bluuebunny/crossref_metadata_2025_split huggingface dataset:
Review of data and knowledge gaps regarding yellow fever vaccine-induced immunity and duration of protection
Authors: Staples J. Erin , Barrett Alan D. T. , Wilder-Smith Annelies , Hombach Joachim 
Published: July 2020

AbstractYellow fever (YF) virus is a mosquito-borne flavivirus found in Sub-Saharan Africa and tropical South America. The virus causes YF, a viral hemorrhagic fever, which can be prevented by a live-attenuated vaccine, strain 17D. Despite the vaccine being very successful at decreasing disease risk, YF is considered a re-emerging disease due to the increased numbers of cases in the last 30 years. Until 2014, the vaccine was recommended to be administered with boosters every 10 years, but in 2014 the World Health Organization recommended removal of booster doses for all except special populations. This recommendation has been questioned and there have been reports of waning antibody titers in adults over time and more recently in pediatric populations. Clearly, the potential of waning antibody titers is a very important issue that needs to be carefully evaluated. In this Perspective, we review what is known about the correlate of protection for full-dose YF vaccine, current information on waning antibody titers, and gaps in knowledge. Overall, fundamental questions exist on the durability of protective immunity induced by YF vaccine, but interpretation of studies is complicated by the use of different assays and different cut-offs to measure seroprotective immunity, and differing results among certain endemic versus non-endemic populations. Notwithstanding the above, there are few well-characterized reports of vaccine failures, which one would expect to observe potentially more with the re-emergence of a severe disease. Overall, there is a need to improve YF disease surveillance, increase primary vaccination coverage rates in at-risk populations, and expand our understanding of the mechanism of protection of YF vaccine.
Interconnection of bacterial and phytoplanktonic communities with hydrochemical parameters from ice and under-ice water in coastal zone of Lake Baikal
Authors: Bukin Yu. S. , Bondarenko N. A. , Rusanov I. I. , Pimenov N. V. , Bukin S. V. , Pogodaeva T. V. , Chernitsyna S. M. , Shubenkova O. V. , Ivanov V. G. , Zakharenko A. S. , Zemskaya T. I. 
Published: July 2020

AbstractWe analysed the relationship between the chemical complex (concentration of dissolved ions, nutrients, pH) and biological parameters (primary production, biomass of phytoplankton, abundance and activity of bacterial communities) at estuaries of rivers and coastal waters of Southern Baikal during the under-ice period. Correlation network analysis revealed CO2 to be the main limiting factor for the development of algae and microbial communities in the coastal zone of Lake Baikal. This study indicates that primarily reverse synthesis of bicarbonate and carbonate ions associated with the development of phytoplankton and accumulation of dissolved CO2 during photosynthesis regulates pH in the Baikal water. We did not detect the anthropogenic factors that influence the change in pH and acidification. Near the Listvyanka settlement (Lake Baikal, Listvennichnaya Bay), there was a great number of organotrophs and thermotolerant bacteria with low bacterioplankton activity and high concentration of organic carbon. This evidences eutrophication due to the influx of organic matter having an anthropogenic source. Nutrients produced during the bacterial destruction of this matter may explain the changes in bottom phytocenoses of Listvennichnaya Bay.
Identification and characterization of Colletotrichum species causing apple bitter rot in New York and description of C. noveboracense sp. nov.
Authors: Khodadadi Fatemeh , González Jonathan B. , Martin Phillip L. , Giroux Emily , Bilodeau Guillaume J. , Peter Kari A. , Doyle Vinson P. , Aćimović Srđan G. 
Published: July 2020

AbstractApple bitter rot caused by Colletotrichum species is a growing problem worldwide. Colletotrichum spp. are economically important but taxonomically un-resolved. Identification of Colletotrichum spp. is critical due to potential species-level differences in pathogenicity-related characteristics. A 400-isolate collection from New York apple orchards were morphologically assorted to two groups, C. acutatum species complex (CASC) and C. gloeosporioides species complex (CGSC). A sub-sample of 44 representative isolates, spanning the geographical distribution and apple varieties, were assigned to species based on multi-locus phylogenetic analyses of nrITS, GAPDH and TUB2 for CASC, and ITS, GAPDH, CAL, ACT, TUB2, APN2, ApMat and GS genes for CGSC. The dominant species was C. fioriniae, followed by C. chrysophilum and a novel species, C. noveboracense, described in this study. This study represents the first report of C. chrysophilum and C. noveboracense as pathogens of apple. We assessed the enzyme activity and fungicide sensitivity for isolates identified in New York. All isolates showed amylolytic, cellulolytic and lipolytic, but not proteolytic activity. C. chrysophilum showed the highest cellulase and the lowest lipase activity, while C. noveboracense had the highest amylase activity. Fungicide assays showed that C. fioriniae was sensitive to benzovindiflupyr and thiabendazole, while C. chrysophilum and C. noveboracense were sensitive to fludioxonil, pyraclostrobin and difenoconazole. All species were pathogenic on apple fruit with varying lesion sizes. Our findings of differing pathogenicity-related characteristics among the three species demonstrate the importance of accurate species identification for any downstream investigations of Colletotrichum spp. in major apple growing regions.
Unspoken Assumptions in Multi-layer Modularity maximization
Authors: Hanteer Obaida , Magnani Matteo 
Published: July 2020

AbstractA principled approach to recover communities in social networks is to find a clustering of the network nodes into modules (i.e groups of nodes) for which the modularity over the network is maximal. This guarantees partitioning the network nodes into sparsely connected groups of densely connected nodes. A popular extension of modularity has been proposed in the literature so it applies to multi-layer networks, that is, networks that model different types/aspects of interactions among a set of actors. In this extension, a new parameter, the coupling strength ω, has been introduced to couple different copies (i.e nodes) of the same actor with specific weights across different layers. This allows two nodes that refer to the same actor to reward the modularity score with an amount proportional to ω when they appear in the same community. While this extension seems to provide an effective tool to detect communities in multi-layer networks, it is not always clear what kind of communities maximising the generalised modularity can identify in multi-layer networks and whether these communities are inclusive to all possible community structures possible to exist in multi-layer networks. In addition, it has not been thoroughly investigated yet how to interpret ω in real-world scenarios, and whether a proper tuning of ω, if exists, is enough to guarantee an accurate recoverability for different types of multi-layer community structures. In this article, we report the different ways used in the literature to tune ω. We analyse different community structures that can be recovered by maximising the generalised modularity in relation to ω. We propose different models for multi-layer communities in multiplex and time-dependent networks and test if they are recoverable by modularity-maximization community detection methods under any assignment of ω. Our main finding is that only few simple models of multi-layer communities in multiplex and time-dependent networks are recoverable by modularity maximisation methods while more complex models are not accurately recoverable under any assignment of ω.
Evolutionary-driven C-MYC gene expression in mammalian fibroblasts
Authors: Moura Marcelo T. , Silva Roberta L. O. , Cantanhêde Ludymila F. , Ferreira-Silva José C. , Nascimento Pábola S. , Benko-Iseppon Ana M. , Oliveira Marcos A. L. 
Published: July 2020

AbstractThe extent to which mammalian cells share similar transcriptomes remains unclear. Notwithstanding, such cross-species gene expression inquiries have been scarce for defined cell types and most lack the dissection of gene regulatory landscapes. Therefore, the work was aimed to determineC-MYCrelative expression across mammalian fibroblasts (Ovis ariesandBos taurus) via cross-species RT-qPCR and comprehensively explore its regulatory landscape by in silico tools. The prediction of transcription factor binding sites inC-MYCand its 2.5 kb upstream sequence revealed substantial variation, thus indicating evolutionary-driven re-wiring of cis-regulatory elements.C-MYCand its downstream targetTBX3were up-regulated inBos taurusfibroblasts. The relative expression ofC-MYCregulators [RONIN(also known asTHAP11),RXRβ, andTCF3] and theC-MYC-associated transcript elongation factorCDK9did not differ between species. Additional in silico analyses suggestedBos taurus-specificC-MYCexonization, alternative splicing, and binding sites for non-coding RNAs.C-MYCprotein orthologs were highly conserved, while variation was in the transactivation domain and the leucine zipper motif. Altogether, mammalian fibroblasts display evolutionary-drivenC-MYCrelative expression that should be instructive for understanding cellular physiology, cellular reprogramming, andC-MYC-related diseases.
Effects of biochar-based controlled release nitrogen fertilizer on nitrogen-use efficiency of oilseed rape (Brassica napus L.)
Authors: Liao Jiayuan , Liu Xiangrong , Hu Ang , Song Haixing , Chen Xiuzhi , Zhang Zhenhua 
Published: July 2020

AbstractBiochar-based controlled release nitrogen fertilizers (BCRNFs) have received increasing attention due to their ability to improve nitrogen-use efficiency (NUE) and increase crop yields. We previously developed a novel BCRNF, but its effects on soil microbes, NUE, and crop yields have not been reported. Therefore, we designed a pot experiment with five randomised treatments: CK (without urea and biochar), B (addition biochar without urea), B + U (biochar mixed urea), Urea (addition urea without biochar), and BCRNF (addition BCRNF), to investigate the effects of BCRNF on nitrifiers and denitrifiers, and how these impact nitrogen supply and NUE. Results of high-throughput sequencing revealed bacterial community groups with higher nutrient metabolic cycling ability under BCRNF treatment during harvest stage. Compared to Urea treatment, BCRNF treatment stimulated nitrification by increasing the copy number of the bacterial amoA gene and reducing nitrous oxide emission by limiting the abundance of nirS and nirK. Eventually, BCRNF successfully enhanced the yield (~ 16.6%) and NUE (~ 58.79%) of rape by slowly releasing N and modulating the abundance of functional microbes through increased soil nitrification and reduced denitrification, as compared with Urea treatment. BCRNF significantly improved soil NO3−, leading to an increase in N uptake by rape and NUE, thereby promoting rape growth and increasing grain yield.
Y2O3–Al2O3 microsphere crystallization analyzed by electron backscatter diffraction (EBSD)
Authors: Wisniewski Wolfgang , Švančárek Peter , Prnová Anna , Parchovianský Milan , Galusek Dušan 
Published: July 2020

AbstractThe crystallization of glass microspheres in the Y2O3–Al2O3-system produced from precursor powders of four different nominal compositions via flame synthesis is analyzed in detail by electron microscopy with a focus on electron backscatter diffraction (EBSD). Growth models are formulated for individual microspheres crystallized during flame synthesis as well as after an additional heat treatment step. 16 different types of crystallized bodies are cataloged for future reference. They are presented without regard for their relative occurrence; some are extremely rare but illustrate the possibilities of flame synthesis in the analyzed system. All three phases in the binary Y2O3–Al2O3-phase diagram (Y3Al5O12, YAlO3 and Y4Al2O9) and α-alumina are located by EBSD. Energy dispersive X-ray spectrometry results obtained from these microspheres show that their chemical composition can deviate from the nominal composition of the precursor powder. The multitude of differing microsphere types showing polygon and dendritic crystal growth as well as phase separation indicate that flame synthesis can lead to a wide variety of parameters during microsphere production, e.g. via irregular flight paths through the flame, contaminants or irregular cooling rates.
The effects of atrazine on the microbiome of the eastern oyster: Crassostrea virginica
Authors: Britt Adrian , Bernini Megan , McSweeney Benjamin , Dalapati Sony , Duchin Sophia , Cavanna Kathryn , Santos Nicolette , Donovan Grace , O’Byrne Katherine , Noyes Sarah , Romero Manuela , Poonacha Kavery Nivana Theethira , Scully Tara 
Published: July 2020

AbstractLong-standing evidence supports the importance of maintaining healthy populations of microbiota for the survival, homeostasis, and complete development of marine mollusks. However, the long-term ecological effects of agricultural runoff on these populations remains largely unknown. Atrazine (6-Chloro-n-ethyl-n′-(1-methylethyl)-triazine-2,4-diamine), a prevalent herbicide in the United States, is often used along tributaries of the Chesapeake Bay where oyster breeding programs are concentrated. To investigate any potential effects atrazine maybe having on mollusk-prokaryote interactions, we used 16S rRNA gene amplicons to evaluate how microbial compositions shift in response to exposure of environmentally relevant concentrations of atrazine previously found within the Chesapeake Bay. The dominant bacterial genera found within all groups included those belonging toPseudoalteromonas,Burkholderia,Bacteroides,Lactobacillis,Acetobacter,Allobaculum,Ruminococcus,andNocardia. Our results support previously published findings of a possible core microbial community inCrassostrea virginica. We also report a novel finding: oysters exposed to atrazine concentrations as low as 3 µg/L saw a significant loss of a key mutualistic microbial species and a subsequent colonization of a pathogenic bacteriaNocardia. We conclude that exposure to atrazine in the Chesapeake Bay may be contributing to a significant shift in the microbiomes of juvenile oysters that reduces fitness and impedes natural and artificial repopulation of the oyster species within the Bay.
Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning
Authors: Govind Darshana , Jen Kuang-Yu , Matsukuma Karen , Gao Guofeng , Olson Kristin A. , Gui Dorina , Wilding Gregory. E. , Border Samuel P. , Sarder Pinaki 
Published: July 2020

AbstractThe Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the number of Ki-67-positive and Ki-67-negative tumor cells within a subjectively picked hot-spot. Intraobserver variability in this procedure as well as difficulty in distinguishing tumor from non-tumor cells can lead to inaccurate Ki-67 indices and possibly incorrect tumor grades. We introduce two computational tools that utilize Ki-67 and synaptophysin double-immunostained (DS) slides to improve the accuracy of Ki-67 index quantitation in GI-NETs: (1) Synaptophysin-KI-Estimator (SKIE), a pipeline automating Ki-67 index quantitation via whole-slide image (WSI) analysis and (2) deep-SKIE, a deep learner-based approach where a Ki-67 index heatmap is generated throughout the tumor. Ki-67 indices for 50 GI-NETs were quantitated using SKIE and compared with DS slide assessments by three pathologists using a microscope and a fourth pathologist via manually ticking off each cell, the latter of which was deemed the gold standard (GS). Compared to the GS, SKIE achieved a grading accuracy of 90% and substantial agreement (linear-weighted Cohen’s kappa 0.62). Using DS WSIs, deep-SKIE displayed a training, validation, and testing accuracy of 98.4%, 90.9%, and 91.0%, respectively, significantly higher than using SS WSIs. Since DS slides are not standard clinical practice, we also integrated a cycle generative adversarial network into our pipeline to transform SS into DS WSIs. The proposed methods can improve accuracy and potentially save a significant amount of time if implemented into clinical practice.
Four-dot masking in monoptic and dichoptic viewing
Authors: Nakamura Tomoya , Lavrenteva Sofia , Murakami Ikuya 
Published: July 2020

AbstractIn visual backward masking paradigms, the visibility of a target is reduced using various kinds of mask stimuli presented immediately after the target. Four-dot masking is one such kind of backward masking, caused by four surrounding dots neither spatially adjacent nor similar to the target. Four-dot masking is often considered to involve object-level interferences. However, low-level contributions such as lateral inhibition and motion detection are also possible. To elucidate the loci of the underlying mechanism within the visual hierarchy, we compared the masking effect between monoptic and dichoptic viewing conditions. A target and a four-dot mask, which also served as a spatial cue to the target location, were presented to the same eye in monoptic viewing, whereas they were presented to different eyes in dichoptic viewing. Observers were then asked to discriminate the target shape. We found a significant decline in the correct response rate compared to the baseline condition in which the four-dot mask was not presented, and the masking effect was equivalent between the monoptic and dichoptic viewings. These results demonstrate that four-dot masking stems exclusively from processing within the binocular pathway.
Societal attention toward extinction threats: a comparison between climate change and biological invasions
Authors: Jarić Ivan , Bellard Céline , Courchamp Franck , Kalinkat Gregor , Meinard Yves , Roberts David L. , Correia Ricardo A. 
Published: July 2020

AbstractPublic attention and interest in the fate of endangered species is a crucial prerequisite for effective conservation programs. Societal awareness and values will largely determine whether conservation initiatives receive necessary support and lead to adequate policy change. Using text data mining, we assessed general public attention in France, Germany and the United Kingdom toward climate change and biological invasions in relation to endangered amphibian, reptile, bird and mammal species. Our analysis revealed that public attention patterns differed among species groups and countries but was globally higher for climate change than for biological invasions. Both threats received better recognition in threatened than in non-threatened species, as well as in native species than in species from other countries and regions. We conclude that more efficient communication regarding the threat from biological invasions should be developed, and that conservation practitioners should take advantage of the existing attention toward climate change.
FMR1 locus isoforms: potential biomarker candidates in fragile X-associated tremor/ataxia syndrome (FXTAS)
Authors: Zafarullah Marwa , Tang Hiu-Tung , Durbin-Johnson Blythe , Fourie Emily , Hessl David , Rivera Susan M. , Tassone Flora 
Published: July 2020

AbstractFragile X associated tremor/ataxia syndrome (FXTAS) is a late adult-onset neurodegenerative disorder that affects movement and cognition in male and female carriers of a premutation allele of 55–200 CGG repeats in the Fragile X mental retardation (FMR1) gene. It is currently unknown if and when an individual carrier of a premutation allele will develop FXTAS, as clinical assessment fails to identify carriers at risk before significant neurological symptoms are evident. The primary objective of this study was to investigate the alternative splicing landscape at the FMR1 locus in conjunction with brain measures in male individuals with a premutation allele enrolled in a very first longitudinal study, compared to age-matched healthy male controls, with the purpose of identifying biomarkers for early diagnosis, disease prediction and, a progression of FXTAS. Our findings indicate that increased expression of FMR1 mRNA isoforms, including Iso4/4b, Iso10/10b, as well as of the ASFMR1 mRNAs Iso131bp, are present in premutation carriers as compared to non-carrier healthy controls. More specifically, we observed a higher expression of Iso4/4b and Iso10/10b, which encode for truncated proteins, only in those premutation carriers who developed symptoms of FXTAS over time as compared to non-carrier healthy controls, suggesting a potential role in the development of the disorder. In addition, we found a significant association of these molecular changes with various measurements of brain morphology, including the middle cerebellar peduncle (MCP), superior cerebellar peduncle (SCP), pons, and midbrain, indicating their potential contribution to the pathogenesis of FXTAS. Interestingly, the high expression levels of Iso4/4b observed both at visit 1 and visit 2 and found to be associated with a decrease in mean MCP width only in those individuals who developed FXTAS over time, suggests their role as potential biomarkers for early diagnosis of FXTAS.
Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study
Authors: Benning Leo , Peintner Andreas , Finkenzeller Günter , Peintner Lukas 
Published: July 2020

AbstractThe last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledged tool to investigate cell behaviour in a tissue-like environment. Cells growing in spheroids differentiate and develop different characteristics in comparison to their two-dimensionally grown counterparts and are hence seen to exhibit a more in vivo-like phenotype. However, generating, treating and analysing spheroids in high quantities remains labour intensive and therefore limits its applicability in drugs and compound research. Here we present a fully automated pipetting robot that is able to (a) seed hanging drops from single cell suspensions, (b) treat the spheroids formed in these hanging drops with drugs and (c) analyse the viability of the spheroids by an image-based deep learning based convolutional neuronal network (CNN). The model is trained to classify between ‘unaffected’, ‘mildly affected’ and ‘affected’ spheroids after drug exposure. All corresponding spheroids are initially analysed by viability flow cytometry analysis to build a labelled training set for the CNN to subsequently reduce the number of misclassifications. Hence, this approach allows to efficiently examine the efficacy of drug combinatorics or new compounds in 3D cell culture. Additionally, it may provide a valuable instrument to screen for new and individualized systemic therapeutic strategies in second and third line treatment of solid malignancies using patient derived primary cells.