bluuebunny/crossref_metadata_2025_split huggingface dataset:
Direct Quantification of in vivo Mutagenesis and Carcinogenesis Using Duplex Sequencing
Authors: Valentine Charles C. , Young Robert R. , Fielden Mark R. , Kulkarni Rohan , Williams Lindsey N. , Li Tan , Minocherhomji Sheroy , Salk Jesse J. 
Published: June 2020

ABSTRACTThe ability to accurately measure mutations is critical for basic research and identification of potential drug and chemical carcinogens. Current methods for in vivo quantification of mutagenesis are limited because they rely on transgenic rodent systems that are low-throughput, expensive, prolonged, and don’t fully represent other species such as humans. Next generation sequencing (NGS) is a conceptually attractive alternative for mutation detection in the DNA of any organism, however, the limit of resolution for standard NGS is poor. Technical error rates (~1×10−3) of NGS obscure the true abundance of somatic mutations, which can exist at pernucleotide frequencies ≤1×10−7. Using Duplex Sequencing, an extremely accurate error-corrected NGS (ecNGS) technology, we were able to detect mutations induced by 3 carcinogens in 5 tissues of 2 strains of mice within 31 days following exposure. We observed a strong correlation between mutation induction measured by Duplex Sequencing and the gold-standard transgenic rodent mutation assay. We identified exposure-specific mutation spectra of each compound through trinucleotide patterns of base substitution. We observed variation in mutation susceptibility by genomic region, as well as by DNA strand. We also identified the primordial signs of carcinogenesis in a cancer-predisposed strain of mice, as evidenced by clonal expansions of cells carrying an activated oncogene, less than a month after carcinogen exposure. These findings demonstrate that ecNGS is a powerful method for sensitively detecting and characterizing mutagenesis and the early clonal evolutionary hallmarks of carcinogenesis. Duplex Sequencing can be broadly applied to chemical safety testing, basic mutational research, and related clinical uses.SIGNIFICANCE STATEMENTError-corrected next generation sequencing (ecNGS) can be used to rapidly detect and quantify the in vivo mutagenic impact of environmental exposures or endogenous processes in any tissue, from any species, at any genomic location. The greater speed, higher scalability, richer data outputs, as well as cross-species and cross-locus applicability of ecNGS compared to existing methods make it a powerful new tool for mutational research, regulatory safety testing, and emerging clinical applications.
SARS-CoV-2 serological testing using electrochemiluminescence reveals a rapid onset of seroconversion in severe COVID-19 patients
Authors: Munitz A , Edry-Botzer L , Itan M , Tur-Kaspa R , Dicker D , Markovitch D , Goren M , Mor M , Lev S , Gottesman T , Muhsen K , Cohen D , Stein M , Qimron U , Freund N , Wine Y , Gerlic M 
Published: June 2020

AbstractDespite ongoing efforts to characterize the host response toward SARS-CoV-2, a major gap in our knowledge still exists regarding the magnitude and duration of the humoral response. We report the development of a rapid, highly specific and sensitive electrochemiluminescent assay for detecting IgM, IgA, and IgG antibodies toward two distinct SARS-CoV-2 antigens namely, the receptor binding domain (RBD) and the nuclear protein (NP). Whereas IgM antibodies toward RBD were detected at early stages of the disease, IgM antibodies against NP did not develop. Analysis of the antibody response in mild versus moderate/severe patients revealed a rapid onset of IgG and IgA antibodies, specifically in moderate/severe patients. Finally, we observed a marked reduction in IgM/IgA antibodies and to lesser extent, IgG, over time. We provide a comprehensive analysis of the human antibody response, and has major implications on our understanding and monitoring of SARS-CoV-2 infections, as well as finding effective vaccines.One Sentence SummaryUsing a newly developed assay to detect anti-SARS-Cov-2 IgM, IgG and IgA antibodies we reveal a rapid onset of IgG and IgA antibodies towards distinct viral antigens, specifically in moderate/severe COVID-19 patients,
Data presented by the UK government as lockdown was eased shows the transmission of COVID-19 had already increased
Authors: Lonergan Mike 
Published: June 2020

AbstractBackgroundCoronavirus disease 2019 (COVID-19) is an international emergency that has been addressed in many countries by changes in and restrictions on behaviour. These are often collectively labelled social distancing and lockdown. On the 23rd June 2020, Boris Johnson, the Prime Minister of the United Kingdom announced substantial easings of restrictions. This paper examines some of the data he presented.MethodsGeneralised additive models, with negative binomial errors and cyclic term representing day-of-week effects, were fitted to data on the daily numbers of new confirmed cases of COVID-19. Exponential rates for the epidemic were estimated for different periods, and then used to calculate R, the reproduction number, for the disease in different periods.ResultsAfter an initial stabilisation, the lockdown reduced R to around 0.81 (95% CI: 0.79, 0.82). This value increased to around 0.94 (95% CI 0.89, 0.996) for the fortnight from the 9th June 2020.ConclusionsOfficial UK data, presented as the easing of the lockdown was announced, shows that R was already more than half way back to 1 at that point. That suggests there was little scope for the announced changes to be implemented without restarting the spread of the disease.
Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks
Authors: Blischak Paul D. , Barker Michael S. , Gutenkunst Ryan N. 
Published: June 2020

AbstractInferring the frequency and mode of hybridization among closely related organisms is an important step for understanding the process of speciation and can help to uncover reticulated patterns of phylogeny more generally. Phylogenomic methods to test for the presence of hybridization come in many varieties and typically operate by leveraging expected patterns of genealogical discordance in the absence of hybridization. An important assumption made by these tests is that the data (genes or SNPs) are independent given the species tree. However, when the data are closely linked, it is especially important to consider their non-independence. Recently, deep learning techniques such as convolutional neural networks (CNNs) have been used to perform population genetic inferences with linked SNPs coded as binary images. Here we use CNNs for selecting among candidate hybridization scenarios using the tree topology (((P1,P2),P3),Out) and a matrix of pairwise nucleotide divergence (dXY) calculated in windows across the genome. Using coalescent simulations to train and independently test a neural network showed that our method, HyDe-CNN, was able to accurately perform model selection for hybridization scenarios across a wide-breath of parameter space. We then used HyDe-CNN to test models of admixture inHeliconiusbutterflies, as well as comparing it to a random forest classifier trained on introgression-based statistics. Given the flexibility of our approach, the dropping cost of long-read sequencing, and the continued improvement of CNN architectures, we anticipate that inferences of hybridization using deep learning methods like ours will help researchers to better understand patterns of admixture in their study organisms.
Functional and structural basis of extreme non-coding conservation in vertebrate 5’UTRs
Authors: Byeon Gun Woo , Cenik Elif Sarinay , Jiang Lihua , Tang Hua , Das Rhiju , Barna Maria 
Published: June 2020

AbstractThe lack of knowledge about extreme conservation in genomes remains a major gap in our understanding of the evolution of gene regulation. While previous findings have mainly focused on the role of extreme conservation at the level of DNA in transcriptional regulation, its implications for RNA biology remains largely unexplored. Here, we reveal an unexpected role of extremely conserved 5’UTRs in translational regulation that is linked to the emergence of essential developmental features in vertebrate species. Endogenous deletion of conserved elements within these 5’UTRs decreased gene expression at the post-transcriptional level. A large-scale reporter library of extremely conserved 5’UTRs revealed the widespread presence of cis-regulatory elements that promote cell-type specific regulation of translation. As these elements function as RNA molecules, further understanding of their potential structures was essential. We therefore developed in-cell mutate-and-map (icM2), a novel methodology that maps RNA structure using high-throughput mutational analysis, previously impossible to perform inside cells. Using icM2, we determined that an extremely conserved 5’UTR encodes multiple alternative structures whose relative proportions are actively maintained by ATP-dependent RNA helicases. We further show that each single nucleotide within the extremely conserved element maintains the balance of alternative structures important to control the dynamic range of protein expression. These results explain how extreme sequence conservation can lead to RNA-level biological functions encoded in the untranslated regions of vertebrate genomes.
Functional solubilisation of the β2-adrenoceptor (β2AR) using Diisobutylene maleic acid (DIBMA)
Authors: Harwood C. R. , Sykes D. A. , Hoare B. , Heydenreich F. M. , Uddin R. , Poyner D. R. , Briddon S. J. , Veprintsev D. B. 
Published: June 2020

AbstractThe β2-adrenoceptor (β2AR) is a well-established target in asthma and a prototypical GPCR for biophysical studies. Solubilisation of membrane proteins has classically involved the use of detergents. However, the detergent environment differs from the native membrane environment and often destabilises membrane proteins. Use of amphiphilic copolymers is a promising strategy to solubilise membrane proteins within their native lipid environment in the complete absence of detergents. Here we show the isolation of the β2AR in the polymer Diisobutylene maleic acid (DIBMA). We demonstrate that β2AR remains functional in the DIBMA lipid particle (DIBMALP) and shows improved thermal stability compared to the n-Dodecyl-β-D-Maltopyranoside (DDM) detergent solubilised β2AR. This unique method of extracting β2AR offers significant advantages over previous methods routinely employed such as the introduction of thermostabilising mutations and the use of detergents, particularly for functional biophysical studies.
Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19
Authors: Sekine Takuya , Perez-Potti André , Rivera-Ballesteros Olga , Strålin Kristoffer , Gorin Jean-Baptiste , Olsson Annika , Llewellyn-Lacey Sian , Kamal Habiba , Bogdanovic Gordana , Muschiol Sandra , Wullimann David J. , Kammann Tobias , Emgård Johanna , Parrot Tiphaine , Folkesson Elin , Rooyackers Olav , Eriksson Lars I. , Sönnerborg Anders , Allander Tobias , Albert Jan , Nielsen Morten , Klingström Jonas , Gredmark-Russ Sara , Björkström Niklas K. , Sandberg Johan K. , Price David A. , Ljunggren Hans-Gustaf , Aleman Soo , Buggert Marcus ,   Karolinska COVID-19 Study Group
Published: June 2020

ABSTRACTSARS-CoV-2-specific memory T cells will likely prove critical for long-term immune protection against COVID-19. We systematically mapped the functional and phenotypic landscape of SARS-CoV-2-specific T cell responses in a large cohort of unexposed individuals as well as exposed family members and individuals with acute or convalescent COVID-19. Acute phase SARS-CoV-2-specific T cells displayed a highly activated cytotoxic phenotype that correlated with various clinical markers of disease severity, whereas convalescent phase SARS-CoV-2-specific T cells were polyfunctional and displayed a stem-like memory phenotype. Importantly, SARS-CoV-2-specific T cells were detectable in antibody-seronegative family members and individuals with a history of asymptomatic or mild COVID-19. Our collective dataset shows that SARS-CoV-2 elicits robust memory T cell responses akin to those observed in the context of successful vaccines, suggesting that natural exposure or infection may prevent recurrent episodes of severe COVID-19 also in seronegative individuals.
Zonal human hepatocytes are differentially permissive toPlasmodium falciparummalaria parasites
Authors: Yang Annie S.P. , van Waardenburg Youri M. , van de Vegte-Bolmer Marga , van Gemert Geert-Jan A. , Graumans Wouter , de Wilt Johannes H.W. , Sauerwein Robert W. 
Published: June 2020

AbstractPlasmodium falciparum (Pf)is a major cause of malaria. The mosquito-borne parasite asymptomatically infects hepatocytes in the liver. The resulting schizonts undergo massive replication to generate blood-infective merozoites. Liver lobules are zonated: hepatocytes in different zones perform differential metabolic functions. In search for specific host conditions that affect infectability, we studied thePfparasite liver stage development in relation to the metabolic heterogeneity of fresh human hepatocytes. We show selective preference of differentPfstrains for a minority of zone 3 hepatocytes characterized by the particular presence of glutamine synthetase (hGS). Parasite schizont growth is significantly enhanced by hGS uptake early in development, which showcases an import system at this stage of the parasite life-cycle. In conclusion,Pfdevelopment is strongly determined by the differential metabolic status in hepatocyte subtypes. These findings underscore the importance of detailed understanding of hepatocyte host-Pfinteractions and may delineate novel pathways for intervention strategies.
The Filter Detection Task for measurement of breathing-related interoception and metacognition
Authors: Harrison Olivia K. , Garfinkel Sarah N. , Marlow Lucy , Finnegan Sarah , Marino Stephanie , Nanz Laura , Allen Micah , Finnemann Johanna , Keur-Huizinga Laura , Harrison Samuel J. , Stephan Klaas E. , Pattinson Kyle T. S. , Fleming Stephen M. 
Published: June 2020

AbstractThe study of the brain’s processing of sensory inputs from within the body (‘interoception’) has been gaining rapid popularity in neuroscience, where interoceptive disturbances are thought to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity (accuracy), decision bias, metacognitive bias, and metacognitive performance. Two major developments address some of the challenges presented by low trial numbers in interoceptive experiments: (i) a novel adaptive algorithm to maintain task performance at 70-75% accuracy; (ii) an extended hierarchical metacognitive model to estimate regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of the task and analysis developments, using both simulated data and three empirical datasets. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with clinical settings.
Agent-Based Modeling of T Cell Receptor Cooperativity
Authors: Siokis Anastasios , Robert Philippe A. , Meyer-Hermann Michael 
Published: June 2020

AbstractImmunological synapse (IS) formation is a key event during antigen recognition by T cells. Recent experimental evidence suggests that the affinity between T cell receptors (TCRs) and antigen is actively modulated during the early steps of TCR signaling. In this work, we used an agent-based model to study possible mechanisms for affinity modulation during IS formation. We show that, without any specific active mechanism, the observed affinity between receptors and ligands evolves over time, and depends on the density of ligand pMHC (antigen peptide presented by major histocompatibility complexes) and TCR molecules. Comparison between the presence or absence of TCR-pMHC centrally directed flow due to F-actin coupling suggest centripetal transport is a potential mechanism for the affinity modulation. The model further suggests that the time point of affinity measurement during immune synapse formation is critical. Finally, a mathematical model of F-actin foci formation incorporated in the agent-based model, shows that TCR affinity can potentially be actively modulated by a positive/negative feedback of F-actin foci on the TCR-pMHC association ratekon.
Unbiased metabolic flux inference through combined thermodynamic and13C flux analysis
Authors: Saldida Joana , Muntoni Anna Paola , de Martino Daniele , Hubmann Georg , Niebel Bastian , Schmidt A. Mareike , Braunstein Alfredo , Milias-Argeitis Andreas , Heinemann Matthias 
Published: June 2020

ABSTRACTQuantification of cellular metabolic fluxes, for instance with13C-metabolic flux analysis, is highly important for applied and fundamental metabolic research. A current challenge in13C-flux analysis is that the available experimental data are usually insufficient to resolve metabolic fluxes in large metabolic networks without making assumptions on flux directions and reversibility. To infer metabolic fluxes in a more unbiased manner, we devised an approach that does not require such assumptions. The developed three-step approach integrates thermodynamics, metabolome, physiological data, and13C labelling data, and involves a novel method to comprehensively sample the complex thermodynamically-constrained metabolic flux space. Applying our approach to budding yeast with its compartmentalised metabolism and parallel pathways, we could resolve metabolic fluxes in an unbiased manner, we obtained an uncertainty estimate for each flux, and we found novel flux patterns that until now had remained unknown, likely due to assumptions made in previous13C flux analysis studies. We expect that our approach will be an important step forward to determine metabolic fluxes with improved accuracy in microorganisms and possibly also in more complex organisms.
Metal contamination and oxidative stress biomarkers in estuarine fish following a mine tailing disaster
Authors: Gabriel Fabrício Ângelo , Hauser-Davis Rachel Ann , Soares Lorena Oliveira Souza , de Azevedo Mazzuco Ana Carolina , Rocha Rafael Christian Chávez , Saint’Pierre Tatiana Dillenburg , Saggioro Enrico Mendes , Correia Fábio Veríssimo , Ferreira Tiago Osório , Bernardino Angelo Fraga 
Published: June 2020

AbstractThe Rio Doce estuary in Brazil was impacted by the deposition of mine tailings caused by the collapse of a mining dam in 2015. Since the disaster, the estuary is experiencing chronic trace metal contamination effects, but potential trace metal accumulation in fishes has not been reported. Trace metals in aquatic ecosystems pose severe threats to the aquatic biota, so we hypothesized that the accumulation of trace metals in estuarine sediments nearly two years after the disaster would cause contaminant bioaccumulation, resulting in the biosynthesis of metal-responsive proteins in fishes. We determined trace metal concentrations in sediment samples, metal concentrations, and quantified stress protein concentrations in the liver and muscle tissue of five different fish species in the estuary. Our results revealed high concentrations of trace metals in estuarine sediments when compared to published baseline values for this estuary. The demersal fish speciesCathorops spixiiandGenidens genidenshad the highest Hg, As, Se, Cr, and Mn concentrations in both hepatic and muscle tissues. Metal bioaccumulation in fish was statistically correlated with the biosynthesis of metallothionein and reduced glutathione in both fish liver and muscle tissue. The trace metals detected in fish tissues resemble those in the contaminated sediments present at the estuary at the time of this study and were also significantly correlated to protein levels. Trace metals in fish muscle were above the maximum permissible limits for human consumption, suggesting potential human health risks that require further determination. Our study supports the high biogeochemical mobility of trace metals between contaminated sediments and local biota in estuarine ecosystems.
Frame-by-frame annotation of video recordings using deep neural networks
Authors: Conway Alexander M. , Durbach Ian N. , McInnes Alistair , Harris Robert N. 
Published: June 2020

AbstractVideo data are widely collected in ecological studies but manual annotation is a challenging and time-consuming task, and has become a bottleneck for scientific research. Classification models based on convolutional neural networks (CNNs) have proved successful in annotating images, but few applications have extended these to video classification. We demonstrate an approach that combines a standard CNN summarizing each video frame with a recurrent neural network (RNN) that models the temporal component of video. The approach is illustrated using two datasets: one collected by static video cameras detecting seal activity inside coastal salmon nets, and another collected by animal-borne cameras deployed on African penguins, used to classify behaviour. The combined RNN-CNN led to a relative improvement in test set classification accuracy over an image-only model of 25% for penguins (80% to 85%), and substantially improved classification precision or recall for four of six behaviour classes (12–17%). Image-only and video models classified seal activity with equally high accuracy (90%). Temporal patterns related to movement provide valuable information about animal behaviour, and classifiers benefit from including these explicitly. We recommend the inclusion of temporal information whenever manual inspection suggests that movement is predictive of class membership.