bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variant analysis of SARS-CoV-2 genomes in the Middle East
Authors: Bindayna Khalid Mubarak , Crinion Shane 
Published: October 2020

AbstractBackgroundCoronavirus (COVID-19) was introduced into society in late 2019 and has now reached over 26 million cases and 850,000 deaths. The Middle East has a death toll of ∼50,000 and over 20,000 of these are in Iran, which has over 350,000 confirmed cases. We expect that Iranian cases caused outbreaks in the neighbouring countries and that variant mapping and phylogenetic analysis can be used to prove this. We also aim to analyse the variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) to characterise the common genome variants and provide useful data in the global effort to prevent further spread of COVID-19.MethodsThe approach uses bioinformatics approaches including multiple sequence alignment, variant calling and annotation and phylogenetic analysis to identify the genomic variants found in the region. The approach uses 122 samples from the 13 countries of the Middle East sourced from the Global Initiative on Sharing All Influenza Data (GISAID).FindingsWe identified 2200 distinct genome variants including 129 downstream gene variants, 298 frame shift variants, 789 missense variants, 1 start lost, 13 start gained, 1 stop lost, 249 synonymous variants and 720 upstream gene variants. The most common, high impact variants were 10818delTinsG, 2772delCinsC, 14159delCinsC and 2789delAinsA. Variant alignment and phylogenetic tree generation indicates that samples from Iran likely introduced COVID-19 to the rest of the Middle East.InterpretationThe phylogenetic and variant analysis provides unique insight into mutation types in genomes. Initial introduction of COVID-19 was most likely due to Iranian transmission. Some countries show evidence of novel mutations and unique strains. Increased time in small populations is likely to contribute to more unique genomes. This study provides more in depth analysis of the variants affecting in the region than any other study.FundingNone
Bacterial precursors and unsaturated long-chain fatty acids are biomarkers of North-Atlantic demosponges
Authors: de Kluijver Anna , Nierop Klaas G.J. , Morganti Teresa M. , Bart Martijn C. , Slaby Beate M. , Hanz Ulrike , de Goeij Jasper M. , Mienis Furu , Middelburg Jack J. 
Published: October 2020

AbstractSponges produce distinct fatty acids (FAs) that (potentially) can be used as chemotaxonomic and ecological biomarkers to study endosymbiont-host interactions and the functional ecology of sponges. Here, we present FA profiles of five common habitat-building deep-sea sponges (class Demospongiae, order Tetractinellida), which are classified as high microbial abundance (HMA) species.Geodia hentscheli, G. parva, G. atlantica, G. barretti, andStelletta rhaphidiophorawere collected from boreal and Arctic sponge grounds in the North-Atlantic Ocean. Bacterial FAs dominated in all five species and particularly isomeric mixtures of mid-chain branched FAs (MBFAs, 8- and 9-Me-C16:0and 10 and 11-Me-C18:0) were found in high abundance (together ≥ 20% of total FAs) aside more common bacterial markers. In addition, the sponges produced long-chain linear, mid- anda(i)-branched unsaturated FAs (LCFAs) with a chain length of 24‒28 C atoms and had predominantly the typical Δ5,9unsaturation, although also Δ9,19and (yet undescribed) Δ11,21unsaturations were identified.G. parvaandS. rhaphidiophoraeach produced distinct LCFAs, whileG. atlantica, G. barretti, andG. hentscheliproduced similar LCFAs, but in different ratios. The different bacterial precursors varied in carbon isotopic composition (δ13C), with MBFAs being more enriched compared to other bacterial (linear anda(i)-branched) FAs. We propose biosynthetic pathways for different LCFAs from their bacterial precursors, that are consistent with small isotopic differences found in LCFAs. Indeed, FA profiles of deep-sea sponges can serve as chemotaxonomic markers and support the conception that sponges acquire building blocks from their endosymbiotic bacteria.
SARS-CoV-2 infection induces mixed M1/M2 phenotype in circulating monocytes and alterations in both dendritic cell and monocyte subsets
Authors: Sanja Matic , Suzana Popovic , Predrag Djurdjevic , Danijela Todorovic , Natasa Djordjevic , Zeljko Mijailovic , Predrag Sazdanovic , Dragan Milovanovic , Dejana Ruzic Zecevic , Marina Petrovic , Maja Sazdanovic , Nenad Zornic , Vladimir Vukicevic , Ivana Petrovic , Snezana Matic , Marina Karic Vukicevic , Dejan Baskic 
Published: October 2020

AbstractClinical manifestations of SARS-CoV-2 infection range from mild to critically severe. The aim of the study was to highlight the immunological events associated with the severity of SARS-CoV-2 infection, with an emphasis on cells of innate immunity. Thirty COVID-19 patients with mild/moderate symptoms and 27 patients with severe/critically severe symptoms were recruited from the Clinical Center of Kragujevac during April 2020. Flow cytometric analysis was performed to reveal phenotypic and functional alterations of peripheral blood cells and to correlate them with the severity of the disease. In severe cases, the number of T and B lymphocytes, dendritic cells, NK cells, and HLA-DR-expressing cells was drastically decreased. In the monocyte population proportion between certain subsets was disturbed and cells coexpressing markers of M1 and M2 monocytes were found in intermediate and non-classical subsets. In mild cases decline in lymphocyte number was less pronounced and innate immunity was preserved as indicated by an increased number of myeloid and activated dendritic cells, NK cells that expressed activation marker at the same level as in control and by low expression of M2 marker in monocyte population. In patients with severe disease, both innate and adoptive immunity are devastated, while in patients with mild symptoms decline in lymphocyte number is lesser, and the innate immunity is preserved.
In-stream habitat availability for river dolphins in response to flow: use of ecological integrity to manage river flows
Authors: Paudel Shambhu , Koprowski John L. , Thakuri Usha 
Published: October 2020

AbstractPopulation decline and extinction risk of riverine cetaceans are primarily associated with flow alteration. Previous studies predominantly highlighted maintenance of adequate flow for low water seasons when habitats contract and the risk of local extinction escalates. Although riverine cetaceans are sensitive to reduction in river flow, no studies quantify the relationships between flow and ecology of riverine cetaceans to mitigate the potential adverse impacts of flow alteration. We quantify the relationships between flow and the ecology of river cetaceans with reference to Ganges River dolphins (GRD;Platanista gangetica gangetica) usable area availability (AWS) for the low water season at wider flows (50-575 m3/s) at finer spatial and temporal scales. This study reveals that distribution of usable area to GRD highly regulated by the adequate flow level as the interaction of appropriate velocity and depth at particular geomorphic that likely offer energetically efficient modes of locomotion to increase surfacing behavior efficiency, suggesting the hydro-physical environment as a major determinant of river cetaceans distribution and abundance. Flow and AWS relationships indicate that the flow during dry season negatively contributed to AWS, whereas that of pre-monsoon maximized the AWS, suggesting that modifying flow regimes does alter in-stream habitats at varying spatial scales and may influence life-history strategies. Substantial fragmentation in suitable pool availability and loss of longitudinal connectivity exhibited by dry season flow suggested a higher risk of adverse biological effects during the dry season, which may reduce population viability by reducing survivorship and reproduction failure. Owing to riverine cetaceans’ dependence on the attribute of freshwater flow, they can be expected to be more affected by flow regulations as interactive effects. Considering the seasonal effects and changes in the availability of usable areas by flow alteration, adopting effective habitat retention plans by water-based development projects appears critical to avoid further ecological risks in aquatic species conservation. Identifying priority riverscapes for river cetaceans and prioritizing investment opportunities is an essential first step towards effective riverine cetacean conservation.
Forecasting COVID-19 cases at the Amazon region: a comparison of classical and machine learning models
Authors: de Souza Dalton Garcia Borges , Alves Júnior Francisco Tarcísio , Soma Nei Yoshihiro 
Published: October 2020

AbstractBACKGROUNDSince the first reports of COVID-19, decision-makers have been using traditional epidemiological models to predict the days to come. However, the enhancement of computational power, the demand for adaptable predictive frameworks, the short past of the disease, and uncertainties related to input data and prediction rules, also make other classical and machine learning techniques viable options.OBJECTIVEThis study investigates the efficiency of six models in forecasting COVID-19 confirmed cases with 17 days ahead. We compare the models autoregressive integrated moving average (ARIMA), Holt-Winters, support vector regression (SVR), k-nearest neighbors regressor (KNN), random trees regressor (RTR), seasonal linear regression with change-points (Prophet), and simple logistic regression (SLR).MATERIAL AND METHODSWe implement the models to data provided by the health surveillance secretary of Amapáa, a Brazilian state fully carved in the Amazon rainforest, which has been experiencing high infection rates. We evaluate the models according to their capacity to forecast in different historical scenarios of the COVID-19 progression, such as exponential increases, sudden decreases, and stability periods of daily cases. To do so, we use a rolling forward splitting approach for out-of-sample validation. We employ the metrics RMSE, R-squared, and sMAPE in evaluating the model in different cross-validation sections.FINDINGSAll models outperform SLG, especially Holt-Winters, that performs satisfactorily in all scenarios. SVR and ARIMA have better performances in isolated scenarios. To implement the comparisons, we have created a web application, which is available online.CONCLUSIONThis work represents an effort to assist the decision-makers of Amapá in future decisions to come, especially under scenarios of sudden variations in the number of confirmed cases of Amapá, which would be caused, for instance, by new contamination waves or vaccination. It is also an attempt to highlight alternative models that could be used in future epidemics.
Activation of MAP3K DLK and LZK in Purkinje Cells Causes Rapid and Slow Degeneration Depending on Signaling Strength
Authors: Li Yunbo , Ritchie Erin M , Steinke Christopher L. , Qi Cai , Chen Lizhen , Zheng Binhai , Jin Yishi 
Published: October 2020

SummaryThe conserved MAP3K Dual leucine zipper kinases can activate JNK via MKK4 or MKK7. Vertebrate DLK and LZK share similar biochemical activities and undergo auto-activation upon increased expression. Depending on cell-type and nature of insults DLK and LZK can induce pro-regenerative, pro-apoptotic or pro-degenerative responses, although the mechanistic basis of their action is not well understood. Here, we investigated these two MAP3Ks in cerebellar Purkinje cells using loss- and gain-of function mouse models. While loss of each or both kinases does not cause discernible defects in Purkinje cells, activating DLK causes rapid death and activating LZK leads to slow degeneration. Each kinase induces JNK activation and caspase-mediated apoptosis independent of each other. Significantly, deleting CELF2, which regulates alternative splicing ofMkk7, strongly attenuates Purkinje cell degeneration induced by activation of LZK, but not DLK. Thus, controlling the activity levels of DLK and LZK is critical for neuronal survival and health.
Integrated multivariate analysis of transcriptomic data reveals immunological mechanisms in mice afterLeishmania infantuminfection
Authors: Palacios Génesis , Diaz-Solano Raquel , Valladares Basilio , Dorta-Guerra Roberto , Carmelo Emma 
Published: October 2020

ABSTRACTTranscriptional analysis of complex biological scenarios has been extensively used, even though sometimes results may prove imprecise or difficult-to interpret due to an overwhelming amount of information. In this study, a large-scale Real-time qPCR experiment was coupled to multivariate statistical analysis to describe the main immunological events underlying the earlyL. infantuminfection in livers of BALB/c mice. High-throughput qPCR was used to evaluate the expression of 223 genes related to immunometabolism 1-, 3-, 5- and 10-days post infection. This integrative analysis showed strikingly different gene signatures at 1- and 10-days post infection, revealing progression of infection in the experimental model based on the upregulation of particular immunological response patterns and mediators. This approach addresses the challenge of integrating large collections of transcriptional data for the identification of candidate biomarkers in experimental models.
RBMX enables productive RNA processing of ultra-long exons important for genome stability
Authors: Luzzi Sara , Hysenaj Gerald , Siachisumo Chileleko , Cheung Kathleen , Gazzara Matthew , James Katherine , Dalgliesh Caroline , Chadegani Mahsa Kheirollahi , Ehrmann Ingrid , Smith Graham R , Cockell Simon J , Munkley Jennifer , Barash Yoseph , Elliott David J 
Published: October 2020

AbstractPreviously we showed that the germline-specific RNA binding protein RBMXL2 is essential for male meiosis where it represses cryptic splicing patterns (1). Here we find that its ubiquitously expressed paralog RBMX helps underpin human genome stability by preventing non-productive splicing. In particular, RBMX blocks selection of aberrant splice and polyadenylation sites within some ultra-long exons that would interfere with genes needed for normal replication fork activity. Target exons include within theETAA1(Ewings Tumour Associated 1) gene, where RBMX collaborates with its interaction partner Tra2β to enable full-length exon inclusion by blocking selection of an aberrant 3’ splice site. Our data reveal a novel group of RNA processing targets potently repressed by RBMX, and help explain why RBMX is associated with gene expression networks in cancer, replication and sensitivity to genotoxic drugs.
The influence of intergenerational transfer of white matter tracts on early reading development
Authors: Vandermosten Maaike , Schevenels Klara , Economou Maria , Hoeft Fumiko 
Published: October 2020

AbstractParents have large genetic and environmental influences on their children’s cognition, behavior, and brain. Previous studies have indicated intergenerational transfer of the behavior of reading. Despite a close coupling between brain and behavior however, the intergenerational transfer of reading-related structural brain networks have not been investigated. Therefore, we investigated its parent-child associations for the first time. We examined how white matter tracts i.e., Arcuate Fasciculus (AF) and Inferior Fronto-Occipital Fasciculus (IFOF), are associated with children’s early reading development from Kindergarten to Grade 3 in 33 families. First, we observed in our sample of children -who all had typical reading skills despite half of them having an increased risk for dyslexia- that fractional anisotropy in bilateral IFOF and right AF correlated with reading development. Second, parent-child correlations were observed for bilateral IFOF but not for AF. Finally, we demonstrated that the relation between children’s IFOF and reading development was largely explained by parental IFOF. The findings preliminarily suggest that white matter organization in IFOF represents a pre-existing protective factor in children at risk, as it is mainly determined by biological parental factors. Large-scale intergenerational, multi-level and longitudinal studies are needed to understand the dynamic interrelations between brain, environment and behavior.
Synaptic counts approximate synaptic contact area in Drosophila
Authors: Barnes Christopher L. , Bonnéry Daniel , Cardona Albert 
Published: October 2020

AbstractThe pattern of synaptic connections among neurons defines the circuit structure, which constrains the computations that a circuit can perform. The strength of synaptic connections is costly to measure yet important for accurate circuit modeling. It has been shown that synaptic surface area correlates with synaptic strength, yet in the emerging field of connectomics, most studies rely instead on the counts of synaptic contacts between two neurons. Here we quantified the relationship between synaptic count and synaptic area as measured from volume electron microscopy of the larval Drosophila central nervous system. We found that the total synaptic surface area, summed across all synaptic contacts from one presynaptic neuron to a postsynaptic one, can be accurately predicted solely from the number of synaptic contacts, for a variety of neurotransmitters. Our findings support the use of synaptic counts for approximating synaptic strength when modeling neural circuits.
Distinct roles of nonmuscle myosin II isoforms for establishing tension and elasticity during cell morphodynamics
Authors: Weißenbruch Kai , Grewe Justin , Hippler Marc , Fladung Magdalena , Tremmel Moritz , Stricker Kathrin , Schwarz Ulrich S. , Bastmeyer Martin 
Published: October 2020

AbstractNonmuscle myosin II (NM II) is an integral part of essential cellular processes, including adhesion and migration. Mammalian cells express up to three isoforms termed NM IIA, B, and C. We used U2OS cells to create CRISPR/Cas9-based knockouts of all three isoforms and analyzed the phenotypes on homogeneous substrates, in collagen gels, and on micropatterned substrates. We find that NM IIA is essential to build up cellular tension during initial stages of force generation, while NM IIB is necessary to elastically stabilize NM IIA-generated tension. A scale-bridging mathematical model explains our observations by relating actin fiber stability to the molecular rates of the myosin crossbridge cycle. A dynamic cell stretch/release experiment confirms these predictions and in addition reveals a novel role for NM IIC, namely the ability to establish tensional homeostasis.
PRC1 drives Polycomb-mediated gene repression by controlling transcription initiation and burst frequency
Authors: Dobrinić Paula , Szczurek Aleksander T. , Klose Robert J. 
Published: October 2020

AbstractThe Polycomb repressive system plays a fundamental role in controlling gene expression during mammalian development. To achieve this, Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) bind target genes and use histone modification-dependent feedback mechanisms to form Polycomb chromatin domains and repress transcription. The interrelatedness of PRC1 and PRC2 activity at these sites has made it difficult to discover the specific components of Polycomb chromatin domains that drive gene repression and to understand mechanistically how this is achieved. Here, by exploiting rapid degron-based approaches and time-resolved genomics we kinetically dissect Polycomb-mediated repression and discover that PRC1 functions independently of PRC2 to counteract RNA polymerase II binding and transcription initiation. Using single-cell gene expression analysis, we reveal that PRC1 acts uniformly within the cell population, and that repression is achieved by controlling transcriptional burst frequency. These important new discoveries provide a mechanistic and conceptual framework for Polycomb-dependent transcriptional control.
The VCBS superfamily, a diverse group of β-propellers that includes tachylectin and integrins
Authors: Pereira Joana , Lupas Andrei N. 
Published: October 2020

Abstractβ-Propellers are found in great variety across all kingdoms of life. They assume many cellular roles, primarily as scaffolds for macromolecular interactions and catalysis. Despite their diversity, most β-propeller families clearly originated by amplification from the same ancient peptide - the β-propeller blade. In cluster analyses, β-propellers of the WD40 superfamily always formed the largest group, to which some important families, such as the α-integrin, Asp-box, and glycoside hydrolase β-propellers connected weakly. Motivated by the dramatic growth of sequence databases we revisited these connections, with a special focus on VCBS-like β-propellers, which have not been analysed for their evolutionary relationships so far. We found that they form a supercluster with integrin-like β-propellers and tachylectins, clearly delimited from the superclusters formed by WD40 and Asp-Box β-propeller. Connections between the three superclusters are made mainly through PQQ-like β-propeller. Our results present a new, greatly expanded view of the β-propeller classification landscape.
Learning when effort matters: Neural dynamics underlying updating and adaptation to changes in performance efficacy
Authors: Grahek Ivan , Frömer Romy , Fahey Mahalia Prater , Shenhav Amitai 
Published: October 2020

AbstractTo determine how much cognitive control to invest in a task, people need to consider whether exerting controlmattersfor obtaining rewards. In particular, they need to account for the efficacy of their performance – the degree to which rewards are determined by performance or by independent factors. Yet it remains unclear how people learn about theirperformance efficacyin an environment. Here we combined computational modeling with measures of task performance and EEG, to provide a mechanistic account of how people (a) learn and update efficacy expectations in a changing environment, and (b) proactively adjust control allocation based on current efficacy expectations. Across two studies subjects performed an incentivized cognitive control task while their performance efficacy (the likelihood that rewards are performance- contingent or random) varied over time. We show that people update their efficacy beliefs based on prediction errors – leveraging similar neural and computational substrates as those that underpin reward learning – and adjust how much control they allocate according to these beliefs. Using computational modeling, we show that these control adjustments reflect changes in information processing, rather than the speed-accuracy tradeoff. These findings demonstrate the neurocomputational mechanism through which people learn how worthwhile their cognitive control is.