bluuebunny/crossref_metadata_2025_split huggingface dataset:
Repeatability and reproducibility of in-vivo brain temperature measurements
Authors: Sharma Ayushe A. , Nenert Rodolphe , Mueller Christina , Maudsley Andrew , Younger Jarred , Szaflarski Jerzy P. 
Published: November 2020

ABSTRACTBackgroundMagnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that can be used to noninvasively map brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range.MethodsHealthy participants aged 23-46 years (N=18; 7 females) were scanned at two time points, ∼12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values.ResultsThe mean global brain temperature over all subjects was 37.2°C, with spatial variations across ROIs. There was a significant main effect for time (F(1, 1591)=37.0, p < 0.0001) and for brain region (F(46, 1591)=2.66, p<0.0001). The time*brain region interaction was not significant (F(46, 1591)=0.80, p=0.83)). Participants’ TCRE was stable for each ROI across both time points, with ROIs’ COVrep ranging from 0.81 – 3.08% (mean COVrep = 1.92%); 30 ROIs had a COVrep < 2.0%.ConclusionsBrain temperature demonstrated subtle regional variations that were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring pathological brain temperature changes when other modalities are unrevealing. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.
From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance
Authors: Peddireddy Akhil Sai , Xie Dawen , Patil Pramod , Wilson Mandy L. , Machi Dustin , Venkatramanan Srinivasan , Klahn Brian , Porebski Przemyslaw , Bhattacharya Parantapa , Dumbre Shirish , Raymond Erin , Marathe Madhav 
Published: November 2020

AbstractThe COVID-19 pandemic brought to the forefront an unprecedented need for experts, as well as citizens, to visualize spatio-temporal disease surveillance data. Web application dashboards were quickly developed to fill this gap, including those built by JHU, WHO, and CDC, but all of these dashboards supported a particular niche view of the pandemic (ie, current status or specific regions). In this paper1, we describe our work developing our own COVID-19 Surveillance Dashboard, available at https://nssac.bii.virginia.edu/covid-19/dashboard/, which offers a universal view of the pandemic while also allowing users to focus on the details that interest them. From the beginning, our goal was to provide a simple visual way to compare, organize, and track near-real-time surveillance data as the pandemic progresses. Our dashboard includes a number of advanced features for zooming, filtering, categorizing and visualizing multiple time series on a single canvas. In developing this dashboard, we have also identified 6 key metrics we call the 6Cs standard which we propose as a standard for the design and evaluation of real-time epidemic science dashboards. Our dashboard was one of the first released to the public, and remains one of the most visited and highly used. Our group uses it to support federal, state and local public health authorities, and it is used by people worldwide to track the pandemic evolution, build their own dashboards, and support their organizations as they plan their responses to the pandemic. We illustrate the utility of our dashboard by describing how it can be used to support data story-telling – an important emerging area in data science.
Estimates of the Value of Life Lost from COVID-19 in Ohio
Authors: Mallow Peter J. 
Published: November 2020

AbstractThe economic burden of mortality due to the novel coronavirus (COVID-19) was estimated for the State of Ohio. Data from the Ohio Department of Public Health and Social Security Administration was used to estimate the years of potential life lost, 56,518, and economic value of those lost lives, $13.60 billion. These estimates may be used to assess the risk-trade off of COVID-19 mitigation strategies in Ohio.
Impact of environmental factors in predicting daily severity scores of atopic dermatitis
Authors: Hurault Guillem , Delorieux Valentin , Kim Young-Min , Ahn Kangmo , Williams Hywel C. , Tanaka Reiko J. 
Published: November 2020

ABSTRACTBackgroundAtopic dermatitis (AD) is a chronic inflammatory skin disease that affects 20% of children worldwide. Although environmental factors including weather and air pollutants have been shown to be associated with AD symptoms, the time-dependent nature of such a relationship has not been adequately investigated.ObjectiveThis paper aims to assess the short-term impact of weather and air pollutants on AD severity scores.MethodsUsing longitudinal data from a published panel study of 177 paediatric patients followed up for 17 months, we developed statistical machine learning models to predict daily AD severity scores for individual study participants. Exposures consisted of daily meteorological variables and concentrations of air pollutants and outcomes were daily recordings of scores for six AD signs. We developed a mixed effect autoregressive ordinal logistic regression model, validated it in a forward-chaining setting, and evaluated the effects of the environmental factors on the predictive performance.ResultsOur model outperformed benchmark models for daily prediction of the AD severity scores. The predictive performance of AD severity scores was not improved by the addition of measured environmental factors. Any potential short-term influence of environmental exposures on AD severity scores was outweighed by the underlying persistence of preceding scores.ConclusionsOur data does not offer enough evidence to support a claim that AD symptoms are associated with weather or air pollutants on a short-term basis. Inferences about the magnitude of the effect of environmental factors require consideration of the time-dependence of the AD severity scores.
Features of creatine-kinase in COVID-19 patients with different ages, clinical types and outcomes: A cohort study
Authors: Wan Shanshan , Qu Gaojing , Yu Hui , Zhu Haoming , Huang Guoxin , Chen Lei , Zhang Meiling , Liu Jiangtao , Pei Bin 
Published: November 2020

AbstractObjectivesTo study the features of creatine-kinase (CK) in COVID-19 patients with different ages, clinical types and outcomes and quantify the relationship between CK value and clinical type.MethodsAll laboratory confirmed COVID-19 patients hospitalized in Xiangyang No.1 People’s Hospital were included. Patients’ general information, clinical type, all CK values and outcome were collected.ResultsThe peak median value of CK in cases aged ≥ 71 years old (appeared at T2) was higher than that in cases aged ≤ 70 years old. There was statistical difference between the two groups (P=0.001). Similarly, the peak in critical cases (appeared at T2) was higher than moderate and severe types, and significant difference were existed among moderate, severe, and critical types (P=0.000). Moreover, the peak value in death group (appeared at T2) was higher than those in survival group. Significant difference was also found between them (P=0.000). According to the optimal scale regression model, the CK value (P=0.000) and age (P=0.000) were associated with the clinical type.ConclusionsDifference of the CK in different ages, clinical types, and outcomes were significant. The results of the optimal scale regression model are helpful to judge the clinical type of COVID-19 patients.
Features of α-Hydroxybutyrate Dehydrogenase during various specific periods in COVID-19 patients within Xiangyang, China: a cohort study
Authors: Zhu Haoming , Qu Gaojing , Yu Hui , Huang Guoxin , Chen Lei , Zhang Meiling , Wan Shanshan , Pei Bin 
Published: November 2020

AbstractBackgroundCoronavirus disease-2019 (COVID-19) has spread all over the world and brought extremely huge losses. There is no study to systematically analyse the features of hydroxybutyrate dehydrogenase (α-HBDH) in COVID-19 patients during the periods before and after illness progression, before death and course from exposure onset.MethodsWe collected all included patients’ general information, clinical type, α-HBDH value and outcome, and analyzed α-HBDH values within different initial time and different periods.ResultsIn the first 30 days after symptom onset, the α-HBDH median value was 156.33 U/L. The first test of α-HBDH since exposure onset appeared on the 8th day, it increased from the 8th day to 18th day and decreased after the 18th day. α-HBDH median value showed a slight change until it started to increase 1 day before transforming to severe type, while it continued to increase during 4 days before and after transforming to critical type. The α-HBDH median value ranged from 191.11 U/L to 455.11U/L before death.Conclusionsα-HBDH value increases in some COVID-19 patients, obviously in severe type, critical type and death patients, and mainly in 18 days after exposure onset and 10 days after symptom onset. α-HBDH increases 1 day before transforming to severe type, continues to increase in critical type and death patients, increases rapidly 5 days before death. The increase of α-HBDH suggests that COVID-19 patients have tissues and organs damage, mainly in heart. In brief, α-HBDH is an important indicator to judge the severity and prognosis of COVID-19.
Forecasting new daily confirmed cases infected by COVID-19 in Italy from April 9th to May 18th 2020
Authors: Jamshidi Babak , Talaei-Khoei Amir , Zargaran Shahriar Jamshidi , Rezaei Mansour 
Published: November 2020

AbstractWe aim at forecasting the outbreak of COVID-19 in Italy by using a two-part time series to model the daily relative increments. Our model is based on the data observed from 22 February to 8 April 2020 and its objective is forecasting 40 days from 9 April to 18 May 2020. All the calculations, simulations, and results in the present paper have been done in MatLab R2015b. The average curve and 80% upper and lower bounds are calculated based on 100 simulations of the fitted models. According to our model, it is expected that by May 18th, 2020, the relative increment (RI) falls to the interval of 0.31% to 1.24% (average equal to 0.78%). During the last three days of the studied period, the RI belonged to the interval 2.5% to 3%. Accordingly, It is expected that the new daily confirmed cases face a decreasing to around 1900 on average. Finally, our prediction establishes that the cumulative number of confirmed cases reaches 237635 (with 80% confidence interval equal to [226340 248417] by May 18th, 2020.
Lightweight Model For The Prediction of COVID-19 Through The Detection And Segmentation of Lesions in Chest CT Scans
Authors: Ter-Sarkisov Aram 
Published: November 2020

AbstractWe introduce a lightweight Mask R-CNN model that segments areas with the Ground Glass Opacity and Consolidation in chest CT scans. The model uses truncated ResNet18 and ResNet34 nets with a single layer of Feature Pyramid Network as a backbone net, thus substantially reducing the number of the parameters and the training time compared to similar solutions using deeper networks. Without any data balancing and manipulations, and using only a small fraction of the training data, COVID-CT-Mask-Net classification model with 6.12M total and 600K trainable parameters derived from Mask R-CNN, achieves 91.35% COVID-19 sensitivity, 91.63% Common Pneumonia sensitivity, 96.98% true negative rate and 93.95% overall accuracy on COVIDx-CT dataset (21191 images). We also present a thorough analysis of the regional features critical to the correct classification of the image. The full source code, models and pretrained weights are available on https://github.com/AlexTS1980/COVID-CT-Mask-Net.
Infant Inhibited Temperament in Primates Predicts Adult Behavior, is Heritable, and is Associated with Anxiety-Relevant Genetic Variation
Authors: Fox AS , Harris RA , Del Rosso L , Raveendran M , Kamboj S , Kinnally EL , Capitanio JP , Rogers J 
Published: November 2020

ABSTRACTAn anxious or inhibited temperament (IT) early in life is a major risk factor for the later development of stress-related psychopathology. Starting in infancy, nonhuman primates, like humans, begin to reveal their temperament when exposed to novel situations. Here, in Study 1 we demonstrate this infant IT predicts adult behavior. Specifically, in over 600 monkeys, we found that individuals scored as inhibited during infancy were more likely to refuse treats offered by potentially-threatening human experimenters as adults. In Study 2, using a sample of over 4000 monkeys from a large multi-generational family pedigree, we demonstrate that infant IT is partially heritable. The data revealed infant IT to reflect a co-inherited substrate that manifests across multiple latent variables. Finally, in Study 3 we performed whole-genome sequencing in 106 monkeys to identify IT-associated single-nucleotide variations (SNVs). Results demonstrated a genome-wide significant SNV nearCTNNA2, suggesting a molecular target worthy of additional investigation. Moreover, we observed lower p-values in genes implicated in human association studies of neuroticism and depression. Together, these data demonstrate the utility of our model of infant inhibited temperament in the rhesus monkey to facilitate discovery of genes that are relevant to the long-term inherited risk to develop anxiety and depressive disorders.
Phenology and Robustness in plant-pollinator networks
Authors: Guzman Laura Melissa , Chamberlain Scott A. , Elle Elizabeth 
Published: November 2020

AbstractMany metrics that describe the structure of mutualistic plant-pollinator networks have been found to be important for network stability and robustness. These metrics are impacted by a suite of variables, including species traits, species abundances, their spatial configuration, and their phylogenetic history. Here, we consider a specific trait, phenology, or the timing of life history events. We expect that timing and duration of activity of pollinators, or of flowering in plants, could greatly affect the structure of the networks in which they are embedded. Using plant-pollinator networks from 33 sites in southern British Columbia, Canada, we asked a) how phenological species traits, specifically timing of first appearance in the network and duration of activity in a network, were related to network structure, and b) how those traits affected network robustness to phenologically biased species loss. We found that long duration of activity increased connection within modules for both pollinators and plants and among modules for plants. We also found that date of first appearance was positively related to interaction strength asymmetry in plants but negatively related in pollinators. Networks were generally more robust to the loss of pollinators than plants, but robustness declined with loss of early-flying or long-duration pollinators. These pollinators tended to be among-module connectors. Our results show that changes in phenology have the potential to impact plant-pollinator networks, which may have conservation relevance in a time of changing climate.
Transcriptomic signature and metabolic programming of bovine classical and nonclassical monocytes indicate distinct functional specializations
Authors: Talker Stephanie C. , Barut G. Tuba , Rufener Reto , von Münchow Lilly , Summerfield Artur 
Published: November 2020

AbstractSimilar to human monocytes, bovine monocytes can be split into CD14+CD16−classical and CD14−CD16+nonclassical monocytes (cM and ncM, respectively). Here, we present an in-depth analysis of their steady-state transcriptomes, highlighting pronounced functional specializations. Gene transcription indicates that pro-inflammatory and antibacterial processes are associated with cM, while ncM appear to be specialized in regulatory/anti-inflammatory functions and tissue repair, as well as antiviral responses and T-cell immunomodulation. In support of these functional differences, we found that oxidative phosphorylation prevails in ncM, whereas cM are clearly biased towards aerobic glycolysis. Furthermore, bovine monocyte subsets differed in their responsiveness to TLR ligands, supporting an antiviral role of ncM. Taken together, these data clearly indicate a variety of subset-specific functions in cM and ncM that are likely to be transferable to monocyte subsets of other species, including humans.
Mating and starvation modulate feeding and host-seeking responses in female bed bugs,Cimex lectularius
Authors: Saveer Ahmed M. , DeVries Zachary C. , Santangelo Richard , Schal Coby 
Published: November 2020

ABSTRACTAdaptive insect behavior is subject to modulation by internal physiological states and external social contexts to enhance reproductive fitness and survival. The common bed bug,Cimex lectulariusis an obligate hematophagous ectoparasite that requires host blood for growth, development, and reproduction. We investigated how mating, starvation and social factors such as harassment by males affect host-seeking, blood feeding, oviposition, and survival of female bed bugs. The percentage of females that fed and the amount of blood they ingested were greater in mated females (90–100%) than in unmated females (48–60%). Mating state also modulated the female’s orientation towards human skin odor in an olfactometer; more mated (69%) than unmated (23%) females responded to human odors. The response rate of unmated females (60%) to human odor increased with longer starvation period, while the opposite pattern was observed in mated females (20%). Although fecundity after a single blood meal was unaffected by long or short residence with males, females subjected to frequent copulations had lower survivorship and lifespan than females subjected to males for only 24 h. Taken together, these results indicate that behaviors are adaptively expressed based on the internal physiological state to maximize survival and reproductive fitness.
Paper-based Sensing of Fucosylated Biological Compounds
Authors: Enam Fatima , Kramer Emily , Robinson Frederick , Alvarez-Acosta Andrea , Cademartiri Rebecca , Mansell Thomas J. 
Published: November 2020

SummaryAdvances in sensing technology have enabled rapid analysis of various biomolecules including complex carbohydrates. However, glycan analysis is limited by the throughput and complexity of assays for quantifying them. We describe a simple, low-cost enzymatic assay for the rapid analysis of fucosylation, down to linkage specificity, and its application to high-throughput screening of biologically relevant fucosylated compounds, to facilitate simple and straightforward analytical techniques. Paper-based devices integrate biosensor platforms and other diagnostic assays by fusing them with wax printing technology, making their fabrication even more inexpensive and simple. The specificity of the assay is established by linkage-specific glycosidic enzymes and the colorimetric output is visible to the naked eye, with costs that are lower than fluorescence/luminescence-based assays ($0.02/reaction). This platform was further improved by enhancing storage stability to retain analytical performance over time using desiccation and freeze-drying techniques. The assay platform allows analysis of hundreds of samples in minutes and we anticipate that this rapid and simple analytical method will be extended towards developing a universal glyco-barcoding platform for high throughput screening of glycosylation.
Leapfrog dynamics in phage-bacteria coevolution revealed by joint analysis of cross-infection phenotypes and whole genome sequencing
Authors: Gupta Animesh , Peng Shengyun , Leung Chung Yin , Borin Joshua M. , Medina Sarah J. , Weitz Joshua S. , Meyer Justin R. 
Published: November 2020

AbstractViruses and their hosts can undergo coevolutionary arms races where hosts evolve increased resistance and viruses evolve counter-resistance. Given these arms race dynamics (ARD), viruses and hosts are each predicted to evolve along a single trajectory as more recently evolved genotypes replace their predecessors. Here, by coupling phenotypic and genomic analyses of coevolving populations of bacteriophage λ andEscherichia coli, we find conflicting evidence for ARD. Virus-host infection phenotypes fit the ARD model, yet whole genome analyses did not. Rather than coevolution unfolding along a single trajectory, cryptic genetic variation emerges during initial virus-host coevolution. This variation is maintained across generations and eventually supplants dominant lineages. These observations constitute what we term ‘leapfrog’ coevolutionary dynamics, revealing weaknesses in the predictive power of standard coevolutionary models. The findings shed light on the mechanisms that structure coevolving ecological networks and reveal the limits of using phenotypic assays alone in characterizing coevolutionary dynamics.
Soaring styles of extinct giant birds and pterosaurs
Authors: Goto Yusuke , Yoda Ken , Weimerskirch Henri , Sato Katsufumi 
Published: November 2020

SummaryThe largest extinct volant birds (Pelagornis sandersiandArgentavis magnificens) and pterosaurs (PteranodonandQuetzalcoatlus) are thought to have used wind-dependent soaring flight, similar to modern large birds. There are two types of soaring: thermal soaring, used by condors and frigatebirds, which involves the use of updrafts to ascend and then glide horizontally over the land or the sea; and dynamic soaring, used by albatrosses, which involves the use of wind speed differences with height above the sea surface. Previous studies have suggested thatPelagornis sandersiused dynamic soaring, whileArgenthavis magnificens, Pteranodon, andQuetzalcoatlusused thermal soaring. However, the performance and wind speed requirements of dynamic and thermal soaring for these species have not yet been quantified comprehensively. We quantified these values using aerodynamic models and compared them with that of extant birds. For dynamic soaring, we quantified maximum flight speeds and maximum upwind flight speeds. For thermal soaring, we quantified the animal’s sinking speed circling at a given radius and how far it could glide losing a given height. Our results confirmed those from previous studies thatPteranodonandArgentavis magnificensused thermal soaring. Conversely, the results forPelagornis sandersiandQuetzalcoatluswere contrary to those from previous studies.Pelagornis sandersiused thermal soaring, andQuetzalcoatlushad a poor ability both in dynamic and thermal soaring. Our results demonstrate the need for comprehensive assessments of performance and required wind conditions when estimating soaring styles of extinct flying species.