bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some fluid mechanical constraints on crystallization and recharge within sills
Authors: Woods Andrew W. , Stock Michael J. 
Published: January 2019

The injection of hot magma into a sill can lead to heating and melting of the walls and roof of the reservoir while the injected magma cools and crystallizes. If the crystals are relatively dense, they will try to sediment from the injected magma to form a cumulate layer. In this cumulate layer, the crystals form a porous framework which traps the melt as it is built up. As the melt within the sill continually cools and precipitates dense crystals, there will be a gradual reduction in the density of the remaining silicate liquid. As a result, the melt which is progressively trapped in the pore space of the cumulate layer will become stably stratified in density. Using an idealized model of the fluid mechanical and thermodynamical principles, we explore some of the controls on the thickness and density stratification of cumulate layers following replenishment of a sill-like magma chamber. We show the balance between jamming of the crystal laden melt to form a homogeneous layer and the formation of a stratified cumulate zone depends on the cooling time scale compared to the sedimentation time scale. A key finding is that the composition and stratification in a packed crystal–melt suspension and the associated cumulate layer formed by cooling an intrusion of hot melt injected into the crust may have considerable variability, depending on the properties of the overlying roof melt and the size and hence fall speed of crystals which form in the melt.
This article is part of the Theo Murphy meeting issue ‘Magma reservoir architecture and dynamics’.
Characterization of a vascular bundle localizing Gossypium hirsutum NAC4 transcription factor promoter for its role in environmental stress responses
Authors: Trishla Vikas Shalibhadra , Marriboina Sureshbabu , Boyidi Prasanna , Gudipalli Padmaja , Kirti Pulugurtha Bharadwaja 
Published: January 2019

AbstractWe have studied the expression of GhNAC4, a NAC domain-containing transcription factor from Gossypium hirsutum. The expression of GhNAC4 was upregulated by ABA, cytokinin, JA, GA, auxin, and ethylene. Its expression was also highly induced by drought, osmotic stress, oxidative stress, salinity, high and low-temperature stress, and wounding. To corroborate these observations, we isolated the promoter of GhNAC4 and fused it transcriptionally with uidA (GUS) gene for analyzing its patterns of expression in transgenic tobacco. The Promoter-GUS fusion was also induced by various phytohormones and environmental stresses. The spatio-temporal analysis of the promoter of the GhNAC4 gene revealed that GUS expression was mostly localized to the vascular bundles along with shoot apical meristem and guard cells. We also observed intense staining in other cells upon wounding. A sequence analysis of the promoter revealed the presence of several motifs pertaining to phytohormone responsiveness, stress-inducibility, light and sugar-responsiveness and tissue-specificity. These data were corroborated by a detailed bioinformatic analysis of the promoter sequence of GhNAC4 for identifying the conserved sequences that are associated with the expression of genes in a spatio-temporal or inducive manner. All these data suggests that GhNAC4 is a vascular tissue localizing NAC transcription factor, which might act as a node integrating environmental stress signals for modulating plant growth and development with the aid of phytohormonal stimuli.Key messageGhNAC4 transcription factor from cotton localizes to vascular bundles and is highly upregulated by phytohormones and environmental stresses.
A ribosome assembly stress response regulates transcription to maintain proteome homeostasis
Authors: Albert Benjamin , Kos-Braun Isabelle C. , Henras Anthony , Dez Christophe , Rueda Maria Paula , Zhang Xu , Gadal Olivier , Kos Martin , Shore David 
Published: January 2019

AbstractRibosome biogenesis is a complex and energy-demanding process requiring tight coordination of ribosomal RNA (rRNA) and ribosomal protein (RP) production. Alteration of any step in this process may impact growth by leading to proteotoxic stress. Although the transcription factor Hsf1 has emerged as a central regulator of proteostasis, how its activity is coordinated with ribosome biogenesis is unknown. Here we show that arrest of ribosome biogenesis in the budding yeast S. cerevisiae triggers rapid activation of a highly specific stress pathway that coordinately up-regulates Hsf1 target genes and down-regulates RP genes. Activation of Hsf1 target genes requires neo-synthesis of RPs, which accumulate in an insoluble fraction, leading to sequestration of the RP transcriptional activator Ifh1. Our data suggest that levels of newly-synthetized RPs, imported into the nucleus but not yet assembled into ribosomes, work to continuously balance Hsf1 and Ifh1 activity, thus guarding against proteotoxic stress during ribosome assembly.
Rigorous equations for isothermal titration calorimetry: theoretical and practical consequences
Authors: Dumas Philippe 
Published: January 2019

The author has withdrawn his manuscript because:The withdrawn preprint was about methodological aspects in Isothermal Titration Calorimetry (ITC) used to obtain thermodynamic information about reactions like A + B ⇄ C where A is initially in the cell and B injected from a syringe. The preprint considered the two possible methods in ITC:1/ the Multiple Injection Method (MIM) making use of short-time injections separated by sufficient time to allow the reaction to reach equilibrium before a new injection.2/ the Single Injection Method (SIM) making use of a slow continuous injection.The first result mentioned is about a new equation linking the rate of heat evolution with the injected volume (equations 9 and 10). With this equation and with the hypothesis that there is always perfect mixing of the cell content it was concluded that an ideal titration curve (i.e. not affected by any external influence) for a simple reaction like A + B ⇄ C cannot change sign (section 3.2). This conclusion turns out to be incorrect when taking in consideration real conditions with imperfect mixing, particularly with MIM using injections often of very short duration, which prevents from reaching perfect mixing. The major problem is that this erroneous conclusion was accompanied with comparisons of the results from well-established programs, which led to the conclusion that these were in error on this point (section 3.6).I therefore felt necessary to withdraw this preprint to avoid casting doubts unduly on these programs used extensively.Note that many other aspects in this preprint remain correct (section 3.8). A new version of this work, limited to SIM and considering imperfect mixing, will be submitted for publication under the title: “Isothermal titration calorimetry in the single-injection mode with imperfect mixing”.If you have any questions, please contact me at dumasp@igbmc.fr or at p.dumas@unistra.frSorry for the inconvenience.Philippe DumasNovember 6, 2021
Enhancer transcription identifies cis-regulatory elements for photoreceptor cell types
Authors: Nadadur Rangarajan D. , Perez-Cervantes Carlos , Lonfat Nicolas , Smith Linsin A. , Hughes Andrew E. O. , Wang Sui , Corbo Joseph C. , Cepko Connie , Moskowitz Ivan P. 
Published: January 2019

AbstractIdentification of the cis-regulatory elements (CREs) that regulate gene expression in specific cell types is critical for defining the gene regulatory networks (GRNs) that control normal physiology and disease states. We previously utilized non-coding RNA (ncRNA) profiling to define CREs that comprise a GRN in the adult mouse heart1. Here, we applied ncRNA profiling to the mouse retina in the presence and absence of Nrl, a rod photoreceptor-specific transcription factor required for rod versus cone photoreceptor cell fate. Differential expression of Nrl-dependent ncRNAs positively correlated with differential expression of Nrl-dependent local genes. Two distinct Nrl-dependent regulatory networks were discerned in parallel: Nrl-activated ncRNAs were enriched for accessible chromatin in rods but not cones whereas Nrl-repressed ncRNAs were enriched for accessible chromatin in cones but not rods. Furthermore, differential Nrl-dependent ncRNA expression levels quantitatively correlated with photoreceptor cell type-specific ATAC-seq read density. Direct assessment of Nrl-dependent ncRNA-defined loci identified functional cone photoreceptor CREs. This work supports differential ncRNA profiling as a platform for identifying context-specific regulatory elements and provides insight into the networks that define photoreceptor cell types.
Extracellular mycobacterial DNA drives disease progression by triggering Caspase-11-dependent pyroptosis of infected macrophages
Authors: Varela Monica , van der Vaart Michiel , Groenewoud Arwin , Meijer Annemarie H. 
Published: January 2019

ABSTRACTDeregulated inflammation seriously complicates life-threatening microbial infections, including tuberculosis (TB). Assembly of multiprotein inflammasome complexes is an important trigger of inflammation, but how this impacts TB progression remains unknown. Here,in vivoimaging in the zebrafish TB model revealed that mycobacterial expansion in TB granulomas is driven by inflammasomes and ensuing pyroptotic cell death of infected macrophages. We show that an Asc-independent pathway induces macrophage pyroptosis and impairs host resistance, in contrast to host-protective roles of Asc-dependent inflammasome activation and Il1b secretion. Using ASC-deficient murine macrophages, we demonstrate extracellular bacterial DNA to induce CASP11-dependent pyroptosis in a manner dependent on phagosome permeabilization. Finally, we propose that mycobacteria induce pyroptosis to escape cell-in-cell structures, formed within granulomas when living infected cells are engulfed by neighbor cells. This study provides new insight into the role of pyroptosis in TB pathogenesis and reveals a novel link between nucleic acid sensing and CASP11-dependent pyroptosis.
The role of hippocampal spatial representations in contextualization and generalization of fear
Authors: de Voogd Lycia D. , Murray Yannick P. J. , Barte Ramona M. , van der Heide Anouk , Fernández Guillén , Doeller Christian F. , Hermans Erno J. 
Published: January 2019

AbstractUsing contextual information to predict aversive events is a critical ability that protects from generalizing fear responses to safe contexts. Animal models have demonstrated the importance of spatial context representations within the hippocampal formation in contextualization of fear learning. The ventromedial prefrontal cortex (vmPFC) is known to play an important role in safety learning, possibly also through the incorporation of context information. However, if contextual representations are related to context-dependent expression of fear memory in humans remains unclear. Twenty-one healthy participants underwent functional MRI combined with a cue-context conditioning paradigm within a self-navigated virtual reality environment. The environment included two buildings (Threat and Safe context), which had distinct features outside but were identical inside. Within each context, participants saw two cues (CS+, CS−). The CS+ was consistently (100% reinforcement rate) paired with an electric shock in the Threat context, but never in the Safe context. The CS− was never paired with a shock. We found robust differential skin conductance responses (SCRs; CS+ > CS−) in the Threat context, but also within the Safe context, indicating fear generalization. Within the Safe context, vmPFC responses to the CS+ were larger than those in the Threat context. We furthermore found environment-specific representations for the two contexts in the training paradigm (i.e., before conditioning took place) in the hippocampus to be related to fear expression and generalization. Namely, participants with a weak context representation (z-score < 1.65) showed stronger fear generalization compared to participants with a strong context representation (z-score > 1.65). Thus, a low neural representation of spatial context may explain overgeneralization of memory to safe contexts. In addition, our findings demonstrate that context-dependent regulation of fear expression engages ventromedial prefrontal pathways suggesting this involves a similar mechanism that is known to be involved in retrieval of extinction memory.
Frequency of mutations in 21 hereditary breast and ovarian cancer susceptibility genes among high-risk Chinese individuals
Authors: Shao Di , Cheng Shaomin , Guo Fengming , Yuan Yuying , Hu Kunling , Wang Zhe , Meng Xuan , Jin Xin , Xiong Yun , Chai Xianghua , Li Hong , Zhang Yu , Zhang Hongyun , Liu Jihong , Ye Mingzhi 
Published: January 2019

AbstractTo determine the prevalence and clinical prediction factors associated with deleterious mutations among 882 high-risk Chinese individuals who underwent multigene panel testing for hereditary breast and ovarian cancer (HBOC) risk assessment. Subjects were selected from individuals referred for genetic testing using a 21-gene panel (Oseq-BRCA) between January 2015 and March 2018. The distribution and prevalence of deleterious mutations were analyzed for the full cohort as well as subtypes. Overall, 176 deleterious mutations were observed in 19.50% (n = 172) individuals. Of these, 26 mutations are not reported in public databases and literatures. In the ovarian cancer only subgroup, 115 deleterious mutations were identified in 429 patients (48.6%). Patients with ovarian cancer with mutations were enriched for a family history of breast or ovarian cancers (p < 0.05). In the breast cancer only subgroup, 31 deleterious mutations were identified in 261 patients. Most mutations occurred inBRCA1(8; 25.8%) andBRCA2(11; 35.5%). An additional 12 deleterious mutations (38.7%) were found in 7 other susceptibility genes. An increased frequency of mutation rate (57.9%) was observed in the subgroup of subjects with histories of both breast and ovarian cancer. Taken together, 19.50% of individuals carried a deleterious mutation in HBOC susceptibility genes in our cohort. Subgroup of subjects with histories of both breast and ovarian cancer had the highest prevalence of mutations. Our results highlighted the genetic heterogeneity of HBOC and the efficiency of multigene panel in performing risk assessment.
Cortisol associated with hypometabolism across the Alzheimer’s disease spectrum
Authors: Wirth Miranka , Lange Catharina , Huijbers Willem ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2019

AbstractObjectiveHypothalamic-pituitary-adrenal (HPA) dysregulation is proposed as a risk factor for Alzheimer’s disease (AD). This cross-sectional study assessed relationships between plasma cortisol levels and neuroimaging biomarkers, specifically brain glucose metabolism and gray matter volume, across the AD spectrum.MethodsCognitively normal older adults and patients with mild cognitive impairment (MCI) and AD dementia were included from the Alzheimer’s Disease Neuroimaging Initiative. Participants (n = 556) were selected based on availability of baseline measures of plasma cortisol levels and gray matter volume, as estimated with magnetic resonance imaging. Within a subsample (n = 288), we examined brain glucose metabolism (n = 288) as with positron emission tomography. Relationships between plasma cortisol and AD neuroimaging biomarkers were assessed using regions-of-interest and voxel-wise analyses.ResultsAcross the entire cohort, higher plasma cortisol was also related to lower gray matter volume, most notably in the left lateral temporal-parietal-occipital regions. Importantly, higher plasma cortisol concentration was also related to hypometabolism, especially in lateral temporo-parietal and medial parietal regions. When stratified by diagnosis, these negative associations were most pronounced in MCI and AD patients.InterpretationHigh plasma cortisol was associated with hypometabolism predominantly in AD-sensitive regions. Our results indicate that HPA axis activation could influence brain metabolism and exacerbate existing AD pathological processes. This is consistent with a notion that stress is a conceivable target for intervention to slow down AD progression. Future studies should delineate underlying pathological mechanisms and investigate if clinical or lifestyle interventions could alleviate negative actions of stress on AD.
Planar differential growth rates determine the position of folds in complex epithelia
Authors: Tozluo◻lu Melda , Duda Maria , Kirkland Natalie J. , Barrientos Ricardo , Burden Jemima J. , Muñoz José J. , Mao Yanlan 
Published: January 2019

SummaryFolding is a fundamental process shaping epithelial sheets into 3D architectures of organs. Initial positioning of folds is the foundation for the emergence of correct tissue morphology. Mechanisms forming individual folds have been studied, yet the precise positioning of the folds in complex, multi-folded epithelia is an open question. We present a model of morphogenesis, encompassing local differential growth, and tissue mechanics to investigate tissue fold positioning. We useDrosophila melanogasterwing imaginal disc as our model system, and show that there is spatial and temporal heterogeneity in its planar growth rates. This planar differential growth is the main driver for positioning the folds. Increased stiffness of the apical layer and confinement by the basement membrane drive fold formation. These influence fold positions to a lesser degree. The model successfully predicts the emergent morphology ofwingless spademutantin vivo, via perturbations solely on planar differential growth ratesin silico.
Connectivity of variants in eQTL networks dictates reproducibility and functionality
Authors: Gaynor Sheila M. , Fagny Maud , Lin Xihong , Platig John , Quackenbush John 
Published: January 2019

AbstractNetwork analyses are a natural approach for identifying genetic variants and genes that work together to drive disease phenotypes. The relationship between SNPs and genes, captured in expression quantitative trait locus (eQTL) analysis, can be represented as a network with edges connecting SNPs and genes. Existing network methods treat such edges as fixed and known when they are most often thresholded estimates from eQTL regression. We consider various characterizations of an essential feature of nodes of eQTL networks, their degree centrality, that retains different data on eQTLs. We define the network metric of degree to be estimated by false discovery rates, test statistics, and p-values of the eQTL regressions in order to represent how central and potentially influential a SNP is to the network. We calculate degree metrics for data from 21 tissues from the GTEx project to assess the reproducibility, correlation across tissues, and, functional importance of degree.
StormGraph: A graph-based algorithm for quantitative clustering analysis of diverse single-molecule localization microscopy data
Authors: Scurll Joshua M. , Abraham Libin , Zheng Da Wei , Tafteh Reza , Chou Keng C. , Gold Michael R. , Coombs Daniel 
Published: January 2019

AbstractClustering of proteins is crucial for many cellular processes and can be imaged at nanoscale resolution using single-molecule localization microscopy (SMLM). Ideally, molecular clustering in regions of interest (ROIs) from SMLM images would be assessed using computational methods that are robust to sample and experimental heterogeneity, account for uncertainties in localization data, can analyze both 2D and 3D data, and have practical computational requirements in terms of time and hardware. While analyzing surface protein clustering on B lymphocytes using SMLM, we encountered limitations with existing cluster analysis methods. This inspired us to develop StormGraph, an algorithm using graph theory and community detection to identify clusters in heterogeneous sets of 2D and 3D SMLM data while accounting for localization uncertainties. StormGraph generates both multi-level and single-level clusterings and can quantify cluster overlap for two-color SMLM data. Importantly, StormGraph automatically determines scale-dependent thresholds from the data using scale-independent input parameters. This makes identical choices of input parameter values suitable for disparate ROIs, eliminating the need to tune parameters for different ROIs in heterogeneous SMLM datasets. We show that StormGraph outperforms existing algorithms at analyzing heterogeneous sets of simulated SMLM ROIs where ground-truth clusters are known. Applying StormGraph to real SMLM data in 2D, we reveal that B-cell antigen receptors (BCRs) reside in a heterogeneous combination of small and large clusters following stimulation, which suggests for the first time that two conflicting models of BCR activation are not mutually exclusive. We also demonstrate application of StormGraph to real two-color and 3D SMLM data.
Multiplexed electron microscopy by fluorescent barcoding allows screening for ultrastructural phenotype
Authors: Bykov Yury S. , Cohen Nir , Gabrielli Natalia , Manenschijn Hetty , Welsch Sonja , Chlanda Petr , Kukulski Wanda , Patil Kiran R. , Schuldiner Maya , Briggs John A.G. 
Published: January 2019

AbstractGenetic screens performed using high-throughput fluorescent microscopes have generated large datasets that have contributed many insights into cell biology. However, such approaches typically cannot tackle questions requiring knowledge of ultrastructure below the resolution limit of fluorescent microscopy. Electron microscopy (EM) is not subject to this resolution limit, generating detailed images of cellular ultrastructure, but requires time consuming preparation of individual samples, limiting its throughput. Here we overcome this obstacle and describe a robust method for screening by high-throughput electron microscopy. Our approach uses combinations of fluorophores as barcodes to mark the genotype of each cell in mixed populations, and correlative light and electron microscopy to read the fluorescent barcode of each cell before it is imaged by electron microscopy. Coupled with an easy-to-use software workflow for correlation, segmentation and computer image analysis, our method allows to extract and analyze multiple cell populations from each EM sample preparation. We demonstrate the method on several organelles with samples that each contain up to 15 different yeast variants. The methodology is not restricted to yeast, can be scaled to higher-throughput, and can be utilized in multiple ways to enable electron microscopy to become a powerful screening methodology.