bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variation in scion water relations mediated by two newly released Geneva series rootstocks
Authors: Casagrande-Biasuz E. , Kalcsits L.A. 
Published: July 2021

ABSTRACTDwarfing rootstocks are used to control tree vigor allowing for increased densities that increase apple production. Although there is considerable variation among rootstocks in dwarfing capacity, the mechanisms by which rootstocks affect vigor in apple scions remains unclear. Here, ‘Honeycrisp’ apple growth and water relations were compared among three rootstocks; M-9 as the industry standard and two less studied Geneva series rootstocks; G.87 and G. 814 in Washington, USA. Trees were acquired from a commercial nursery and planted in 2017. In 2018 and 2019, scion physiological, isotopic and morphological traits were measured to better understand the link between rootstock-driven vigor and physiological traits. Rootstock affected scion shoot growth (P <0.001), stomatal conductance (P< 0.01) and stem water potential (P <0.001). Rootstocks with low vegetative vigor like M.9 also had lower stomatal conductance and enriched leaf δ13C and δ18O isotope composition. Plant growth was positively correlated with stomatal conductance and stem water potential. Rootstocks also affected plant water status and net gas exchange. Here, we report an association between rootstock-induced vigor and scion physiological traits such as gas exchange, stem water potential, and leaf carbon and oxygen isotope composition. This research has implications for the understanding of the mechanisms of dwarfing by rootstocks in apple.
Adolescent Development of Biological Rhythms: Estradiol Dependence and Effects of Combined Contraceptives
Authors: Grant Azure D. , Wilbrecht Linda , Kriegsfeld Lance J. 
Published: July 2021

AbstractPurposeAdolescence is a period of continuous development, including the maturation of endogenous rhythms across systems and timescales. Although these dynamic changes are well recognized, their continuous structure and hormonal dependence have not been systematically characterized. Given the well-established link between core body temperature (CBT) and reproductive hormones in adults, we hypothesized that high-resolution CBT can be applied to passively monitor pubertal development and disruption with high fidelity.MethodsTo examine this possibility, we used signal processing to investigate the trajectory of CBT rhythms at the within-day (ultradian), daily (circadian), and ovulatory timescales, their dependence on estradiol, and the effects of hormonal contraceptives.ResultsPuberty onset was marked by a rise in fecal estradiol (fE2), followed by an elevation in CBT and circadian power. This time period marked the commencement of 4-day rhythmicity in fE2, CBT, and ultradian power marking the onset of the estrous cycle. The rise in circadian amplitude was accelerated by E2 treatment, indicating a role for this hormone in rhythmic development. Contraceptive administration in later adolescence reduced CBT and circadian power and resulted in disruption to 4-day cycles that persisted after discontinuation.ConclusionsOur data reveal with precise temporal resolution how biological rhythms change across adolescence and demonstrate a role for E2 in the emergence and preservation of multiscale rhythmicity. These findings also demonstrate how hormones delivered exogenously in a non-rhythmic pattern can disrupt rhythmic development. These data lay the groundwork for a future in which temperature metrics provide an inexpensive, convenient method for monitoring pubertal maturation and support the development of hormone therapies that better mimic and support human chronobiology.
Defining the prototypical DNA replication fork trap in bacteria
Authors: Toft Casey J. , Moreau Morgane J. J. , Perutka Jiri , Mandapati Savitri , Enyeart Peter , Sorenson Alanna E. , Ellington Andrew D. , Schaeffer Patrick M. 
Published: July 2021

ABSTRACTInEscherichia coli, DNA replication termination is orchestrated by two clusters ofTersites forming a DNA replication fork trap when bound by Tus proteins. The formation of a ‘locked’ Tus-Tercomplex is essential for halting incoming DNA replication forks. However, the absence of replication fork arrest at someTersites raised questions about their significance. In this study, we examined the genome-wide distribution of Tus and found that only the six innermostTersites (TerA-EandG) were significantly bound by Tus. We also found that a single ectopic insertion ofTerBin its non-permissive orientation could not be achieved, advocating against a need for ‘back-up’Tersites. Finally, examination of the genomes of a variety of Enterobacterales revealed a new replication fork trap architecture exclusively found outside the Enterobacteriaceae family. Taken together, our data enabled the delineation of a narrow prototypical Tus-dependent DNA replication fork trap consisting of only twoTersites.Graphical Abstract
SGLT2-Inhibition reverts urinary peptide changes associated with severe COVID-19: anin-silicoproof-of-principle of proteomics-based drug repurposing
Authors: Latosinska Agnieszka , Siwy Justyna , Cherney David Z. , Perkins Bruce A. , Mischak Harald , Beige Joachim 
Published: July 2021

AbstractSevere COVID-19 is reflected by significant changes in multiple urine peptides. Based on this observation, a clinical test based on urinary peptides predicting COVID-19 severity, CoV50, was developed and registered as IVD in Germany. We have hypothesized that molecular changes displayed by CoV50, to a large degree likely reflective of endothelial damage, can be significantly reversed by specific drugs. To test this hypothesis, we have collected urinary peptide data from patients without COVID-19 prior and after drug treatment. The drugs chosen were selected based on availability of sufficient number of participants in the dataset (n>20) and potential value of drug therapies in the treatment of COVID-19 based on reports in the literature. In these participants without COVID-19, while spironolactone did not demonstrate a significant impact on CoV50 scoring, empagliflozin treatment resulted in a significant change in CoV50 scoring, indicative of a potential therapeutic benefit. The results serve as a proof-of-principle for a drug repurposing approach based on human urinary peptide signatures and support the initiation of a randomised control trial testing a potential positive effect of empagliflozin in the treatment of severe COVID-19, possibly via endothelial protective mechanisms.Significance of the studyCOVID-19 pandemic has imposed a heavy burden on society, health care and economics. Although multiple drugs have been tested in the context of COVID-19, effective treatments for patients experiencing severe disease are still missing, with some drugs demonstrating benefit only at earlier disease stage. Computational drug repurposing emerged as a promising approach to boost drug development, allowing to predict drug efficacy based on the molecular signature of drug impact, mainly using transcriptomics data from cell lines.Recently we demonstrated that urinary proteomics profiles significantly differ between patients with severe COVID-19 course and those with mild/ moderate disease. This resulted in the development of a molecular signature associated with COVID-19 severity (CoV50), allowing to predict COVID-19 course, and enabling guiding intervention.Here we report on the first study demonstrating the application of clinical proteomics data (from clinical trial participants) in a drug repurposing approach. We used the CoV50 signature to examine if the molecular changes associated with COVID-19 severity in patients without COVID-19 might be altered by existing drugs. In a study population without COVID-19, empagliflozin demonstrated a partial, yet significant reversion of the CoV50 signature, indicating a potential benefit in the context of severe COVID-19.
Spread of infection and treatment interruption among Japanese workers during the COVID-19 pandemic: a cross-sectional study
Authors: Akashi Jun , Hino Ayako , Tateishi Seiichiro , Nagata Tomohisa , Tsuji Mayumi , Ogami Akira , Matsuda Shinya , Kataoka Masaharu , Fujino Yoshihisa ,   CORoNaWork Project
Published: July 2021

AbstractObjectivesThis study aimed to examine the relationship between regional infection level and treatment interruption for chronic diseases.MethodsA cross-sectional Internet monitoring survey was performed between December 22 and 26, 2020. Data from 9,510 (5,392 males and 4,118 females) participants needing regular treatment or hospital visits were analyzed. We determined the age-sex- and multivariate-adjusted odds ratios (ORs) of treatment interruption associated with various indices of infection level by nesting multilevel logistic models in prefecture of residence. In the multivariate model, sex, age, marital status, job type, equivalent household income, education, self-rated health, and anxiety were adjusted.ResultsThe ORs of treatment interruption for the lowest versus highest levels of infection were 1.32 (95% CI: 1.09–1.59) for the overall incidence rate (per 1,000 population), 1.34 (95% CI: 1.10–1.63) for the overall number of people infected, 1.28 (95% CI: 1.06–1.54) for the monthly incidence rate (per 1,000 population), and 1.38 (95% CI: 1.14–1.67) for the number of people infected per month. For each index of infection level, higher infection was linked to more workers experiencing treatment interruption.ConclusionHigher local infection levels were linked to more workers experiencing treatment interruption. Our results suggest that apart from individual characteristics such as socioeconomic and health status, treatment interruptions during the pandemic were also subject to contextual effects related to regional infection levels. Preventing community spread of COVID-19 may thus protect individuals from indirect effects of the pandemic, such as treatment interruption.
Concentration of SARS-CoV-2 from large volumes of raw wastewater is enhanced with the inuvai R180 system
Authors: Monteiro Silvia , Rente Daniela , Cunha Mónica V. , Marques Tiago A. , Cardoso Eugénia , Álvaro Pedro , Vilaça João , Ribeiro Jorge , Silva Marco , Coelho Norberta , Brôco Nuno , Carvalho Marta , Santos Ricardo 
Published: July 2021

AbstractWastewater-based epidemiology (WBE) for severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) is a powerful tool to complement syndromic surveillance: first, as an early-warning system for the spread of the virus in the community, second, to find hotspots of infection, and third, to aid in the early detection and follow-up of circulating virus variants.Although detection of SARS-CoV-2 in raw wastewater may be prompted with good recoveries during periods of high community prevalence, in the early stages of population outbreaks concentration procedures are required to overcome low viral concentrations. Several methods have become available for the recovery of SARS-CoV-2 from raw wastewater, generally involving filtration. However, these methods are limited to small sample volumes, possibly missing the early stages of virus circulation, and restrained applicability across different water matrices. The aim of this study was thus to evaluate the performance of three methods enabling the concentration of SARS-CoV-2 from large volumes of wastewater: i) hollow fiber filtration using the inuvai R180, with an enhanced elution protocol and polyethylene glycol (PEG) precipitation; ii) PEG precipitation; and iii) skimmed milk flocculation. The performance of the three approaches was evaluated in wastewater from multiple wastewater treatment plants (WWTP) with distinct singularities, according to: i) effective volume; ii) percentage of recovery; iii) extraction efficiency; iv) inhibitory effect; and v) the limits of detection and quantification (The inuvai R180 system had the best performance, with detection of spiked controls across all samples, average recovery percentages of 64% for SARS-CoV-2 control and 68% for porcine epidemic diarrhea virus (PEDV), with low variability.The inuvai R180 enables the scalability of volumes without negative impact on the costs, time for analysis, and recovery/inhibition. Moreover, hollow fiber filters favor the concentration of different microbial taxonomic groups. Such combined features make this technology attractive for usage in environmental waters monitoring.
Accounting for the Role of Asymptomatic Patients in Understanding the Dynamics of the COVID-19 Pandemic: A Case Study from Singapore
Authors: Teck Liew Fu , Ghosh Palash , Chakraborty Bibhas 
Published: July 2021

AbstractObjectivesTo forecast the true growth of COVID-19 cases in Singapore after accounting for asymptomatic infections, we study and make modifications to the SEIR (Susceptible-Exposed-Infected-Recovered) epidemiological model by incorporating hospitalization dynamics and the presence of asymptomatic cases. We then compare the simulation results of our three epidemiological models of interest against the daily reported COVID-19 case counts across the time period from 23rd January to 6th April 2020. Finally, we compare and evaluate on the performance and accuracy of the aforementioned models’ simulations.MethodsThree epidemiological models are used to forecast the true growth of COVID-19 case counts by accounting for asymptomatic infections in Singapore. They are the exponential model, SEIR model with hospitalization dynamics (SEIHRD), and the SEIHRD model with inclusion of asymptomatic cases (SEAIHRD).ResultsSimulation results of all three models reflect underestimation of COVID-19 cases in Singapore during the early stages of the pandemic. At a 40% asymptomatic proportion, we report basic reproduction number R0 = 3.28 and 3.74 under the SEIHRD and SEAIHRD models respectively. At a 60% asymptomatic proportion, we report R0 = 3.48 and 3.96 under the SEIHRD and SEAIHRD models respectively.ConclusionsBased on the results of different simulation scenarios, we are highly confident that the number of COVID-19 cases in Singapore was underestimated during the early stages of the pandemic. This is supported by the exponential increase of COVID-19 cases in Singapore as the pandemic developed.
The infinite alleles model revisited: a Gibbs sampling approach
Authors: Manceau Marc 
Published: July 2021

AbstractThe SARS-CoV-2 outbreak started in late 2019 in the Hubei province in China and the first viral sequence was made available to the scientific community on early January 2020. From there, viral genomes from all over the world have followed at an outstanding rate, reaching already more than 105on early May 2020, and more than 106by early March 2021. Phylodynamics methods have been designed in recent years to process such datasets and infer population dynamics and sampling intensities in the past. However, the unprecedented scale of the SARS-CoV-2 dataset now calls for new methodological developments, relying e.g. on simplifying assumptions of the mutation process.In this article, I build on theinfinite alleles modelstemming from the field of population genetics to develop a new Bayesian statistical method allowing the joint reconstruction of the outbreak’s effective population sizes and sampling intensities through time. This relies on prior conjugacy properties that prove useful both to develop a Gibbs sampler and to gain intuition on the way different parameters of the model are linked and inferred. I finally illustrate the use of this method on SARS-CoV-2 genomes sequenced during the first wave of the outbreak in four distinct European countries, thus offering a new perspective on the evolution of the sampling intensity through time in these countries from genetic data only.
Spatial and Temporal Organization of Composite Receptive Fields in the Songbird Auditory Forebrain
Authors: Vahidi Nasim W. 
Published: July 2021

AbstractThe mechanisms underlying how single auditory neurons and neuron populations encode natural and acoustically complex vocal signals, such as human speech or bird songs, are not well understood. Classical models focus on individual neurons, whose spike rates vary systematically as a function of change in a small number of simple acoustic dimensions. However, neurons in the caudal medial nidopallium (NCM), an auditory forebrain region in songbirds that is analogous to the secondary auditory cortex in mammals, have composite receptive fields (CRFs) that comprise multiple acoustic features tied to both increases and decreases in firing rates. Here, we investigated the anatomical organization and temporal activation patterns of auditory CRFs in European starlings exposed to natural vocal communication signals (songs). We recorded extracellular electrophysiological responses to various bird songs at auditory NCM sites, including both single and multiple neurons, and we then applied a quadratic model to extract large sets of CRF features that were tied to excitatory and suppressive responses at each measurement site. We found that the superset of CRF features yielded spatially and temporally distributed, generalizable representations of a conspecific song. Individual sites responded to acoustically diverse features, as there was no discernable organization of features across anatomically ordered sites. The CRF features at each site yielded broad, temporally distributed responses that spanned the entire duration of many starling songs, which can last for 50 s or more. Based on these results, we estimated that a nearly complete representation of any conspecific song, regardless of length, can be obtained by evaluating populations as small as 100 neurons. We conclude that natural acoustic communication signals drive a distributed yet highly redundant representation across the songbird auditory forebrain, in which adjacent neurons contribute to the encoding of multiple diverse and time-varying spectro-temporal features.
Short-chain fatty acids activate acetyltransferase p300
Authors: Thomas Sydney P. , Denu John M. 
Published: July 2021

AbstractShort-chain fatty acids (SCFAs) acetate, propionate, and butyrate are produced in large quantities by the gut microbiome and contribute to a wide array of physiological processes. While the underlying mechanisms are largely unknown, many effects of SCFAs have been traced to changes in the cell’s epigenetic state. Here, we systematically investigate how SCFAs alter the epigenome. Using quantitative proteomics of histone modification states, we identified rapid and sustained increases in histone acetylation after addition of butyrate or propionate, but not acetate. While decades of prior observations would have suggested that hyperacetylation induced by SCFAs are attributed to inhibition of histone deacetylases (HDACs), we found that propionate and butyrate instead activate the acetyltransferase p300. Propionate and butyrate are rapidly converted to the corresponding acyl-CoAs which are then used by p300 to catalyze auto-acylation of the autoinhibitory loop, activating the enzyme for histone/protein acetylation. This data challenges the long-held belief that SCFAs mainly regulate chromatin by inhibiting HDACs, and instead reveals a previously unappreciated mechanism of HAT activation that can explain how even low levels of SCFAs alter global chromatin states.Summary Figure
Microbial association networks in cheese: a meta-analysis
Authors: Parente Eugenio , Zotta Teresa , Ricciardi Annamaria 
Published: July 2021

AbstractInteractions among starter and non-starter microorganisms (starter bacteria, naturally occurring or intentionally added non-starter bacteria, yeasts and filamentous fungi, spoilage and pathogenic microorganisms and, finally bacteriophages and even arthropods) deeply affect the dynamics of cheese microbial communities and, as a consequence, multiple aspects of cheese quality, from metabolites affecting the taste, aroma and flavour, to body, texture and colour. Understanding and exploiting microbial interactions is therefore key to managing cheese quality. This is true for the simplest systems (fresh cheeses produced from pasteurized milk using defined starters composed solely of Lactic Acid Bacteria) and the more so for complex, dynamic systems, like surface ripened cheese produced from raw milk, in which a dynamic succession of diverse microorganisms is essential for obtained the desired combination of sensory properties while guaranteeing safety. Positive (commensalism, protocooperation) and negative (competition, amensalism, predation and parasitism) among members of the cheese biota have been reviewed multiple times. Although the complex, multidimensional datasets generated by multi-omic approaches to cheese microbiology and biochemistry are ideally suited for the representation of biotic and metabolic interactions as networks, network science concepts and approaches are rarely applied to cheese microbiology.In this review we first illustrate concepts relevant to the description of microbial interaction networks using network science concepts. Then, we briefly review methods used for the inference and analysis of microbial association networks and their potential use in the interpretation of the cheese interactome. Since these methods can only be used for mining microbial associations, a review of the experimental methods used to confirm the nature of microbial interactions among cheese microbes. Finally, we demonstrate the potential of microbial association network inference by mining metataxonomic data stored in the public database DairyFMBN, a specialized version of FoodMicrobionet which collates data on 74 metataxonomic studies on dairy products. Microbial association networks were inferred from 34 studies on cheese with up to 4 different methods and the results discussed to evaluate several aspects (choice of method, level of taxonomic resolution for the analysis, network, node and edge properties) which provide insight on the usefulness of this approach as explorative tool in the detection of microbial interactions in cheese.HighlightsApproaches for inference of association networks from metataxonomic data were reviewedA metastudy on association networks in cheese was carried out using 34 recent studiesInference method and taxonomic resolution should be chosen carefullySPIEC-EASI may be used as a conservative method for microbial association inferenceEdge and node properties support the formulation of testable hypotheses for microbial interactions
MyD88-dependent TLR signaling oppositely regulates hematopoietic progenitor and stem cell formation in the embryo
Authors: Bennett Laura F. , Mumau Melanie D. , Li Yan , Speck Nancy A. 
Published: July 2021

AbstractHemogenic endothelial (HE) cells in the dorsal aorta undergo an endothelial to hematopoietic transition (EHT) to form lympho-myeloid biased progenitors (LMPs), pre-hematopoietic stem cells (pre-HSCs) and adult-repopulating HSCs. These briefly accumulate in intra-arterial hematopoietic clusters (IAHCs) before being released into the circulation. It is generally assumed that the number of IAHC cells correlates with the number of HSCs. Here we show that changes in the number of IAHC cells, LMPs, and HSCs can be uncoupled. Mutations impairing MyD88-dependent toll-like receptor (TLR) signaling decreased the number of IAHC cells and LMPs but increased the number of HSCs in the aorta-gonad-mesonephros region of mouse embryos. TLR4 -deficient embryos generated normal numbers of HE cells but the proliferation of IAHC cells was decreased. Loss of MyD88-dependent TLR signaling in innate immune myeloid cells had no effect on IAHC cell numbers. Instead, TLR4 deletion in endothelial cells recapitulated the phenotype observed with germline deletion, demonstrating that MyD88-dependent TLR signaling in endothelial cells and/or in IAHCs regulates the balance between generating LMPs and HSCs.Summary StatementToll-like receptor signaling in endothelial cells restricts the number of hematopoietic stem cells but increases the number of committed progenitors and intra-arterial hematopoietic cluster cells by promoting their proliferation.