bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ancient ancestry informative markers for identifying fine-scale ancient population structure in Eurasians
Authors: Esposito Umberto , Das Ranajit , Pirooznia Mehdi , Elhaik Eran 
Published: May 2018

AbstractThe rapid accumulation of ancient human genomes from various areas and time periods potentially allows the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations known to misrepresent the population structure. Past studies addressed these problems using ancestry informative markers (AIMs). However, it is unclear whether AIMs derived from contemporary human genomes can capture ancient population structure and whether AIM finding methods are applicable to ancient DNA (aDNA) provided that the high missingness rates in ancient, oftentimes haploid, DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperforms all competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of population microarrays and the interpretation of aDNA results.
Convolving Pre-Trained Convolutional Neural Networks at Various Magnifications to Extract Diagnostic Features for Digital Pathology
Authors: Sidhom John-William , Baras Alexander S. 
Published: May 2018

ABSTRACTDeep learning is an area of artificial intelligence that has received much attention in the past few years due to both an increase in computational power with the increased use of graphics processing units (GPU’s) for computational analyses and the performance of these class of algorithms on visual recognition tasks. They have found utility in applications ranging from image search to facial recognition for security and social media purposes. Their continued success has propelled their use across many new domains including the medical field, in areas of radiology and pathology in particular, as these fields are thought to be driven by visual recognition tasks. In this paper, we present an application of deep learning, termed ‘transfer learning’, using ResNet50, a pre-trained convolutional neural network (CNN) to act as a ‘feature-detector’ at various magnifications to identify low and high level features in digital pathology images of various breast lesions for the purpose of classifying them correctly into the labels of normal, benign, in-situ, or invasive carcinoma as provided in the ICIAR 2018 Breast Cancer Histology Challenge (BACH).
sppIDer: a species identification tool to investigate hybrid genomes with high-throughput sequencing
Authors: Langdon Quinn K. , Peris David , Kyle Brian , Hittinger Chris Todd 
Published: May 2018

AbstractThe genomics era has expanded our knowledge about the diversity of the living world, yet harnessing high-throughput sequencing data to investigate alternative evolutionary trajectories, such as hybridization, is still challenging. Here we present sppIDer, a pipeline for the characterization of interspecies hybrids and pure species,that illuminates the complete composition of genomes. sppIDer maps short-read sequencing data to a combination genome built from reference genomes of several species of interest and assesses the genomic contribution and relative ploidy of each parental species, producing a series of colorful graphical outputs ready for publication. As a proof-of-concept, we use the genus Saccharomyces to detect and visualize both interspecies hybrids and pure strains, even with missing parental reference genomes. Through simulation, we show that sppIDer is robust to variable reference genome qualities and performs well with low-coverage data. We further demonstrate the power of this approach in plants, animals, and other fungi. sppIDer is robust to many different inputs and provides visually intuitive insight into genome composition that enables the rapid identification of species and their interspecies hybrids. sppIDer exists as a Docker image, which is a reusable, reproducible, transparent, and simple-to-run package that automates the pipeline and installation of the required dependencies (https://github.com/GLBRC/sppIDer).
WNT signaling memory is required for ACTIVIN to function as a morphogen in human gastruloids
Authors: Yoney Anna , Etoc Fred , Ruzo Albert , Metzger Jakob J. , Martyn Iain , Li Shu , Kirst Christoph , Carroll Thomas , Siggia Eric D. , Brivanlou Ali H. 
Published: May 2018

ABSTRACTSelf-organization of discrete fates in human gastruloids is mediated by a hierarchy of signaling pathways. How these pathways are integrated in time, and whether cells maintain a memory of their signaling history remains obscure. Here, we dissect the temporal integration of two key pathways, WNT and ACTIVIN, which along with BMP control gastrulation. CRISPR/Cas9 live reporters of SMAD1, 2 and 4 demonstrate that in contrast to the stable signaling by SMAD1, signaling and transcriptional response by SMAD2 is transient, and while necessary for pluripotency, it is insufficient for differentiation. Pre-exposure to WNT, however, endows cells with the competence to respond to graded levels of ACTIVIN, which induces differentiation without changing SMAD2 dynamics. This cellular memory of WNT signaling is necessary for ACTIVIN morphogen activity. A re-evaluation of the evidence gathered over decades in model systems, re-enforces our conclusions and points to an evolutionarily conserved mechanism.
Optogenetic manipulation of medullary neurons in the locust optic lobe
Authors: Wang Hongxia , Dewell Richard B. , Ehrengruber Markus U. , Segev Eran , Reimer Jacob , Roukes Michael L. , Gabbiani Fabrizio 
Published: May 2018

AbstractLocust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts (Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered firing of a postsynaptic, looming-sensitive neuron, the Lobula Giant Movement Detector (LGMD). These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects.New and NoteworthyUsing Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and of an identified postsynaptic target neuron, the LGMD neuron. This technique allows to manipulate the neuronal activity in locust neural circuits using optogenetics.
Transcriptome-wide analysis of auxin-induced carotenoid accumulation in Chlorella microalgae
Authors: Alsenani Faisal , Wass Taylor J. , Ma Ruijuan , Eltanahy Eladl , Netzel Michael E. , Schenk Peer M. 
Published: May 2018

AbstractMicroalgae are a commercially viable route for the production of carotenoids, including β-carotene and astaxanthin. In the current study, the commercially relevant microalga, Chlorella sp. BR2 was treated with four plant hormones: indole-3-acetic acid, salicylic acid, abscisic acid and methyl jasmonate, over a range of dosages and screened for enhanced carotenoid production. Indole-3-acetic acid was the only hormone with an inductive effect on carotenoid accumulation. As such, the transcriptome under the condition with the highest carotenoid increase was profiled using RNA-Seq and expressed sequences reconstructed with de novo assembly. This allowed for the profiling of transcriptome-wide changes following auxin treatment, revealing the active pathway components of auxininduced carotenogenesis. Data analysis specified the differentially expressed genes involved in auxin biosynthesis and signal transduction, which suggest a close relationship to equivalent pathways in higher plants. However unlike in plants, the ancient ABP1/SCFSKP2A/IBR5-mediated pathways for auxin response likely acted as the primary signaling route in Chlorella. As carotenoids are precursors for abscisic acid, the findings suggest a causative link between auxin signaling and abiotic stress tolerance.HighlightTranscriptomics of plant hormone-treated Chlorella revealed the active pathway components of auxin-induced carotenogenesis and included the ancient ABP1/SCFSKP2A/IBR5-mediated pathways. The manuscript presents the first documented transcriptomic data of auxin-treated microalgae.
Co-outbreak of ST37 and a novel ST3006 Klebsiella pneumoniae from multi-site infection in a neonatal intensive care unit: a retrospective study
Authors: Chen Dongjie , Hu Xinlan , Chen Falin , Li Hongru , Wang Daxuan , Li Xiaoqin , Wu Changsheng , Li Ning , Wu Shaolian , Li Zhen , Chen Liqing , Chen Yusheng 
Published: May 2018

SummaryBackgroundThe outbreak of carbapenems resistant Klebsiella pneumoniae (K. pneumoniae) is a serious public health problem, especially in the neonatal intensive care unit (NICU).MethodsFifteen strains of K. pneumoniae were isolated from seven neonates during June 3–28, 2017 in a NICU. Antimicrobial susceptibility was determined by the Vitek 2 system and micro-broth dilution method. Multi-locus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) were used to analyse the genetic relatedness of isolates. Genome sequencing and gene function analyses were performed for investigating pathogenicity and drug resistance and screening genomic islands.FindingsTwo K. pneumoniae clones were identified from seven neonates, one ST37 strain and another new sequence type ST3006. The ST37 strain exhibited multi-drug resistance genes and resistance to carbapenem. MLST and PFGE showed that 15 strains were divided into three groups, with a high level of homology. Gene sequencing and analysis indicated that KPN1343 harboured 12 resistance genes, 15 genomic islands and 205 reduced virulence genes. KPN1344 harboured four resistance genes, 19 genomic islands and 209 reduced virulence genes.ConclusionCo-outbreak of K. pneumoniae involved two clones, ST36 and ST3006, causing multi-site infection. Genome sequencing and analysis is an effective method for studying bacterial resistance genes and their functions.
Diagnosing Bacterial Vaginosis with a Novel, Clinically-Actionable Molecular Diagnostic Tool
Authors: Jarvis Joseph P. , Rains Doug , Kradel Steven J. , Elliott James , Diamond Evan E. , Avaniss-Aghajani Erik , Yasharpour Farid , Shaman Jeffrey A. 
Published: May 2018

Abstract/SummaryBacterial vaginosis is a common condition among women of reproductive age and is associated with potentially serious side-effects, including an increased risk of preterm birth. Recent advancements in microbiome sequencing technologies have produced novel insights into the complicated mechanisms underlying bacterial vaginosis and have given rise to new methods of diagnosis. Here we report on the validation of a quantitative, molecular diagnostic algorithm based on the relative abundances of ten potentially pathogenic bacteria and four commensal Lactobacillus species in research subjects (n = 172) classified as symptomatic (n = 149) or asymptomatic (n = 23). We observe a clear and reinforcing pattern among patients diagnosed by the algorithm that is consistent with the current understanding of biological dynamics and dysregulation of the vaginal microbiome during infection. Using this enhanced assessment of the underlying biology of infection, we demonstrate improved diagnostic sensitivity (93%) and specificity (90%) relative to current diagnostic tools. Our algorithm also appears to provide enhanced diagnostic capabilities in ambiguous classes of patients for whom diagnosis and medical decision-making is complicated, including asymptomatic patients and those deemed “intermediate” by Nugent scoring. Ultimately, we establish CLS2.0q as a quantitative, sensitive, specific, accurate, robust, and flexible algorithm for the clinical diagnosis of bacterial vaginosis – importantly, one that is also ideal for the differential diagnosis of non-BV infections with clinically similar presentations.
Antimicrobial Activity of Tetrabromobisphenol A (TBBPA) against Staphylococcus aureus Skin Infections
Authors: Wang Chang , Ji Fang , Chen Fengjie , Chen Bolei , Zhou Zhen , Li Zhi , Liang Yong 
Published: May 2018

AbstractTetrabromobisphenol A (TBBPA) is a brominated flame retardant with selective antimicrobial activity against Gram-positive bacteria. We show that TBBPA exerts bactericidal effects by damaging the cell wall and membrane of Staphylococcus aureus (SA) without inducing antimicrobial resistance. In vivo skin infection assays indicate that a low dose of TBBPA could contribute to wound closure and attenuate SA infection and inflammatory infiltration. TBBPA has potential for use as an antimicrobial agent against Gram-positive pathogens.
Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing datasets
Authors: Evans Perry , Wu Chao , Lindy Amanda , McKnight Dianalee A. , Lebo Matthew , Sarmady Mahdi , Abou Tayoun Ahmad N. 
Published: May 2018

AbstractRecent advances in DNA sequencing technologies have expanded our understanding of the molecular underpinnings for several genetic disorders, and increased the utilization of genomic tests by clinicians. Given the paucity of evidence to assess each variant, and the difficulty of experimentally evaluating a variant’s clinical significance, many of the thousand variants that can be generated by clinical tests are reported as variants of unknown clinical significance. However, the creation of population-scale variant databases can significantly improve clinical variant interpretation. Specifically, pathogenicity prediction for novel missense variants can now utilize features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Several computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant dataset. Here we introduce one variant dataset derived from clinical sequencing panels, and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This dataset is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further utilize this dataset to demonstrate the necessity of disease-specific classifiers, and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant level features. PathoPredictor achieves an average precision greater than 90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. Accumulation of larger clinical variant datasets and their utilization to train existing pathogenicity metrics can significantly enhance their performance in a disease and gene-specific manner.
Extracellular Degradation into Adenosine and the Activities of Adenosine Kinase and AMPK Mediate Extracellular NAD+-produced increases in the Adenylate Pool of BV2 Microglia under Basal Conditions
Authors: Zhang Jie , Wang Caixia , Wu Danhong , Ying Weihai 
Published: May 2018

AbstractCumulating evidence has indicated NAD+ deficiency as a common central pathological factor of multiple diseases and aging. NAD+ supplement is highly protective in various disease and aging models, while two key questions remain unanswered: 1) Does extracellular NAD+ also produce its effects through its degradation product adenosine? 2) Does extracellular NAD+ produce the protective effects by affecting cells under pathological insults only, or by affecting both normal cell and cells under pathological insults? Since extracellular NAD+ can be degraded into adenosine, and endogenous adenosine levels are in the nanomolar range under physiological conditions, extracellular NAD+ may produce its effects through its degradation into adenosine. In this study we used BV2 microglia as a cellular model to test our hypothesis that NAD+ treatment can increase the intracellular adenylate pool under basal conditions through its extracellular degradation into adenosine. Our study has shown that extracellular NAD+ increases the adenylate pool of BV2 microglia under basal conditions through its degradation into adenosine that enters the cells through equilibrative nucleoside transporters. The intracellular adenosine is converted to AMP by adenosine kinase, which increases intracellular ATP by both activating AMPK and increasing ADP that drives mitochondrial FoF1-ATP synthase. Collectively, our study has suggested that extracellular NAD+ can enhance defensive capacity of normal cells through a novel pathway, which includes extracellular NAD+ degradation into adenosine and the activities of adenosine kinase and AMPK. Our findings have also suggested that NAD+ administration in various disease and aging models may significantly affect the microglia under basal conditions.
Redefining mesothelioma types as a continuum uncovers the immune and vascular systems as key players in the diagnosis and prognosis of this disease
Authors: Alcala Nicolas , Caux Christophe , Girard Nicolas , McKay J.D. , Galateau-Salle Francoise , Foll Matthieu , Fernandez-Cuesta Lynnette 
Published: May 2018

SummaryMalignant Pleural Mesothelioma (MPM) is an aggressive disease related to asbestos exposure, which incidence is expected to increase in the future, and with no effective therapeutic options. We have performed unsupervised analyses of publicly available RNAseq data for 297 MPM. We found that the molecular profile and the prognosis of this disease is better explained by a continuous model rather than by the current WHO classification into the epitheloid, biphasic and sarcomatoid histological types. The main source of variation of this continuum was explained by the immune and vascular pathways, with strong differences in the expression of pro-angiogenic genes and immune checkpoint inhibitors across samples. These data may inform future classifications of MPM and may also guide personalised therapeutic approaches for this disease.SignificanceMalignant Pleural Mesothelioma (MPM) is an aggressive disease with no effective therapeutic options. Unsupervised transcriptomic analyses of 297 MPM unveiled the vascular and the immune systems as key players in the prognosis of this disease, and identified potential therapeutic approaches for this disease targeting these pathways.
Chorioamnionitis Is a Risk Factor for Intraventricular Hemorrhage in Preterm Infants: A Systematic Review and Meta-Analysis
Authors: Villamor-Martinez Eduardo , Fumagalli Monica , Rahim Owais Mohammed , Passera Sofia , Cavallaro Giacomo , Degraeuwe Pieter , Mosca Fabio , Villamor Eduardo 
Published: May 2018

AbstractAlthough chorioamnionitis (CA) is a well-known risk factor for white matter disease of prematurity, the association with intraventricular hemorrhage (IVH) is controversial and has not been yet systematically reviewed. We performed a systematic review and meta-analysis of studies exploring the association between CA and IVH. A comprehensive literature search was conducted using PubMed/MEDLINE and EMBASE, from their inception to 1 July 2017. Studies were included if they examined preterm infants and reported primary data that could be used to measure the association between exposure to CA and the presence of IVH. A random-effects model was used to calculate odds ratios (OR) and 95% confidence intervals (CI). We found 1284 potentially relevant studies, of which 85 met the inclusion criteria (46,244 infants, 13,432 CA cases). Meta-analysis showed that CA exposure was significantly associated with all grades IVH (OR 1.88, 95% CI 1.61-2.19), with grades 1-2 IVH (OR 1.69, 95% CI 1.22-2.34), and with grades 3-4 IVH (OR 1.62, 95% CI 1.42-1.85). Both clinical and histological CA were associated with an increased risk for developing IVH in very preterm infants. In contrast, the presence of funisitis did not increase IVH risk when compared to CA in the absence of funisitis (OR 1.22, 95% CI 0.89-1.67). Further meta-analyses confirmed earlier findings that CA-exposed infants have significantly lower gestation age (GA; mean difference [MD] −1.20 weeks) and lower birth weight (BW; MD −55g) than the infants not exposed to CA. However, meta-regression and subgroup analysis could not demonstrate an association between the lower GA and BW and the risk of IVH in the CA-exposed infants. In conclusion, our data show that CA is a risk factor for IVH, but also a risk factor for greater prematurity and more clinical instability. In contrast to other complications of prematurity, such as patent ductus arteriosus, retinopathy of prematurity, or bronchopulmonary dysplasia, the effect of CA on IVH appears to be independent of CA as causative factor for very preterm birth.
The interaction of p130Cas with PKN3 promotes malignant growth
Authors: Gemperle Jakub , Dibus Michal , Koudelková Lenka , Rosel Daniel , Brábek Jan 
Published: May 2018

AbstractProtein p130Cas constitutes an adaptor protein mainly involved in integrin signaling downstream of Src kinase. Owing to its modular structure, p130Cas acts as a general regulator of cancer cell growth and invasiveness induced by different oncogenes. However, other mechanisms of p130Cas signaling leading to malignant progression are poorly understood. Here, we show a novel interaction of p130Cas with Ser/Thr kinase PKN3, which is implicated in prostate and breast cancer growth downstream of phosphoinositide 3-kinase. This direct interaction is mediated by the p130Cas SH3 domain and the centrally located PKN3 polyproline sequence. PKN3 is the first identified Ser/Thr kinase to bind and phosphorylate p130Cas and to colocalize with p130Cas in cell structures that have a pro-invasive function. Moreover, the PKN3-p130Cas interaction is important for mouse embryonic fibroblast growth and invasiveness independent of Src transformation, indicating a distinct mechanism from that previously characterized for p130Cas. Together, our results suggest that the PKN3-p130Cas complex may represent an attractive therapeutic target in late-stage malignancies.SummaryGemperle et al. present the first report of an interaction between p130Cas with the serine/threonine kinase PKN3, implicated in prostate and breast cancer growth. They show that p130Cas colocalizes with PKN3 in cell structures that have a pro-invasive function and enhance our understanding of PKN3-mediated signaling and tumor growth.