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We propose to use the Generalized Morse Wavelets (GMWs) instead of commonly-used Morlet (or Gabor) wavelets in the Scattering Transform Network (STN), which we call the GMW-STN, for signal classification problems. The GMWs form a parameterized family of truly analytic wavelets while the Morlet wavelets are only approximately analytic. The analyticity of underlying wavelet filters in the STN is particularly important for nonstationary oscillatory signals such as music signals because it improves interpretability of the STN representations by providing multi-scale amplitude and phase (and consequently frequency) information of input signals. We demonstrate the superiority of the GMW-STN over the conventional STN in music genre classification using the so-called GTZAN database. Moreover, we show the performance improvement of the GMW-STN by increasing its number of layers to three over the typical two-layer STN. 

Background Health care personnel (HCP) are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment (PPE) may mitigate this risk, prospective data collection on its use and other risk factors for seroconversion in this population is needed. Objective The primary objectives of this study are to (1) determine the incidence of, and risk factors for, SARS-CoV-2 infection among HCP at a tertiary care medical center and (2) actively monitor PPE use, interactions between study participants via electronic sensors, secondary cases in households, and participant mental health and well-being. Methods To achieve these objectives, we designed a prospective, observational study of SARS-CoV-2 infection among HCP and their household contacts at an academic tertiary care medical center in North Carolina, USA. Enrolled HCP completed frequent surveys on symptoms and work activities and provided serum and nasal samples for SARS-CoV-2 testing every 2 weeks. Additionally, interactions between participants and their movement within the clinical environment were captured with a smartphone app and Bluetooth sensors. Finally, a subset of participants’ households was randomly selected every 2 weeks for further investigation, and enrolled households provided serum and nasal samples via at-home collection kits. Results As of December 31, 2020, 211 HCP and 53 household participants have been enrolled. Recruitment and follow-up are ongoing and expected to continue through September 2021. Conclusions Much remains to be learned regarding the risk of SARS-CoV-2 infection among HCP and their household contacts. Through the use of a multifaceted prospective study design and a well-characterized cohort, we will collect critical information regarding SARS-CoV-2 transmission risks in the health care setting and its linkage to the community. International Registered Report Identifier (IRRID) DERR1-10.2196/25410 

Coronary artery disease (CAD), or atherosclerosis, is responsible for nearly a third of all American deaths annually. Detection of plaques and differentiation of plaque stage remains a complicating factor for treatment. Classification of plaque before significant blockage or rupture could inform clinical decisions and prevent mortality. Current detection methods are either nonspecific, slow, or require the use of potentially harmful contrast agents. Recent advances in hyperspectral imaging could be used to detect changes in the autofluorescence of arteries associated with vessel remodeling and subsequent plaque formation and could detect and classify existing lesions. Here, we present data comparing spectral image characteristics of a mouse model designed to undergo vessel remodeling. C57Bl/6 mice underwent ligation of three of four caudal branches of the left common carotid artery (left external carotid, internal carotid, and occipital artery) with the superior thyroid artery left intact under IACUC approved protocol. Vessels were harvested at a variety of timepoints to compare degrees of remodeling, including 4 weeks and 5 months post-surgery. Immediately following harvest, vessels were prepared by longitudinal opening to expose the luminal surface to a 20X objective. A custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter arrary (Versachrome, Semrock, Inc.) were used to achieve spectral imaging. Excitation scans utilized wavelengths between 340 nm and 550 nm in 5 nm increments. Hyperspectral data were generated and analyzed with custom Matlab scripts and visualized in ENVI. Preliminary data suggest consistent spectral features associated with control and remodeled vessels. © (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. 

Targeting Clostridium difficile infection is challenging because treatment options are limited, and high recurrence rates are common. One reason for this is that hypervirulent C. difficile strains often have a binary toxin termed the C. difficile toxin, in addition to the enterotoxins TsdA and TsdB. The C. difficile toxin has an enzymatic component, termed CDTa, and a pore-forming or delivery subunit termed CDTb. CDTb was characterized here using a combination of single-particle cryoelectron microscopy, X-ray crystallography, NMR, and other biophysical methods. In the absence of CDTa, 2 di-heptamer structures for activated CDTb (1.0 MDa) were solved at atomic resolution, including a symmetric ( Sym CDTb; 3.14 Å) and an asymmetric form ( Asym CDTb; 2.84 Å). Roles played by 2 receptor-binding domains of activated CDTb were of particular interest since the receptor-binding domain 1 lacks sequence homology to any other known toxin, and the receptor-binding domain 2 is completely absent in other well-studied heptameric toxins (i.e., anthrax). For Asym CDTb, a Ca 2+ binding site was discovered in the first receptor-binding domain that is important for its stability, and the second receptor-binding domain was found to be critical for host cell toxicity and the di-heptamer fold for both forms of activated CDTb. Together, these studies represent a starting point for developing structure-based drug-design strategies to target the most severe strains of C. difficile . 

Spectral imaging approaches provide new possibilities for measuring and discriminating fluorescent molecules in living cells and tissues. These approaches often employ tunable filters and robust image processing algorithms to identify many fluorescent labels in a single image set. Here, we present results from a novel spectral imaging technology that scans the fluorescence excitation spectrum, demonstrating that excitation‐scanning hyperspectral image data can discriminate among tissue types and estimate the molecular composition of tissues. This approach allows fast, accurate quantification of many fluorescent species from multivariate image data without the need of exogenous labels or dyes. We evaluated the ability of the excitation‐scanning approach to identify endogenous fluorescence signatures in multiple unlabeled tissue types. Signatures were screened using multi‐pass principal component analysis. Endmember extraction techniques revealed conserved autofluorescent signatures across multiple tissue types. We further examined the ability to detect known molecular signatures by constructing spectral libraries of common endogenous fluorophores and applying multiple spectral analysis techniques on test images from lung, liver and kidney. Spectral deconvolution revealed structure‐specific morphologic contrast generated from pure molecule signatures. These results demonstrate that excitation‐scanning spectral imaging, coupled with spectral imaging processing techniques, provides an approach for discriminating among tissue types and assessing the molecular composition of tissues. Additionally, excitation scanning offers the ability to rapidly screen molecular markers across a range of tissues without using fluorescent labels. This approach lays the groundwork for translation of excitation‐scanning technologies to clinical imaging platforms.

 

Predator–prey interactions shape ecosystems and can help maintain biodiversity. However, for many of the earth's most biodiverse and abundant organisms, including terrestrial arthropods, these interactions are difficult or impossible to observe directly with traditional approaches. Based on previous theory, it is likely that predator–prey interactions for these organisms are shaped by a combination of predator traits, including body size and species‐specific hunting strategies. In this study, we combined diet DNA metabarcoding data of 173 individual invertebrate predators from nine species (a total of 305 individual predator–prey interactions) with an extensive community body size data set of a well‐described invertebrate community to explore how predator traits and identity shape interactions. We found that (1) mean size of prey families in the field usually scaled with predator size, with species‐specific variation to a general size‐scaling relationship (exceptions likely indicating scavenging or feeding on smaller life stages). We also found that (2) although predator hunting traits, including web and venom use, are thought to shape predator–prey interaction outcomes, predator identity more strongly influenced our indirect measure of the relative size of predators and prey (predator:prey size ratios) than either of these hunting traits. Our findings indicate that predator body size and species identity are important in shaping trophic interactions in invertebrate food webs and could help predict how anthropogenic biodiversity change will influence terrestrial invertebrates, the earth's most diverse animal taxonomic group.