bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiology and biology of a herpesvirus in rabies endemic vampire bat populations
Authors: Griffiths Megan E. , Bergner Laura M. , Broos Alice , Meza Diana K. , Filipe Ana da Silva , Davison Andrew , Tello Carlos , Becker Daniel J. , Streicker Daniel G. 
Published: November 2020

AbstractRabies is a viral zoonosis transmitted by vampire bats across Latin America. Substantial public health and agricultural burdens remain, despite decades of bats culls and livestock vaccinations. Virally vectored vaccines that spread autonomously through bat populations are a theoretically appealing solution to managing rabies in its reservoir host. We investigate the biological and epidemiological suitability of a vampire bat betaherpesvirus (DrBHV) to act as a vaccine vector. In 25 sites across Peru with serological and/or molecular evidence of rabies circulation, DrBHV infects 80–100% of bats, suggesting potential for high population-level vaccine coverage. Phylogenetic analysis reveals host specificity within neotropical bats, limiting risks to non-target species. Finally, deep sequencing illustrates DrBHV super-infections in individual bats, implying that DrBHV-vectored vaccines might invade despite the highly prevalent wild-type virus. These results indicate DrBHV as a promising candidate vector for a transmissible rabies vaccine, and provide a framework to discover and evaluate candidate viral vectors for vaccines against bat-borne zoonoses.
Aerosol jet printed capacitive strain gauge for soft structural materials
Authors: Fujimoto Kiyo T. , Watkins Jennifer K. , Phero Timothy , Litteken Doug , Tsai Kevin , Bingham Takoda , Ranganatha Kshama Lakshmi , Johnson Benjamin C. , Deng Zhangxian , Jaques Brian , Estrada David 
Published: November 2020

AbstractSoft structural textiles, or softgoods, are used within the space industry for inflatable habitats, parachutes and decelerator systems. Evaluating the safety and structural integrity of these systems occurs through structural health monitoring systems (SHM), which integrate non-invasive/non-destructive testing methods to detect, diagnose, and locate damage. Strain/load monitoring of these systems is limited while utilizing traditional strain gauges as these gauges are typically stiff, operate at low temperatures, and fail when subjected to high strain that is a result of high loading classifying them as unsuitable for SHM of soft structural textiles. For this work, a capacitance based strain gauge (CSG) was fabricated via aerosol jet printing (AJP) using silver nanoparticle ink on a flexible polymer substrate. Printed strain gauges were then compared to a commercially available high elongation resistance-based strain gauge (HE-RSG) for their ability to monitor strained Kevlar straps having a 26.7 kN (6 klbf) load. Dynamic, static and cyclic loads were used to characterize both types of strain monitoring devices. Printed CSGs demonstrated superior performance for high elongation strain measurements when compared to commonly used HE-RSGs, and were observed to operate with a gauge factor of 5.2 when the electrode arrangement was perpendicular to the direction of strain.
Assessing the relationship between routine and schizophrenia symptoms with passively sensed measures of behavioral stability
Authors: He-Yueya Joy , Buck Benjamin , Campbell Andrew , Choudhury Tanzeem , Kane John M. , Ben-Zeev Dror , Althoff Tim 
Published: November 2020

AbstractIncreased stability in one’s daily routine is associated with well-being in the general population and often a goal of behavioral interventions for people with serious mental illnesses like schizophrenia. Assessing behavioral stability has been limited in clinical research by the use of retrospective scales, which are susceptible to reporting biases and memory inaccuracies. Mobile passive sensors, which are less susceptible to these sources of error, have emerged as tools to assess behavioral patterns in a range of populations. The present study developed and examined a metric of behavioral stability from data generated by a passive sensing system carried by 61 individuals with schizophrenia for one year. This metric—the Stability Index—appeared orthogonal from existing measures drawn from passive sensors and matched the predictive performance of state-of-the-art features. Specifically, greater stability in social activity (e.g., calls and messages) were associated with lower symptoms, and greater stability in physical activity (e.g., being still) appeared associated with elevated symptoms. This study provides additional support for the predictive value of individualized over population-level data in psychiatric populations. The Stability Index offers also a promising tool for generating insights about the impact of behavioral stability in schizophrenia-spectrum disorders.
North American historical monthly spatial climate dataset, 1901–2016
Authors: MacDonald Heather , McKenney Daniel W. , Papadopol Pia , Lawrence Kevin , Pedlar John , Hutchinson Michael F. 
Published: November 2020

AbstractWe present historical monthly spatial models of temperature and precipitation generated from the North American dataset version “j” from the National Oceanic and Atmospheric Administration’s (NOAA’s) National Centres for Environmental Information (NCEI). Monthly values of minimum/maximum temperature and precipitation for 1901–2016 were modelled for continental United States and Canada. Compared to similar spatial models published in 2006 by Natural Resources Canada (NRCAN), the current models show less error. The Root Generalized Cross Validation (RTGCV), a measure of the predictive error of the surfaces akin to a spatially averaged standard predictive error estimate, averaged 0.94 °C for maximum temperature models, 1.3 °C for minimum temperature and 25.2% for total precipitation. Mean prediction errors for the temperature variables were less than 0.01 °C, using all stations. In comparison, precipitation models showed a dry bias (compared to recorded values) of 0.5 mm or 0.7% of the surface mean. Mean absolute predictive errors for all stations were 0.7 °C for maximum temperature, 1.02 °C for minimum temperature, and 13.3 mm (19.3% of the surface mean) for monthly precipitation.
Structure and electrical properties of BCZT ceramics derived from microwave-assisted sol–gel-hydrothermal synthesized powders
Authors: Ji Xiang , Wang Chuanbin , Harumoto Takashi , Zhang Song , Tu Rong , Shen Qiang , Shi Ji 
Published: November 2020

AbstractA novel microwave-assisted sol–gel-hydrothermal method was employed to rapidly synthesize Ba0.85Ca0.15Zr0.1Ti0.9O3 (BCZT) powders. The effects of reaction time on the structure, crystallinity, purity and morphology of the products were investigated. The results of XRD, FTIR, SEM and TEM indicated that BCZT powders could be obtained in even 60 min at a low synthesis temperature of 180 °C, which were well-crystallized with stoichiometric composition and uniform grain size (~ 85 nm). BCZT ceramic derived from the rapidly-synthesized powders had a dense microstructure and good electrical properties (εm = 9579, d33 = 496 pC/N, 2Pr = 25.22 µC/cm2, 2Ec = 7.52 kV/cm). The significant electrical properties were closely related to the high activity of the BCZT powders, resulting from the rapid microwave-assisted sol–gel-hydrothermal process.
Comprehensive assessment of TP53 loss of function using multiple combinatorial mutagenesis libraries
Authors: Carbonnier Vincent , Leroy Bernard , Rosenberg Shai , Soussi Thierry 
Published: November 2020

AbstractThe diagnosis of somatic and germline TP53 mutations in human tumors or in individuals prone to various types of cancer has now reached the clinic. To increase the accuracy of the prediction of TP53 variant pathogenicity, we gathered functional data from three independent large-scale saturation mutagenesis screening studies with experimental data for more than 10,000 TP53 variants performed in different settings (yeast or mammalian) and with different readouts (transcription, growth arrest or apoptosis). Correlation analysis and multidimensional scaling showed excellent agreement between all these variables. Furthermore, we found that some missense mutations localized in TP53 exons led to impaired TP53 splicing as shown by an analysis of the TP53 expression data from the cancer genome atlas. With the increasing availability of genomic, transcriptomic and proteomic data, it is essential to employ both protein and RNA prediction to accurately define variant pathogenicity.
Bioengineering of non-pathogenic Escherichia coli to enrich for accumulation of environmental copper
Authors: Gahlot Dharmender K. , Taheri Nayyer , Mahato Dhani Ram , Francis Matthew S. 
Published: November 2020

AbstractHeavy metal sequestration from industrial wastes and agricultural soils is a long-standing challenge. This is more critical for copper since copper pollution is hazardous both for the environment and for human health. In this study, we applied an integrated approach of Darwin’s theory of natural selection with bacterial genetic engineering to generate a biological system with an application for the accumulation of Cu2+ ions. A library of recombinant non-pathogenic Escherichia coli strains was engineered to express seven potential Cu2+ binding peptides encoded by a ‘synthetic degenerate’ DNA motif and fused to Maltose Binding Protein (MBP). Most of these peptide-MBP chimeras conferred tolerance to high concentrations of copper sulphate, and in certain cases in the order of 160-fold higher than the recognised EC50 toxic levels of copper in soils. UV–Vis spectroscopic analysis indicated a molar ratio of peptide-copper complexes, while a combination of bioinformatics-based structure modelling, Cu2+ ion docking, and MD simulations of peptide-MBP chimeras corroborated the extent of Cu2+ binding among the peptides. Further, in silico analysis predicted the peptides possessed binding affinity toward a broad range of divalent metal ions. Thus, we report on an efficient, cost-effective, and environment-friendly prototype biological system that is potentially capable of copper bioaccumulation, and which could easily be adapted for the removal of other hazardous heavy metals or the bio-mining of rare metals.
ClassifyCNV: a tool for clinical annotation of copy-number variants
Authors: Gurbich Tatiana A. , Ilinsky Valery Vladimirovich 
Published: November 2020

AbstractCopy-number variants (CNVs) are an important part of human genetic variation. They can be benign or can play a role in human disease by creating dosage imbalances and disrupting genes and regulatory elements. Accurate identification and clinical annotation of CNVs is essential, however, manual evaluation of individual CNVs by clinicians is challenging on a large scale. Here, we present ClassifyCNV, an easy-to-use tool that implements the 2019 ACMG classification guidelines to assess CNV pathogenicity. ClassifyCNV uses genomic coordinates and CNV type as input and reports a clinical classification for each variant, a classification score breakdown, and a list of genes of potential importance for variant interpretation. We validate ClassifyCNV’s performance using a set of known clinical CNVs and a set of manually evaluated variants. ClassifyCNV matches the pathogenicity category for 81% of manually evaluated variants with the significance of the remaining pathogenic and benign variants automatically determined as uncertain, requiring a further evaluation by a clinician. ClassifyCNV facilitates the implementation of the latest ACMG guidelines in high-throughput CNV analysis, is suitable for integration into NGS analysis pipelines, and can decrease time to diagnosis. The tool is available at https://github.com/Genotek/ClassifyCNV.
Central nervous system pathology in preclinical MPS IIIB dogs reveals progressive changes in clinically relevant brain regions
Authors: Egeland Martin T. , Tarczyluk-Wells Marta M. , Asmar Melissa M. , Adintori Evan G. , Lawrence Roger , Snella Elizabeth M. , Jens Jackie K. , Crawford Brett E. , Wait Jill C. M. , McCullagh Emma , Pinkstaff Jason , Cooper Jonathan D. , Ellinwood N. Matthew 
Published: November 2020

AbstractMucopolysaccharidosis type IIIB (MPS IIIB; Sanfilippo syndrome B) is an autosomal recessive lysosomal storage disorder caused by the deficiency of alpha-N-acetylglucosaminidase activity, leading to increased levels of nondegraded heparan sulfate (HS). A mouse model has been useful to evaluate novel treatments for MPS IIIB, but has limitations. In this study, we evaluated the naturally occurring canine model of MPS IIIB for the onset and progression of biochemical and neuropathological changes during the preclinical stages (onset approximately 24–30 months of age) of canine MPS IIIB disease. Even by 1 month of age, MPS IIIB dogs had elevated HS levels in brain and cerebrospinal fluid. Analysis of histopathology of several disease-relevant regions of the forebrain demonstrated progressive lysosomal storage and microglial activation despite a lack of cerebrocortical atrophy in the oldest animals studied. More pronounced histopathology changes were detected in the cerebellum, where progressive lysosomal storage, astrocytosis and microglial activation were observed. Microglial activation was particularly prominent in cerebellar white matter and within the deep cerebellar nuclei, where neuron loss also occurred. The findings in this study will form the basis of future assessments of therapeutic efficacy in this large animal disease model.
Small molecule modulation of the p75 neurotrophin receptor inhibits multiple amyloid beta-induced tau pathologies
Authors: Yang Tao , Tran Kevin C. , Zeng Anne Y. , Massa Stephen M. , Longo Frank M. 
Published: November 2020

AbstractLongitudinal preclinical and clinical studies suggest that Aβ drives neurite and synapse degeneration through an array of tau-dependent and independent mechanisms. The intracellular signaling networks regulated by the p75 neurotrophin receptor (p75NTR) substantially overlap with those linked to Aβ and to tau. Here we examine the hypothesis that modulation of p75NTR will suppress the generation of multiple potentially pathogenic tau species and related signaling to protect dendritic spines and processes from Aβ-induced injury. In neurons exposed to oligomeric Aβ in vitro and APP mutant mouse models, modulation of p75NTR signaling using the small-molecule LM11A-31 was found to inhibit Aβ-associated degeneration of neurites and spines; and tau phosphorylation, cleavage, oligomerization and missorting. In line with these effects on tau, LM11A-31 inhibited excess activation of Fyn kinase and its targets, tau and NMDA-NR2B, and decreased Rho kinase signaling changes and downstream aberrant cofilin phosphorylation. In vitro studies with pseudohyperphosphorylated tau and constitutively active RhoA revealed that LM11A-31 likely acts principally upstream of tau phosphorylation, and has effects preventing spine loss both up and downstream of RhoA activation. These findings support the hypothesis that modulation of p75NTR signaling inhibits a broad spectrum of Aβ-triggered, tau-related molecular pathology thereby contributing to synaptic resilience.
A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction
Authors: Spooner Annette , Chen Emily , Sowmya Arcot , Sachdev Perminder , Kochan Nicole A. , Trollor Julian , Brodaty Henry 
Published: November 2020

AbstractData collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need for methods that can overcome these challenges to model this complex data. At present there is no cure for dementia and no treatment that can successfully change the course of the disease. Machine learning models that can predict the time until a patient develops dementia are important tools in helping understand dementia risks and can give more accurate results than traditional statistical methods when modelling high-dimensional, heterogeneous, clinical data. This work compares the performance and stability of ten machine learning algorithms, combined with eight feature selection methods, capable of performing survival analysis of high-dimensional, heterogeneous, clinical data. We developed models that predict survival to dementia using baseline data from two different studies. The Sydney Memory and Ageing Study (MAS) is a longitudinal cohort study of 1037 participants, aged 70–90 years, that aims to determine the effects of ageing on cognition. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal study aimed at identifying biomarkers for the early detection and tracking of Alzheimer's disease. Using the concordance index as a measure of performance, our models achieve maximum performance values of 0.82 for MAS and 0.93 For ADNI.
Quantitative proteomics reveal lineage-specific protein profiles in iPSC-derived Marfan syndrome smooth muscle cells
Authors: Iosef Cristiana , Pedroza Albert J. , Cui Jason Z. , Dalal Alex R. , Arakawa Mamoru , Tashima Yasushi , Koyano Tiffany K. , Burdon Grayson , Churovich Samantha M. P. , Orrick Joshua O. , Pariani Mitchel , Fischbein Michael P. 
Published: November 2020

AbstractMarfan syndrome (MFS) is a connective tissue disorder caused by mutations in the FBN1 gene that produces wide disease phenotypic variability. The lack of ample genotype–phenotype correlation hinders translational study development aimed at improving disease prognosis. In response to this need, an induced pluripotent stem cell (iPSC) disease model has been used to test patient-specific cells by a proteomic approach. This model has the potential to risk stratify patients to make clinical decisions, including timing for surgical treatment. The regional propensity for aneurysm formation in MFS may be related to distinct smooth muscle cell (SMC) embryologic lineages. Thus, peripheral blood mononuclear cell (PBMC)-derived induced pluripotent stem cells (iPSC) were differentiated into lateral mesoderm (LM, aortic root) and neural crest (NC, ascending aorta/transverse arch) SMC lineages to model MFS aortic pathology. Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) proteomic analysis by tandem mass spectrometry was applied to profile LM and NC iPSC SMCs from four MFS patients and two healthy controls. Analysis revealed 45 proteins with lineage-dependent expression in MFS patients, many of which were specific to diseased samples. Single protein-level data from both iPSC SMCs and primary MFS aortic root aneurysm tissue confirmed elevated integrin αV and reduced MRC2 in clinical disease specimens, validating the iPSC iTRAQ findings. Functionally, iPSC SMCs exhibited defective adhesion to a variety of extracellular matrix proteins, especially laminin-1 and fibronectin, suggesting altered cytoskeleton dynamics. This study defines the aortic embryologic origin-specific proteome in a validated iPSC SMC model to identify novel protein markers associated with MFS aneurysm phenotype. Translating iPSC findings into clinical aortic aneurysm tissue samples highlights the potential for iPSC-based methods to model MFS disease for mechanistic studies and therapeutic discovery in vitro.
Forecasting the spread of COVID-19 under different reopening strategies
Authors: Liu Meng , Thomadsen Raphael , Yao Song 
Published: November 2020

AbstractWe combine COVID-19 case data with mobility data to estimate a modified susceptible-infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we find that the incidence of COVID-19 spread is concave in the number of infectious individuals, as would be expected if people have inter-related social networks. This concave shape has a significant impact on forecasted COVID-19 cases. In particular, our model forecasts that the number of COVID-19 cases would only have an exponential growth for a brief period at the beginning of the contagion event or right after a reopening, but would quickly settle into a prolonged period of time with stable, slightly declining levels of disease spread. This pattern is consistent with observed levels of COVID-19 cases in the US, but inconsistent with standard SIR modeling. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19.
Long-term efficacy of BCG vaccination in goat herds with a high prevalence of tuberculosis
Authors: Arrieta-Villegas Claudia , Allepuz Alberto , Grasa Miriam , Martín Maite , Cervera Zoraida , Mercader Irene , López-Soria Sergio , Domingo Mariano , Pérez de Val Bernat 
Published: November 2020

AbstractVaccination of goats against tuberculosis (TB) has been promoted as an ancillary tool for controlling the disease in infected livestock herds. A three-year trial to assess the efficacy of BCG vaccine was carried out in five goat herds. At the beginning of the trial (month 0), all animals were tested for TB using thee different diagnostic tests. Animals negative to all tests were vaccinated with BCG and all replacement goat kids were also systematically vaccinated throughout the trial. All animals were tested by Interferon-gamma release assay (IGRA) using vaccine compatible reagents at months 6, 12, 24, and 36. The risk factors for TB infection were also evaluated. At the end of the study, four out of five farms showed variable reductions of the initial prevalence (93.5%, 28.5%, 23.2%, and 14.3% respectively), and an overall incidence reduction of 50% was observed in BCG vaccinated goats, although adult vaccinated goats showed higher incidences than vaccinated goat kids. The unvaccinated positive animals remaining in herds and adult BCG vaccinated goats significantly enhanced the risk of infection in vaccinated animals. A systematic vaccination of goats with BCG, together with the removal of positive unvaccinated animals, may contribute to reducing the TB prevalence in goat herds.
Rotating edge-field driven processing of chiral spin textures in racetrack devices
Authors: Schäffer Alexander F. , Siegl Pia , Stier Martin , Posske Thore , Berakdar Jamal , Thorwart Michael , Wiesendanger Roland , Vedmedenko Elena Y. 
Published: November 2020

AbstractTopologically distinct magnetic structures like skyrmions, domain walls, and the uniformly magnetized state have multiple applications in logic devices, sensors, and as bits of information. One of the most promising concepts for applying these bits is the racetrack architecture controlled by electric currents or magnetic driving fields. In state-of-the-art racetracks, these fields or currents are applied to the whole circuit. Here, we employ micromagnetic and atomistic simulations to establish a concept for racetrack memories free of global driving forces. Surprisingly, we realize that mixed sequences of topologically distinct objects can be created and propagated over far distances exclusively by local rotation of magnetization at the sample boundaries. We reveal the dependence between chirality of the rotation and the direction of propagation and define the phase space where the proposed procedure can be realized. The advantages of this approach are the exclusion of high current and field densities as well as its compatibility with an energy-efficient three-dimensional design.