bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silicate, Oxide and Sulphide Trends in Neo-Archean Rocks from the Nilgiri Block, Southern India: the Role of Fluids During High-grade Metamorphism
Authors: Samuel Vinod O , Harlov Daniel E , Kwon Sanghoon , Sajeev K 
Published: April 2019

Abstract
The Nilgiri Block, southern India represents an exhumed section of lower, late Archean (2500 Ma) crust. The northern highlands of the Nilgiri Block are characterized by metagabbros with pyroxenite inlayers. A two-pyroxene granulite zone acts as a transition between the metagabbros and charnockites, which are exposed in the central and southern part of the Nilgiri highlands. Thermobarometry results indicate a SW–NE regional trend both in temperature (∼650–800°C) and in pressure (700–1100 MPa) over the Nilgiri highlands. In the charnockites, composite rutile–ilmenite grains are the dominant oxide assemblage. In the two-pyroxene granulites, hemo-ilmenite–magnetite is dominant with coexisting rutile–ilmenite composite grains in a few samples in the vicinity of the boundary with the charnockites. In the metagabbros, hemo-ilmenite–magnetite is the dominant oxide assemblage. The principal sulphide mineral in the charnockite is pyrrhotite with minor pyrite–chalcopyrite exsolution lamellae or blebs. In the two-pyroxene granulites and the metagabbros, the principal sulphide assemblage consists of discrete pyrite grains with magnetite rims and pyrite–pyrrhotite–chalcocopyrite associations. From these observations, a specific oxidation trend is seen. The northern granulite-facies metagabbros and two-pyroxene granulites of the Nilgiri highlands are highly oxidized compared with the charnockites from the central and southern regions. This higher oxidation state is proposed to be the result of highly oxidizing agents (probably as SO3) in low H2O activity grain boundary NaCl saline fluids with a dissolved CaSO4 component present during granulite-facies metamorphism of the metagabbros and two-pyroxene granulites. Eventually these agents became more reducing, owing to the inherent buffering of the original tonalite–granodiorite granitoids at the graphite–CO2 buffer, such that S took the form of H2S during the granulite-facies metamorphism of the charnockites. At the same time, these saline fluids were also responsible the solid-state conversion of biotite and amphibole to orthopyroxene and clinopyroxene in the metagabbro, two-pyroxene granulite, and charnockite.
Using the basic reproduction number to assess the risk of transmission of lumpy skin disease virus by biting insects
Authors: Gubbins Simon 
Published: April 2019

SummaryIn recent years, lumpy skin disease virus (LSDV) has emerged as a major threat to cattle outside Africa, where it is endemic. Although evidence suggests that LSDV is transmitted by the bites of blood sucking arthropods, few studies have assessed the risk of transmission posed by particular vector species. Here this risk is assessed by calculating the basic reproduction number (R0) for transmission of LSDV by five species of biting insect: the stable fly, Stomoxys calcitrans, the biting midge, Culicoides nubeculosus, and three mosquito species, Aedes aegypti, Anopheles stephensi and Culex quinquefasciatus. Parameters relating to mechanical transmission of LSDV were estimated using new analyses of previously-published data from transmission experiments, while vector life history parameters were derived from the published literature. Uncertainty and sensitivity analyses were used to compute R0 for each species and to identify those parameters which influence its magnitude. Results suggest that S. calcitrans is likely to be the most efficient at transmitting LSDV, with Ae. aegypti also an efficient vector. By contrast, C. nubeculosus, An. stephensi, and Cx. quinquefasciatus are likely to be inefficient vectors of LSDV. However, there is considerable uncertainty associated with the estimates of R0, reflecting uncertainty in most of the constituent parameters. Sensitivity analysis suggests that future experimental work should focus on estimating the probability of transmission from insect to bovine and on the virus inactivation rate in insects.
Commercial gene expression tests for prostate cancer prognosis provide paradoxical estimates of race-specific risk
Authors: Creed Jordan H. , Berglund Anders E. , Rounbehler Robert J. , Awasthi Shivanshu , Cleveland John L. , Park Jong Y. , Yamoah Kosj , Gerke Travis A. 
Published: April 2019

AbstractBackgroundCommercial gene expression signatures of prostate cancer (PCa) prognosis were developed and validated in cohorts of predominantly European American men (EAM). Limited research exists on the value of such signatures in African American men (AAM), who have poor PCa outcomes. We explored differences in gene expression between EAM and AAM for three commercially available panels recommended by the National Comprehensive Cancer Network for PCa prognosis. Materials and Methods: 232 EAM and 95 AAM patients provided radical prostatectomy specimens. Gene expression was quantified using Nanostring for 60 genes spanning the Oncotype DX Prostate, Prolaris, and Decipher panels. A continuous expression-based risk score was approximated for each. Differential expression, intrapanel co-expression and risk by race were assessed.Results and limitationsClinical and pathologic features were similar between AAM and EAM. Differential expression by race was observed for 48% of genes measured, though the magnitudes of expression differences were small. Coexpression patterns were more strongly preserved by race group for Oncotype DX and Decipher versus Prolaris (integrative correlations of 0.87, 0.73, and 0.62, respectively). Poorer prognosis was estimated in EAM versus AAM for Oncotype DX (p < 0.001), whereas no difference in prognosis was predicted between AAM and EAM using Prolaris or Decipher (p > 0.05). Replication of our findings directly on the commercial panels with long-term follow-up is warranted.ConclusionsDue to observed racial differences across three commercial gene expression panels for PCa prognosis, caution is warranted when applying these panels in clinical decision-making in AAM.
Blue carbon sequestration dynamics within tropical seagrass sediments: Long-term incubations for changes over climatic scales
Authors: Hoe Chuan Chee , Gallagher John Barry , Theng Chew Swee , Zanuri Norlaila Binti Mohd. 
Published: April 2019

AbstractDetermination of blue carbon sequestration in seagrass sediments over climatic time scales relies on several assumptions, such as no loss of particulate organic carbon (POC) after one or two years, tight coupling between POC loss and CO2emissions, no dissolution of carbonates and removal of the stable black carbon (BC) contribution. We tested these assumptions via 500-day anoxic decomposition/mineralisation experiments to capture centennial parameter decay dynamics from two sediment horizons robustly dated as 2 and 18 years old. No loss of BC was detected, and decay of POC was best described for both horizons by near-identical reactivity continuum models. The models predicted average losses of 49% and 51% after 100 years of burial and 20–22 cm horizons, respectively. However, the loss rate of POC was far greater than the release rate of CO2, both before and after accounting for CO2from anoxic particulate inorganic carbon (PIC) production, possibly as siderite. The deficit could not be attributed to dissolved organic carbon or dark CO2fixation. Instead, evidence based on δ13CO2, acidity and lack of sulphate reduction suggested methanogenesis. The results indicate the importance of centennial losses of POC and PIC precipitation and possibly methanogenesis in estimating carbon sequestration rates.
A pipeline to create predictive functional networks: application to the tumor progression of hepatocellular carcinoma
Authors: Folschette Maxime , Legagneux Vincent , Poret Arnaud , Chebouba Lokmane , Guziolowski Carito , Théret Nathalie 
Published: April 2019

AbstractBackgroundIntegrating genome-wide gene expression patient profiles with regulatory knowledge is a challenging task because of the inherent heterogeneity, noise and incompleteness of biological data. From the computational side, several solvers for logic programs are able to perform extremely well in decision problems for combinatorial search domains. The challenge then is how to process the biological knowledge in order to feed these solvers to gain insights in a biological study. It requires formalizing the biological knowledge to give a precise interpretation of this information; currently, very few pathway databases offer this possibility.ResultsThe presented work proposes an automatic pipeline to extract automatically regulatory knowledge from pathway databases and generate novel computational predictions related to the state of expression or activity of biological molecules. We applied it in the context of hepatocellular carcinoma (HCC) progression, and evaluate the precision and the stability of these computational predictions. Our working base is a graph of 3,383 nodes and 13,771 edges extracted from the KEGG database, in which we integrate 209 differentially expressed genes between low and high aggressive HCC across 294 patients. Our computational model predicts the shifts of expression of 146 initially non-observed biological components. Our predictions were validated at 88% using a larger experimental dataset and cross-validation techniques. In particular, we focus on the protein complexes predictions and show for the first time that NFKB1/BCL-3 complexes are activated in aggressive HCC. In spite of the large dimension of the reconstructed models, our analyses over the computational predictions discover a well constrained region where KEGG regulatory knowledge constrains gene expression of several biomolecules. These regions can offer interesting windows to perturb experimentally such complex systems.ConclusionThis new pipeline allows biologists to develop their own predictive models based on a list of genes. It facilitates the identification of new regulatory biomolecules using knowledge graphs and predictive computational methods. Our workflow is implemented in an automatic python pipeline which is publicly available at https://github.com/LokmaneChebouba/key-pipe and contains as testing data all the data used in this paper.
Disruption of genes associated with Charcot-Marie-Tooth type 2 lead to common behavioural, cellular and molecular defects inCaenorhabditis elegans
Authors: Soh Ming S. , Cheng Xinran , Liu Jie , Neumann Brent 
Published: April 2019

AbstractCharcot-Marie-Tooth (CMT) disease is an inherited peripheral motor and sensory neuropathy. The disease is divided into demyelinating (CMT1) and axonal (CMT2) neuropathies, and although we have gained molecular information into the details of CMT1 pathology, much less is known about CMT2. Due to its clinical and genetic heterogeneity, coupled with a lack of animal models, common underlying mechanisms remain elusive. In order to understand the biological importance of CMT2-casuative genes, we have studied the behavioural, cellular and molecular consequences of mutating nine different genes associated with CMT2 in the nematodeCaenorhabditis elegans(lin-41/TRIM2, dyn-1/DMN2, unc-116/KIF5A, fzo-1/MFN2, osm-9/TRPV4, cua-1/ATP7A, hsp-25/HSPB1, hint-1/HINT1, nep-2/MME). We show thatC. elegansdefective for these genes display debilitated movement in crawling and swimming assays. Severe morphological defects in cholinergic motors neurons are also evident in two of the mutants (dyn-1andunc-116). Furthermore, we establish novel methods for quantifying muscle morphology and use these to demonstrate striking loss of muscle structure across the mutants that correspond with reductions in muscle function. Finally, using electrophysiological recordings of neuromuscular junction (NMJ) activity, we uncover reductions in spontaneous postsynaptic current frequency inlin-41, dyn-1, unc-116andfzo-1mutants. By comparing the consequences of mutating numerous CMT2-related genes, this study reveals common deficits in muscle structure and function, as well as NMJ signalling when these genes are disrupted.
Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts
Authors: Nair Surag , Kim Daniel S. , Perricone Jacob , Kundaje Anshul 
Published: April 2019

AbstractMotivationGenome-wide profiles of chromatin accessibility and gene expression in diverse cellular contexts are critical to decipher the dynamics of transcriptional regulation. Recently, convolutional neural networks (CNNs) have been used to learn predictive cis-regulatory DNA sequence models of context-specific chromatin accessibility landscapes. However, these context-specific regulatory sequence models cannot generalize predictions across cell types.ResultsWe introduce multi-modal, residual neural network architectures that integrate cis-regulatory sequence and context-specific expression of trans-regulators to predict genome-wide chromatin accessibility profiles across cellular contexts. We show that the average accessibility of a genomic region across training contexts can be a surprisingly powerful predictor. We leverage this feature and employ novel strategies for training models to enhance genome-wide prediction of shared and context-specific chromatin accessible sites across cell types. We interpret the models to reveal insights into cis and trans regulation of chromatin dynamics across 123 diverse cellular contexts.AvailabilityThe code is available athttps://github.com/kundajelab/ChromDragoNNContactakundaje@stanford.edu
Nuclear RNA export factor variant initiates piRNA-guided co-transcriptional silencing
Authors: Murano Kensaku , Iwasaki Yuka W. , Ishizu Hirotsugu , Mashiko Akane , Shibuya Aoi , Kondo Shu , Adachi Shungo , Suzuki Saori , Saito Kuniaki , Natsume Tohru , Siomi Mikiko C. , Siomi Haruhiko 
Published: April 2019

SummaryThe PIWI-interacting RNA (piRNA) pathway preserves genomic integrity by repressing transposable elements (TEs) in animal germ cells. Among PIWI-clade proteins inDrosophila, Piwi transcriptionally silences its targets through interactions with cofactors, including Panoramix (Panx) and forms heterochromatin characterized by H3K9me3 and H1. Here, we identified Nxf2, a nuclear RNA export factor (NXF) variant, as a protein that forms complexes with Piwi, Panx, and p15. Panx-Nxf2-p15 complex formation is necessary in the silencing by stabilizing protein levels of Nxf2 and Panx. Notably, ectopic targeting of Nxf2 initiates co-transcriptional repression of the target reporter in a manner independent of H3K9me3 marks or H1. However, continuous silencing requires HP1a and H1. In addition, Nxf2 directly interacts with target TE transcripts in a Piwi-dependent manner. These findings suggest a model in which the Nxf2-Panx-p15 complex enforces the association of Piwi with target transcripts to trigger co-transcriptional repression, prior to heterochromatin formation in the nuclear piRNA pathway.HighlightsNxf2 plays an essential role in the Piwi–piRNA pathwayFormation of Piwi-Panx-Nxf2-p15 (PPNP) complexes stabilizes both Panx and Nxf2The PPNP complex triggers transcriptional silencing before heterochromatin formationNxf2 directly binds to target transcripts in a Piwi-dependent manner
U-PASS: unified power analysis and forensics for qualitative traits in genetic association studies
Authors: Gao Zheng , Terhorst Jonathan , Van Hout Cristopher , Stoev Stilian 
Published: April 2019

AbstractSummaryDespite the availability of existing calculators for statistical power analysis in genetic association studies, there has not been a model-invariant and test-independent tool that allows for both planning of prospective studies and systematic review of reported findings. In this work, we develop a web-based application U-PASS (Unified Power analysis of ASsociation Studies), implementing a unified framework for the analysis of common association tests for binary qualitative traits. The application quantifies the shared asymptotic power limits of the common association tests, and visualizes the fundamental statistical trade-off between risk allele frequency (RAF) and odds ratio (OR). The application also addresses the applicability of asymptotics-based power calculations in finite samples, and provides guidelines for single- SNP-based association tests. In addition to designing prospective studies, U-PASS enables researchers to retrospectively assess the statistical validity of previously reported associations.Availability and implementationU-PASS is available as a web-based R Shiny application at https://power.stat.lsa.umich.edu. Source code is available at https://github.com/Pill-GZ/U-PASS.Contactgaozheng@umich.eduSupplementary informationSupplementary data are available in the application.
Hyperactive TORC1 sensitizes yeast cells to endoplasmic reticulum stress by compromising cell wall integrity
Authors: Ahmed Khadija , Carter David E. , Lajoie Patrick 
Published: April 2019

ABSTRACTThe disruption of protein folding homeostasis in the endoplasmic reticulum (ER) results in an accumulation of toxic misfolded proteins and activates a network of signaling events collectively known as the unfolded protein response (UPR). While UPR activation upon ER stress is well characterized, how other signaling pathways integrate into the ER proteostasis network is unclear. Here, we sought to investigate how the target of rapamycin complex 1 (TORC1) signaling cascade acts in parallel with the UPR to regulate ER stress sensitivity. UsingS. cerevisiae, we found that TORC1 signaling is attenuated during ER stress and constitutive activation of TORC1 increases sensitivity to ER stressors such as tunicamycin and inositol deprivation. This phenotype is independent of the UPR. Transcriptome analysis revealed that TORC1 hyperactivation results in cell wall remodelling. Conversely, hyperactive TORC1 sensitizes cells to cell wall stressors, including the antifungal caspofungin. Elucidating the crosstalk between the UPR, cell wall integrity, and TORC1 signaling may uncover new paradigms through which the response to protein misfolding is regulated, and thus have crucial implications for the development of novel therapeutics against pathogenic fungal infections.IMPORTANCEThe prevalence of pathogenic fungal infections, coupled with the emergence of new fungal pathogens, has brought these diseases to the forefront of global health problems. While antifungal treatments have advanced over the last decade, patient outcomes have not substantially improved. These shortcomings are largely attributed to the evolutionary similarity between fungi and humans, which limits the scope of drug development. As such, there is a pressing need to understand the unique cellular mechanisms that govern fungal viability. Given thatSaccharomyces cerevisiaeis evolutionarily related to a number of pathogenic fungi, and in particular to theCandidaspecies, most genes fromS. cerevisiaeare highly conserved in pathogenic fungal strains. Here we show that hyperactivation of TORC1 signaling sensitizesS. cerevisiaecells to both endoplasmic reticulum stress and cell wall stressors by compromising cell wall integrity. Therefore, targeting TORC1 signaling and endoplasmic reticulum stress pathways may be useful in developing novel targets for antifungal drugs.
Noda-like RNA viruses infectingCaenorhabditisnematodes: sympatry, diversity and reassortment
Authors: Frézal Lise , Jung Hyeim , Tahan Stephen , Wang David , Félix Marie-Anne 
Published: April 2019

AbstractThree RNA viruses related to nodaviruses were previously described to naturally infect the nematodeCaenorhabditis elegansand its relativeC. briggsae. Here we report on a collection of over 50 viral variants from wild-caughtCaenorhabditis. We describe the discovery of a new related virus, the Mělník virus, infectingC. briggsae, which similarly infects intestinal cells. In France, a frequent pattern of co-infection ofC. briggsaeby the Santeuil virus and Le Blanc virus was observed at the level of an individual nematode and even a single cell. We do not find evidence of reassortment between the RNA1 and RNA2 molecules of Santeuil and Le Blanc viruses. However, by studying patterns of evolution of each virus, reassortments of RNA1 and RNA2 among variants of each virus were identified. We develop assays to test the relative potency and competitive ability of the viral variants and detect an interaction between host genotype and Santeuil virus genotype, such that the result of the competition depends on the host strain.ImportanceThe roundwormCaenorhabditis elegans is a laboratory model organism in biology. We study natural populations of this small animal and its relativeC. briggsaeand the viruses that infect them. We previously discovered three RNA viruses related to nodaviruses and here describe a fourth one, called the Melnik virus. These viruses have a genome composed of two RNA molecules. We find that two viruses may infect the same animal and the same cell. The two RNA molecules may be exchanged between variants of a given viral species. We study the diversity of each viral species and devise an assay of their competitive ability. Using this assay, we show that the outcome of the competition also depends on the host.
Parsers, Data Structures and Algorithms for Macromolecular Analysis Toolkit (MAT): Design and Implementation
Authors: Kalyan Gazal , Junghare Vivek , S S John , Chattopadhyay Anupam , Mitra Pralay , Hazra Saugata 
Published: April 2019

AbstractThe structural information of biological macromolecules are stored in .pdb, .mm-cif and lately mmtf files and thus it requires accurate and efficient biological tools for various utilities. Here, we describe Macromolecular Analysis Toolkit (MAT) that parses .pdb, .mmcif and .mmtf files; and builds data structures from the input. This original program is written in C++ programming language to ensure efficiency and consistency to organize structural information in an integral way. The novelty of the program lies in the addition of new structure-based biological algorithms and applications. This package also stands out from other similar libraries by being 1) faster and 2) accurate. We also provide detailed comparison of available parsers on the whole PDB database. The parser of MAT is designed in such a way that it allows quick extraction and organized loading of the core data structure. The same data structure is extended to accommodate information from the .mmcif and .mmtf file parsers. Tokenization of the data allows the extraction of information from disordered text, making it compatible for accurate identification of the entities present in the .pdb file. Additionally, we add a new approach of performance optimization by creating a few derived data structures, namely kD-Tree, Octree and graphs, for certain applications that need spatial coordinate calculations. MAT provides advanced data structure which is time efficient and is designed to avail reusability and consistency in a systematic framework. MAT parser can be accessed online through bitbucket at https://bitbucket.org/gazalk/pdb_parser/.