A multiscale correlation of wavelet coefficients approach to spike detection

Extracellular chronic recordings have been used as important evidence in neuroscientific studies to unveil the fundamental neural network mechanisms in the brain. Spike detection is the first step in the analysis of recorded neural waveforms to decipher useful information and provide useful signals for brain-machine interface applications. The process of spike detection is to extract action potentials from the recordings, which are often compounded with noise from different sources. This study proposes a new detection algorithm that leverages a technique from wavelet-based image edge detection. It utilizes the correlation between wavelet coefficients at different sampling scales to create a robust spike detector. The algorithm has one tuning parameter, which potentially reduces the subjectivity of detection results. Both artificial benchmark data sets and real neural recordings are used to evaluate the detection performance of the proposed algorithm. Compared with other detection algorithms, the proposed method has a comparable or better detection performance. In this letter, we also demonstrate its potential for real-time implementation.     

Microwave-assisted proteomics

State-of-the-art proteomic analysis has recently undergone a rapid evolution; with more high-throughput analytical instrumentation and informatic tools available, sample preparation is becoming one of the rate-limiting steps in protein characterization workflows. Recently several protocols have appeared in the literature that employ microwave irradiation as a tool for the preparation of biological samples for subsequent mass spectrometric characterization. Techniques for microwave-assisted bio-catalyzed reactions (including sample reduction and alkylation, enzymatic and chemical digestion, removal and analysis of post-translational modifications and characterization of enzymes and protein-interaction sites) are described. This review summarizes the various approaches undertaken, instrumentation employed, and reduction in overall experimental time observed when microwave assistance is applied.     

Quantitative Isotopomer Rates in Real-Time Metabolism of Cells Determined by NMR Methods

Tracer-based metabolism is becoming increasingly important for studying metabolic mechanisms in cells. NMR spectroscopy offers several approaches to measure label incorporation in metabolites, including ¹³C- and ¹H-detected spectra. The latter are generally more sensitive, but quantification depends on the proton–carbon ¹J_CH coupling constant, which varies significantly between different metabolites. It is therefore not possible to have one experiment optimised for all metabolites, and quantification of ¹H-edited spectra such as HSQCs requires precise knowledge of coupling constants. Increasing interest in tracer-based and metabolic flux analysis requires robust analyses with reasonably small acquisition times. Herein, we compare ¹³C-filtered and ¹³C-edited methods for quantification and show the applicability of the methods for real-time NMR spectroscopy of cancer-cell metabolism, in which label incorporations are subject to constant flux. We find an approach using a double filter to be most suitable and sufficiently robust to reliably obtain ¹³C incorporations from difference spectra. This is demonstrated for JJN3 multiple myeloma cells processing glucose over 24 h. The proposed method is equally well suited for calculating the level of label incorporation in labelled cell extracts in the context of metabolic flux analysis.     

Effect of commercial breakfast fibre cereals compared with corn flakes on postprandial blood glucose,gastric emptying and satiety in healthy subjects: a randomized blinded crossover trial

Background  

Dietary fibre food intake is related to a reduced risk of developing diabetes mellitus. However, the mechanism of this effect is still not clear. The aim of this study was to evaluate the effect of commercial fibre cereals on the rate of gastric emptying, postprandial glucose response and satiety in healthy subjects.     

Assessing innovation in emerging energy technologies: Socio-technical dynamics of carbon capture and storage (CCS) and enhanced geothermal systems (EGS) in the USA

This study applies a socio-technical systems perspective to explore innovation dynamics of two emerging energy technologies with potential to reduce greenhouse gas emissions from electrical power generation in the United States: carbon capture and storage (CCS) and enhanced geothermal systems (EGS). The goal of the study is to inform sustainability science theory and energy policy deliberations by examining how social and political dynamics are shaping the struggle for resources by these two emerging, not-yet-widely commercializable socio-technical systems. This characterization of socio-technical dynamics of CCS and EGS innovation includes examining the perceived technical, environmental, and financial risks and benefits of each system, as well as the discourses and actor networks through which the competition for resources – particularly public resources – is being waged. CCS and EGS were selected for the study because they vary considerably with respect to their social, technical, and environmental implications and risks, are unproven at scale and uncertain with respect to cost, feasibility, and life-cycle environmental impacts. By assessing the two technologies in parallel, the study highlights important social and political dimensions of energy technology innovation in order to inform theory and suggest new approaches to policy analysis.     

Visualization of 3‐D computer‐aided design objects

There are many significant human factors issues associated with the design and visualization of complex, computer‐generated images. One such issue is to determine the most effective techniques for providing engineers with realistic three‐dimensional (3‐D) objects. Differences in subjects’ ability to discriminate between the shape of two 3‐D, perspective, computer‐aided design‐type (CAD‐type) objects were investigated for various levels of monocular coding techniques and the binocular cue stereopsis. Performance was assessed at all combinations of five levels of monocular cues and two levels of disparity. The task was similar to the classic mental rotation paradigm except that subjects were provided with the ability to rotate one of the objects using a two‐dimensional (2‐D) joystick. Results indicate that interposition was the only depth cue that significantly enhanced subject performance. One explanation for the lack of significance of stereopsis is that, for this particular task, depth information provided by disparity was not needed. Detailed analysis of object rotation data using an orientation index (OI) suggests that subjects employed a feature‐by‐feature comparison task strategy. With tools that can evaluate cognitive activity such as the mental rotation paradigm and orientation index, researchers can learn more about how designers visualize and understand 3‐D CAD objects.     

A Review of “College Libraries and Student Culture: What We Now Know”

This article discusses a student-guided Instagram program for first-year English composition classes at the University of Montevallo during Fall 2013. The activity engaged aspects of critical pedagogy by placing value on students’ prior experiences as creators and users of information and encouraging a classroom environment guided by student input. Since the program was meant for students in their first semester, it was also designed to be fun and social. The Instagram program helped students encounter the unfamiliar academic library environment through the familiar medium of social media, alleviating library anxiety as they produced online content representing their experience.