The NTD Nanoscope: potential applications and implementations

<p>Abstract</p> <p>Background</p> <p>Nanopore transduction detection (NTD) offers prospects for a number of highly sensitive and discriminative applications, including: (i) single nucleotide polymorphism (SNP) detection; (ii) targeted DNA re-sequencing; (iii) protein isoform assaying; and (iv) biosensing via antibody or aptamer coupled molecules. Nanopore event transduction involves single-molecule biophysics, engineered information flows, and nanopore cheminformatics. The NTD Nanoscope has seen limited use in the scientific community, however, due to lack of information about potential applications, and lack of availability for the device itself. Meta Logos Inc. is developing both pre-packaged device platforms and component-level (unassembled) kit platforms (the latter described here). In both cases a lipid bi-layer workstation is first established, then augmentations and operational protocols are provided to have a nanopore transduction detector. In this paper we provide an overview of the NTD Nanoscope applications and implementations. The NTD Nanoscope Kit, in particular, is a component-level reproduction of the standard NTD device used in previous research papers.</p> <p>Results</p> <p>The NTD Nanoscope method is shown to functionalize a single nanopore with a channel current modulator that is designed to transduce events, such as binding to a specific target. To expedite set-up in new lab settings, the calibration and troubleshooting for the NTD Nanoscope kit components and signal processing software, the NTD Nanoscope Kit, is designed to include a set of test buffers and control molecules based on experiments described in previous NTD papers (the model systems briefly described in what follows). The description of the Server-interfacing for advanced signal processing support is also briefly mentioned.</p> <p>Conclusions</p> <p>SNP assaying, SNP discovery, DNA sequencing and RNA-seq methods are typically limited by the accuracy of the error rate of the enzymes involved, such as methods involving the polymerase chain reaction (PCR) enzyme. The NTD Nanoscope offers a means to obtain higher accuracy as it is a single-molecule method that does not inherently involve use of enzymes, using a functionalized nanopore instead.</p

DNA Molecule Classification Using Feature Primitives

BACKGROUND: We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent classification performance for five different DNA hairpins that differ in only one base-pair. For multi-class DNA classification problems, practitioners usually adopt approaches that use decision trees consisting of binary classifiers. Finding the best tree topology requires exploring all possible tree topologies and is computationally prohibitive. We propose a computational framework based on feature primitives that eliminates the need of a decision tree of binary classifiers. In the first phase, we generate a pool of weak features from nanopore blockade current measurements by using HMM analysis, principal component analysis and various wavelet filters. In the next phase, feature selection is performed using AdaBoost. AdaBoost provides an ensemble of weak learners of various types learned from feature primitives. RESULTS AND CONCLUSION: We show that our technique, despite its inherent simplicity, provides a performance comparable to recent multi-class DNA molecule classification results. Unlike the approach presented by Winters-Hilt et al., where weaker data is dropped to obtain better classification, the proposed approach provides comparable classification accuracy without any need for rejection of weak data. A weakness of this approach, on the other hand, is the very "hands-on" tuning and feature selection that is required to obtain good generalization. Simply put, this method obtains a more informed set of features and provides better results for that reason. The strength of this approach appears to be in its ability to identify strong features, an area where further results are actively being sought

Support Vector Machine Implementations for Classification & Clustering

BACKGROUND: We describe Support Vector Machine (SVM) applications to classification and clustering of channel current data. SVMs are variational-calculus based methods that are constrained to have structural risk minimization (SRM), i.e., they provide noise tolerant solutions for pattern recognition. The SVM approach encapsulates a significant amount of model-fitting information in the choice of its kernel. In work thus far, novel, information-theoretic, kernels have been successfully employed for notably better performance over standard kernels. Currently there are two approaches for implementing multiclass SVMs. One is called external multi-class that arranges several binary classifiers as a decision tree such that they perform a single-class decision making function, with each leaf corresponding to a unique class. The second approach, namely internal-multiclass, involves solving a single optimization problem corresponding to the entire data set (with multiple hyperplanes). RESULTS: Each SVM approach encapsulates a significant amount of model-fitting information in its choice of kernel. In work thus far, novel, information-theoretic, kernels were successfully employed for notably better performance over standard kernels. Two SVM approaches to multiclass discrimination are described: (1) internal multiclass (with a single optimization), and (2) external multiclass (using an optimized decision tree). We describe benefits of the internal-SVM approach, along with further refinements to the internal-multiclass SVM algorithms that offer significant improvement in training time without sacrificing accuracy. In situations where the data isn't clearly separable, making for poor discrimination, signal clustering is used to provide robust and useful information – to this end, novel, SVM-based clustering methods are also described. As with the classification, there are Internal and External SVM Clustering algorithms, both of which are briefly described

From clump to disc scales in W3 IRS4 A case study of the IRAM NOEMA large programme CORE

Context. High-mass star formation typically takes place in a crowded environment, with a higher likelihood of young forming stars affecting and being affected by their surroundings and neighbours, as well as links between different physical scales affecting the outcome. However, observational studies are often focused on either clump or disc scales exclusively. Aims. We explore the physical and chemical links between clump and disc scales in the high-mass star formation region W3 IRS4, a region that contains a number of different evolutionary phases in the high-mass star formation process, as a case-study for what can be achieved as part of the IRAM NOrthern Extended Millimeter Array (NOEMA) large programme named CORE: “Fragmentation and disc formation in high-mass star formation”. Methods. We present 1.4 mm continuum and molecular line observations with the IRAM NOEMA interferometer and 30 m telescope, which together probe spatial scales from ~0.3−20′′ (600−40 000 AU or 0.003−0.2 pc at 2 kpc, the distance to W3). As part of our analysis, we used XCLASS to constrain the temperature, column density, velocity, and line-width of the molecular emission lines. Results. The W3 IRS4 region includes a cold filament and cold cores, a massive young stellar object (MYSO) embedded in a hot core, and a more evolved ultra-compact (UC)H II region, with some degree of interaction between all components of the region that affects their evolution. A large velocity gradient is seen in the filament, suggesting infall of material towards the hot core at a rate of 10−3−10−4 M⊙ yr−1, while the swept up gas ring in the photodissociation region around the UCH II region may be squeezing the hot core from the other side. There are no clear indications of a disc around the MYSO down to the resolution of the observations (600 AU). A total of 21 molecules are detected, with the abundances and abundance ratios indicating that many molecules were formed in the ice mantles of dust grains at cooler temperatures, below the freeze-out temperature of CO (≲35 K). This contrasts with the current bulk temperature of ~50 K, which was obtained from H2CO. Conclusions. CORE observations allow us to comprehensively link the different structures in the W3 IRS4 region for the first time. Our results argue that the dynamics and environment around the MYSO W3 IRS4 have a significant impact on its evolution. This context would be missing if only high resolution or continuum observations were available

Heterosexual couples and prostate cancer support groups: a gender relations analysis.

Introduction: Men diagnosed with prostate cancer (PCa) can receive supportive care from an array of sources including female partners and prostate cancer support groups (PCSGs). However, little is known about how heterosexual gender relations and supportive care play out among couples who attend PCSGs. Distilling such gender relation patterns is a key to understanding and advancing supportive care for men who experience PCa and their families

Patients' experiences of the quality of long-term care among the elderly: comparing scores over time

Contains fulltext : 108999.pdf (publisher's version ) (Open Access)BACKGROUND: Every two years, long-term care organizations for the elderly are obliged to evaluate and publish the experiences of residents, representatives of psychogeriatric patients, and/or assisted-living clients with regard to quality of care. Our hypotheses are that publication of this quality information leads to improved performance, and that organizations with substandard performance will improve more than those whose performance is relatively good. METHODS: The analyses included organizational units that measured experiences twice between 2007 (t(0)) and 2009 (t(1)). Experiences with quality of care were measured with Consumer Quality Index (CQI) questionnaires. Besides descriptive analyses (i.e. mean, 5(th) and 95(th) percentile, and 90% central range) of the 19 CQI indicators and change scores of these indicators were calculated. Differences across five performance groups (ranging from 'worst' to 'best') were tested using an ANOVA test and effect sizes were measured with omega squared (omega(2)). RESULTS: At t0 experiences of residents, representatives, and assisted-living clients were positive on all indicators. Nevertheless, most CQI indicators had improved scores (up to 0.37 change score) at t(1). Only three indicators showed a minor decline (up to -0.08 change score). Change scores varied between indicators and questionnaires, e.g. they were more profound for the face-to-face interview questionnaire for residents in nursing homes than for the other two mail questionnaires (0.15 vs. 0.05 and 0.04, respectively), possibly due to more variation between nursing homes on the first measurement, perhaps indicating more potential for improvement. A negative relationship was found between prior performance and change, particularly with respect to the experiences of residents (omega(2) = 0.16) and assisted-living clients (omega(2) = 0.15). However, the relation between prior performance and improvement could also be demonstrated with respect to the experiences reported by representatives of psychogeriatric patients and by assisted-living clients. For representatives of psychogeriatric patients, the performance groups 1 and 2 ([much] below average) improved significantly more than the other three groups (omega(2) = 0.05). CONCLUSIONS: Both hypotheses were confirmed: almost all indicator scores improved over time and long-term care organizations for the elderly with substandard performance improved more than those with a performance which was already relatively good

In Vivo Dynamics of the Musculoskeletal System Cannot Be Adequately Described Using a Stiffness-Damping-Inertia Model

Background: Visco-elastic properties of the (neuro-)musculoskeletal system play a fundamental role in the control of posture and movement. Often, these properties are described and identified using stiffness-damping-inertia (KBI) models. In such an approach, perturbations are applied to the (neuro-)musculoskeletal system and subsequently KBI-model parameters are optimized to obtain a best fit between simulated and experimentally observed responses. Problems with this approach may arise because a KBI-model neglects critical aspects of the real musculoskeletal system. Methodology/Principal Findings: The purpose of this study was to analyze the relation between the musculoskeletal properties and the stiffness and damping estimated using a KBI-model, to analyze how this relation is affected by the nature of the perturbation and to assess the sensitivity of the estimated stiffness and damping to measurement errors. Our analyses show that the estimated stiffness and damping using KBI-models do not resemble any of the dynamical parameters of the underlying system, not even when the responses are very accurately fitted by the KBI-model. Furthermore, the stiffness and damping depend non-linearly on all the dynamical parameters of the underlying system, influenced by the nature of the perturbation and the time interval over which the KBI-model is optimized. Moreover, our analyses predict a very high sensitivity of estimated parameters to measurement errors. Conclusions/Significance: The results of this study suggest that the usage of stiffness-damping-inertia models t

To Clone or Not To Clone: Method Analysis for Retrieving Consensus Sequences In Ancient DNA Samples

The challenges associated with the retrieval and authentication of ancient DNA (aDNA) evidence are principally due to post-mortem damage which makes ancient samples particularly prone to contamination from “modern” DNA sources. The necessity for authentication of results has led many aDNA researchers to adopt methods considered to be “gold standards” in the field, including cloning aDNA amplicons as opposed to directly sequencing them. However, no standardized protocol has emerged regarding the necessary number of clones to sequence, how a consensus sequence is most appropriately derived, or how results should be reported in the literature. In addition, there has been no systematic demonstration of the degree to which direct sequences are affected by damage or whether direct sequencing would provide disparate results from a consensus of clones

Checkpoints in a Yeast Differentiation Pathway Coordinate Signaling during Hyperosmotic Stress

All eukaryotes have the ability to detect and respond to environmental and hormonal signals. In many cases these signals evoke cellular changes that are incompatible and must therefore be orchestrated by the responding cell. In the yeast Saccharomyces cerevisiae, hyperosmotic stress and mating pheromones initiate signaling cascades that each terminate with a MAP kinase, Hog1 and Fus3, respectively. Despite sharing components, these pathways are initiated by distinct inputs and produce distinct cellular behaviors. To understand how these responses are coordinated, we monitored the pheromone response during hyperosmotic conditions. We show that hyperosmotic stress limits pheromone signaling in at least three ways. First, stress delays the expression of pheromone-induced genes. Second, stress promotes the phosphorylation of a protein kinase, Rck2, and thereby inhibits pheromone-induced protein translation. Third, stress promotes the phosphorylation of a shared pathway component, Ste50, and thereby dampens pheromone-induced MAPK activation. Whereas all three mechanisms are dependent on an increase in osmolarity, only the phosphorylation events require Hog1. These findings reveal how an environmental stress signal is able to postpone responsiveness to a competing differentiation signal, by acting on multiple pathway components, in a coordinated manner