implied high rates of attribute non-attendance for some attributes. Finally, we also highlight a number of general issues with attribute non-attendance, in particular relating to the computation of willingness to pay measures.

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

Targeted Impersonation As A Tool For The Detection Of Biometric System Vulnerabilities

This paper argues that biometric verification evaluations can obscure vulnerabilities that increase the chances that an attacker could be falsely accepted. This can occur because existing evaluations implicitly assume that an imposter claiming a false identity would claim a random identity rather than consciously selecting a target to impersonate. This paper shows how an attacker can select a target with a similar biometric signature in order to increase their chances of false acceptance. It demonstrates this effect using a publicly available iris recognition algorithm. The evaluation shows that the system can be vulnerable to attackers targeting subjects who are enrolled with a smaller section of iris due to occlusion. The evaluation shows how the traditional DET curve analysis conceals this vulnerability. As a result, traditional analysis underestimates the importance of an existing score normalisation method for addressing occlusion. The paper concludes by evaluating how the targeted false acceptance rate increases with the number of available targets. Consistent with a previous investigation of targeted face verification performance, the experiment shows that the false acceptance rate can be modelled using the traditional FAR measure with an additional term that is proportional to the logarithm of the number of available targets.

Beyond the standard work model? Varieties of flexible working time in European economies

Working time has been among the first aspect of the employment relation to be the object of intense regulation at the national and supra-national level. This standard regulation of working time comprised a number of elements: full-time hours, rigid working schedules, strong employers’ control and clear boundaries around working time In spite of general claims about the erosion of this model, few studies have investigated this process in a comparative and empirical perspective. The aim of this paper is to investigate the diversity of working time arrangements in European economies by applying latent class analysis to data
from the European Working Conditions Survey (EWCS). This analysis shows the existence of six different types of working time organization highlighting five cross-national patterns: multiple flexibilities, extended flexibility, standard, rigid and fragmented time.

ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

Overconfidence, sexual health awareness and sexual health risk among young female users of sexual health clinics

This study explored the patterning of young people’s sexual health competence, and how this relates to sexual health outcomes. A survey of 381 young people attending two sexual health clinics in Northern Ireland was carried out between 2009 and 2010. Latent profile analysis of self-rated decision making, self-rated sexual health knowledge, and knowledge of sexually transmitted disease questionnaire scores was used to determine typologies of sexual health competence. Analysis revealed three categories of sexual health competence and explored their association with other behaviours and social characteristics. Young people’s subjective opinion of their sexual health competency, when not matched with a corresponding knowledge of sexual health, could place people at an increased risk of poor sexual health outcomes. Greater levels of peer pressure to have sex and early sexual debut were associated with poorer sexual health knowledge. This finding warrants further investigation, as the importance of self-perceived competence for sexual health screening and education programmes are considerable.

Turbo-smt: Accelerating coupled sparse matrix-tensor factorizations by 200x

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem.

Can we accelerate any CMTF solver, so that it runs within a few minutes instead of tens of hours to a day, while maintaining good accuracy? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, by up to 200x, along with an up to 65 fold increase in sparsity, with comparable accuracy to the baseline.

We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy.

Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review

Background: There is growing interest in the potential utility of real-time polymerase chain reaction (PCR) in diagnosing bloodstream infection by detecting pathogen deoxyribonucleic acid (DNA) in blood samples within a few hours. SeptiFast (Roche Diagnostics GmBH, Mannheim, Germany) is a multipathogen probe-based system targeting ribosomal DNA sequences of bacteria and fungi. It detects and identifies the commonest pathogens causing bloodstream infection. As background to this study, we report a systematic review of Phase III diagnostic accuracy studies of SeptiFast, which reveals uncertainty about its likely clinical utility based on widespread evidence of deficiencies in study design and reporting with a high risk of bias. 

Objective: Determine the accuracy of SeptiFast real-time PCR for the detection of health-care-associated bloodstream infection, against standard microbiological culture. 

Design: Prospective multicentre Phase III clinical diagnostic accuracy study using the standards for the reporting of diagnostic accuracy studies criteria. 

Setting: Critical care departments within NHS hospitals in the north-west of England. 

Participants: Adult patients requiring blood culture (BC) when developing new signs of systemic inflammation. 

Main outcome measures: SeptiFast real-time PCR results at species/genus level compared with microbiological culture in association with independent adjudication of infection. Metrics of diagnostic accuracy were derived including sensitivity, specificity, likelihood ratios and predictive values, with their 95% confidence intervals (CIs). Latent class analysis was used to explore the diagnostic performance of culture as a reference standard. 

Results: Of 1006 new patient episodes of systemic inflammation in 853 patients, 922 (92%) met the inclusion criteria and provided sufficient information for analysis. Index test assay failure occurred on 69 (7%) occasions. Adult patients had been exposed to a median of 8 days (interquartile range 4–16 days) of hospital care, had high levels of organ support activities and recent antibiotic exposure. SeptiFast real-time PCR, when compared with culture-proven bloodstream infection at species/genus level, had better specificity (85.8%, 95% CI 83.3% to 88.1%) than sensitivity (50%, 95% CI 39.1% to 60.8%). When compared with pooled diagnostic metrics derived from our systematic review, our clinical study revealed lower test accuracy of SeptiFast real-time PCR, mainly as a result of low diagnostic sensitivity. There was a low prevalence of BC-proven pathogens in these patients (9.2%, 95% CI 7.4% to 11.2%) such that the post-test probabilities of both a positive (26.3%, 95% CI 19.8% to 33.7%) and a negative SeptiFast test (5.6%, 95% CI 4.1% to 7.4%) indicate the potential limitations of this technology in the diagnosis of bloodstream infection. However, latent class analysis indicates that BC has a low sensitivity, questioning its relevance as a reference test in this setting. Using this analysis approach, the sensitivity of the SeptiFast test was low but also appeared significantly better than BC. Blood samples identified as positive by either culture or SeptiFast real-time PCR were associated with a high probability (> 95%) of infection, indicating higher diagnostic rule-in utility than was apparent using conventional analyses of diagnostic accuracy. 

Conclusion: SeptiFast real-time PCR on blood samples may have rapid rule-in utility for the diagnosis of health-care-associated bloodstream infection but the lack of sensitivity is a significant limiting factor. Innovations aimed at improved diagnostic sensitivity of real-time PCR in this setting are urgently required. Future work recommendations include technology developments to improve the efficiency of pathogen DNA extraction and the capacity to detect a much broader range of pathogens and drug resistance genes and the application of new statistical approaches able to more reliably assess test performance in situation where the reference standard (e.g. blood culture in the setting of high antimicrobial use) is prone to error.

Environmental forensic investigations: The potential use of a novel heavy metal sensor and novel taggants

This chapter presents a novel hand-held instrument capable of real-time in situ detection and identification of heavy metals, along with the potential use of novel taggants in environmental forensic investigations. The proposed system provides the facilities found in a traditional laboratory-based instrument but in a hand held design, without the need for an associated computer. The electrochemical instrument uses anodic stripping voltammetry, which is a precise and sensitive analytical method with excellent limits of detection. The sensors comprise a small disposable plastic strip of screen-printed electrodes rather than the more common glassy carbon disc and gold electrodes. The system is designed for use by a surveyor on site, allowing them to locate hotspots, thus avoiding the expense and time delay of prior laboratory analysis. This is particularly important in environmental forensic analysis when a site may have been released back to the owner and samples could be compromised on return visits. The system can be used in a variety of situations in environmental assessments, the data acquired from which provide a metals fingerprint suitable for input to a database. The proposed novel taggant tracers, based on narrow-band atomic fluorescence, are under development for potential deployment as forensic environmental tracers. The use of discrete fluorescent species in an environmentally stable host has been investigated to replace existing toxic, broadband molecular dye tracers. The narrow band emission signals offer the potential for tracing a large number of signals in the same environment. This will give increased data accuracy and allow multiple source environmental monitoring of environmental parameters.

Utilisation of a novel ProteaseTag™ activity immunoassay for the specific measurement of neutrophil elastase in patients with Cystic Fibrosis

Neutrophil elastase (NE), a biomarker of infection and inflammation, correlates with the severity of several respiratory diseases including cystic fibrosis (CF) however, its detection and quantification in biological samples is confounded by a lack of robust methodologies. Standard assays using chromogenic or fluorogenic substrates are not specific when added to complex samples containing multiple proteolytic and hydrolytic enzymes, resulting in an over-estimation of the target protease. ELISA systems measure total protein levels which can be a mixture of latent, active and protease-inhibitor complexes. We have therefore developed a novel immunoassay (NE-Tag ELISA), incorporating an activity dependent ProteaseTag™ and a specific antibody step, which is selective and specific for the capture of active NE. The objective of this study was to clinically validate NE-Tag ELISA for the detection of active NE in sputum from CF patients. Sputum (n=45) was recovered from CF patients hospitalised for acute exacerbation. Sol was recovered and analysed for NE activity using the NE-Tag ELISA and two fluorogenic substrate-based assays [1. Suc-AAPV-AMC (Sigma) and 2. InnozymeTM Immunocapture assay (Calbiochem)]. NE activity between assays and with a range of clinical parameters was correlated.A highly significant correlation was shown between assays. NE activity (NE-Tag) further correlated appropriately with clinical parameters: inversely with FEV1 (p = 0.036) and positively with CRP (p = 0.035), neutrophils and total white cell counts (p < 0.001). The InnozymeTM assay showed similar correlations with the clinical parameters (with the exception of CRP). No correlations with any of the clinical parameters were observed when NE was measured using the standard fluorogenic substrate.

Multiloop robust H∞ control design based on the dynamic PLS approach to chemical processes

In this paper, a multiloop robust control strategy is proposed based on H∞ control and a partial least squares (PLS) model (H∞_PLS) for multivariable chemical processes. It is developed especially for multivariable systems in ill-conditioned plants and non-square systems. The advantage of PLS is to extract the strongest relationship between the input and the output variables in the reduced space of the latent variable model rather than in the original space of the highly dimensional variables. Without conventional decouplers, the dynamic PLS framework automatically decomposes the MIMO process into multiple single-loop systems in the PLS subspace so that the controller design can be simplified. Since plant/model mismatch is almost inevitable in practical applications, to enhance the robustness of this control system, the controllers based on the H∞ mixed sensitivity problem are designed in the PLS latent subspace. The feasibility and the effectiveness of the proposed approach are illustrated by the simulation results of a distillation column and a mixing tank process. Comparisons between H∞_PLS control and conventional individual control (either H∞ control or PLS control only) are also made