bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of three nasopharyngeal swab types and the impact of physiochemical properties for optimal SARS-CoV-2 detection
Authors: Kahamba Trish R. , Noble Lara , Stevens Wendy , Scott Lesley 
Published: October 2020

AbstractAdequate swab specimen collection, release and detection of nucleic acids by molecular diagnostic assays is largely attributed to the physical and chemical characteristics of different swab types. We investigated properties of three types of commercial nasopharyngeal swabs (nylon flocked: Type 1-Media Merge; Type 2-Kang Jian Medical Apparatus, China and Type 3-Wuxi NEST Biotechnology Co. Ltd, China) used in clinical diagnostics with the aim to establish if different swab designs and configurations had any effect on swab performance. Properties investigated included viral absorption, release, capture, extraction and recovery efficiency from each swab for the detection of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). All swab types (n=18) were inoculated with different amounts of SARS-CoV-2 live viral cultures (1:10, 1:100 and 1:1000 copies/ml) and eluted in sterile phosphate buffer saline. RNA was extracted from all swab eluates using a fully automated system (BD MAX™ System) and cycle threshold (Ct) values were compared. RNA stability was also investigated after dry storage of swabs at room temperature for 72 hours. Statistically significant differences (p<0.05) were observed in the absorption and release capabilities between Type 1 and 3 as well as between Type 2 and 3 swabs, however, no significant difference was observed between Type 1 and 2. Ct values and extraction efficiency amounts of SARS-CoV-2 varied amongst the swab types. We conclude that in order to facilitate accurate SARS-CoV-2 diagnosis, assessment of NP swab characteristics is of importance before implementation for specimen collection in the clinical setting.
Supervised self-collected SARS-CoV-2 testing in indoor summer camps to inform school reopening
Authors: Cooch Peter , Watson Annalisa , Olarte Apryl , Crawford Emily ,   CLIAhub Consortium, DeRisi Joe , Greenhouse Bryan , Hakim Jill , Turcios Keirstinne , Atkinson-McEvoy Lee , Hirsch Raphael , Keller Roberta L. , Ruel Theodore , Cohen-Ross Auritte , Leon Araceli , Bardach Naomi 
Published: October 2020

AbstractBackground and ObjectivesTesting strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in school settings are needed to assess the efficacy of infection mitigation strategies and inform school reopening policies. We hypothesized that supervised serial self-collected non-nasopharyngeal testing in summer camp settings would be acceptable and feasible.MethodsWe performed a cohort study at two urban day camps for kindergarten-8th graders in June and July 2020. Eligible participants were campers, up to two adult household contacts, and camp staff. We assessed participation rates for providing, at two time points, supervised, self-collected anterior nares samples for reverse transcription polymerase chain reaction (RT-PCR) and saliva samples for antibody testing. We qualitatively assessed testing feasibility and adherence to stated camp infection mitigation strategies.Results76% (186/246) of eligible participants consented. The cohort completing both rounds of testing (n=163) comprised 67 campers, 76 household contacts, and 20 staff. Among those present, 100% of campers and staff completed test collection at both time points. Testing was feasible to implement, including staff participation supervising camper test collection. No virus was detected by RT-PCR; seven participants had antibodies. Observed adherence to stated camp mitigation policies for masking, physical distancing, and stable cohorting was generally high.ConclusionsSupervised, self-collected serial anterior nasal and saliva-based SARS-CoV-2 testing was acceptable, with successful repeated participation by children ages 5-14. This strategy for testing and the observed infection mitigation practices comprise potential core components for safe school reopening.
Survey of Attitudes on Personal Protection Interventions Against COVID-19 Including MMR Vaccination and Future Anti-COVID Vaccines
Authors: Schulman Joseph D. , Cooper James N. , Crooks Gary W. 
Published: October 2020

AbstractAn electronic survey was conducted in October, 2020 among individuals primarily age 60 and older regarding their degree of confidence of deriving personal protection from 8 different anti-COVID interventions – social isolation, lockdowns, avoiding restaurants, taking MMR vaccine, wearing masks when indoors with others, avoiding hotels, avoiding commercial air travel, and using the first future specific anti-COVID vaccine. Responses were received from 135 persons from many different U.S. regions and 5 foreign countries. Respondents were generally individuals with very high levels of education and personal achievement. Results demonstrated wide diversity of responses regarding each of these interventions. None were strongly supported by a majority of respondents, but those receiving the largest proportions of strong support were social isolation (41%), wearing masks indoors (41%), and using the first anti-COVID vaccine (41%). MMR (measles-mumps-rubella) vaccination was viewed much more positively than negatively but had the highest proportion of individuals who felt they had insufficient data to formulate an opinion. The largest number of strong negative assessments were toward lockdowns (37%). We speculate that the wide variation in perception of possible benefits from the surveyed interventions, most of which have been widely practiced by or imposed upon millions of individuals, in this highly accomplished older population at increased personal risk from COVID-19 reflects the current absence of rigorous scientific proof of the efficacy of any these interventions, and the continuation of the epidemic despite the widespread utilization of most of them.
Serological surveillance of SARS-CoV-2: Six-month trends and antibody response in a cohort of public health workers
Authors: Harris Ross J , Whitaker Heather J , Andrews Nick J , Aiano Felicity , Amin-Chowdhury Zahin , Flood Jessica , Borrow Ray , Linley Ezra , Ahmad Shazaad , Stapley Lorraine , Hallis Bassam , Amirthalingam Gayatri , Höschler Katja , Parker Ben , Horsley Alex , Brooks Timothy J G , Brown Kevin E , Ramsay Mary E , Ladhani Shamez N 
Published: October 2020

AbstractBackgroundAntibody waning after SARS-CoV-2 infection may result in reduction in long-term immunity following natural infection and vaccination, and is therefore a major public health issue. We undertook prospective serosurveillance in a large cohort of healthy adults from the start of the epidemic in England.MethodsClinical and non-clinical healthcare workers were recruited across three English regions and tested monthly from March to November 2020 for SARS-CoV-2 spike (S) protein and nucleoprotein (N) antibodies using five different immunoassays. In positive individuals, antibody responses and long-term trends were modelled using mixed effects regression.FindingsIn total, 2246 individuals attended 12,247 visits and 264 were seropositive in ≥2 assays. Most seroconversions occurred between March and April 2020. The assays showed >85% agreement for ever-positivity, although this changed markedly over time. Antibodies were detected earlier with Abbott (N) but declined rapidly thereafter. With the EuroImmun (S) and receptor-binding domain (RBD) assays, responses increased for 4 weeks then fell until week 12-16 before stabilising. For Roche (N), responses increased until 8 weeks, stabilised, then declined, but most remained above the positive threshold. For Roche (S), responses continued to climb over the full 24 weeks, with no sero-reversions. Predicted proportions sero-reverting after 52 weeks were 100% for Abbott, 59% (95% credible interval 50-68%) Euroimmun, 41% (30-52%) RBD, 10% (8-14%) Roche (N) <2% Roche (S).InterpretationTrends in SARS-CoV-2 antibodies following infection are highly dependent on the assay used. Ongoing serosurveillance using multiple assays is critical for monitoring the course and long-term progression of SARS-CoV-2 antibodies.
Prediction of the infection of COVID-19 in Bangladesh by classical SIR model
Authors: Parvez Sofi Mahmud , Tabassum Faria , Ali H. M. Shahadat , Hossain Md. Murad 
Published: October 2020

AbstractThe ongoing outbreak of the novel coronavirus (COVID-19) started from Wuhan, China, at the end of December 2019. It is one of the leading public health challenges in the world because of high transmissibility. The first patient of COVID-19 was officially reported on March 8, 2020, in Bangladesh. Using the epidemiological data up to October 17, 2020, we try to estimate the infectious size. In this paper, we used Classical SIR (Susceptible-Infected-Recovered), model. The epidemic has now spread to more than 216 countries around the world. The necessary reproduction number R0 of Bangladesh is 1.92. The primary data was collected from the Coronavirus (COVID-19) Dashboard (BANGLADESH: CASE TREND). In our analysis, the statistical parameters specify the best import to provide the predicted result. We projected that the epidemic curve pulling down in Bangladesh will start from the first week of November (November 4, 2020) and may end in the last week of July (July 24, 2021). It is also estimated that the start of acceleration on May 24, 2020, in 53 days, and the start of steady growth on September 10, 2020, in 109 days. The start of the ending phase of the epidemic may appear in the first week of November 2020, and the epidemic is expected to be finished by the last week of July 2021. However, these approximations may become invalid if a large variety of data occurs in upcoming days.
Ggtree: a serialized data object for visualization of phylogenetic tree and annotation data
Authors: Yu Guangchuang 
Published: October 2020

AbstractGgtree supports mapping and visualizing associated external data on phylogeny with two general methods. The output of ggtree is a ggtree graphic object that can be rendered as a static image. Most importantly, the input tree and associated data that used in visualization can be extracted from the graphic object, making it an ideal data structure for publishing tree (image, tree and data in one single object) and thus enhance data reuse and analytic reproducibility.
Sleep Enhances Neural Representations of True and False Memories: An Event-Related Potential Study
Authors: Jano Sophie , Romeo Julia , Hendrickx Matthew D. , Chatburn Alex 
Published: October 2020

AbstractEpisodic memory is reconstructive and is thus prone to false memory formation. Although false memories are proposed to develop via associative processes, the nature of their neural representations, and the effect of sleep on false memory processing is currently under debate. The present research employed the Deese-Roediger-McDermott (DRM) paradigm and a daytime nap to determine whether semantic false memories and true memories could be differentiated using event-related potentials (ERPs). We also sought to illuminate the role of sleep in memory formation and learning, with the use of a daytime nap. Healthy participants (N= 34, 28F, mean age = 23.23, range = 18-33) completed the DRM task with the learning and recognition phases separated by either a 2hr daytime nap or an equivalent wake period. Linear mixed modelling revealed larger LPC amplitudes for true memories in contrast to false memories, and larger P300 amplitudes for false compared to true memories. Those in the nap group also exhibited larger LPC and P300 amplitudes than participants in the wake group. Additionally, a larger P300 amplitude at delayed recognition (following a consolidation opportunity) was associated with increased true memory accuracy. These findings are argued to be reflective of sleep’s ability to promote pattern separation and pattern completion, with true memories arising from distinct memory traces, and false memories arising from thematic extraction and overlap in neural representations. The present research supports the perspective that both true and false memories are reflective of adaptive memory processes, whilst also suggesting that P300 amplitude affects episodic memory accuracy.
In silicosecretome characterization of clinicalMycobacterium abscessusisolates provides insights into antigenic differences
Authors: Cornejo-Granados Fernanda , Kohl Thomas A. , Sotomayor Flor Vásquez , Andres Sönke , Hernández-Pando Rogelio , Hurtado-Ramírez Juan Manuel , Utpatel Christian , Niemann Stefan , Maurer Florian P. , Ochoa-Leyva Adrian 
Published: October 2020

AbstractMycobacterium abscessus(MAB) is a widely disseminated pathogenic non-tuberculous mycobacterium (NTM). Like withM. tuberculosiscomplex (MTBC), excreted / secreted (ES) proteins play an essential role for its virulence and survival inside the host. ES proteins contain highly immunogenic proteins, which are of interest for novel diagnostic assays and vaccines. Here, we used a robust bioinformatics pipeline to predict the secretome of theM. abscessusATCC 19977 reference strain and fifteen clinical isolates belonging to all three MAB subspecies,M. abscessussubsp.abscessus,M. abscessussubsp.bolletii,andM. abscessussubsp.massiliense.We found that ~18% of the proteins encoded in the MAB genomes were predicted as secreted and that the three MAB subspecies shared > 85 % of the predicted secretomes. MAB isolates with a rough (R) colony morphotype showed larger predicted secretomes than isolates with a smooth (S) morphotype. Additionally, proteins exclusive to the secretomes of MAB R variants had higher antigenic densities than those exclusive to S variants, independently of the subspecies. For all investigated isolates, ES proteins had a significantly higher antigenic density than non-ES proteins. We identified 337 MAB ES proteins with homologues in previously investigatedM. tuberculosissecretomes. Among these, 222 have previous experimental support of secretion, and some proteins showed homology with protein drug targets reported in the DrugBank database. The predicted MAB secretomes showed a higher abundance of proteins related to quorum-sensing and Mce domains as compared to MTBC indicating the importance of these pathways for MAB pathogenicity and virulence. Comparison of the predicted secretome ofM. abscessusATCC 19977 with the list of essential genes revealed that 99 secreted proteins corresponded to essential proteins required forin vitrogrowth. All predicted secretomes were deposited in the Secret-AAR web-server (http://microbiomics.ibt.unam.mx/tools/aar/index.php).
Resting-state Co-activation Patterns as Accurate Predictors of Alzheimer’s Disease in Aged Mice
Authors: Adhikari Mohit H. , Belloy Michaël E. , Van der Linden Annemie , Keliris Georgios A. , Verhoye Marleen 
Published: October 2020

AbstractAlzheimer’s disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-beta (Aβ) plaques leads to progressive loss of memory and cognitive function. Resting state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task positive resting state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed resting state networks (RSNs) and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and 8 wild type littermates at 18 months of age. Subsequently we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly activated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate for a diagnostic, and potentially, prognostic biomarker of Alzheimer’s disease.
Transport of Alzheimer’s Associated Amyloid-β Catalyzed by P-glycoprotein
Authors: McCormick James W. , Ammerman Lauren , Chen (党陈) Gang , Vogel Pia D. , Wise John G. 
Published: October 2020

ABSTRACTP-glycoprotein (P-gp) is a critical membrane transporter in the blood brain barrier (BBB) and is implicated in Alzheimer’s disease (AD). However, previous studies on the ability of P-gp to directly transport the Alzheimer’s associated amyloid-β (Aβ) protein have produced contradictory results. Here we use molecular dynamics (MD) simulations, transport substrate accumulation studies in cell culture, and biochemical activity assays to show that P-gp actively transports Aβ. We observed transport of Aβ40 and Aβ42 monomers by P-gp in explicit MD simulations of a putative catalytic cycle. Inin vitroassays with P-gp overexpressing cells, we observed enhanced accumulation of fluorescently labeled Aβ42 in the presence of Tariquidar, a potent P-gp inhibitor. We also showed that Aβ42 stimulated the ATP hydrolysis activity of isolated P-gp in nanodiscs. Our findings expand the substrate profile of P-gp, and suggest that P-gp may contribute to the onset and progression of AD.
A new method to accurately identify single nucleotide variants using small FFPE breast samples
Authors: Fortunato Angelo , Mallo Diego , Rupp Shawn M. , King Lorraine M. , Hardman Timothy , Lo Joseph Y. , Hall Allison , Marks Jeffrey R. , Hwang E. Shelley , Maley Carlo C. 
Published: October 2020

AbstractMost tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however, it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing algorithms. We found that the SNV-identification accuracy declined when there was less than 40ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ (DCIS) of the breast to their adjacent invasive ductal carcinoma (IDC) samples. We observed an increased number of mutations (paired-samples sign test, p<0.05), and a higher genetic divergence in the invasive samples (paired-samples sign test, p<0.01). Our algorithm provides a significant improvement in detecting SNVs in FFPE samples over previous approaches.Key PointsThe sequencing of reduced quantities of DNA extracted from FFPE samples leads to substantial sequencing errors that require correction in order to obtain accurate detection of somatic mutations.We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants using small amounts of DNA extracted from archival FFPE samples of breast cancers.Variant calling software packages need to be optimized to reduce the impact of sequencing errors. Our bioinformatics pipeline represents a significant methodological advance compared to the currently available bioinformatic tools used for the analysis of small FFPE samples.
Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data
Authors: Qin Tingting , Lee Christopher , Cavalcante Raymond , Orchard Peter , Yao Heming , Zhang Hanrui , Wang Shuze , Patil Snehal , Boyle Alan P , Sartor Maureen A 
Published: October 2020

AbstractRevealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial andin silicoapproaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1,860 human genome-wide distalEnhancer toTarget geneDefinitions (EnTDefs). To evaluate performance, we used gene set enrichment testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology (GO) annotations., assuming that greater concordance with TF-GO annotation signifies better enrichment results and thus more accurate enhancer-to-gene assignments. Notably, the top ranked 741 (40%) EnTDefs significantly outperformed the common, naïve approach of linking distal regions to the nearest genes (FDR < 0.05), and the top 10 ranked EnTDefs performed well when applied to ChIP-seq data of other cell types. These general EnTDefs also showed comparable performance to EnTDefs generated using cell-type-specific data. Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.