bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plasma lipidomics identifies a signature of NAFLD in children that couples with cardiometabolic outcomes in adults
Authors: Mann Jake P. , Jenkins Benjamin , Furse Samuel , Snowden Stuart G. , Alisi Anna , Draijer Laura G. ,   EU-PNAFLD investigators, Karnebeek Kylie , Kelly Deirdre A. , Koot Bart G. , Mosca Antonella , Salvestrini Camilla , van Mourik Indra , Vreugdenhil Anita , Zilbauer Matthias , Koulman Albert 
Published: April 2020

AbstractNon-alcoholic fatty liver disease (NAFLD) is an increasingly common condition in children and adults characterized by insulin resistance and altered lipid metabolism. Affected patients are at increased risk of cardiovascular disease (CVD) and children with NAFLD are likely to be at risk of premature cardiac events. Evaluation of the plasma lipid profile of children with NAFLD offers the opportunity to investigate these perturbations and understand how closely they mimic the changes seen in adults with cardiometabolic disease. We hypothesized that change in the concentration of lipid species in pediatric NAFLD would mimic the alterations known to be associated with CVD in adults (and be largely reflective of insulin resistance). Here, we performed untargeted liquid chromatography mass spectrometry (LC-MS) plasma lipidomics on 287 children: 19 lean controls, 146 from an obese cohort, and 122 NAFLD cases who had undergone liver biopsy. Associations between lipid species and liver histology were assessed using regression adjusted for age and sex. Results were then replicated using data from 9,500 adults with metabolic phenotyping. Phosphatidylcholine (PC) and triglyceride (TG) desaturation and chain length were inversely associated with histological severity of paediatric NAFLD. Nine lipids species (lyso-PC, PC, and TG classes) were also associated with hepatic steatosis and insulin resistance in an independent cohort of adults. Five of the 9 lipids replicated in the adults cohort (including PC(36:4)) have been directly linked to death and cardiometabolic disease in adults, as well as indirectly via genetic variants that influence the concentration of these species. Together, these findings suggest that lipid metabolism is altered in paediatric NAFLD in a similar way as in cardiometabolic disease in adults and it is therefore critical to alleviate insulin resistance in these children to mitigate their long-term morbidity.
PreTA: A network meta-analysis ranking metric measuring the probability of being preferable than the average treatment
Authors: Nikolakopoulou Adriani , Mavridis Dimitris , Chiocchia Virginia , Papakonstantinou Theodoros , Furukawa Toshi A , Salanti Georgia 
Published: April 2020

AbstractBackgroundNetwork meta-analysis (NMA) produces complex outputs as many comparisons between interventions are of interest and a treatment ranking is often included in the aims of the evidence synthesis. The estimated relative treatment effects are usually displayed in a forest plot or in a league table and several ranking metrics are calculated and presented, such as the median and mean treatment ranks.MethodsWe estimate relative treatment effects of each competing treatment against a fictional ‘average’ treatment using the ‘deviation from the means’ coding that has been used to parametrize categorical covariates in regression models. Based on this alternative parametrization of the NMA model, we present a new ranking metric (PreTA: Preferable Than Average) interpreted as the probability that a treatment is better than a fictional treatment of average performance.ResultsWe compare PreTA with existing probabilistic ranking metrics in 232 networks of interventions. We use two networks of interventions, a network of 18 antidepressants for acute depression and a network of four interventions for heavy menstrual bleeding, to illustrate the methodology. The agreement between PreTA and existing ranking metrics depends on the precision with which relative effects are estimated.ConclusionsPreTA is a viable alternative to existing ranking metrics which can be interpreted as the probability of being better than the ‘average’ treatment. It enriches the decision-making arsenal with a ranking metric which is interpreted as a probability and considers the entire ranking distributions of the involved treatments.
COVID-19 outbreak in Wuhan demonstrates the limitations of publicly available case numbers for epidemiological modelling
Authors: Raimúndez Elba , Dudkin Erika , Vanhoefer Jakob , Alamoudi Emad , Merkt Simon , Fuhrmann Lara , Bai Fan , Hasenauer Jan 
Published: April 2020

AbstractEpidemiological models are widely used to analyse the spread of diseases such as the global COVID-19 pandemic caused by SARS-CoV-2. However, all models are based on simplifying assumptions and on sparse data. This limits the reliability of parameter estimates and predictions.In this manuscript, we demonstrate the relevance of these limitations by performing a study of the COVID-19 outbreak in Wuhan, China. We perform parameter estimation, uncertainty analysis and model selection for a range of established epidemiological models. Amongst others, we employ Markov chain Monte Carlo sampling, parameter and prediction profile calculation algorithms.Our results show that parameter estimates and predictions obtained for several established models on the basis of reported case numbers can be subject to substantial uncertainty. More importantly, estimates were often unrealistic and the confidence / credibility intervals did not cover plausible values of critical parameters obtained using different approaches. These findings suggest, amongst others, that several models are oversimplistic and that the reported case numbers provide often insufficient information.
More prevalent, less deadly? Bayesian inference of the COVID19 Infection Fatality Ratio from mortality data
Authors: Delius G. W. , Powell B. J. , Bees M. A. , Constable G. W. A. , MacKay N. J. , Pitchford J. W. 
Published: April 2020

AbstractWe use an established semi-mechanistic Bayesian hierarchical model of the COVID-19 pandemic [1], driven by European mortality data, to estimate the prevalence of immunity. We allow the infection-fatality ratio (IFR) to vary, adapt the model’s priors to better reflect emerging information, and re-evaluate the model fitting in the light of current mortality data. The results indicate that the IFR of COVID-19 may be an order of magnitude smaller than the current consensus, with the corollary that the virus is more prevalent than currently believed. These results emerge from a simple model and ought to be treated with caution. They emphasise the value of rapid community-scale antibody testing when this becomes available.
High frequency neuronal bursting is essential for circadian and sleep behaviors inDrosophila
Authors: Fernandez-Chiappe Florencia , Frenkel Lia , Colque Carina Celeste , Ricciuti Ana , Hahm Bryan , Cerredo Karina , Muraro Nara Inés , Ceriani María Fernanda 
Published: April 2020

AbstractCircadian rhythms have been extensively studied inDrosophila, however, still little is known about how the electrical properties of clock neurons are specified. We have performed a behavioral genetic screen through the downregulation of candidate ion channels in the lateral ventral neurons (LNvs) and show that the hyperpolarization-activated cation current Ihis important for the behaviors that the LNvs command: temporal organization of locomotor activity and sleep. Using whole-cell patch clamp electrophysiology we demonstrate that small LNvs are bursting neurons, and that Ihis necessary to achieve the high frequency bursting firing pattern characteristic of both types of LNvs. Since firing in bursts has been associated to neuropeptide release, we hypothesized that Ihwould be important for LNvs communication. Indeed, herein we demonstrate that Ihis fundamental for the recruitment of PDF filled dense core vesicles to the terminals at the dorsal protocerebrum and for their timed release, and hence for the temporal coordination of circadian behaviors.
Identifying female phenotypes that promote behavioral isolation in a sexually dimorphic species of fish (Etheostoma zonale)
Authors: Roberts Natalie S. , Mendelson Tamra C. 
Published: April 2020

AbstractIn sexually dimorphic species characterized by exaggerated male ornamentation, behavioral isolation is often attributed to female preferences for conspecific male signals. Yet, in a number of sexually dimorphic species, male mate choice also results in behavioral isolation. In many of these cases, the female traits that mediate species boundaries are unclear. Females in sexually dimorphic species typically lack many of the elaborate traits that are present in males and that are often diagnostic of species. In a diverse and largely sexually dimorphic group of fishes called darters (Percidae:Etheostoma), male mate choice contributes to behavioral isolation between a number of species; however, it is not clear which female traits males prefer. In the current study, we identified the dominant female pattern for two sympatric species,Etheostoma zonaleandE. barrenense, using pattern energy analysis, and we used discriminate function analysis to identify which aspects of female patterning can reliably classify species. We then tested the role of female features in male mate choice forE. zonale, by measuring male preference for computer animations displaying the identified (species-specific) conspecific features as well as the dominant male pattern that is preferred by females. We found that the region above the lateral line is important in mediating male mate preferences, with males spending significantly more time with animations exhibiting conspecific female patterning in this region than with animations exhibiting heterospecific female patterning. Our results suggest that the aspects of female phenotypes that are the target of male mate choice are different from the male phenotypes that characterize species. This research highlights the importance of using objective measures in the study of behavioral isolation via male mate choice.
PanGIA: A Metagenomics Analytical Framework for Routine Biosurveillance and Clinical Pathogen Detection
Authors: Li Po-E , Russell Joseph A. , Yarmosh David , Shteyman Alan G. , Parker Kyle , Wood Hillary , Aspinwall J.R. , Winegar Richard , Davenport Karen , Lo Chien-chi , Bagnoli John , Davis Phillip , Jacobs Jonathan L. , Chain Patrick S.G. 
Published: April 2020

ABSTRACTMetagenomics is emerging as an important tool in biosurveillance, public health, and clinical applications. However, ease-of-use for execution and data analysis remains a barrier-of-entry to the adoption of metagenomics in applied health and forensics settings. In addition, these venues often have more stringent requirements for reporting, accuracy, and precision than the traditional ecological research role of the technology. Here, we present PanGIA (Pan-Genomics forInfectiousAgents), a novel bioinformatics analysis platform for hosting, processing, analyzing, and reporting shotgun metagenomics data of complex samples suspected of containing one or more pathogens. PanGIA was developed to address gaps that often preclude clinicians, medical technicians, forensics personnel, or other non-expert end-users from the routine application of metagenomics for pathogen identification. Though primarily designed to detect pathogenic microorganisms within clinical and environmental metagenomics data, PanGIA also serves as an analytical framework for microbial community profiling and comparative metagenomics. To provide statistical confidence in PanGIA’s taxonomic assignments, the system provides two independent estimations of probability for species and strain level detection. First, PanGIA integrates coverage data with ‘uniqueness’ information mapped across each reference genome for a stand-alone determination of confidence for each query sequence at each taxonomy level. Second, if a negative-control sample is provided, PanGIA compares this sample with a corresponding experimental unknown sample and determines a measure of confidence associated with ‘detection above background’. An integrated graphical user interface allows interactive interrogation and enables users to summarize multiple sample results by confidence score, normalized read abundance, reference genome linear coverage, depth-of-coverage, RPKM, and other metrics to detect specific organisms-of-interest. Comparison testing of the PanGIA algorithm against a number of recent k-mer, read-mapping, and marker-gene based taxonomy classifiers across various real-world datasets with spiked targets shows superior mean positive predictive value, sensitivity, and specificity. PanGIA can process a five million paired-end read dataset in under 1 hour on commodity computational hardware. The source code and documentation are publicly available athttps://github.com/LANL-Bioinformatics/PanGIAorhttps://github.com/mriglobal/PanGIA. The database for PanGIA can be downloaded fromftp://bioinformatics.mriglobal.org/. The full GUI-based PanGIA analysis environment is available in a Docker container and can be installed fromhttps://hub.docker.com/r/poeli/pangia/.
Greater local diversity under older species pools may arise from enhanced competitive equivalence
Authors: Leopold Devin R. , Fukami Tadashi 
Published: April 2020

AbstractLocal ecological communities tend to contain more species when they are located within a geologically older region, a pattern that has traditionally been attributed to the accumulation of species in the regional species pool. In this explanation, local species interactions are assumed to play a minor role in the formation of the regional species pool, which is instead thought to be driven by speciation and dispersal occurring across larger areas. Here, we provide evidence suggesting a more important role of local species interactions than generally assumed. In an experiment in which we assembled 320 local communities of root-associated fungi under 80 species pools, we varied the species richness of the experimental species pools and the mean age of the sites from which we collected the fungal species across a 4-myr soil chronosequence in Hawaii. We found that realized local species diversity in the assembled communities increased more extensively with increasing species-pool richness when species were from older sites. We also found that older species pools had lower functional and phylogenetic diversity, indicating that the evolution of greater competitive equivalence among potential colonists enabled higher local diversity under older species pools. Our results suggest that the tendency of older regions to have higher local richness arises not simply because older species pools are more speciose, but also because the constituent species have evolved traits that allow them to co-occur more readily in local communities.
Candida aurisphenotypic heterogeneity determines pathogenicityin vitro
Authors: Brown Jason L , Delaney Chris , Short Bryn , Butcher Mark C , McKloud Emily , Williams Craig , Kean Ryan , Ramage Gordon 
Published: April 2020

AbstractCandida aurisis an enigmatic yeast that provides substantial global risk in healthcare facilities and intensive care units. A unique phenotype exhibited by certain isolates ofC. aurisis their ability to form small clusters of cells known as aggregates, which have been to a limited extent described in the context of pathogenic traits. In this study, we screened several non-aggregative and aggregativeC. aurisisolates for biofilm formation, where we observed a level of heterogeneity amongst the different phenotypes. Next, we utilised an RNA-sequencing approach to investigate the transcriptional responses during biofilm formation of a non-aggregative and aggregative isolate of the initial pool. Observations from these analyses indicate unique transcriptional profiles in the two isolates, with several genes identified relating to proteins involved in adhesion and invasion of the host in other fungal species. From these findings we investigated for the first time the fungal recognition and inflammatory responses of a three-dimensional skin epithelial model to these isolates. In these models, a wound was induced to mimic a portal of entry forC. auris. We show both phenotypes elicited minimal response in the model minus induction of the wound, yet in the wounded tissue both phenotypes induced a greater response, with the aggregative isolate more pro-inflammatory. This capacity of aggregativeC. aurisbiofilms to generate such responses in the wounded skin highlights how this opportunistic yeast is a high risk within the intensive care environment where susceptible patients have multiple indwelling lines.ImportanceCandida aurishas recently emerged as an important cause of concern within healthcare environments due to its ability to persist and tolerate commonly used antiseptics and disinfectants, particularly when surface attached (biofilms). This yeast is able to colonise and subsequently infect patients, particularly those that are critically ill or immunosuppressed, which may result in death. We have undertaken analysis on two different types of this yeast, using molecular and immunological tools to determine whether either of these has a greater ability to cause serious infections. We describe that both isolates exhibit largely different transcriptional profiles during biofilm development. Finally, we show that the inability to form small aggregates (or clusters) of cells has an adverse effect on the organisms immuno-stimulatory properties, suggestive the non-aggregative phenotype may exhibit a certain level of immune evasion.
Astrocytes and neurons share brain region-specific transcriptional signatures
Authors: Herrero-Navarro Álvaro , Puche-Aroca Lorenzo , Moreno-Juan Verónica , Sempere-Ferràndez Alejandro , Espinosa Ana , Susín Rafael , Torres-Masjoan Laia , Leyva-Díaz Eduardo , Karow Marisa , Figueres-Oñate María , López-Mascaraque Laura , López-Atalaya José P. , Berninger Benedikt , López-Bendito Guillermina 
Published: April 2020

SUMMARYNeuronal cell diversity is essential to endow distinct brain regions with specific functions. During development, progenitors within these regions are characterised by specific gene expression programs, contributing to the generation of diversity in postmitotic neurons and glia. While the region-specific molecular diversity of neurons and astrocytes is increasingly understood, whether these cells share region-specific programs remains unknown. Here, we show that in the neocortex and thalamus, neurons and astrocytes express shared region-specific transcriptional and epigenetic signatures. These signatures not only distinguish cells across brain regions but are also detected across substructures within regions, such as distinct thalamic nuclei, where clonal analysis revealed the existence of common nucleus-specific progenitors for neurons and glia. Consistent with their shared molecular signature, regional specificity was maintained following astrocyte-to-neuron reprogramming. A detailed understanding of these regional-specific signatures may thus inform strategies for future cell-based brain repair.
Determining the Depth Limit of Bioluminescent Sources in Scattering Media
Authors: Raghuram Ankit , Ye Fan , Adams Jesse K. , Shaner Nathan , Robinson Jacob T. , Veeraraghavan Ashok 
Published: April 2020

AbstractBioluminescence has several potential advantages compared to fluorescence microscopy forin vivobiological imaging. Because bioluminescence does not require excitation light, imaging can be performed for extended periods of time without phototoxicity or photobleaching, and optical systems can be smaller, simpler, and lighter. Eliminating the need for excitation light may also affect how deeply one can image in scattering biological tissue, but the imaging depth limits for bioluminescence have yet to be reported. Here, we perform a theoretical study of the depth limits of bioluminescence microscopy and find that cellular resolution imaging should be possible at a depth of 5-10 mean free paths (MFPs). This limit is deeper than the depth limit for confocal microscopy and slightly lower than the imaging limit expected for two-photon microscopy under similar conditions. We also validate our predictions experimentally using tissue phantoms. Overall we show that with advancements in the brightness of bioluminescent indicators, it should be possible to achieve deep, long-term imaging in biological tissue with cellular resolution.
The environment-sensing aryl-hydrocarbon receptor inhibits the chondrogenic fate of modulated smooth muscle cells in atherosclerotic lesions
Authors: Kim Juyong Brian , Zhao Quanyi , Nguyen Trieu , Pjanic Milos , Cheng Paul , Wirka Robert , Nagao Manabu , Kundu Ramendra , Quertermous Thomas 
Published: April 2020

AbstractIntroductionSmooth muscle cells (SMC) play a critical role in atherosclerosis. The Aryl hydrocarbon receptor (AHR) is an environment-sensing transcription factor that contributes to vascular development, and has been implicated in coronary artery disease (CAD) risk. We hypothesized that AHR can affect atherosclerosis by regulating phenotypic modulation of SMC.MethodsWe combined RNA-Seq, ChIP-Seq, ATAC-Seq and in-vitro assays in human coronary artery SMC (HCASMC), with single-cell RNA-Seq (scRNA-Seq), histology, and RNAscope in an SMC-specific lineage-tracingAhrknockout mouse model of atherosclerosis to better understand the role ofAHRin vascular disease.ResultsGenomic studies coupled with functional assays in cultured HCASMC revealed thatAHRmodulates HCASMC phenotype and suppresses ossification in these cells. Lineage tracing and activity tracing studies in the mouse aortic sinus showed that theAhrpathway is active in modulated SMC in the atherosclerotic lesion cap. Furthermore, scRNA-Seq studies of the SMC-specific Ahr knockout mice showed a significant increase in the proportion of modulated SMC expressing chondrocyte markers such asCol2a1andAlpl, which localized to the lesion neointima. These cells, which we term “chondromyocytes” (CMC), were also identified in the neointima of human coronary arteries. In histological analyses, these changes manifested as larger lesion size, increased lineage-traced SMC participation in the lesion, decreased lineage-traced SMC in the lesion cap, and increased alkaline phosphatase activity in lesions in theAhrknockout compared to wild-type mice. We propose thatAHRis likely protective based on these data and inference from human genetic analyses.ConclusionOverall, we conclude thatAHRpromotes maintenance of lesion cap integrity and diminishes the disease related SMC-to-CMC transition in atherosclerotic tissues.
Modeling robust and efficient coding in the mouse primary visual cortex using computational perturbations
Authors: Cai Binghuang , Billeh Yazan N. , Chettih Selmaan N. , Harvey Christopher D. , Koch Christof , Arkhipov Anton , Mihalas Stefan 
Published: April 2020

AbstractInvestigating how visual inputs are encoded in visual cortex is important for elucidating the roles of cell populations in circuit computations. We here use a recently developed, large-scale model of mouse primary visual cortex (V1) and perturb both single neurons as well as functional- and cell-type defined population of neurons to mimic equivalent optogenetic perturbations. First, perturbations were performed to study the functional roles of layer 2/3 excitatory neurons in inter-laminar interactions. We observed activity changes consistent with the canonical cortical model (Douglas and Martin 1991). Second, single neuron perturbations in layer 2/3 revealed a center-surround inhibition-dominated effect, consistent with recent experiments. Finally, perturbations of multiple excitatory layer 2/3 neurons during visual stimuli of varying contrasts indicated that the V1 model has both efficient and robust coding features. The circuit transitions from predominantly broad like-to-like inhibition at high contrasts to predominantly specific like-to-like excitation at low contrasts. Thesein silicoresults demonstrate how the circuit can shift from redundancy reduction to robust codes as a function of stimulus contrast.