bluuebunny/crossref_metadata_2025_split huggingface dataset:
White Matter Hyperintensity Quantification in Large-Scale Clinical Acute Ischemic Stroke Cohorts – The MRI-GENIE Study
Authors: Schirmer Markus D. , Dalca Adrian V. , Sridharan Ramesh , Giese Anne-Katrin , Donahue Kathleen L. , Nardin Marco J. , Mocking Steven J. T. , McIntosh Elissa C. , Frid Petrea , Wasselius Johan , Cole John W. , Holmegaard Lukas , Jern Christina , Jimenez-Conde Jordi , Lemmens Robin , Lindgren Arne G. , Meschia James F. , Roquer Jaume , Rundek Tatjana , Sacco Ralph L. , Schmidt Reinhold , Sharma Pankaj , Slowik Agnieszka , Thijs Vincent , Woo Daniel , Vagal Achala , Xu Huichun , Kittner Steven J. , McArdle Patrick F. , Mitchell Braxton D. , Rosand Jonathan , Worrall Bradford B. , Wu Ona , Golland Polina , Rost Natalia S. ,   on behalf of the MRI-GENIE Investigators
Published: February 2019

AbstractWhite matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery.In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95) and Pearson correlation of total brain volume (r=0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N=2783) and identify a decrease in total brain volume of -2.4cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing.Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2,533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.
Infection triggers tumor regression through activation of innate immunity inDrosophila
Authors: Jacqueline Camille , Parvy Jean-Philippe , Faugère Dominique , Renaud François , Missé Dorothée , Thomas Frédéric , Roche Benjamin 
Published: February 2019

AbstractThe pioneering work of Dr. William Coley has shown that infections can stimulate the immune system and improve tumor growth control. However, the immune mechanisms responsible for the protective role of infectious agents have still not been identified. Here, we investigated the role of innate immune pathways in tumor regression by performing experimental infections in genetically modifiedDrosophilathat develop invasive neoplastic tumors. After quantifying tumor size, through image processing, and immune gene expression with transcriptomic analyses, we analyzed the link between tumor size and pathogen-induced immune responses thanks to a combination of statistical and mathematical modeling.Drosophilalarvae infected with a naturally-occurring bacterium showed a smaller tumor size compared to controls and fungus-infected larvae, thanks to an increase expression of Imd and Toll pathways. Our mathematical model reinforces this idea by showing that repeated acute infection could results in an even higher decrease in tumor size. Thus, our study suggests that infectious agents can induce tumor regression through the alteration of innate immune responses. This phenomenon, currently neglected in oncology, could have major implications for the elaboration of new preventive and immunotherapeutic strategies.One Sentence SummaryBacterial infections can decrease cancer cell accumulation through stimulation of innate immune responses.
Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole Genome Sequencing Studies
Authors: Li Zilin , Li Xihao , Liu Yaowu , Shen Jincheng , Chen Han , Zhou Hufeng , Morrison Alanna C. , Boerwinkle Eric , Lin Xihong 
Published: February 2019

AbstractWhole genome sequencing (WGS) studies are being widely conducted to identify rare variants associated with human diseases and disease-related traits. Classical single-marker association analyses for rare variants have limited power, and variant-set based analyses are commonly used to analyze rare variants. However, existing variant-set based approaches need to pre-specify genetic regions for analysis, and hence are not directly applicable to WGS data due to the large number of intergenic and intron regions that consist of a massive number of non-coding variants. The commonly used sliding window method requires pre-specifying fixed window sizes, which are often unknown as a priori, are difficult to specify in practice and are subject to limitations given genetic association region sizes are likely to vary across the genome and phenotypes. We propose a computationally-efficient and dynamic scan statistic method (Scan the Genome (SCANG)) for analyzing WGS data that flexibly detects the sizes and the locations of rare-variants association regions without the need of specifying a prior fixed window size. The proposed method controls the genome-wise type I error rate and accounts for the linkage disequilibrium among genetic variants. It allows the detected rare variants association region sizes to vary across the genome. Through extensive simulated studies that consider a wide variety of scenarios, we show that SCANG substantially outperforms several alternative rare-variant association detection methods while controlling for the genome-wise type I error rates. We illustrate SCANG by analyzing the WGS lipids data from the Atherosclerosis Risk in Communities (ARIC) study.
Delivering on the Vision of Bench to Bedside: A Rare Disease Funding Community Collaboration to Develop Effective Therapies for Neurofibromatosis Type 1 Tumors
Authors: Rosa Salvatore La , Browder Vidya , Bakker Annette C. , Blakeley Jaishri O. , Verma Sharad K. , Wong Ling M. , Morris Jill A. , Bora Naba 
Published: February 2019

AbstractThe time from target identification to new drug approval is often measured in decades. This can be even more challenging for rare diseases. Indeed, 95% of rare diseases do not have a specific therapy approved. Coordinated efforts to support research along the drug development pipeline can provide long term and comprehensive support to enable scientific breakthroughs for rare diseases. However, this requires coordination across multiple stakeholders. The present article analyzes the funding efforts of four major federal and philanthropic organizations to accelerate the advancement of MEK inhibitors to human clinical trials for NF1-associated tumors.
Harnessing phenotypic networks and structural equation models to improve genome-wide association analysis
Authors: Momen Mehdi , Campbell Malachy T. , Walia Harkamal , Morota Gota 
Published: February 2019

AbstractPlant breeders and breeders alike seek to develop cultivars with maximal agronomic value. The merit of breeding material is often assessed using many, often genetically correlated traits. As intervention on one trait will affect the value of another, breeding decisions should consider the relationships between traits. With the proliferation of multi-trait genome-wide association studies (MTM-GWAS), we can infer putative genetic signals at the multivariate scale. However, a standard MTM-GWAS does not accommodate the network structure of phenotypes, and therefore does not address how the traits are interrelated. We extended the scope of MTM-GWAS by incorporating phenotypic network structures into GWAS using structural equation models (SEM-GWAS). In this network GWAS model, one or more phenotypes appear in the equations for other phenotypes as explanatory variables. A salient feature of SEM-GWAS is that it can partition the total single nucleotide polymorphism (SNP) effects into direct and indirect effects. In this paper, we illustrate the utility of SEM-GWAS using biomass, root biomass, water use, and water use efficiency in rice. We found that water use efficiency is directly impacted by biomass and water use and indirectly by biomass and root biomass. In addition, SEM-GWAS partitioned significant SNP effects influencing water use efficiency into direct and indirect effects as a function of biomass, root biomass, and water use efficiency, providing further biological insights. These results suggest that the use of SEM may enhance our understanding of complex relationships between GWAS traits.
Two novel heteropolymer-forming proteins maintain multicellular shape of the cyanobacteriumAnabaenasp. PCC 7120
Authors: Springstein Benjamin L. , Nürnberg Dennis J. , Woehle Christian , Weissenbach Julia , Theune Marius L. , Helbig Andreas O. , Maldener Iris , Dagan Tal , Stucken Karina 
Published: February 2019

AbstractPolymerizing and filament-forming proteins are instrumental for numerous cellular processes such as cell division and growth. Their function in stabilization and localization of protein complexes and replicons is achieved by a filamentous structure. Known filamentous proteins assemble into homopolymers consisting of single subunits – e.g. MreB and FtsZ in bacteria – or heteropolymers that are composed of two subunits, e.g. keratin and α/β tubulin in eukaryotes. Here, we describe two novel coiled-coil-rich proteins (CCRPs) in the filament forming cyanobacteriumAnabaenasp. PCC 7120 (hereafterAnabaena) that assemble into a heteropolymer and function in the maintenance of theAnabaenamulticellular shape (termed trichome). The two CCRPs – Alr4504 and Alr4505 (named ZicK and ZacK) – are strictly interdependent for the assembly of protein filamentsin vivoand polymerize nucleotide-independentlyin vitro, similar to known intermediate filament (IF) proteins. A ΔzicKΔzacK double mutant is characterized by a zigzagged cell arrangement and hence a loss of the typical linearAnabaenatrichome shape. ZicK and ZacK interact with themselves, with each other, with the elongasome protein MreB, the septal junction protein SepJ and the divisome associate septal protein SepI. Our results suggest that ZicK and ZacK function in cooperation with SepJ and MreB to stabilize theAnabaenatrichome and are likely essential for the manifestation of the multicellular shape inAnabaena. Our study reveals the presence of filament-forming IF-like proteins whose function is achieved through the formation of heteropolymers in cyanobacteria.
In-silico predictive identification of K-RasG12V inhibitors in natural compounds
Authors: Aliyar Masoud , Aryapour Hassan , Mahdavi Majid 
Published: February 2019

AbstractAs RAS protein is highly significant in signaling pathways, involving cell growth, differentiation and apoptosis; the Ras GTPase proteins play a significant as a master switch in the appearance of many diseases, including 20-30% of all cancers. So, the K-RasG12V mutant was selected as a drug target in present study. This mutant is involved in gastric cancer, lung and pancreatic carcinoma, and colon cancers. So, we employed the structure-based drug design methods and molecular dynamics simulations to undergo virtual screening on natural products small molecules and predicted some new potent therapeutic inhibitors. Finally, ZINC15671852, ZINC85592862, ZINC85567582 and ZINC03616630 final Hits were identified as potent inhibitors from among more than 79,000 bioactive compounds from natural resource. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-P/GBSA) calculation results have also demonstrated that these molecules obtained higher binding free energy than co-crystalized reference ligand.
Sex-biased gene expression is masculinized in asexual females
Authors: Parker Darren J. , Bast Jens , Jalvingh Kirsten , Dumas Zoé , Robinson-Rechavi Marc , Schwander Tanja 
Published: February 2019

AbstractMales and females feature strikingly different phenotypes, despite sharing most of their genome. The resolution of this apparent paradox is through differential gene expression, whereby genes are expressed at different levels in each sex. This resolution, however, is likely to be incomplete, leading to conflict between males and females over the optimal expression of genes. We test the hypothesis that gene expression in females is constrained from evolving to its optimum level due to sexually antagonistic selection on males, by examining changes sex-biased gene expression in five obligate asexual species of stick insect, which do not produce males. We predicted that the transcriptome of asexual females would be feminized as asexual females do not experience any sexual conflict. Contrary to our prediction we find that asexual females feature masculinized gene expression, and hypothesise that this is due to shifts in female optimal gene expression levels following the suppression of sex.
Phospho-sRNA-seq reveals extracellular mRNA/lncRNA fragments as potential biomarkers in human plasma
Authors: Giraldez Maria D. , Spengler Ryan M. , Etheridge Alton , Goicochea Annika Jane , Tuck Missy , Choi Sung Won , Galas David J. , Tewari Muneesh 
Published: February 2019

AbstractExtracellular RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Whereas extracellular microRNAs (miRNAs) in blood plasma are extensively characterized, extracellular messenger RNAs (mRNA) and long noncoding RNAs (lncRNA) are less well-studied. We report that plasma contains fragmented mRNAs and lncRNAs that are largely missed by standard small RNA-seq protocols due to lack of 5’ phosphate or presence of 3’ phosphate. These fragments were revealed using a modified protocol (“phospho-sRNA-seq”) incorporating RNA treatment with T4-polynucleotide kinase, which we compared with standard small RNA-seq for sequencing synthetic RNAs with varied 5’ and 3’ ends, as well as human plasma exRNA. Analyzing phospho-sRNA-seq data using a custom, high-stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue-specific gene sets. In a longitudinal study of bone marrow transplant patients, bone marrow-and liver-enriched exRNA genes tracked with bone marrow recovery and liver injury, respectively, providing proof-of-concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho-sRNA-seq opens up new possibilities for plasma transcriptomic biomarker development.
Meiotic DNA repair in the nucleolus employs a non-homologous end joining mechanism
Authors: Sims Jason , Copenhaver Gregory P. , Schlögelhofer Peter 
Published: February 2019

AbstractRibosomal RNA genes are arranged in large arrays with hundreds of rDNA units in tandem. These highly repetitive DNA elements pose a risk to genome stability since they can undergo non-allelic exchanges. During meiosis DNA double strand breaks (DSBs) are induced as part of the regular program to generate gametes. Meiotic DSBs initiate homologous recombination (HR) which subsequently ensures genetic exchange and chromosome disjunction.InArabidopsis thalianawe demonstrate that all 45S rDNA arrays become transcriptionally active and are recruited into the nucleolus early in meiosis. This shields the rDNA from acquiring canonical meiotic chromatin modifications, meiotic cohesin and meiosis-specific DSBs. DNA breaks within the rDNA arrays are repaired in a RAD51-independent, but LIG4-dependent manner, establishing that it is non-homologous end joining (NHEJ) that maintains rDNA integrity during meiosis. Utilizing ectopically integrated rDNA repeats we validate our findings and demonstrate that the rDNA constitutes a HR-refractory genome environment.
The distribution of fitness effects among synonymous mutations in a gene under selection
Authors: Lebeuf-Taylor E. , McCloskey N. , Bailey S.F. , Hinz A. , Kassen R. 
Published: February 2019

AbstractThe fitness effects of synonymous mutations, nucleotide changes that do not alter the encoded amino acid, have often been assumed to be neutral, but a growing body of evidence suggests otherwise. We used site-directed mutagenesis coupled with direct measures of competitive fitness to estimate the distribution of fitness effects among synonymous mutations for a gene under selection. Synonymous mutations had highly variable fitness effects, both deleterious and beneficial, resembling those of nonsynonymous mutations in the same gene. This variation in fitness was underlain by changes in transcription linked to the creation of internal promoter sites. A positive correlation between fitness and the presence of synonymous substitutions across a phylogeny of related Pseudomonads suggests these mutations may be common in nature. Taken together, our results provide the most compelling evidence to date that synonymous mutations with non-neutral fitness effects may in fact be commonplace.
Detecting natural hybridization among Indian major carps through advance morphometric approach
Authors: Dwivedi Arvind Kumar 
Published: February 2019

AbstractInterspecific natural hybridization is an indicator of altered ecosystem. Habitat destruction increases competition with fish species in close proximity for spawning habitat with overlapping reproductive activities, thereby causing natural hybridization. This study is first investigation on detecting hybrids among Indian major carps (Labeo rohita, Cirrhinus mrigala and Gibelion catla) from the Ganga River by applying a cost-effective method, “Geometric Morphometrics”. The relative warps (RW), principal component analysis (PCA) and canonical variate analysis (CVA) were employed on superimposed images to determine morphometric variations. Deformation grid of RW showed that G. catla and hybrid specimens have a deeper whereas L. rohita and C. mrigala specimens have slender body profile. The PCA showed separation among specimens of four groups (three species and one hybrid) with slight overlap between G. catla and hybrid. CVA extracted Mahalanobis and Procrustes distances among four non-overlapping groups found to be highly significant (P < 0.0001) with hybrid specimens lying between position of L. rohita and G. catla specimens in close proximity to G. catla, suggesting that hybrids are product of crossing between L. rohita and G. catla. The CVA separated four groups with 100.00% classification, indicating that all the three species and hybrid were clearly distinct from each other. In this study, all the four specimens of hybrid were caught from upstream of four barrages (Bijnor, Narora, Kanpur and Farakka) commissioned along the middle and lower stretch of the Ganga River. This suggests that, barrages obstruct upward movement of fish population and impact on reproductive activities, thereby increases possibilities of natural hybridization among these species.
The benefits of insect-swarm hunting in echolocating bats, and its influence on the evolution of bat echolocation signals
Authors: Boonman Arjan , Yovel Yossi , Fenton Brock 
Published: February 2019

AbstractPredation on swarms of prey, especially using visual information, has drawn much interest in studies of collective movement. Surprisingly, in the field of biosonar this aspect of prey detection, which is probably very common, has received little to no attention. Here, we combine computer simulations and actual echo measurements to accurately estimate the echo intensity of insect swarms of different size and density. We show that swarm echo intensity increases with 3dB for every doubling of insect number, irrespective of swarm density. Thus swarms will be much easier to detect than single insects. Many of the insects bats eat are so small that they are only detectable by echolocation at very short distances. By focusing on detection of swarms of insects, a bat may increase its operating range and diversify its diet. Interestingly, interference between the sound waves reflected from a swarm of insects can sometimes result in echoes that are much much weaker than echoes from single insects. We show that bats can reduce this problem by increasing the bandwidth of their echolocation calls. Specifically, a bandwidth of 3-8 kHz would guarantee receiving loud echoes from any angle relative to the swarm. Indeed, many bat species, and specifically bats hunting in open spaces, where swarms are abundant, use echolocation signals with a bandwidth of several kHz. Our results might also explain how the first echolocating bats that probably had limited echolocation abilities, could detect insects through swarm hunting.
In silico analysis ofIDH3Agene revealed Novel mutations associated with Retinitis Pigmentosa
Authors: Mahmoud Thwayba A. , Abdelmoneim Abdelrahman H. , Murshed Naseem S. , Mohammed Zainab O. , Ahmed Dina T. , Altyeb Fatima A. , Mahmoud Nuha A. , Mohammed Mayada A. , Arayah Fatima A. , Mohammed Wafaa I. , Abayazed Omnia S. , Akasha Amna S. , Mustafa Mujahed I. , Hassan Mohamed A. 
Published: February 2019

AbstractBackgroundRetinitis Pigmentosa (RP) refers to a group of inherited disorders characterized by the death of photoreceptor cells leading to blindness. The aim of this study is to identify the pathogenic SNPs in the IDH3A gene and their effect on the structure and function of the protein.Methodwe used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein.Result20 deleterious SNPs out of 178 were found to have a damaging effect on the protein structure and function.Conclusionthis is the first in silico analysis of IDH3A gene and 20 novel mutations were found using different bioinformatics tools, and they could be used as diagnostic markers for Retinitis Pigmentosa.
Metabolomic profiling revels systemic signatures of premature aging induced by Hutchinson-Gilford Progeria Syndrome
Authors: Monnerat Gustavo , Caprini Evaristo Geisa Paulino , Medeiros Evaristo Joseph Albert , dos Santos Caleb Guedes Miranda , Carneiro Gabriel , Maciel Leonardo , Carvalho Vânia Oliveira , Sousa Nogueira Fábio César , Domont Gilberto Barbosa , de Carvalho Antonio Carlos Campos 
Published: February 2019

AbstractHutchinson-Gilford Progeria Syndrome (HGPS) is an extremely rare genetic disorder. HGPS children present a high incidence of cardiovascular complications along with altered metabolic processes and accelerated aging process. No metabolic biomarker is known and the mechanisms underlying premature aging are not fully understood. The present study analysed plasma from six HGPS patients of both sexes (7.7±1.4 years old; mean±SD) and eight controls (8.6±2.3 years old) by LC-MS/MS in high-resolution non-targeted metabolomics (Q-Exactive Plus). Several endogenous metabolites with statistical difference were found. Multivariate statistics analysis showed a clear separation between groups. Potential novel metabolic biomarkers are identified using the multivariate area under ROC curve (AUROC) based analysis, showing an AUC value higher than 0.80 using only two metabolites, and reaching 1.00 when increasing the number of metabolites in the AUROC model. Targeted metabolomics was used to validate some of the metabolites identified by the non-targeted method. Taken together, changed metabolic pathways in that panel involve sphingolipid, amino acid, and oxidation of fatty acids among others. In conclusion our data show significant alterations in cellular energy use and availability, in signal transduction, and in lipid metabolites, creating new insights on metabolic alterations associated with premature aging.