bluuebunny/crossref_metadata_2025_split huggingface dataset:
HiCzin: Normalizing metagenomic Hi-C data and detecting spurious contacts using zero-inflated negative binomial regression
Authors: Du Yuxuan , Laperriere Sarah M. , Fuhrman Jed , Sun Fengzhu 
Published: March 2021

AbstractHigh-throughput chromosome conformation capture (Hi-C) has recently been applied to natural microbial communities and revealed great potential to study multiple genomes simultaneously. Several extraneous factors may influence chromosomal contacts rendering the normalization of Hi-C contact maps essential for downstream analyses. However, the current paucity of metagenomic Hi-C normalization methods and the ignorance for spurious inter-species contacts weaken the interpretability of the data. Here, we report on two types of biases in metagenomic Hi-C experiments: explicit biases and implicit biases, and introduce HiCzin, a parametric model to correct both types of biases and remove spurious inter-species contacts. We demonstrate that the normalized metagenomic Hi-C contact maps by HiCzin result in lower biases, higher capability to detect spurious contacts, and better performance in metagenomic contig clustering. The HiCzin software and Supplementary Material are available athttps://github.com/dyxstat/HiCzin.
High Initial Titres of Anti-Spike Antibodies following SARS-CoV-2 Infection is Associated with Faster Decay Rates at Four Months Follow-Up
Authors: Menon Vidya , Shariff Masood A , Gutierrez Victor Perez , Carreño Juan M , Yu Bo , Jawed Muzamil , Gossai Marcia , Valdez Elisenda , Pillai Anjana , Venugopal Usha , Kasubhai Moiz , Dimitrov Vihren , Krammer Florian 
Published: March 2021

AbstractBackgroundDynamics of humoral immune responses to SARS-CoV-2 antigens following infection suggests an initial decay of antibody followed by subsequent stabilization. We aim to understand the longitudinal humoral responses to SARS-CoV-2 nucleocapsid (N) protein and spike (S) protein and to evaluate their correlation to clinical symptoms among healthcare workers (HCW).MethodsIn this cross-sectional longitudinal cohort study done in two phases over four months, HCW underwent serial qualitative serology testing for anti-N antibody, quantitative MSH-ELISA to detect Receptor Binding Domain and full-length S reactive antibodies and completed online surveys about COVID-19 related symptoms and healthcare/community exposure.ResultsAnti-N antibody positivity was 27% and anti-S positivity was 28% in Phase 1. In Phase 2 anti-S titres were higher in symptomatic than in asymptomatic positive subjects in Phase 1. Marginally higher titers were seen in asymptomatic compared to the symptomatic positive subgroup in Phase 2. A positive correlation was noted between age, number and duration of symptoms, and Phase 1 anti-S antibody titre. A strong correlation was observed between Phase 1 titers and decay of anti-S antibody titres between the two phases. Significant correlation with rate of decay was also noted with fever, GI symptoms, and total number and duration of COVID-19 symptoms.ConclusionsHigher initial anti-S antibody titres were associated with larger number and longer duration of symptoms as well as faster decay during the two time points.Key PointsQuestionWhat is the decay rate of neutralizing antibodies among SARS-CoV-2 infected healthcare workers?FindingsIn this cohort study that included 178 healthcare workers, over a 4-month period following the COVID-19 pandemic, participants had an initial rise in anti-nucleocapsid (N) and anti-spike (S) antibodies, which was followed by decay and stabilization of the titres. Significant correlation with rate of decay was noted with the symptomatic participants.MeaningA strong correlation is observed in the decay of anti-S antibody titres based on symptomology, thus eluding to the fact that continued recommendations for infection protection and COVID-19 vaccine campaigns are necessary.
365 days with COVID-19 in Iran: data analysis and epidemic curves
Authors: Sahafizadeh Ebrahim , Azad Saeed Talatian 
Published: March 2021

AbstractBackgroundThe first confirmed cases of COVID-19 in Iran were reported on February 19, 2020. This study aimed to analyze the epidemic curves and to investigate the correlation between epidemic parameters and furthermore to analyze the impact of control measures on the spread of COVID-19 in Iran during 365 days of the epidemic.MethodsWe used data from February 20, 2020, to February 18, 2021, on the number of COVID-19 cases reported by Iranian governments. Pearson correlation coefficient was applied to investigate the correlation between different epidemic parameters. The number of daily deaths per daily new cases was averaged to calculate daily death rate and the same method was used to investigate the rate of daily positive tests. Furthermore, we employed two different methods to calculate the effective reproduction number using reported data.ResultsThe results showed that there was a strong correlation between the number of daily deaths and the number of daily new cases (specially the admitted cases). The results also indicated that the mean of daily death rate of COVID-19 during 365 days was 4.9 percent, and averagely 13.9 percent of daily tests results were positive. Furthermore, epidemic curves showed that implementing strict social distancing measures effectively reduced the number of confirmed cases. The effective reproduction curve indicated that social distancing is still necessary to control the spread of COVID-19 in Iran.ConclusionsAnalyzing the prevention and control measures indicated that the strict social distancing implemented by the government effectively reduces the number of new cases and deaths. The curve of reproduction number also showed that effective reproduction number is still above one; hence, it is necessary to continue strict social distancing and control travelling to prevent causing another wave of outbreak especially in Persian New Year.
A Nonlinear Observer to Estimate the Effective Reproduction Number of Infectious Diseases
Authors: Hasan Agus 
Published: March 2021

AbstractIn this paper, we design a Nonlinear Observer (NLO) to estimate the effective reproduction number (ℛt) of infectious diseases. The NLO is designed from a discrete-time augmented Susceptible-Infectious-Removed (SIR) model. The observer gain is obtained by solving a Linear Matrix Inequality (LMI). The method is used to estimate ℛt in Jakarta using epidemiological data during COVID-19 pandemic. If the observer gain is tuned properly, this approach produces similar result compared to existing approach such as Extended Kalman filter (EKF).
Antigen and Checkpoint Receptor Recalibration of T Cell Receptor Signal Strength
Authors: Elliot Thomas A.E. , Jennings Emma K. , Lecky David A.J. , Thawait Natasha , Flores-Langarica Adriana , Wraith David C. , Bending David 
Published: March 2021

SummaryHow T cell receptor (TCR) signal strength modulates T cell function and to what extent this is modified by immune checkpoint blockade (ICB) are key questions in immunology. Using Nr4a3-Tocky mice as a digital read-out of NFAT pathway activity, we identify the rapid quantitative and qualitative changes that occur in CD4+T cells in response to a range of TCR signalling strengths. We demonstrate that the time and dose dependent programming of distinct co-inhibitory receptors rapidly re-calibrates T cell activation thresholds. By developing a newin vivomodel, we analyse the immediate effects of ICB on T cell re-activation. Our findings reveal that anti-PD1 but not anti-Lag3 immunotherapy leads to an increased TCR signal strength. We define a strong TCR signal metric of five genes specifically upregulated by anti-PD1 in T cells (TCR.strong), which can stratify clinical outcomes during anti-PD1 monotherapy in melanoma patients. Our study therefore reveals how analysis of TCR signal strength – and its manipulation – can provide powerful metrics for monitoring outcomes to immunotherapy.Key PointsTCR signal strength-dependent programming of CD4+T cells revealed over time in vivoInhibitory receptor expression is dynamic, TCR signal strength dependent, and rapidly re-calibrates T cell activation thresholdsPD1 but not Lag3 blockade leads to a unique and increased TCR signal strength signature (coined TCR.strong)TCR.strong metric stratifies melanoma patient survival in response to Nivolumab (anti-PD1) therapy
Plant hydraulics coordinated with photosynthetic traits and climate
Authors: Xu Huiying , Wang Han , Prentice I. Colin , Harrison Sandy P. , Wright Ian J. 
Published: March 2021

AbstractThe coupling between water loss and carbon dioxide uptake drives the coordination of plant hydraulic and photosynthetic traits. Analysing multi-species measurements on a 3000 m elevation gradient, we found that hydraulic and leaf-economic traits were less plastic, and more closely associated with phylogeny, than photosynthetic traits. The two trait sets are linked by the sapwood-to-leaf area ratio (Huber value,vH), shown here to be codetermined by sapwood hydraulic conductance (KS), leaf mass-per-area (LMA) and photosynthetic capacity (Vcmax). Substantial hydraulic diversity was related to the trade-off betweenKSandvH. Leaf drought tolerance (inferred from turgor loss point, –πtlp) increased with wood density, but the trade-off between hydraulic efficiency (KS) and –πtlpwas weak. The least-cost optimality framework was extended to predict trait (KS-dominated) and environmental (temperature-dominated) effects onvH. These results suggest an approach to include photosynthetic-hydraulic coordination in land-surface models; however, prediction of non-plastic trait distributions remains a challenge.
Genomic characterization of four novel bacteriophages infecting the clinical pathogenKlebsiella pneumoniae
Authors: Bonilla Boris Estrada , Costa Ana Rita , Rossum Teunke van , Hagedoorn Stefan , Walinga Hielke , Xiao Minfeng , Song Wenchen , Haas Pieter-Jan , Nobrega Franklin L. , Brouns Stan J.J. 
Published: March 2021

AbstractBacteriophages are an invaluable source of novel genetic diversity. Sequencing of phage genomes can reveal new proteins with potential uses as biotechnological and medical tools, and help unravel the diversity of biological mechanisms employed by phages to take over the host during viral infection. Aiming to expand the available collection of phage genomes, we have isolated, sequenced, and assembled the genome sequences of four phages that infect the clinical pathogenKlebsiella pneumoniae:vB_KpnP_FBKp16, vB_KpnP_FBKp27, vB_KpnM_FBKp34, and Jumbo phage vB_KpnM_FBKp24. The four phages show very low (0-13%) identity to genomic phage sequences deposited in the Genbank database. Three of the four phages encode tRNAs and have a GC content very dissimilar to that of the host. Importantly, the genome sequences of the phages reveal potentially novel DNA packaging mechanisms as well as distinct clades of tubulin spindle and nucleus shell proteins that some phages use to compartmentalize viral replication. Overall, this study contributes to uncovering previously unknown virus diversity, and provides novel candidates for phage therapy applications against antibiotic-resistantK. pneumoniaeinfections.
A modular, dynamic, DNA-based platform for regulating cargo distribution and transport between lipid domains
Authors: Rubio-Sánchez Roger , Barker Simone Eizagirre , Walczak Michal , Cicuta Pietro , Di Michele Lorenzo 
Published: March 2021

AbstractCell membranes regulate the distribution of biological machinery between phase-separated lipid domains to facilitate key processes including signalling and transport, which are among the life-like functionalities that bottom-up synthetic biology aims to replicate in artificial-cellular systems. Here, we introduce a modular approach to program partitioning of amphiphilic DNA nanostructures in co-existing lipid domains. Exploiting the tendency of different hydrophobic “anchors” to enrich different phases, we modulate the lateral distribution of our devices by rationally combining hydrophobes, and by changing nanostructure size and its topology. We demonstrate the functionality of our strategy with a bio-inspired DNA architecture, which dynamically undergoes ligand-induced reconfiguration to mediate cargo transport between domainsvialateral re-distribution. Our findings pave the way to next-generation biomimetic platforms for sensing, transduction, and communication in synthetic cellular systems.
ORT: A workflow linking genome-scale metabolic models with reactive transport codes
Authors: Rubinstein Rebecca L. , Borton Mikayla A. , Zhou Haiyan , Shaffer Michael , Hoyt David W. , Stegen James , Henry Christopher S. , Wrighton Kelly C. , Versteeg Roelof 
Published: March 2021

AbstractMotivationNutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As ‘omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed.ResultsWe propose a workflow (‘Omics to Reactive Transport – ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBASE and PFLOTRAN.Availability and ImplementationInteractive models available athttps://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available athttps://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available athttps://narrative.kbase.us/narrative/71260or static narrative (no login required) athttps://kbase.us/n/71260/258Contactrebecca.rubinstein@subsurfaceinsights.comorroelof.versteeg@subsurfaceinsights.comSupplementary informationSupplementary data are available online.
Towards a global investigation of transcriptomic signatures through co-expression networks and pathway knowledge for the identification of disease mechanisms
Authors: Figueiredo Rebeca Queiroz , Raschka Tamara , Kodamullil Alpha Tom , Hofmann-Apitius Martin , Mubeen Sarah , Domingo-Fernández Daniel 
Published: March 2021

AbstractIn this work, we attempt to address a key question in the joint analysis of transcriptomic data: can we correlate the patterns we observe in transcriptomic datasets to known molecular interactions and pathway knowledge to broaden our understanding of disease pathophysiology? We present a systematic approach that sheds light on the patterns observed in hundreds of transcriptomic datasets from over sixty indications by using pathways and molecular interactions as a template. Our analysis employs transcriptomic datasets to construct dozens of disease specific co-expression networks, alongside a human interactome network of protein-protein interactions described in the literature. Leveraging the interoperability between these two network templates, we explore patterns both common and particular to these diseases on three different levels. Firstly, at the node-level, we identify the most and least common proteins in these diseases and evaluate their consistency against the interactome as a proxy for their prevalence in the scientific literature. Secondly, we overlay both network templates to analyze common correlations and interactions across diseases at the edge-level. Thirdly, we explore the similarity between patterns observed at the disease level and pathway knowledge to identify pathway signatures associated with specific diseases and indication areas. Finally, we present a case scenario in the context of schizophrenia, where we show how our approach can be used to investigate disease pathophysiology.
High-quality complete genome resource of plant pathogenic bacteriumDickeya solanistrain IPO 2019 isolated fromHyacinthus orientalis
Authors: Czajkowski Robert , Rabalski Lukasz , Bartnik Przemysław , Jafra Sylwia 
Published: March 2021

AbstractDickeya solaniis an emerging plant pathogenic bacterium, causing disease symptoms in a variety of agriculturally relevant crop species worldwide. To date a number ofD. solanigenomes have been sequenced and characterized, the great majority of these genomes have however come fromD. solanistrains isolated from potato (Solanum tuberosumL.) and not from other plant hosts. Herewith, we present the first complete, high-quality genome ofD. solanistrain IPO 2019 (LMG 25990) isolated from ornamental plantHyacinthus orientalis. The genome ofD. solanistrain IPO 2019 consists of one chromosome of 4,919,542 bp., with a GC content of 56.2% and no plasmids. The genome contains 4502 annotated features, 22 rRNA genes, 73 tRNA genes and 1 CRISPRS. We believe that the information of this high-quality, complete, closed genome ofD. solanistrain isolated from host plant different than potato (i.e. hyacinth) will provide resources for comparative genomic studies as well as for analyses targeting adaptation and ecological fitness mechanisms present inDickeya solanispecies.
Arabidopsis annexin 5 controls plasma membrane properties in mature pollen grains
Authors: Lichocka Małgorzata , Krzymowska Magdalena , Górecka Magdalena , Hennig Jacek 
Published: March 2021

AbstractIn Arabidopsis, a dry stigma surface enables a gradual hydration of pollen grains by a controlled release of water. Occasionally the grains may be exposed to extreme precipitations that cause rapid water influx, swelling and eventually lead to pollen membrane (PM) rupture. In metazoans, calcium- and phospholipids-binding proteins, referred to as annexins participate in repair of the plasma membrane damages. It remains unclear, however, how this process is conducted in plants. Here, we examined whether the plant annexin 5 (ANN5), the most abundant member of the annexin family in pollen, is involved in the restoration of PM integrity. We analyzed a cellular dynamics of ANN5 in the pollen grains undergoingin vitroandin vivohydration. We observed a transient ANN5 association to PM during thein vitrohydration that did not occur in the pollen grains being hydrated on the stigma. To simulate a rainfall, we performed spraying of the pollinated stigma with deionized water that induced ANN5 accumulation at PM. Similarly, calcium or magnesium application affected PM properties and induced ANN5 recruitment to PM. Our data suggest a model, in which ANN5 is involved in the maintenance of membrane integrity in pollen grains exposed to osmotic or ionic imbalances.
Prostaglandin analog effects on cerebrospinal fluid reabsorption via nasal mucosa
Authors: Pedler Michelle G. , Petrash J. Mark , Subramanian Prem S. 
Published: March 2021

AbstractIntroductionCerebrospinal fluid (CSF) outflow has been demonstrated along nasal lymphatics via olfactory nerve projections; flow may be increased by stimulating lymphatic contractility using agents such as noradrenaline and the thromboxane A2 analog U46619. Lymphatics elsewhere in the body show increased contractility upon exposure to the prostaglandin F2alpha analog isoprostane-8-epi-prostaglandin. We investigated the ability of ophthalmic prostaglandin F2alpha analogs to increase CSF outflow when applied to the nasal mucosa by inhalation.MethodsLatanoprost (0.1, 0.5, or 1mg/ml), bimatoprost (0.3 or 3mg/ml), travoprost (0.04 or 0.4mg/ml), latanoprostene bunod (0.24 or 2.4mg/ml), tafluprost (0.25 or 2.5mg/ml), or vehicle (10% DMSO) was administered to awake adult C57B/6 mice by nasal inhalation of 2μl droplets. A total of 67 animals were studied including controls. General anesthesia was induced by injection, and fluorescent tracer (AlexaFluor647-labelled ovalbumin) was injected under stereotaxic guidance into the right lateral ventricle. Nasal turbinate tissue was harvested and homogenized after 1 hour for tracer detection by ELISA and fluorometric analysis.ResultsInhalation of latanoprost 0.5mg/ml and 1mg/ml led to a 11.5-fold increase in tracer recovery from nasal turbinate tissues compared to controls (3312 pg/ml vs 288 pg/ml, p<0.001 for 0.5mg/ml; 3355 pg/ml vs 288 pg/ml, p<0.001 for 1mg/ml), while latanoprost 0.1 mg/ml enhanced recovery 6-fold (1713 pg/ml vs 288 pg/ml, p<0.01). Tafluprost 0.25mg/ml and bimatoprost 0.3mg/ml showed a modest (1.4x, p<0.05) effect, and the remaining agents showed no significant effect on tracer recovery.ConclusionsProstaglandin F2alpha analogs delivered by nasal inhalation resulted in increased nasal recovery of a CSF fluorescent tracer, implying increased CSF outflow via the nasal lymphatics. The greatest effect, partially dose-dependent, was observed using latanoprost. Further studies are needed to determine the efficacy of these agents in reducing ICP in short and long-term applications.