bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine learning approach for the spatiotemporal forecasting of ecological phenomena using dates of species occurrence records
Authors: Capinha César 
Published: October 2018

AbstractSpatiotemporal forecasts of ecological phenomena are highly useful and significant in scientific and socio-economic applications. Nevertheless, developing the correlative models to make these forecasts is often stalled by the inadequate availability of the ecological time-series data. On the contrary, considerable amounts of temporally discrete biological records are being stored in public databases, and often include the sites and dates of the observation. While these data are reasonably suitable for the development of spatiotemporal forecast models, this possibility remains mostly untested.In this paper, we test an approach to develop spatiotemporal forecasts based on the dates and locations found in species occurrence records. This approach is based on ‘time-series classification’, a field of machine learning, and involves the application of a machine-learning algorithm to classify between time-series representing the environmental conditions that precede the occurrence records and time-series representing other environmental conditions, such as those that generally occur in the sites of the records. We employed this framework to predict the timing of emergence of fruiting bodies of two mushroom species (Boletus edulis and Macrolepiota procera) in countries of Europe, from 2009 to 2015. We compared the predictions from this approach with those from a ‘null’ model, based on the calendar dates of the records.Forecasts made from the environmental-based approach were consistently superior to those drawn from the date-based approach, averaging an area under the receiver operating characteristic curve (AUC) of 0.9 for B. edulis and 0.88 for M. procera, compared to an average AUC of 0.83 achieved by the null models for both species. Prediction errors were distributed across the study area and along the years, lending support to the spatiotemporal representativeness of the values of accuracy measured.Our approach, based on species occurrence records, was able to provide useful forecasts of the timing of emergence of two mushroom species across Europe. Given the increased availability and information contained in this type of records, particularly those supplemented with photographs, the range of events that could be possible to forecast is vast.
Use of a filter cartridge combined with intra-cartridge bead beating improves detection of microbial DNA from water samples
Authors: Ushio Masayuki 
Published: October 2018

AbstractMicrobial communities play an important role in driving the dynamics of aquatic ecosystems. As difficulties in DNA sequencing faced by microbial ecologists are continuously being reduced, sample collection methods and the choice of DNA extraction protocols are becoming more critical to the outcome of any sequencing study. In the present study, I added a manual, intra-cartridge, bead-beating step in the protocol using a DNeasy® Blood & Tissue kit for DNA extraction from a filter cartridge (Sterivex™ filter cartridge) with-out breaking the cartridge unit (“Beads” method), and compared its performance with those of two other protocols that used the filter cartridge (“NoBeads” method, which was similar to the Beads method but without the bead-beating step, and “PowerSoil” method, which followed the manual of the DNeasy® PowerSoil DNA extraction kit after breaking apart the filter cartridge). Water samples were collected from lake, river, pond and coastal ecosystems in Japan, and DNA was extracted using the three protocols. Then, the V4 region of prokaryotic 16S rRNA genes was amplified. In addition, internal standard DNAs were included in the DNA library preparation process to estimate the number of 16S rRNA gene copies. The DNA library was sequenced using Illumina MiSeq, and sequences were analyzed using the amplicon sequence variant (ASV) approach implemented in the DADA2 pipeline. I found that, 1) the total prokaryotic DNA yields were highest with the Beads method, 2) the number of ASVs (a proxy for species richness) was also highest with the Beads method, 3) overall community compositions were significantly different among the three methods, and 4) the number of method-specific ASVs was highest with the Beads method. These results were generally robust across samples from all aquatic ecosystems examined. In conclusion, the inclusion of a bead-beating step performed inside the filter cartridge increased the DNA yield as well as the number of prokaryotic ASVs detected compared with the other two methods. Performing the bead-beating step inside the filter cartridge causes no dramatic increase in either handling time or processing cost and it can reduce the potential contamination risk from the ambient air and/or other samples. Therefore, this method has the potential to become one of the major choices when one aims to extract aquatic microbial DNAs.
Starless bias and parameter-estimation bias in the likelihood-based phylogenetic method
Authors: Xia Xuhua 
Published: October 2018

ABSTRACTI analyzed various site pattern combinations in a 4-OTU case to identify sources of starless bias and parameter-estimation bias in likelihood-based phylogenetic methods, and reported three significant contributions. First, the likelihood method is odd in that it may not generate a star tree with sequences that are equidistant from each other. This behaviour, dubbed starless bias, happens in a 4-OTU tree when there is an excess (i.e., more than expected from a star tree and a substitution model) of conflicting phylogenetic signals supporting the three resolved topologies equally. Special site pattern combinations leading to rejection of a star tree, when sequences are equidistant from each other, were identified. Second, fitting gamma distribution to model rate heterogeneity over sites is strongly confounded with tree topology, especially in conjunction with the starless bias. I present examples to show dramatic differences in the estimated shape parameter α between a star tree and a resolved tree. There may be no rate heterogeneity over sites (with the estimated α > 10000) when a star tree is imposed, but α < 1 (suggesting strong rate heterogeneity over sites) when an (incorrect) resolved tree is imposed. Thus, the dependence of “rate heterogeneity” on tree topology implies that “rate heterogeneity” is not a sequence-specific feature, cautioning against interpreting a small α to mean that some sites are under strong purifying selection and others not. Thirdly, because there is no existing (and working) likelihood method for evaluating a star tree with continuous gamma-distributed rate, I have implemented the method for JC69 in a self-contained R script for a four-OTU tree (star or resolved), in addition to another R script assuming a constant rate over sites. These R scripts should be useful for teaching and exploring likelihood methods in phylogenetics.
Variable Effects on Growth and Defence Traits for Plant Ecotypic Differentiation and Phenotypic Plasticity along Elevation Gradients
Authors: Bakhtiari Moe , Formenti Ludovico , Caggía Veronica , Glauser Gaëtan , Rasmann Sergio 
Published: October 2018

AbstractAlong ecological gradients, ecotypes generally evolve as the result of local adaptation to a specific environment to maximize organisms’ fitness. Alongside ecotypic differentiation, phenotypic plasticity, as the ability of a single genotype to produce different phenotypes under different environmental conditions, can also evolve for favouring increased organisms’ performance in different environments. Currently, there is a lack in our understanding of how varying habitats may contribute to the differential contribution of ecotypic differentiation and plasticity in growth versus defence traits. Using reciprocal transplant-common gardens along steep elevation gradients, we evaluated patterns of ecotypic differentiation and phenotypic plasticity of two coexisting but unrelated plant species,Cardamine pratensisandPlantago major. For both species, we observed ecotypic differentiation accompanied by plasticity in growth related traits. Plants grew faster and produced more biomass when placed at low elevation. In contrast, we observed fixed ecotypic differentiation for defence and resistance traits. Generally, low elevation ecotypes produced higher chemical defences regardless of the growing elevation. Yet, some plasticity was observed for specific compounds, such as indole glucosinolates. We speculate that ecotypic differentiation in defence traits is maintained by costs of chemical defence production, while plasticity in growth traits is regulated by temperature driven growth response maximization.
Interference with HIV infection of the first cell is essential for viral clearance in a pre-exposure prophylaxis model
Authors: De Las Muelas Ana Moyano , Lustig Gila , Rodel Hylton E. , Antal Tibor , Sigal Alex 
Published: October 2018

AbstractPre-exposure prophylaxis (PrEP) uses relatively weak HIV inhibition to reduce transmission between individuals. Why this approach is successful is unclear. Here we derive and experimentally validate a mathematical model for predicting infection clearance with PrEP based on the measured effect of a drug on the HIV replication ratio and number of initial infected cells. We tested the model by inhibiting low dose HIV infection with tenofovir, which reduces infection frequency per cell, and atazanavir, which reduces the cellular burst size of viable virions. Both drugs were at concentrations which allowed similar HIV replication. Reducing infection frequency dramatically increased infection clearance, while reducing burst size did not. This indicates that initial infection is vulnerable to inhibition before it infects the first cell, but not thereafter. Our model explains why PrEP is potent at drug concentrations which are ineffective against established infection, and provides a framework to test drug effectiveness for PrEP.
Interactions of nuclear transport factors and surface-conjugated FG nucleoporins: Insights and limitations
Authors: Hayama Ryo , Sorci Mirco , Keating John J. , Hecht Lee M. , Plawsky Joel L. , Belfort Georges , Chait Brian T. , Rout Michael P. 
Published: October 2018

ABSTRACTProtein-protein interactions are central to biological processes and the methods to thoroughly characterize them are of great interest.In vitromethods to examine protein-protein interactions are generally categorized into two classes: in-solution and surface-based methods. Here, using the multivalent interactions involved in nucleocytoplasmic transport as a model system, we examined the utility of three surface-based methods in characterizing rapid interactions involving intrinsically disordered proteins: atomic force microscopy, quartz crystal microbalance with dissipation, and surface plasmon resonance. Although results were comparable to those of previous reports, the existence of previously overlooked mass transport limitations was revealed. Additional experiments with a loss-of-interaction mutant variant demonstrated the existence of additional physical events and an uncharacterized binding mode. These results suggest the binding events that take place on the surface are more complex than initially assumed, prompting a need for re-interpretation of previous data.
Population receptive field estimates for motion-defined stimuli
Authors: Hughes Anna E. , Greenwood John A. , Finlayson Nonie J. , Schwarzkopf D. Samuel 
Published: October 2018

AbstractThe processing of motion changes throughout the visual hierarchy, from spatially restricted ‘local motion’ in early visual cortex to more complex large-field ‘global motion’ at later stages. Here we used functional magnetic resonance imaging (fMRI) to examine spatially selective responses in these areas related to the processing of random-dot stimuli defined by differences in motion. We used population receptive field (pRF) analyses to map retinotopic cortex using bar stimuli comprising coherently moving dots. In the first experiment, we used three separate background conditions: no background dots (dot-defined bar-only), dots moving coherently in the opposite direction to the bar (kinetic boundary) and dots moving incoherently in random directions (global motion). Clear retinotopic maps were obtained for the bar-only and kinetic-boundary conditions across visual areas V1-V3 and in higher dorsal areas. For the global-motion condition, retinotopic maps were much weaker in early areas and became clear only in higher areas, consistent with the emergence of global-motion processing throughout the visual hierarchy. However, in a second experiment we demonstrate that this pattern is not specific to motion-defined stimuli, with very similar results for a transparent-motion stimulus and a bar defined by a static low-level property (dot size) that should have driven responses particularly in V1. We further exclude explanations based on stimulus visibility by demonstrating that the observed differences in pRF properties do not follow the ability of observers to localise or attend to these bar elements. Rather, our findings indicate that dorsal extrastriate retinotopic maps may primarily be determined by the visibility of the neural responses to the bar relative to the background response (i.e. neural signal-to-noise ratios) and suggests that claims about stimulus selectivity from pRF experiments must be interpreted with caution.
Islet Gene View - a tool to facilitate islet research
Authors: Asplund Olof , Storm Petter , Chandra Vikash , Ottosson-Laakso Emilia , Hatem Gad , Mansour-Aly Dina , Krus Ulrika , Ibrahim Hazem , Ahlqvist Emma , Tuomi Tiinamaija , Renström Erik , Korsgren Olle , Wierup Nils , Wollheim Claes , Artner Isabella , Mulder Hindrik , Hansson Ola , Otonkoski Timo , Groop Leif , Prasad Rashmi B ,   on behalf of the Human Tissue Laboratory at Lund University Diabetes Centre
Published: October 2018

AbstractChanges in the hormone-producing pancreatic islets are central culprits in type 2 diabetes (T2D) pathogenesis. Characterization of gene expression in islets how it is altered in T2D are therefore vital in understanding islet function and T2D pathogenesis. We leveraged RNA-sequencing and genome-wide genotyping in islets from 188 donors to create the Islet Gene View (IGW) platform to make this information easily accessible to the scientific community. The IGW combines expression data for a given gene with phenotypical data such as T2D status, BMI, HbA1c, insulin secretion, purity of islets, etc.), regulation of gene expression by genetic variants e.g., expression quantitative trait loci (eQTLs) and relationship with expression of islet hormones. In IGW, 285 differentially expressed genes (DEGs) were identified in T2D donors islets compared to controls. Forty percent of the DEGs showed cell-type enrichment and a large proportion of them were significantly co-expressed with islet hormone-encoding genes like glucagon (GCG, 56%), amylin (IAPP, 52%), insulin (INS, 44%) and somatostatin (SST, 24%). Inhibition of two DEGs, UNC5D and SERPINE2 impaired glucose-stimulated insulin secretion and impacted cell survival in a human beta-cell model.Significance StatementWe present Islet Gene View (IGW), a web resource facilitating information on gene expression in human pancreatic islets from organ donors easily accessible to the scientific community. In IGW, we explored RNA expression from 188 donor-islets and examined their relationship with islet phenotypes including insulin secretion and expression of genes encoding islet hormones. GWAS have shown 403 genetic variants associated with risk of type 2 diabetes (T2D) risk, however, the target genes and function of these variants in islets are largely unknown. By linking T2D risk variants to expression in islets from T2D and non-diabetic donors as well as islet phenotypes, use of IGW provided new insight into mechanisms by which variants in these loci may increase risk of T2D.
Mosquito Transmission and Human Hepatocyte Infections With Plasmodium ovale curtisi and P. ovale wallikeri
Authors: Kristan Mojca , Thorburn Samuel G. , Hafalla Julius , Sutherland Colin J. , Oguike Mary C. 
Published: October 2018

ABSTRACTHuman ovale malaria is caused by the two closely related species Plasmodium ovale curtisi and P. ovale wallikeri. Both species are known to relapse from quiescent hepatic forms months or years after the primary infection occurred. Although some studies have succeeded in establishing mosquito transmission for ovale malaria, none have specifically described transmission and human hepatocyte infection of both sibling species. Here we describe a simplified protocol for successful transmission of both P. ovale curtisi and P. ovale wallikeri to Anopheles coluzzii mosquitoes, and streamlined monitoring of infection using sensitive parasite DNA detection, by loop-activated amplification, in blood-fed mosquitoes. In one experimental infection with P. ovale curtisi and one with P. ovale wallikeri, viable sporozoites were isolated from mosquito salivary glands, and used to successfully infect cultured human hepatocytes. This protocol provides a method for the utilisation of pre-treatment clinical blood samples from ovale malaria patients, collected in EDTA, for mosquito infection studies and generation of the hepatic life cycle stages of P. ovale curtisi and P. ovale wallikeri. We also demonstrate the utility of LAMP as a rapid and sensitive alternative to dissection for estimating the prevalence of infection in Anopheles mosquitoes fed with Plasmodium-infected blood.
Rapid bacterial identification by direct PCR amplification of 16S rRNA genes using the MinIONTMnanopore sequencer
Authors: Kai Shinichi , Matsuo Yoshiyuki , Nakagawa So , Kryukov Kirill , Matsukawa Shino , Tanaka Hiromasa , Iwai Teppei , Imanishi Tadashi , Hirota Kiichi 
Published: October 2018

AbstractRapid identification of bacterial pathogens is crucial for appropriate and adequate antibiotic treatment, which significantly improves patient outcomes. 16S ribosomal RNA (rRNA) gene amplicon sequencing has proven to be a powerful strategy for diagnosing bacterial infections. We have recently established a sequencing method and bioinformatics pipeline for 16S rRNA gene analysis utilizing the Oxford Nanopore Technologies MinION™ sequencer. In combination with our taxonomy annotation analysis pipeline, the system enabled the molecular detection of bacterial DNA in a reasonable timeframe for diagnostic purposes. However, purification of bacterial DNA from specimens remains a rate-limiting step in the workflow. To further accelerate the process of sample preparation, we adopted a direct PCR strategy that amplifies 16S rRNA genes from bacterial cell suspensions without DNA purification. Our results indicate that differences in cell wall morphology significantly affect direct PCR efficiency and sequencing data. Notably, mechanical cell disruption preceding direct PCR was indispensable for obtaining an accurate representation of the specimen bacterial composition. Furthermore, 16S rRNA gene analysis of mock polymicrobial samples indicated that primer sequence optimization is required to avoid preferential detection of particular taxa and to cover a broad range of bacterial species. This study establishes a relatively simple workflow for rapid bacterial identification via MinIONTMsequencing, which reduces the turnaround time from sample to result, and provides a reliable method that may be applicable to clinical settings.
16S rRNA:rDNA ratios and cell activity staining reveal consistent patterns of soil microbial activity
Authors: Bowsher Alan W. , Kearns Patrick J. , Shade Ashley 
Published: October 2018

AbstractMicrobial activity plays a major role in the processes that support life on Earth. Nevertheless, across diverse ecosystems many microbes are in a state of dormancy, characterized by strongly reduced metabolic rates. Of the methods used to assess microbial activity-dormancy dynamics, 16S rRNA: rDNA amplicons (“16S ratios”) and active cell staining with 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) are two of the most common, yet each method has its own limitations. To better understand the applicability and potential complementarity of these two methods, we conducted two experiments investigating microbial activity in the rhizosphere. In the first experiment, we treated corn rhizosphere soil with common phytohormones to simulate plant-soil signaling during plant stress, and in the second experiment, we used bean exposed to drought or nutrient enrichment to more directly assess the impacts of plant stress on soil microbial activity. Overall, 16S ratios revealed numerous taxa with detectable RNA but no detectable DNA. However, overarching patterns in percent activity across treatments were unaffected by the method used to account for active taxa, or by the threshold 16S ratio used for taxa to be classified as active. 16S ratio distributions were highly similar across microbial phyla and were only weakly correlated with ribosomal operon number. Lastly, over relatively short time courses, 16S ratios are responsive earlier than CTC staining, a finding potentially related to the temporal sensitivity of activity changes detectable by the two methods. Our results suggest that 16S ratios and CTC staining provide robust and complementary estimates of bulk community activity.ImportanceAlthough the majority of microorganisms in natural ecosystems are dormant, relatively little is known about the dynamics of the active and dormant microbial pools through both space and time. The limited knowledge of microbial activity-dormancy dynamics is in part due to uncertainty in the methods currently used to quantify active taxa. Here, we directly compared two of the most common methods (16S ratios and active cell staining) for estimating microbial activity in rhizosphere soil, and found that they were largely in agreement in the overarching patterns, suggesting that either method is robust for assessing comparative activity dynamics. Thus, our results suggest that 16S ratios and active cell staining provide robust and complementary information for measuring and interpreting microbial activity-dormancy dynamics in soils. They also support that 16S rRNA:rDNA ratios have comparative value and offer a high-throughput, sequencing-based option for understanding relative changes in microbiome activity.