bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemical depletion of phagocytic immune cells reveals dual roles of mosquito hemocytes in Anopheles gambiae anti-Plasmodium immunity
Authors: Kwon Hyeogsun , Smith Ryan C. 
Published: September 2018

AbstractMosquito innate immunity is comprised of both cellular and humoral factors that provide protection from invading pathogens. Immune cells, known as hemocytes, have been intricately associated with these immune responses through direct roles in phagocytosis and immune signaling. Recent studies have implicated hemocytes as integral determinants of anti-Plasmodium immunity, yet little is known regarding the specific mechanisms by which hemocytes limit malaria parasite survival. With limited genetic tools to enable their study, we employed a chemical-based treatment widely used for macrophage depletion in mammalian systems for the first time in an invertebrate organism. Upon its application in Anopheles gambiae, we observe distinct populations of phagocytic immune cells that are significantly depleted, causing high mortality following bacterial challenge and an increased intensity of malaria parasite infection. Through these studies, we demonstrate that phagocytes are required for mosquito complement recognition of invading ookinetes, as well as the production of prophenoloxidases that limit oocyst survival. Through these experiments, we also define specific sub-types of phagocytic immune cells in An. gambiae, providing new insights beyond the morphological characteristics that traditionally define mosquito hemocyte populations. Together, this study provides the first definitive insights into the dual roles of mosquito phagocytes in limiting malaria parasite survival, and illustrates the use of clodronate liposomes as an important advancement in the study of invertebrate immunity.
Differential expression and homotypic enrichment of a classic Cadherin directs tissue-level contractile asymmetry during neural tube closure
Authors: Hashimoto Hidehiko , Munro Edwin 
Published: September 2018

SummaryEmbryos pattern force generation at tissue boundaries during morphogenesis, but how they do so remains poorly understood. Here we show how tissue-specific expression of the type II cadherin, Cadherin2 (hereafter Cad2), patterns actomyosin contractility along the neural/epidermal (Ne/Epi) boundary to drive zippering and neural tube closure in the basal chordate,Ciona robusta. Cad2 is differentially expressed and homotypically enriched in neural cells along the Ne/Epi boundary, where RhoA and Myosin are activated during zipper progression. Equalizing Cad2 expression across the Ne/Epi boundary inhibits RhoA/Myosin activation and zipper progression, while creating ectopic Cad2 expression boundaries is sufficient to direct RhoA/Myosin activity to those boundaries. We show that Cad2 polarizes RhoA activity by sequestering the Rho GTPase activating protein, Gap21/23, to homotypic junctions, which in turn redirects RhoA/Myosin activity to heterotypic Ne/Epi junctions. By activating Myosin II along Ne/Epi junctions ahead of zipper and inhibiting Myosin II at new Ne/Ne junctions behind zipper, Cad2 promotes tissue level contractile asymmetry to drive zipper progression.
The impact of a reduced calorie, macronutrient diet change on Caucasian males in relation to genotypes associated with obesity, increased BMI and dietary response
Authors: Ellis L , Collins C. 
Published: September 2018

AbstractObesity is a growing crisis within the 1st world and the causes of obesity are well studied: a lack of physical activity combined with an increased calorie intake. This energy imbalance leads to fat accumulation leading to eventual obesity. Whilst the cause may appear clear, the options of lifestyle change and/or diet planning that is efficient with effective sustainability has been harder to come by. Genetic variants linked to obesity may hold clues on how to best customise a diet plan to an individual leading to an easier to change lifestyle with better sustainability. This study aimed to find correlations with a diet change that decreased kcal intake by 200kcal per day with a macronutrient alteration (decreased carbohydrates and increased unsaturated fat) and genetic components to discover responders and non-responders. Within the study group of Caucasian males the genes TCF7L2, TFAP2B, PPARG2 and FTO all impacted the response of the dietary intervention. In conclusion it would be prudent to consider DNA analysis as part of a battery of diet and lifestyle tests to personalise a sustainable and effective lifestyle/dietary intervention to help control weight.
Pathway analysis of GWAS loci identifies novel drug targets and repurposing opportunities
Authors: Jhamb Deepali , Magid-Slav Michal , Hurle Mark R. , Agarwal Pankaj 
Published: September 2018

AbstractGenome-wide association studies (GWAS) have made considerable progress and there is emerging evidence that genetics-based targets can lead to 28% more launched drugs. However, translating the results of GWAS for drug discovery remains challenging. We analyzed 1,589 GWAS across 1,456 protein interaction pathways to translate these often, imprecise genetic loci into therapeutic hypotheses for 182 diseases. We validate these pathway-based genetic targets by testing if current drug targets are enriched in the pathway space of the same indication. Remarkably, 30% of diseases have significantly more targets in these pathways than expected by chance; the comparable number for GWAS alone (without using pathway analysis) is zero. Although pathway analysis is routine for GWAS, this study shows that the routine analysis can often enrich for drug targets, by performing a systematic global analysis to translate genetic findings into therapeutic hypotheses for new drug discovery and repositioning opportunities for current drugs.
The diurnal transcriptional landscape of the microalga Tetradesmus obliquus
Authors: Carreres Benoit M. , León-Saiki G. Mitsue , Schaap Peter J. , Remmers Ilse M. , van der Veen Douwe , Martins dos Santos Vitor A.P. , Wijffels René H. , Martens Dirk E. , Suarez-Diez Maria 
Published: September 2018

AbstractTetradesmus obliquus is a promising oleaginous microalga. We functionally annotated its genome and characterized the transcriptional landscape of T. obliquus adapted to 16:8h light dark (LD) cycles in turbidostat culture conditions at very high temporal resolution (1h intervals). Revealing a cycle of cellular events, six distinct expression profiles were obtained, each with transcriptional phenotypes correlating with measurements of biochemical composition.The impact of starch deficiency was studied using the starchless mutant slm1. Significant changes in the transcriptional landscape were observed. Starch deficiency resulted in incapacity to supply energy during dark period, resulting in early or late time shift for energy demanding processes. Our study provides new perspectives on the role of starch and the adaptation to LD cycles of oleaginous microalgae.
Molecular Screening of Familial Hypercholesterolemia in the Icelandic Population
Authors: Kellogg Greg , Thorsson Bolli , Cai Ying , Wisotzkey Robert , Pollock Andrew , Akana Matthew , Fox Rebecca , Jansen Michael , Gudmundsson Elias F. , Patel Bonny , Chang Chihyu , Jaremko Malgorzata , Emilsson Valur , Gudnason Vilmundur , Puig Oscar 
Published: September 2018

AbstractFamilial hypercholesterolemia (FH) is a monogenic disease characterized by a lifelong exposure to high LDL-C levels that can lead to early onset coronary heart disease (CHD). The main causes of FH identified to date include loss-of-function mutations in LDLR or APOB, or gain-of-function mutations in PCSK9. Early diagnosis and genetic testing of FH suspects is critical for improved prognosis of affected individuals as lipid lowering treatments are effective in preventing CHD related morbidity and mortality. In the present manuscript, we developed a comprehensive next generation sequencing (NGS) panel which we applied on two different resources of FH in the Icelandic population: 62 subjects from 23 FH families with known or unknown culprit mutations, and a population-based sampling of 315 subjects selected for total cholesterol levels above the 95th percentile cut-point. The application of the NGS panel revealed significant diagnostic yields in identifying pathogenic LDLR mutations in both family and population-based genetic testing.
Process-specific somatic mutation distributions vary with three-dimensional genome structure
Authors: Akdemir Kadir C. , Le Victoria T. , Killcoyne Sarah , King Devin A. , Li Ya-Ping , Tian Yanyan , Inoue Akira , Amin Samir , Robinson Frederick S. , Herrera Rafael E. , Lynn Erica J. , Chan Kin , Seth Sahil , Klimczak Leszek J. , Gerstung Moritz , Gordenin Dmitry A. , O’Brien John , Li Lei , Verhaak Roel G. , Campbell Peter , Fitzgerald Rebecca , Morrison Ashby J. , Dixon Jesse R. , Andrew Futreal P. 
Published: September 2018

AbstractSomatic mutations arise during the life history of a cell. Mutations occurring in cancer driver genes may ultimately lead to the development of clinically detectable disease. Nascent cancer lineages continue to acquire somatic mutations throughout the neoplastic process and during cancer evolution (Martincorena and Campbell, 2015). Extrinsic and endogenous mutagenic factors contribute to the accumulation of these somatic mutations (Zhang and Pellman, 2015). Understanding the underlying factors generating somatic mutations is crucial for developing potential preventive, therapeutic and clinical decisions. Earlier studies have revealed that DNA replication timing (Stamatoyannopoulos et al., 2009) and chromatin modifications (Schuster-Böckler and Lehner, 2012) are associated with variations in mutational density. What is unclear from these early studies, however, is whether all extrinsic and exogenous factors that drive somatic mutational processes share a similar relationship with chromatin state and structure. In order to understand the interplay between spatial genome organization and specific individual mutational processes, we report here a study of 3000 tumor-normal pair whole genome datasets from more than 40 different human cancer types. Our analyses revealed that different mutational processes lead to distinct somatic mutation distributions between chromatin folding domains. APOBEC- or MSI-related mutations are enriched in transcriptionally-active domains while mutations occurring due to tobacco-smoke, ultraviolet (UV) light exposure or a signature of unknown aetiology (signature 17) enrich predominantly in transcriptionally-inactive domains. Active mutational processes dictate the mutation distributions in cancer genomes, and we show that mutational distributions shift during cancer evolution upon mutational processes switch. Moreover, a dramatic instance of extreme chromatin structure in humans, that of the unique folding pattern of the inactive X-chromosome leads to distinct somatic mutation distribution on X chromosome in females compared to males in various cancer types. Overall, the interplay between three-dimensional genome organization and active mutational processes has a substantial influence on the large-scale mutation rate variations observed in human cancer.
goCTF: Geometrically optimized CTF determination for single-particle cryo-EM
Authors: Su Min 
Published: September 2018

ABSTRACTPreferred particle orientation represents a recurring problem in single-particle cryogenic electron microcopy (cryo-EM). A specimen-independent approach through tilting has been attempted to increase particle orientation coverage, thus minimizing anisotropic three-dimensional (3D) reconstruction. However, focus gradient is a critical issue hindering tilt applications from being a general practice in single-particle cryo-EM. The present study describes a newly developed geometrically optimized approach, goCTF, to reliably determine the global focus gradient. A novel strategy of determining contrast transfer function (CTF) parameters from a sector of the signal preserved power spectrum is applied to increase reliability. Subsequently, per-particle based local focus refinement is conducted in an iterative manner to further improve the defocus accuracy. Novel diagnosis methods using a standard deviation defocus plot and goodness fitting heatmap have also been proposed to evaluate CTF fitting quality prior to 3D refinement. In a benchmark study, goCTF processed a published single-particle cryo-EM dataset for influenza hemagglutinin trimer collected at a 40-degree specimen tilt. The resulting 3D reconstruction map was improved from 4.1Å to 3.7Å resolution. The goCTF program is built on the open-source code of CTFFIND4, which adopts a consistent user interface ease of use.
NATF (Native And Tissue-specific Fluorescence): A strategy for bright, tissue-specific GFP labeling of native proteins
Authors: He Siwei , Cuentas-Condori Andrea , Miller David M. 
Published: September 2018

ABSTRACTGFP labeling by genome editing can reveal the authentic location of a native protein but is frequently hampered by weak GFP signals and broad expression across a range cell types in multicellular animals. To overcome these problems, we engineered aNativeAndTissue-specific Fluorescence (NATF) strategy which combines CRISPR/Cas-9 and split-GFP to yield bright, cell-specific protein labeling. We use CRISPR/Cas9 to insert a tandem array of seven copies of the GFP11 β-strand (gfp11x7) at the genomic locus of each target protein. The resultantgfp11x7knock-in strain is then crossed with separate reporter lines that express the complementing split-GFP fragment (gfp1-10) in specific cell types thus affording tissue-specific labeling of the target protein at its native level. We show that NATF reveals the otherwise undetectable intracellular location of the immunoglobulin protein, OIG-1, and demarcates a receptor auxiliary protein LEV-10 at cell-specific synaptic domains in theC. elegansnervous system.
A data-driven approach to selecting invited speakers at conferences: a step toward gender parity
Authors: Vallence Ann-Maree , Hinder Mark R , Fujiyama Hakuei 
Published: September 2018

AbstractWe present a data-driven approach that uses established metrics of scientific quality to select invited speakers; this approach enables gender parity in conference programs while ensuring high scientific standards.Gender disparity continues to be an issue in STEM, with progress requiring consistent and focused efforts. Here, we present a data-driven approach to promote high quality, gender balanced invited speaker selection for neuroscience conferences. We have targeted invited speaker opportunities because underrepresentation of female speakers at international neuroscience conferences remains a major problem, and such opportunities are critical for career development. First, we audited the top ten neuroscience journals (indexed by SCImago Journal and Country Rank; SJR), identifying (1) highly cited papers, (2) gender of first and last authors, and (3) field-weighted citation impact and total publications of first and last authors. Second, we used these data to establish a database of high quality scientists that could be used to select speakers for conferences. We found that research quality (as indexed by field-weighted citation impact and total publications) of authors of highly cited publications in the top 10 neuroscience journals did not differ significantly for females and males. The comparison between the gender base rate in neuroscience and authors publishing highly cited papers in high-quality neuroscience journals shows that female representation, particularly at last author level, is less than the estimated base rate for neuroscience. In summary, we present a data-driven approach to invited speaker selection that would facilitate gender balanced conference programs while maintaining the highest of scientific standards. This approach minimizes the influence of implicit gender bias in speaker selection decisions by using scientific quality metrics that STEM researchers are familiar with, and indeed use to evaluate their own performance. Having an immediate effect on reducing gender disparity in conference programs, our approach would generate a positive spiral for more long-term reduction of gender disparity in STEM.
PlotsOfData – a web app for visualizing data together with its summaries
Authors: Postma Marten , Goedhart Joachim 
Published: September 2018

AbstractReporting of the actual data in graphs and plots increases transparency and enables independent evaluation. On the other hand, data summaries are often used in graphs since they aid interpretation. State-of-the art data visualizations can be made with the ggplot2 package, which uses the ideas of a ‘grammar of graphics’ to generate a graphic from multiple layers of data. However, ggplot2 requires coding skills and an understanding of the tidy data structure. To democratize state-of-the-art data visualization of raw data with a selection of statistical summaries, a web app was written using R/shiny that uses the ggplot2 package for generating plots. A multilayered approach together with adjustable transparency offers a unique flexibility, enabling users can to choose how to display the data and which of the data summaries to add. Four data summaries are provided, mean, median, boxplot, violinplot, to accommodate several types of data distributions. In addition, 95% confidence intervals can be added for visual inferences. By adjusting the transparency of the layers, the visualization of the raw data together with the summary can be tuned for optimal presentation and interpretation. The app is dubbed PlotsOfData and is available at: https://huygens.science.uva.nl/PlotsOfData/
Effects of a complex mixture of persistent organic pollutants (POPs) on steroidogenesis in H295R cells under 10 μM forskolin stimulation - results from a pilot study
Authors: Mohammed Ahmed Kareem Eldin , Frøysa Håvard G , André Karlsen Odd , Elisabeth Zimmer Karin , Friis Berntsen Hanne , Verhaegen Steven , Ropstad Erik , Kellmann Ralf , Goksøyr Anders 
Published: September 2018

AbstractThis study describes the utilization of an LC-MS/MS based H295R assay to assess an environmentally relevant mixture of persistent organic pollutants (POPs). H295R cells were exposed to the POP mixture in two conditions stimulated with 10 μM forskolin and unstimulated. Most importantly, the unstimulated cells responded to the low concentration of the mixture with a significant down-regulation of dehydroepiandrosterone (DHEA). This response was not observed in forskolin-stimulated cells. In stimulated H295R cells, exposure to the highest concentration showed a trend towards induced production of mineralocorticoids and glucocorticoids, although this was not significant. On the other hand, in the same exposure concentration and condition, estrogen and androgen production tended to be down-regulated. In addition to these patterns of responses being different in the stimulated vs unstimulated condition, four steroids were not detectable in the unstimulated condition.
A rotifer-derived paralytic compound prevents transmission of schistosomiasis to a mammalian host
Authors: Gao Jiarong , Yang Ning , Lewis Fred A. , Yau Peter , Collins James J. , Sweedler Jonathan V. , Newmark Phillip A. 
Published: September 2018

AbstractSchistosomes are parasitic flatworms that infect over 200 million people, causing the neglected tropical disease, schistosomiasis. A single drug, praziquantel, is used to treat schistosome infection. Limitations in mass drug administration programs and the emergence of schistosomiasis in non-tropical areas indicate the need for new strategies to prevent infection. It has been known for several decades that rotifers colonizing the schistosome’s snail intermediate host produce a water-soluble factor that paralyzes cercariae, the life-cycle stage infecting humans. In spite of its potential for preventing infection, the nature of this factor has remained obscure. Here, we report the purification and chemical characterization of Schistosome Paralysis Factor (SPF), a novel tetracyclic alkaloid produced by the rotifer Rotaria rotatoria. We show that this compound paralyzes schistosome cercariae and prevents infection, and does so more effectively than analogous compounds. This molecule provides new directions for understanding cercariae motility and new strategies for preventing schistosome infection.
Novel Comparison of Evaluation Metrics for Gene Ontology Classifiers Reveals Drastic Performance Differences
Authors: Plyusnin Ilya , Holm Liisa , Törönen Petri 
Published: September 2018

AbstractAutomated protein annotation using the Gene Ontology (GO) plays an important role in the biosciences. Evaluation has always been considered central to developing novel annotation methods, but little attention has been paid to the evaluation metrics themselves. Evaluation metrics define how well an annotation method performs and allows for them to be ranked against one another. Unfortunately, most of these metrics were adopted from the machine learning literature without establishing whether they were appropriate for GO annotations.We propose a novel approach for comparing GO evaluation metrics calledArtificial Dilution Series(ADS). Our approach uses existing annotation data to generate a series of annotation sets with different levels of correctness (referred to as their signal level). We calculate the evaluation metric being tested for each annotation set in the series, allowing us to identify whether it can separate different signal levels. Finally, we contrast these results with severalfalse positive annotation sets, which are designed to expose systematic weaknesses in GO assessment.We compared 37 evaluation metrics for GO annotation using ADS and identified drastic differences between metrics. We show that some metrics struggle to differentiate between different signal levels, while others give erroneously high scores to the false positive data sets. Based on our findings, we provide guidelines on which evaluation metrics perform well with the Gene Ontology and propose improvements to several well-known evaluation metrics. In general, we argue that evaluation metrics should be tested for their performance and we provide software for this purpose (https://bitbucket.org/plyusnin/ads/). ADS is applicable to other areas of science where the evaluation of prediction results is non-trivial.Author SummaryIn the biosciences, predictive methods are becoming increasingly necessary as novel sequences are generated at an ever-increasing rate. The volume of sequence data necessitates Automated Function Prediction (AFP) as manual curation is often impossible. Unfortunately, selecting the best AFP method is complicated by researchers using different evaluation metrics. Furthermore, many commonly-used metrics can give misleading results. We argue that the use of poor metrics in AFP evaluation is a result of the lack of methods to benchmark the metrics themselves. We propose an approach called Artificial Dilution Series (ADS). ADS uses existing data sets to generate multiple artificial AFP results, where each result has a controlled error rate. We use ADS to understand whether different metrics can distinguish between results with known quantities of error. Our results highlight dramatic differences in performance between evaluation metrics.