bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fenbendazole controlsin vitrogrowth, virulence potential and animal infection in theCryptococcusmodel
Authors: de Oliveira Haroldo C. , Joffe Luna S. , Simon Karina S. , Castelli Rafael F. , Reis Flavia C. G. , Bryan Arielle M. , Borges Beatriz S. , Medeiros Lia C. Soares , Bocca Anamelia L. , Del Poeta Maurizio , Rodrigues Marcio L. 
Published: February 2020

AbstractThe human diseases caused by the fungal pathogensCryptococcus neoformansandC. gattiiare associated with high indices of mortality, and toxic and/or cost-prohibitive therapeutic protocols. The need for affordable antifungals to combat cryptococcal disease is unquestionable. Previous studies suggested benzimidazoles as promising anti-cryptococcal agents combining low cost and high antifungal efficacy, but their therapeutic potential has not been demonstrated so far. In this study, we investigated the antifungal potential of fenbendazole, the most effective anti-cryptococcal benzimidazole. Fenbendazole was inhibitory against 30 different isolates ofC. neoformansandC. gattiiat a low concentration. The mechanism of anti-cryptococcal activity of fenbendazole involved microtubule disorganization, as previously described for human parasites. In combination with fenbendazole, the concentrations of the standard antifungal amphotericin B required to control cryptococcal growth were lower than those required when this antifungal was used alone. Fenbendazole was not toxic to mammalian cells. During macrophage infection, the anti-cryptococcal effects of fenbendazole included inhibition of intracellular proliferation rates and reduced phagocytic escape through vomocytosis. Fenbendazole deeply affected the cryptococcal capsule. In a mice model of cryptococcosis, the efficacy of fenbendazole to control animal mortality was similar to that observed for amphotericin B. These results indicate that fenbendazole is a promising candidate for the future development of an efficient and affordable therapeutic tool to combat cryptococcosis.
TraCurate: efficiently curating cell tracks
Authors: Wagner S. , Thierbach K. , Zerjatke T. , Glauche I. , Roeder I. , Scherf N. 
Published: February 2020

AbstractTraCurate is an open-source software tool to curate and manually annotate cell tracking data from time-lapse microscopy. Although many studies of cellular behavior require high-quality, long-term observations across generations of cells, automated cell tracking is often imperfect and typically yields fragmented results that still contain many errors. TraCurate provides the functionality for the curation and correction of cell tracking data with minimal user interaction and expenditure of time and supports the extraction of complete cell tracks and cellular genealogies from experimental data. Source code and binary packages for Linux, macOS and Windows are available athttps://tracurate.gitlab.io/, as well as all other complementary tools described herein.
Network analysis identifies regulators of lineage-specific phenotypes inMycobacterium tuberculosis
Authors: Banaei-Esfahani Amir , Trauner Andrej , Borrell Sonia , Gygli Sebastian M. , Rustad Tige R. , Feldmann Julia , Gillet Ludovic C. , Schubert Olga T. , Sherman David R. , Beisel Christian , Gagneux Sebastien , Aebersold Ruedi , Collins Ben C. 
Published: February 2020

SummaryTheMycobacterium tuberculosis(Mtb) complex comprises seven phylogenetically distinct human-adapted lineages exhibiting different geographical distribution and degrees of pathogenicity. Among these, Lineage 1 (L1) has been associated with low virulence whereas Lineage 2 (L2) has been linked to hyper-virulence, enhanced transmission and drug resistance. Here, we conducted multi-layer comparative analyses using whole genome sequencing data combined with quantitative transcriptomic and proteomic profiling of a set of L1 and L2 clinical strains, each grown under two different conditionsin vitro. Our data revealed different degrees of correlation between transcript and protein abundances across clinical strains and functional gene categories, indicating variable levels of post-transcriptional regulation in the tested lineages. Contrasting genomic and gene expression data showed that the magnitude of the transcriptional and translational changes was proportional to the phylogenetic distance between strains, with one out of three single nucleotide polymorphisms leading to a transcriptional and/or translational change on average. We devised a new genome-scale transcriptional regulatory model and identified several master transcription factors, strongly linked to the sigma factor network, whose targets were differentially regulated between the two lineages. These differences resulted in a higher basal expression of DosR proteins and a stronger response to nitric oxide (NO) exposure in L2 compared to L1. These patterns are most likely responsible for the shorter NO-induced growth arrest in L2 observed. Given the limited genetic variation between strains, it appears that phenotypic differences in Mtb are substantially driven by differences in the regulation of biochemical networks through master transcriptional regulators.HighlightsProteomic and transcriptomic characterization of fully sequenced diverse L1 and L2 clinical isolates of Mtb.Post-transcriptional control mechanisms for regulatory and virulence genes are mitigated in Mtb L2.By applying a genome-scale transcriptional framework, DosR, Rv1985c, Lsr2 and Rv0691c are identified as master transcription factors responsible for differential target gene expression in L2 strains compared to L1.L1 and L2 DosR proteins respond differently to nitric oxide stress, thus determining a relevant phenotype.
The Clinical Kinase Index: Prioritizing Understudied Kinases as Targets for the Treatment of Cancer
Authors: Essegian Derek , Khurana Rimpi , Stathias Vasileios , Schürer Stephan C. 
Published: February 2020

AbstractThe approval of the first kinase inhibitor, Gleevec, in 2001, ushered in a paradigm shift for oncological treatment—the use of genomic data for targeted, efficacious therapies. Since then, over 48 additional small molecule kinase inhibitors have been approved, solidifying the case for kinases as a highly druggable and attractive target class. Despite the established role deregulated kinase activity plays in cancer, only 8% of the entire kinome has been effectively “drugged”. Moreover, a quarter of the 634 human kinases are vastly understudied. We have developed a comprehensive scoring system which utilizes differential gene expression, clinical and pathological parameters, overall survival and mutational hotspot analysis to rank and prioritize clinically-relevant kinase targets across 17 solid tumor cancers from The Cancer Genome Atlas (TCGA). Collectively, we report that dark kinases have potential clinical value as biomarkers or as new drug targets that warrant further study.
Temperature regulation as a tool to program synthetic microbial community composition
Authors: Krieger Adam , Zhang Jiahao , Lin Xiaoxia Nina 
Published: February 2020

AbstractEngineering of synthetic microbial communities is emerging as a powerful new paradigm for performing various industrially, medically, and environmentally important processes. To reach the fullest potential, however, this approach requires further development in many aspects, a key one being regulating the community composition. Here we leverage well established mechanisms in ecology which govern the relative abundance of multi-species ecosystems and develop a new tool for programming the composition of synthetic microbial communities. Using a simple model system consisting of two microorganismsEscherichia coliandPseudomonas putida, which occupy different but partially overlapping thermal niches, we demonstrate that temperature regulation can be used to enable coexistence and program the community composition. We first investigate a constant temperature regime and show that different temperatures lead to different community compositions. Next, we invent a new cycling temperature regime and show that it can dynamically tune the microbial community, achieving a wide range of compositions depending on parameters that are readily manipulatable. Our work provides conclusive proof of concept that temperature regulation is a versatile and powerful tool capable of programming compositions of synthetic microbial communities.
βIII spectrin controls the planarity of Purkinje cell dendrites by modulating perpendicular axon-dendrite interaction
Authors: Fujishima Kazuto , Kurisu Junko , Yamada Midori , Kengaku Mineko 
Published: February 2020

AbstractThe mechanism underlying the geometrical patterning of axon and dendrite wiring remains elusive, despite its critical importance in the formation of functional neural circuits. Cerebellar Purkinje cell (PC) arborizes a typical planar dendrite, which forms an orthogonal network with granule cell (GC) axons. By using electrospun nanofiber substrates, we reproduce the perpendicular contacts between PC dendrites and GC axons in culture. In the model system, PC dendrites show preference to grow perpendicular to aligned GC axons, which presumably contribute to the planar dendrite arborizationin vivo. We show that βIII spectrin, a causal gene for spinocerebellar ataxia type 5 (SCA5), is required for the biased growth of dendrites. βIII spectrin deficiency causes actin mislocalization and excessive microtubule invasion in dendritic protrusions, resulting in abnormally oriented branch formation. Furthermore, disease-associated mutations affect the ability of βIII spectrin to control dendrite orientation. These data indicate that βIII spectrin organizes the dendritic cytoskeleton and thereby regulates the oriented growth of dendrites with respect to the afferent axons.Summary statementβIII spectrin suppress the microtubule dynamics at the neuronal dendrite to inhibit the abnormal lateral branching, which causes misoriented branch formation.
Resolving a QTL complex for height, heading, and grain yield on chromosome 3A in bread wheat
Authors: Martinez Alba Farre , Lister Clare , Freeman Sue , Ma Jun , Berry Simon , Wingen Luzie , Griffiths Simon 
Published: February 2020

AbstractCrop height (Ht), heading date (Hd), and grain yield (GY) are interrelated traits in wheat. Independent manipulation of each is important for adaptation and performance. Validated QTL for all three collocate on chromosome 3A in the Avalon x Cadenza population. We asked if these are linked or pleiotropic effects. The region was dissected using recombinants derived from Near Isogenic Lines. It was shown that Ht and Hd are controlled by independent genes. The newly defined Ht QTL interval contained a gene cluster involved in cell wall growth and displaying high levels of differential transcript expression. The Hd locus is much larger and rearranged compared to the reference genome butFT2is a candidate of particular interest. The Hd effect was shown to act independently of photoperiod and vernalization but did exhibit genotype x environment interaction suggesting a role in ambient temperature sensitivity. It was the Hd locus that was most associated with increased GY of Cadenza alleles, supporting physiological studies proposing that ‘late’ alleles at this locus increase spike fertility and grain number. The work has uncoupled height from heading and yield and shown that one of very few validated GY QTL in wheat is probably mediated by phenological variation.HighlightThere only are three validated wheat yield QTL. Here, one of them was genetically dissected.This showed that the physiological basis of the yield effect is likely to be phenological.
Accelerated Simulations of Chemical Reaction Systems using the Stochastic Simulation Algorithm on GPUs
Authors: Pino James C. , Prugger Martina , Lubbock Alexander L. R. , Harris Leonard A. , Lopez Carlos F. 
Published: February 2020

1AbstractStochasticity due to fluctuations in chemical reactions can play important roles in cellular network-driven processes. Although the Stochastic Simulation Algorithm (SSA, aka Gillespie Algorithm) has long been accepted as a suitable method to solve the time-dependent chemical master equation, its computational cost is prohibitive for large scale complex networks such as those found in cellular processes. Here we present GPU-SSA, an implementation of the SSA formalism utilizing Graphics Processing Units for use in Python using the PySB modeling framework. We show that the GPU implementation of SSA can achieve significant speedup compared to parallel CPU or single-core CPU implementations. We further include supplementary didactic material to demonstrate how to incorporate GPU-SSA workflows for interested readers.
Simultaneous human intracerebral stimulation and HD-EEG: ground-truth for source localization methods
Authors: Mikulan Ezequiel , Russo Simone , Parmigiani Sara , Sarasso Simone , Zauli Flavia Maria , Rubino Annalisa , Avanzini Pietro , Cattani Anna , Sorrentino Alberto , Gibbs Steve , Cardinale Francesco , Sartori Ivana , Nobili Lino , Massimini Marcello , Pigorini Andrea 
Published: February 2020

AbstractPrecisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we provide the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.
Steroid hormone agonists reduce female fitness in insecticide-resistantAnophelespopulations
Authors: Brown Faye , Paton Douglas G , Catteruccia Flaminia , Ranson Hilary , Ingham Victoria A 
Published: February 2020

AbstractInsecticide based vector control tools such as insecticide treated bednets and indoor residual spraying represent the cornerstones of malaria control programs. Resistance to chemistries used in these programs is now widespread and represents a significant threat to the gains seen in reducing malaria-related morbidity and mortality. Recently, disruption of the 20-hydroxyecdysone steroid hormone pathway was shown to reducePlasmodiumdevelopment time and significantly reduce both longevity and egg production in a laboratory susceptibleAnopheles gambiaepopulation. Here, we demonstrate that disruption of this pathway by application of methoxyfenozide (MET) to insecticide resistantAn. coluzzii, An. gambiae slandAn. funestuspopulations significantly reduces egg production in both topical and tarsal application. Moreover, MET reduces adult longevity when applied topically, and tarsally after blood feeding. As the cytochrome p450s elevated in pyrethroid resistantAnophelesonly bind MET very weakly, this compound is unlikely to be subject to cross-resistance in a field-based setting. Manipulation of this hormonal signalling pathway therefore represents a potential complementary approach to current malaria control strategies, particularly in areas where high levels of insecticide resistance are compromising existing tools.
Conservation Genomic Analyses of African and Asiatic Cheetahs (Acinonyx jubatus) Across Their Current and Historical Species Range
Authors: Prost Stefan , Machado Ana Paula , Zumbroich Julia , Preier Lisa , Mahtani-Williams Sarita , Meissner Rene , Guschanski Katerina , Brealey Jaelle C. , Fernandes Carlos , Vercammen Paul , Hunter Luke T. B. , Abramov Alexei V. , Godsall-Bottriell Lena , Bottriell Paul , Dalton Desire Lee , Kotze Antoinette , Burger Pamela Anna 
Published: February 2020

SummaryCheetahs (Acinonyxjubatus)are majestic carnivores and the fastest land animals; yet, they are quickly heading towards an uncertain future. Threatened by habitat loss, human-interactions and illegal trafficking, there are only approximately 7,100 individuals remaining in the wild. Cheetahs used to roam large parts of Africa, and Western and Southern Asia. Today they are confined to about 9% of their original distribution. To investigate their genetic diversity and conservation status, we generated genome-wide data from historical and modern samples of all four currently recognized subspecies, along with mitochondrial DNA (mtDNA) and major histo-compatibility complex (MHC) data. We found clear genetic differentiation between the sub-species, thus refuting earlier assumptions that cheetahs show only little population differentiation. Our genome-wide nuclear data indicate that cheetahs from East Africa may be more closely related toA. j. soemmeringiithan they are toA. j. jubatus. This supports the need for further research on the classification of cheetah subspecies, as East African cheetahs are currently included in the Southern Africa subspecies,A. j. jubatus. We detected stronger inbreeding in individuals of the Critically EndangeredA. j. venaticus(Iran) andA. j. hecki(Northwest Africa), and show that overall genome-wide heterozygosity in cheetah is lower than that reported for other threatened and endangered felids, such as tigers and lions. Furthermore, we show that MHC class II diversity in cheetahs is generally higher than previously reported, but still lower than in other felids. Our results provide new and important information for efficient genetic monitoring, subspecies assignments and evidence-based conservation policy decisions.
Precise automatic classification of 46 different pollen types with convolutional neural networks
Authors: Sevillano Víctor , Holt Katherine , Aznarte José L. 
Published: February 2020

AbstractIn palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Many industries, including medical and farmaceutical, rely on the accuracy of this manual classification process, which is reported to be around 67%. In this paper, we propose a new method to automatically classify pollen grains using deep learning techniques that improve the correct classification rates in images not previously seen by the models. Our proposal manages to properly classify up to 98% of the examples from a dataset with 46 different classes of pollen grains, produced by the Classifynder classification system. This is an unprecedented result which surpasses all previous attempts both in accuracy and number and difficulty of taxa under consideration, which include types previously considered as indistinguishable.
Sentinel Interaction Mapping (SIM) – A generic approach for the functional analysis of human disease gene variants using yeast
Authors: Young Barry P , Post Kathryn L , Chao Jesse T , Meili Fabian , Haas Kurt , Loewen Christopher JR 
Published: February 2020

AbstractAdvances in sequencing technology have led to an explosion in the number of known genetic variants of human genes. A major challenge is to now determine which of these variants contribute to diseases as a result of their effect on gene function. Here we describe a generic approach using the yeastSaccharomyces cerevisiaeto quickly develop gene-specificin vivoassays that can be used to quantify the level of function of a genetic variant. Using Synthetic Dosage Lethality screening, “sentinel” yeast strains are identified that are sensitive to overexpression of a human disease gene. Variants of the gene can then be functionalized in high-throughput fashion through simple growth assays using either solid or liquid media. Sentinel Interaction Mapping (SIM) has the potential to create functional assays for the large majority of human disease genes that do not have a yeast orthologue. Using the tumour suppressor genePTENas an example, we show that SIM assays can provide a fast and economical means to screen a large number of genetic variants.
A fast linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations
Authors: Boyrie Léa , Moreau Corentin , Frugier Florian , Jacquet Christophe , Bonhomme Maxime 
Published: February 2020

AbstractThe quest for genome-wide signatures of selection in populations using SNP data has proven efficient to uncover genes involved in conserved or adaptive molecular functions, but none of the statistical methods were designed to identify interacting genes as targets of selective processes. Here, we propose a straightforward statistical test aimed at detecting epistatic selection, based on a linkage disequilibrium (LD) measure accounting for population structure and heterogeneous relatedness between individuals. SNP-based (Trv) and window-based (TcorPC1v) statistics fit a Student distribution, allowing to easily and quickly test the significance of correlation coefficients in the frame of Genome-Wide Epistatic Selection Scans (GWESS) using candidate genes as baits. As a proof of concept, use of SNP data from theMedicago truncatulasymbiotic legume plant uncovered a previously unknown gene coadaptation between theMtSUNN(Super Numeric Nodule) receptor and theMtCLE02(CLAVATA3-Like) signalling peptide, and experimental evidence accordingly supported aMtSUNN-dependent negative role ofMtCLE02in symbiotic root nodulation. Using human HGDP-CEPH SNP data, our new statistical test uncovered strong LD betweenSLC24A5andEDARworldwide, which persists after correction for population structure and relatedness in Central South Asian populations. This result suggests adaptive genetic interaction or coselection between skin pigmentation and the ectodysplasin pathway involved in the development of ectodermal organs (hairs, teeth, sweat glands), in some human populations. Applying this approach to genome-wide SNP data will foster the identification of evolutionary coadapted gene networks.Author summaryPopulation genomic methods have allowed to identify many genes associated with adaptive processes in populations with complex histories. However, they are not designed to identify gene coadaptation between genes through epistatic selection, in structured populations. To tackle this problem, we developed a straightforward LD-based statistical test accounting for population structure and heterogeneous relatedness between individuals, using SNP-based (Trv) or windows-based (TcorPC1v) statistics. This allows easily and quickly testing for significance of correlation coefficients between polymorphic loci in the frame of Genome Wide Epistatic Selection Scans (GWESS). Following detection of gene coadaptation using SNP data from human and the model plantMedicago truncatula, we report experimental evidence of genetic interaction between two receptors involved in the regulation of root nodule symbiosis inMedicago truncatula. This test opens new avenues for exploring the evolution of genes as interacting units and thus paves the way to infer new networks based on evolutionary coadaptation between genes.