bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boosting SARS-CoV-2 qRT-PCR detection combining pool sample strategy and mathematical modeling
Authors: Correa Isadora Alonso , Rodrigues Tamires de Souza , Queiroz Alex , Nascimento Leon de França , Wolff Thiago , Akamine Rubens Nobumoto , Kuriyama Sergio Noboru , da Costa Luciana Jesus , Fidalgo-Neto Antonio Augusto 
Published: August 2020

ABSTRACTqRT-PCR is the gold standard technique available for SARS-CoV-2 detection. However, the long test run time and costs associated with this type of molecular testing are a challenge in the actual pandemic scenario. Due to high testing demand, pooling sample strategy is an interesting approach to allow cost savings. We aim to evaluate pooling tests in experimental procedures, as well as perform in silico statistical modeling analysis validated with specimen samples obtained from a mass testing program of Industry Federation of the State of Rio de Janeiro (Brazil). Although the sensitivity reduction in samples pooled with 32 individuals was observed, the high-test sensitivity is maintained even when 16 and 8 samples were pooled. The in silico analysis showed high-cost savings in populations with positive rates lower than 15.0% according to the pool size. This data was validated with the results obtained in our mass testing program: statistical modeling predicted a cost saving of 48.0%, which in practice, was 51.5%, already considering the expenditures with pool sampling that were analyzed individually. Our data confirmed that mathematical modeling is a powerful strategy to improve the pooling approach for SARS-CoV-2 mass testing around the world while maintaining high sensitivity and robustness.
Prevalence and associated factors of burnout in allied healthcare professionals in a tertiary hospital in Singapore
Authors: Teo Yao Hao , Xu Jordan Thet Ke , Ho Cowan , Leong Jui Min , Tan Benjamin Kye Jyn , Tan Elisabeth Ker Hsuen , Goh Wei-An , Neo Elson , Chua Jonathan Yu Jing , Ng Sean Jun Yi , Cheong Julia Jie Yi , Hwang Jeff Yi-Fu , Lim See Ming , Soo Thomas , Sng Judy Gek Khim , Yi Siyan 
Published: August 2020

AbstractObjectiveTo explore the prevalence of burnout, factors associated with burnout, and barriers to seeking psychological help among allied health professionals in Singapore.DesignCross-sectional study.SettingA tertiary hospital in Singapore.ParticipantsAllied health professionals.Primary outcome measureBurnout measured by using Maslach Burnout Inventory (MBI-HSS)ResultsIn total, 328 participants completed the questionnaire. The prevalence of burnout was 67.4%. A majority of the respondents were female (83.9%), Singaporean (73.5%), aged 40 years and below (84.2%), and of Chinese ethnicity (79.9%). In the multiple logistic regression model, burnout was negatively associated with being in the age groups of 31 to 40 (AOR 0.39, 95% CI 0.16–0.93) and ≥40 years (AOR 0.30, 95% CI 0.10–0.87) and a low workload burden (AOR 0.35, 95% CI 0.23–0.52). Burnout was positively associated with a longer work experience of 3 to 5 years (AOR 5.27, 95% CI 1.44–20.93) and more than five years (AOR 4.24; 95% CI 1.16–16.79). Among the 190 participants who completed the PBPT, barriers to seeking psychological help shown to be significantly associated with burnout were a ‘lack of motivation’ and ‘time constraints’ (p< 0.01).ConclusionsThis study shows a high prevalence of burnout and identifies its associated factors among Singapore’s allied health professionals. The findings revealed the urgency of addressing burnout in allied health professionals and the need for effective interventions to reduce burnout. Concurrently, proper consideration of the barriers to seeking help is warranted to improve allied health professionals’ mental wellbeing.Strengths and limitations of this studyThis study is the first to show a high prevalence of burnout and identify its associatedWe used validated scales, including Maslach Burnout Inventory, Areas of Worklife Survey, and Perceived Barriers to Psychological Treatment.Limitations of the study included the cross-sectional design, the low response rate, the potential social desirability bias, and the limited generalizability.This study did not cover factors associated with burnout in previous studies, including the increasing computerization of practices and the participants’ personality traits.
The Development of a Care Home Data Platform in Scotland: Insights from the Care Home Innovation Partnership, Lothian
Authors: Johnston Lucy , Hockley Jo , Henderson David AG , Shenkin Susan D 
Published: August 2020

ABSTRACTCare homes collect a large amount of data about their residents, and the care provided, but there is a lack of consistency in how this information is collected. There is also a need to minimise the burden of data collection on staff, ensure information informs and supports person-centred care, and that this data is then of use to regulatory agencies, policy makers and researchers.We examined the data collected in six Care Homes in Lothian, Scotland. We extracted the meta-data collected, cross-referenced definitions and assessed the degree of current harmonisation between individual care homes and with data sets currently in use in Scotland and internationally. We interviewed the care home managers to identify data collection processes, views and experiences of current data availability, gaps, access and issues of capacity and capability in relation to data management and analytics.Our work has illustrated the scale of the data collected by care homes, the varied formats and heterogeneity of scope and definition. The inventory of 15 core data items that emerged, serves to expose in detail the foundations of care home data sets. The groundwork illuminated the heterogeneity in tools and assessments used to generate the data and the way in which the data is to be used, affects how it is specified and frequency of collection. By making known the reality of how and why care home data is collected, we can understand better the nuances of each individual data item that collectively create a data platform. We make four recommendations for the development of a national care home data platform.
Transcriptional Profiling of Identified Neurons in Leech
Authors: Heath-Heckman Elizabeth , Yoo Shinja , Winchell Christopher , Pellegrino Maurizio , Angstadt James , Lammardo Veronica B. , Bautista Diana , De-Miguel Francisco F. , Weisblat David 
Published: August 2020

ABSTRACTWhile leeches in the genusHirudohave long been models for neurobiology, the molecular underpinnings of nervous system structure and function in this group remain largely unknown. To begin to bridge this gap, we performed RNASeq on pools of identified neurons of the central nervous system (CNS): sensory T (touch), P (pressure) and N (nociception) neurons; neurosecretory Retzius cells; and ganglia from which these four cell types had been removed. Bioinformatic analyses identified 2,812 putative genes whose expression differed significantly among the samples. These genes clustered into 7 groups which could be associated with one or more of the identified cell types. We verified predicted expression patterns throughin situhybridization on whole CNS ganglia, and found that orthologous genes were for the most part similarly expressed in a divergent leech genus, suggesting evolutionarily conserved roles for these genes. Transcriptional profiling allowed us to identify candidate phenotype-defining genes from expanded gene families. Thus, we identified one of eight hyperpolarization-activated cyclic-nucleotide gated (HCN) channels as a candidate for mediating the prominent sag current in P neurons, and found that one of five inositol triphosphate receptors (IP3Rs), representing a sub-family of IP3Rs absent from vertebrate genomes, is expressed with high specificity in T cells. We also identified one of twopiezogenes, two of ~65deg/enacgenes, and one of at least 16transient receptor potential(trp) genes as prime candidates for involvement in sensory transduction in the three distinct classes of leech mechanosensory neurons.
KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response
Authors: Reese Justin , Unni Deepak , Callahan Tiffany J. , Cappelletti Luca , Ravanmehr Vida , Carbon Seth , Fontana Tommaso , Blau Hannah , Matentzoglu Nicolas , Harris Nomi L. , Munoz-Torres Monica C. , Robinson Peter N. , Joachimiak Marcin P. , Mungall Christopher J. 
Published: August 2020

SUMMARYIntegrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community varies drastically for different tasks - the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates biomedical data to produce knowledge graphs (KGs) for COVID-19 response. This KG framework can also be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics.BIGGER PICTUREAn effective response to the COVID-19 pandemic relies on integration of many different types of data available about SARS-CoV-2 and related viruses. KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to enable researchers to explore COVID-19 data and discover relationships.
A toolkit for studyingVarroagenomics and transcriptomics: Preservation, extraction, and sequencing library preparation
Authors: Hasegawa Nonno , Techer Maeva , Mikheyev Alexander S. 
Published: August 2020

AbstractBackgroundThe honey bee parasite,Varroa destructor, is a leading cause of honey bee population declines. In addition to being an obligate ectoparasitic mite,Varroacarries several viruses that infect honey bees and act as the proximal cause of colony collapses. Nevertheless, until recently, studies ofVarroahave been limited by the paucity of genomic tools. Lab- and field-based methods exploiting such methods are still nascent. This study developed a set of methods for preservingVarroaDNA and RNA from the field to the lab and processing them into sequencing libraries. We performed preservation experiments in whichVarroamites were immersed in TRIzol, RNAlater, and absolute ethanol for preservation periods up to 21 days post-treatment to assess DNA and RNA integrity.ResultsFor both DNA and RNA, mites preserved in TRIzol and RNAlater at room temperature degraded within 10 days post-treatment. Mites preserved in ethanol at room temperature and 4°C remained intact through 21 days.Varroamite DNA and RNA libraries were created and sequenced for ethanol preserved samples, 15 and 21 days post-treatment. All DNA sequences mapped to theV. destructorgenome at above 95% on average, while RNA sequences mapped toV. destructor, but also sometimes to high levels of the deformed-wing virus and to various organisms.ConclusionEthanolic preservation of field-collected mites is inexpensive and simple, and allows them to be shipped and processed successfully in the lab for a wide variety of sequencing applications. It appears to preserve RNA from bothVarroaand at least some of the viruses it vectors.
Evaluation of pneumococcal serotyping in nasopharyngeal carriage isolates by latex agglutination, whole genome sequencing (PneumoCaT) and DNA microarray in a high pneumococcal carriage prevalence population in Malawi
Authors: Swarthout Todd D. , Gori Andrea , Bar-Zeev Naor , Kamng’ona Arox W. , Mwalukomo Thandie S. , Bonomali Farouck , Nyirenda Roseline , Brown Comfort , Msefula Jacquline , Everett Dean , Mwansambo Charles , Gould Katherine , Hinds Jason , Heyderman Robert S. , French Neil 
Published: August 2020

AbstractBackgroundAccurate assessment of the serotype distribution associated with pneumococcal colonization and disease is essential for the evaluation and formulation of pneumococcal vaccines and informing vaccine policy.MethodsWe evaluated pneumococcal serotyping concordance between latex agglutination, PneumoCaT by whole genome sequencing (WGS) and DNA microarray using samples from community carriage surveillance in Blantyre, Malawi. Nasopharyngeal swabs were collected, following WHO recommendations, between 2015 and 2017, using stratified random sampling among study populations. Participants included healthy children 3–6 years old (PCV13 vaccinated as part of EPI), healthy children 5–10 years (age-ineligible for PCV13), and HIV-infected adults (18–40yrs) on ART. For phenotypic serotyping we used a 13-valent latex kit (SSI, Denmark). For genomic serotyping we applied PneumoCaT pipeline to whole genome sequence libraries. For molecular serotyping by microarray we used the BUGS Bioscience DNA microarray.Results1347 samples were analysed. Concordance was 90.7% (95% CI: 89.0–92.2) between latex and PneumoCaT; 95.2% (93.9–96.3) between latex and microarray; and 96.6% (95.5–97.5) between microarray and PneumoCaT. By detecting carried vaccine serotype (VT) pneumococcus in low relative abundance (median 8%), microarray increased VT detection by 31.5% compared to latex serotyping.ConclusionAll three serotyping methods were highly concordant in identifying dominant serotypes. Latex serotyping is accurate in identifying vaccine-serotypes and requires the least expertise and resources for field-implementation and analysis. However, WGS, which adds population structure, and microarray, which adds multiple-serotype carriage, should be considered at regional reference laboratories while investigating the importance of VT in low relative abundance in transmission and disease.
Hyperlocal Variation in Soil Iron and Rhizosphere Microbiome Determines Disease Development in Amenity Turfgrass
Authors: Chou Ming-Yi , Shrestha Smita , Rioux Renee , Koch Paul 
Published: August 2020

ABSTRACTDollar spot, caused by the fungal pathogenClarireedia spp., is an economically important disease of amenity turfgrass in temperate climates worldwide. This disease often occurs in a highly variable manner, even on a local scale with relatively uniform environmental conditions. The objective of this study was to investigate mechanisms behind this local variation, focusing on contributions of the soil and rhizosphere microbiome. Turfgrass, rhizosphere, and bulk soil samples were taken from within a 256 m2area of healthy turfgrass, transported to a controlled environment chamber, and inoculated withC. jacksonii. Bacterial communities were profiled targeting the 16s rRNA gene, and 16 different soil chemical properties were assessed. Despite their initial uniform appearance, the samples differentiated into highly susceptible and moderately susceptible groups following inoculation in the controlled environment chamber. The highly susceptible samples harbored a unique rhizosphere microbiome with lower relative abundance of antibiotic-producing bacterial taxa and higher predicted abundance of genes associated with xenobiotic biodegradation pathways. In addition, stepwise regression revealed that bulk soil iron content was the only significant soil characteristic that positively regressed with decreased dollar spot susceptibility during the peak disease development stage. These findings suggest that localized variation in soil iron induces the plant to select for a particular rhizosphere microbiome that alters the disease outcome. More broadly, further research in this area may indicate how plot-scale variability in soil properties can drive variable plant disease development through alterations in the rhizosphere microbiome.IMPORTANCEDollar spot is the most economically important disease of amenity turfgrass, and more fungicides are applied targeting dollar spot than any other turfgrass disease. Dollar spot symptoms are small (3-5 cm), circular patches that develop in a highly variable manner within plot-scale even under seemingly uniform conditions. The mechanism behind this variable development is unknown. This study observed that differences in dollar spot development over a 256 m2area were associated with differences in bulk soil iron concentration and correlated with a particular rhizosphere microbiome. These findings provide important clues for understanding the mechanisms behind the highly variable development of dollar spot, which may offer important clues for innovative control strategies. Additionally, these results also suggest that small changes in soil properties can alter plant activity and hence the plant-associated microbial community which has important implications for a broad array of important agricultural and horticultural plant pathosystems.
In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients
Authors: Park Joonho , Kim Hyeyoon , Kim So Yeon , Kim Yeonjae , Lee Jee-Soo , Seong Moon-Woo , Han Dohyun 
Published: August 2020

ABSTRACTThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over ten million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed indepth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1,222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.
Characterization of histone inheritance patterns in theDrosophilafemale germline
Authors: Kahney Elizabeth W. , Sohn Lydia , Viets-Layng Kayla , Johnston Robert , Chen Xin 
Published: August 2020

ABSTRACTStem cells have the unique ability to undergo asymmetric division which produces two daughter cells that are genetically identical, but commit to different cell fates. The loss of this balanced asymmetric outcome can lead to many diseases, including cancer and tissue dystrophy. Understanding this tightly regulated process is crucial in developing methods to treat these abnormalities. Here, we report that produced from aDrosophilafemale germline stem cell asymmetric division, the two daughter cells differentially inherit histones at key genes related to either maintaining the stem cell state or promoting differentiation, but not at constitutively active or silenced genes. We combined histone labeling with DNA Oligopaints to distinguish old versus new histone distribution and visualize their inheritance patterns at single-gene resolution in asymmetrically dividing cellsin vivo. This strategy can be widely applied to other biological contexts involving cell fate establishment during development or tissue homeostasis in multicellular organisms.
Diapause regulation in newly invaded environments: termination timing allows matching novel climatic constraints in the box tree moth, Cydalima perspectalis (Lepidoptera: Crambidae)
Authors: Poitou Laura , Bras Audrey , Pineau Patrick , Lorme Philippe , Roques Alain , Rousselet Jérôme , Auger-Rozenberg Marie-Anne , Laparie Mathieu 
Published: August 2020

AbstractThe association between indirect environmental cues that modulate insect diapause and the actual stressors is by no means granted when a species encounters new environments. The box tree moth, Cydalima perspectalis, is an Asian pest whose rapid invasion in Europe cause considerable economic and ecological impacts. Larvae enter a winter diapause induced by photoperiod in both native and invaded ranges, but factors that trigger the return to an active phase are still unknown. Yet, identifying them is crucial to understand how diapause end synchronizes with the end of the winter stress encountered in Europe. To test whether activity resumption is regulated by thermal and/or photoperiodic thresholds, or additive effects between these factors often involved in diapause termination, diapausing caterpillars from an invaded area were exposed to crossed treatments at the laboratory. The evolution of diapause rate was monitored over time and compared to that of nearby field sites invaded. A strong positive effect of increasing temperature was found on the rate and dynamics of diapause termination, whereas no compelling effect of photoperiod appeared. Resuming development directly when main stressors fade, not in response to indirect photoperiodic cues that could be mismatched outside native areas, likely contributes to the good match observed between diapause and the new climates this pest encountered in the invaded range.
Region-level Epimutation Rates inArabidopsis thaliana
Authors: Denkena Johanna , Johannes Frank , Colomé-Tatché Maria 
Published: August 2020

AbstractFailure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called ‘spontaneous epimutations’. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phentoypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutational events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as away to identify the epigenetic basis of adaptive traits.