bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic Locus Modulating IOP in the BXD RI Mouse Strains
Authors: King Rebecca , Li Ying , Wang Jiaxing , Struebing Felix L. , Geisert Eldon E. 
Published: November 2017

AbstractPurposeIntraocular pressure (IOP) is the primary risk factor for developing glaucoma. The present study examines genomic contribution to the normal regulation of IOP in the mouse.MethodsThe BXD recombinant inbred (RI) strain set was used to identify genomic loci modulating IOP. We measured the IOP from 532 eyes from 34 different strains. The IOP data will be subjected to conventional quantitative trait analysis using simple and composite interval mapping along with epistatic interactions to define genomic loci modulating normal IOP.ResultsThe analysis defined one significant quantitative trait locus (QTL) on Chr.8 (100 to 106 Mb). The significant locus was further examined to define candidate genes that modulate normal IOP. There are only two good candidate genes within the 6 Mb over the peak, Cdh8 (Cadherin 8) and Cdh11 (Cadherin 11). Expression analysis on gene expression and immunohistochemistry indicate that Cdh11 is the best candidate for modulating the normal levels of IOP.ConclusionsWe have examined the genomic regulation of IOP in the BXD RI strain set and found one significant QTL on Chr. 8. Within this QTL that are two potential candidates for modulating IOP with the most likely gene being Cdh11.
The trauma severity model: An ensemble machine learning approach to risk prediction
Authors: Gorczyca Michael T. , Toscano Nicole C. , Cheng Julius D. 
Published: November 2017

AbstractStatistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appropriate. This is highly relevant in the context of mortality risk prediction for trauma patients, as researchers have focused exclusively on the use of generalized linear models for risk prediction, and generalized linear models may be too inflexible to capture the potentially complex relationships in trauma data. Due to this, we propose a machine learning model, the Trauma Severity Model (TSM), for risk prediction. In order to validate TSM’s performance, this study compares TSM to three established risk prediction models: the Bayesian Logistic Injury Severity Score, the Harborview Assessment for Risk of Mortality, and the Trauma Mortality Prediction Model. Our results indicate that TSM has superior performance, and thereby provides improved risk prediction.Highlights:We propose an ensemble machine learning model for trauma risk prediction.A hyper-parameter search scheme is proposed for model development.We compare our model to established models for trauma risk prediction.Our model improves over established models for each performance metric considered.
Carry-over effects of larval microclimate on the transmission potential of a mosquito-borne pathogen
Authors: Evans Michelle V. , Shiau Justine C. , Solano Nicole , Brindley Melinda A. , Drake John M. , Murdock Courtney C. 
Published: November 2017

AbstractClimate shapes the transmission of mosquito-borne pathogens through impacts on both the vector and the pathogen. In addition to direct effects of the environment, carry-over effects from previous life history stages can influence mosquito traits relevant to disease transmission. While this has been explored in a laboratory setting, the net effect of temperature-mediated carry-over effects due to relevant environmental variation in the larval stage is ambiguous. Here, we use data collected from a semi-field experiment investigating dengue dynamics inAedes albopictusacross a natural environmental gradient to parameterize a dengue transmission model. We rearedAe. albopictusacross three different land classes characterized by their proportion of impervious surface. Emerged females were offered a dengue infectious bloodmeal, kept at a constant 27 °C, and assayed for infection, dissemination, and infectiousness 21 days post infection. Incorporating carry-over effects of larval environment on measures of vector competence resulted in lower predicted dengue transmission potential across land class and season, however a strong positive relationship with larval environmental temperature remained. Given the significant impact of carry-over effects, future mechanistic models of disease transmission should include both direct and carry-over effects of environmental temperature.
Phosphorylation of the synaptonemal complex protein SYP-1 promotes meiotic chromosome segregation
Authors: Sato-Carlton Aya , Nakamura-Tabuchi Chihiro , Chartrand Stephane Kazuki , Uchino Tomoki , Carlton Peter Mark 
Published: November 2017

AbstractChromosomes that have undergone crossing-over in meiotic prophase must maintain sister chromatid cohesion somewhere along their length between the first and second meiotic divisions. While many eukaryotes use the centromere as a site to maintain cohesion, the holocentric organismC. elegansinstead creates two chromosome domains of unequal length termed the short arm and long arm, which become the first and second site of cohesion loss at meiosis I and II. The mechanisms that confer distinct functions to the short and long arm domains remain poorly understood. Here, we show that phosphorylation of the synaptonemal complex protein SYP-1 is required to create these domains. Once crossovers are made, phosphorylated SYP-1 and PLK-2 become cooperatively confined to short arms and guide phosphorylated histone H3 and the chromosomal passenger complex to the site of meiosis I cohesion loss. Our results show that PLK-2 and phosphorylated SYP-1 ensure creation of the short arm subdomain, promoting disjunction of chromosomes in meiosis I.
A size-invariant bud-duration timer enables robustness in yeast cell size control
Authors: Allard Corey A.H. , Decker Franziska , Weiner Orion D. , Toettcher Jared E. , Graziano Brian R. 
Published: November 2017

SUMMARYCell size drives key aspects of cell physiology, including organelle abundance [1, 2] and DNA ploidy [3]. While cells employ diverse strategies to regulate size [4–11], it is unclear how they are integrated to provide robust, systems-level control. In budding yeast, a molecular size sensor restricts passage of small cells through G1, enabling them to gain proportionally more volume than larger cells before progressing to Start [7, 12, 13]. Size control post-Start is less clear. S/G2/M duration in wildtype cells shows only a weak dependence on cell size; and since yeast exhibit exponential growth, larger cells would be expected to add more volume than smaller ones [7, 14–17]. However, even large mother cells produce smaller daughters, suggesting that additional regulation may occur during S/G2/M [7]. To gain further insight into post-Start size control, we prepared ‘giant’ yeast (>10-fold larger than typical volume) using two approaches to reversibly block cell cycle progression but not growth: optogenetic disruption of the cell polarity factor Bem1 [18, 19] and a temperature-sensitivecdk1allele [20]. We reasoned that giant yeast would satisfy pre-Start size control while enabling us to uncover post-Start size-limiting mechanisms though the identification of invariant growth parameters. Upon release from their block, giant mothers reenter the cell cycle and their progeny rapidly return to the original unperturbed size. This behavior is consistent with a size-invariant ‘timer’ specifying the duration of S/G2/M and indicates that yeast use at least two distinct mechanisms at different cell cycle phases to ensure size homeostasis.
Lessons from simple marine models on the bacterial regulation of eukaryotic development
Authors: Woznica Arielle , King Nicole 
Published: November 2017

AbstractMolecular cues from environmental bacteria influence important developmental decisions in diverse marine eukaryotes. Yet, relatively little is understood about the mechanisms underlying these interactions, in part because marine ecosystems are dynamic and complex. With the help of simple model systems, including the choanoflagellate Salpingoeca rosetta, we have begun to uncover the bacterial cues that shape eukaryotic development in the ocean. Here, we review how diverse bacterial cues – from lipids to macromolecules – regulate development in marine eukaryotes. It is becoming clear that there are networks of chemical information circulating in the ocean, with both eukaryotes and bacteria acting as nodes; one eukaryote can precisely respond to cues from several diverse environmental bacteria, and a single environmental bacterium can regulate the development of different eukaryotes.HighlightsCues from environmental bacteria influence the development of many marine eukaryotesThe molecular cues produced by environmental bacteria are structurally diverseEukaryotes can respond to many different environmental bacteriaSome environmental bacteria act as “information hubs” for diverse eukaryotesExperimentally tractable systems, like the choanoflagellate S. rosetta, promise to reveal molecular mechanisms underlying these interactions
High-resolution modeling of thermal thresholds and multiple environmental influences on coral bleaching for regional and local reef managements
Authors: Kumagai Naoki H. , Yamano Hiroya ,   Committee Sango-Map-Project
Published: November 2017

AbstractCorals are one of the communities most threatened by global and local stressors. Excessive summer sea temperatures can cause coral bleaching, resulting in decreases in living coral coverage. Coral bleaching may begin with rising sea temperatures, although the widely used threshold of 1 °C over the local climatological maximum sea temperature has been reconsidered. In this study, we refine thermal indices predicting coral bleaching at high resolution (1 km) by statistically optimizing the thermal threshold and multiple environmental influences on bleaching, such as ultraviolet (UV) radiation, water turbidity, and cooling effects on corals. We use a dataset of coral bleaching events observed during 2004–2016 in Japan derived from the Web-based monitoring system, the Sango (Coral) Map Project, aiming at regional to local conservation of Japanese corals. We show how the ability to predict coral bleaching is improved by the choice of thermal index, statistical optimization of thermal thresholds, usage of multiple environmental influences, and modeling methods (generalized linear model and random forest). After optimization, the differences among the thermal indices in the ability to predict coral bleaching were slight. Among environmental influences, cooling effects, UV radiation, and water turbidity, in addition to a thermal index, well explain the occurrence of coral bleaching. Prediction based on the best explanatory model reveals that recent Japanese coral reefs are experiencing bleaching in many areas, although we show a practical way to reduce bleaching frequency significantly by screening UV radiation. Thus, our high-resolution models may provide a quantitative basis for the management of local reefs under current global and local stressors. The results of this study may be useful to other researchers for selecting a predictive method according to their needs or skills.
Probabilistic Count Matrix Factorization for Single Cell Expression Data Analysis
Authors: Durif G. , Modolo L. , Mold J. E. , Lambert-Lacroix S. , Picard F. 
Published: November 2017

AbstractMotivationThe development of high throughput single-cell sequencing technologies now allows the investigation of the population diversity of cellular transcriptomes. The expression dynamics (gene-to-gene variability) can be quantified more accurately, thanks to the measurement of lowly-expressed genes. In addition, the cell-to-cell variability is high, with a low proportion of cells expressing the same genes at the same time/level. Those emerging patterns appear to be very challenging from the statistical point of view, especially to represent a summarized view of single-cell expression data. PCA is a most powerful tool for high dimensional data representation, by searching for latent directions catching the most variability in the data. Unfortunately, classical PCA is based on Euclidean distance and projections that poorly work in presence of over-dispersed count data with dropout events like single-cell expression data.ResultsWe propose a probabilistic Count Matrix Factorization (pCMF) approach for single-cell expression data analysis, that relies on a sparse Gamma-Poisson factor model. This hierarchical model is inferred using a variational EM algorithm. It is able to jointly build a low dimensional representation of cells and genes. We show how this probabilistic framework induces a geometry that is suitable for single-cell data visualization, and produces a compression of the data that is very powerful for clustering purposes. Our method is competed against other standard representation methods like t-SNE, and we illustrate its performance for the representation of single-cell expression (scRNA-seq) data.AvailabilityOur work is implemented in the pCMF R-package1.
HDAC11 is a fatty-acid deacylase
Authors: Kutil Zsofia , Novakova Zora , Meleshin Marat , Mikesova Jana , Schutkowski Mike , Barinka Cyril 
Published: November 2017

ABSTRACTHistone deacetylase 11 (HDAC11) is a sole member of the class IV HDAC subfamily with negligible intrinsic deacetylation activity. Here we reportin vitroprofiling of HDAC11 deacylase activities, and our data unequivocally show that the enzyme efficiently removes acyl moieties spanning 8–18 carbons from the side chain nitrogen of the lysine residue of a peptidic substrate. Additionally, N-linked lipoic acid and biotin are removed by the enzyme, although with lower efficacy. Catalytic efficiencies toward dodecanoylated and myristoylated peptides exceed 70,000 M−1s−1making HDAC11 the most proficient fatty acid deacylase of the HDAC family. Interestingly, HDAC11 is strongly inhibited by free myristic, palmitic and stearic acids with inhibition constants of 6.5 µM, 0.9 µM, and 1.6 µM, respectively. At the same time, its deacylase activity is stimulated more than 2.5-fold by both palmitoyl-coenzyme A and myristoyl-coenzyme A, pointing toward metabolic control of the enzymatic activity by fatty acid metabolites. Our data reveal novel enzymatic activity of HDAC11 that can, in turn, facilitate the uncovering of additional biological functions of the enzyme as well as the design of isoform-specific HDAC inhibitors.
Universal scaling across biochemical networks on Earth
Authors: Kim Hyunju , Smith Harrison B. , Mathis Cole , Raymond Jason , Walker Sara I. 
Published: November 2017

AbstractThe application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes, and 8,658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical networks to random chemical networks reveals the observed biological scaling is not solely a product of the biochemistry shared across life on Earth. Instead, it emerges due to how the global inventory of biochemical reactions is partitioned into individuals. We show the three domains of life are topologically distinguishable, with > 80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Taken together our results point to a deeper level of organization in biochemical networks than what has been understood so far.
Planar cell polarity: thepricklegene acts independently on both the Ds/Ft and the Stan Systems
Authors: Casal José , Ibáñez-Jiménez Beatriz , Lawrence Peter A. 
Published: November 2017

ABSTRACTEpithelial cells are polarised within the plane of the epithelium, forming oriented structures whose coordinated and consistent polarity (planar cell polarity, PCP) relates to the principal axes of the body or organ. InDrosophilaat least two separate molecular systems generate and interpret intercellular polarity signals: Dachsous/Fat, and the “core” or Stan system. Here we study thepricklegene and its protein products Prickle and Spiny leg. Much research on PCP has focused on the asymmetric localisation of core proteins in the cell and as a resultpricklewas placed in the heart of the Stan system. Here we ask if this view is correct and how thepricklegene relates to the two systems. We find thatpricklecan affect, separately, both systems — however, neither Pk nor Sple are essential components of the Ds/Ft or the Stan system, nor do they act as a functional link between the two systems.
Ligand-Mediated Biofilm Formation via Enhanced Physical Interaction Between a Diguanylate Cyclase and Its Receptor
Authors: Giacalone David , Jarrod Smith T. , Collins Alan J. , Sondermann Holger , Koziol Lori J. , O’Toole George A. 
Published: November 2017

AbstractThe second messenger, cyclic dimeric GMP (c-di-GMP) regulates biofilm formation for many bacteria. The binding of c-d¡-GMP by the inner-membrane protein LapD controls biofilm formation, and the LapD receptor is central to a complex network of c-di-GMP-mediated biofilm formation. In this study, we examine how c-di-GMP signaling specificity by a diguanylate cyclase (DGC), GcbC, is achieved via interactions with the LapD receptor and by small ligand sensing via GcbC’s calcium channel chemotaxis (CACHE) domain. We provide evidence that biofilm formation is stimulated by the environmentally relevant organic acid citrate (and a related compound, isocitrate) in a GcbC-dependent manner through enhanced GcbC-LapD interaction, which results in increased LapA localization to the cell surface. Furthermore, GcbC shows little ability to synthesize c-di-GMP in isolation. However, when LapD is present GcbC activity is significantly enhanced ~8-fold, indicating that engaging the LapD receptor stimulates the activity of this DGC; citrate-enhanced GcbC-LapD interaction further stimulates c-di-GMP synthesis. We propose that the l-site of GcbC serves two roles beyond allosteric control of this enzyme: promoting GcbC-LapD interaction and stabilizing the active conformation of GcbC in the GcbC-LapD complex. Finally, given that LapD can interact with a dozen different DGCs of P. fluorescens, many of which have ligand-binding domains, the ligand-mediated enhanced signaling via LapD-GcbC interaction described here is likely a conserved mechanism of signaling in this network. Consistent with this idea, we identify a second example of ligand-mediated enhancement of DGC-LapD interaction that promotes biofilm formation.ImportanceIn many bacteria, dozens of enzymes produce the dinucleotide signal c-di-GMP, however it is unclear how undesired crosstalk is mitigated in the context of this soluble signal, and how c-di-GMP signaling is regulated by environmental inputs. We demonstrate that GcbC, a DGC, shows little ability to synthesize c-d¡-GMP in the absence of its cognate receptor LapD; GcbC-LapD interaction enhances c-di-GMP synthesis by GcbC, likely mediated by the l-site of GcbC. We further show evidence for a ligand-mediated mechanism of signaling specificity via increased physical interaction of a DGC with its cognate receptor. We envision a scenario wherein a “cloud” of weakly active DGCs can increase their activity by specific interaction with their receptor in response to appropriate environmental signals, concomitantly boosting c-di-GMP production, ligand-specific signaling and biofilm formation.
CRIME, FEAR, AND MENTAL HEALTH IN MEXICO
Authors: VILLARREAL ANDRÉS , YU WEI‐HSIN 
Published: November 2017

AbstractThis article examines the effect of exposure to criminal violence on fear of crime and mental health in Mexico, a country that has experienced a dramatic rise in violent events resulting from the operation of drug trafficking organizations (DTOs). Data are drawn from more than 30,000 respondents to a national longitudinal survey of Mexican households. We use fixed‐effects models which allow us to control for time‐invariant individual and municipal characteristics affecting both exposure to violence and mental health. The results indicate a substantial increase in fear and psychological distress for individuals living in communities that suffered a rise in the local homicide rate even when exposure to other forms of victimization and more personal experiences with crime are taken into account. Because DTO killings occur in response to factors external to a specific neighborhood, they generate fear and psychological distress at a larger geographical scale. They also seem to create a generalized sense of insecurity, leading to increased fear of other types of crimes. We examine the effect of large surges in homicide and the presence of military and paramilitary groups combatting DTOs as these conditions may approximate those in conflict zones elsewhere in the world. We also explore differences in the relative sensitivity to homicide rates between sociodemographic groups.
Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator
Authors: Schifman L.A. , Tryby M.E. , Berner J. , Shuster W.D. 
Published: November 2017

AbstractThe U.S. Environmental Protection Agency National Stormwater Calculator (NSWC) simplifies the task of estimating runoff through a straightforward simulation process based on the EPA Stormwater Management Model. The NSWC accesses localized climate and soil hydrology data, and options to experiment with low‐impact development (LID) features for parcels up to 5 ha in size. We discuss how the NSWC treats the urban hydrologic cycle and focus on the estimation uncertainty in soil hydrology and its impact on runoff simulation by comparing field‐measured soil hydrologic data from 12 cities to corresponding NSWC estimates in three case studies. The default NSWC hydraulic conductivity is 10.1 mm/h, which underestimates conductivity measurements for New Orleans, Louisiana (95 ± 27 mm/h) and overestimates that for Omaha, Nebraska (3.0 ± 1.0 mm/h). Across all cities, the NSWC prediction, on average, underestimated hydraulic conductivity by 10.5 mm/h compared to corresponding measured values. In evaluating how LID interact with soil hydrology and runoff response, we found direct hydrologic interaction with pre‐existing soil shows high sensitivity in runoff prediction, whereas LID isolated from soils show less impact. Simulations with LID on higher permeability soils indicate that nearly all of pre‐LID runoff is treated; while features interacting with less‐permeable soils treat only 50%. We highlight the NSWC as a screening‐level tool for site runoff dynamics and its suitability in stormwater management.