Analysis of factors influencing the modelling of occupant window opening behaviour in an office building in Beijing, China.

This paper introduces a longitudinal study monitoring occupants’ window opening behaviour in a mixed-mode office building in Beijing, China, when natural ventilation is specifically used for controlling the building’s indoor thermal environment. Based on the field measured data, the influence of factors, including outdoor air temperature, outdoor PM2.5, indoor air temperature, time of day, occupancy and previous window state, on the observed state of windows is analysed. All of them are influential on occupants’ window opening behaviour in the case study building, and so they can be used to model occupants’ window opening behaviour in buildings in China to achieve a better consideration of occupant behaviour in dynamic building performance simulation

The Elg1-RFC Clamp-Loading Complex Performs a Role in Sister Chromatid Cohesion

It is widely accepted that of the four Replication Factor C (RFC) complexes (defined by the associations of either Rfc1p, Ctf18p, Elg1p or Rad24p with Rfc2p-Rfc5p), only Ctf18-RFC functions in sister chromatid cohesion. This model is based on findings that CTF18 deletion is lethal in combination with mutations in either CTF7ECO1 or MCD1 sister chromatid cohesion genes and that ctf18 mutant cells exhibit cohesion defects. Here, we report that Elg1-RFC not only participates in cohesion but performs a function that is distinct from that of Ctf18-RFC. The results show that deletion of ELG1 rescues both ctf7eco1 mutant cell temperature sensitivity and cohesion defects. Moreover, over-expression of ELG1 enhances ctf7eco1 mutant cell phenotypes. These findings suggest that the balance of Ctf7pEco1p activity depends on both Ctf18-RFC and Elg1-RFC. We also report that ELG1 deletion produces cohesion defects and intensifies the conditional phenotype of mcd1 mutant cells, further supporting a role for Elg1-RFC in cohesion. Attesting to the specificity of these interactions, deletion of RAD24 neither suppressed nor exacerbated cohesion defects in either ctf7eco1 or mcd1 mutant cells. While parallel analyses failed to uncover a similar role in cohesion for Rad24-RFC, it is well known that Rad24-RFC, Elg1-RFC and Ctf18-RFC play key roles in DNA damage responses. We tested and found that Ctf7pEco1p plays a significant role in Rad24-RFC-based DNA response pathways. In combination, these findings challenge current views and document new and distinct roles for RFC complexes in cohesion and for Ctf7pEco1p in DNA repair

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

types: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.Copyright © 2014 Macmillan Publishers Limited. All rights reserved.This is an open-access articleForest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y(-1) over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y(-1), and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y(-1). Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.NASA Earth System Science Fellowship (NESSF

Enzyme-Linked Immunosorbent Assay-Format Tissue Culture Infectious Dose-50 Test for Titrating Dengue Virus

A dengue nonstructural protein 1 (NS1) antigen capture enzyme-linked immunosorbent assay (ELISA)-based tissue culture infectious dose-50 (TCID50) test (TCID50-ELISA) was developed as an alternative to the standard plaque assay for titrating dengue virus. Virus titers obtained by TCID50-ELISA were comparable to those obtained by the plaque assay and by the traditional TCID50-cytopathic effect (CPE) test (TCID50-CPE), with a better reproducibility and a lower coefficient of variation. Quantitative comparison of TCID50-ELISA and TCID50-CPE resulted in a correlation coefficient of 0.976. Moreover, this new method showed a wider application to C6/36, Vero E6, BHK-21, and Vero cells compared with other titration methods. In summary, the novel TCID50-ELISA method described here provides a more reliable and more accurate alternative compared to the plaque assay and TCID50-CPE for titration of dengue virus

Evolution of H3N2 Influenza Virus in a Guinea Pig Model

Studies of influenza virus evolution under controlled experimental conditions can provide a better understanding of the consequences of evolutionary processes with and without immunological pressure. Characterization of evolved strains assists in the development of predictive algorithms for both the selection of subtypes represented in the seasonal influenza vaccine and the design of novel immune refocused vaccines. To obtain data on the evolution of influenza in a controlled setting, naïve and immunized Guinea pigs were infected with influenza A/Wyoming/2003 (H3N2). Virus progeny from nasal wash samples were assessed for variation in the dominant and other epitopes by sequencing the hemagglutinin (HA) gene to quantify evolutionary changes. Viral RNA from the nasal washes from infection of naïve and immune animals contained 6% and 24.5% HA variant sequences, respectively. Analysis of mutations relative to antigenic epitopes indicated that adaptive immunity played a key role in virus evolution. HA mutations in immunized animals were associated with loss of glycosylation and changes in charge and hydrophobicity in and near residues within known epitopes. Four regions of HA-1 (75–85, 125–135, 165–170, 225–230) contained residues of highest variability. These sites are adjacent to or within known epitopes and appear to play an important role in antigenic variation. Recognition of the role of these sites during evolution will lead to a better understanding of the nature of evolution which help in the prediction of future strains for selection of seasonal vaccines and the design of novel vaccines intended to stimulated broadened cross-reactive protection to conserved sites outside of dominant epitopes

SUMOylation by Pias1 Regulates the Activity of the Hedgehog Dependent Gli Transcription Factors

Hedgehog (Hh) signaling, a vital signaling pathway for the development and homeostasis of vertebrate tissues, is mediated by members of the Gli family of zinc finger transcription factors. Hh signaling increases the transcriptional activity of Gli proteins, at least in part, by inhibiting their proteolytic processing. Conversely, phosphorylation by cAMP-dependent protein kinase (PKA) inhibits Gli transcriptional activity by promoting their ubiquitination and proteolysis. Whether other post-translational modifications contribute to the regulation of Gli protein activity has been unclear.Here we provide evidence that all three Gli proteins are targets of small ubiquitin-related modifier (SUMO)-1 conjugation. Expression of SUMO-1 or the SUMO E3 ligase, Pias1, increased Gli transcriptional activity in cultured cells. Moreover, PKA activity reduced Gli protein SUMOylation. Strikingly, in the embryonic neural tube, the forced expression of Pias1 increased Gli activity and induced the ectopic expression of the Gli dependent gene Nkx2.2. Conversely, a point mutant of Pias1, that lacks ligase activity, blocked the endogenous expression of Nkx2.2.Together, these findings provide evidence that Pias1-dependent SUMOylation influences Gli protein activity and thereby identifies SUMOylation as a post-translational mechanism that regulates the hedgehog signaling pathway

Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2

Lack of Matrilin-2 Favors Liver Tumor Development via Erk1/2 and GSK-3 beta Pathways In Vivo

Matrilin-2 (Matn2) is a multidomain adaptor protein which plays a role in the assembly of extracellular matrix (ECM). It is produced by oval cells during stem cell-driven liver regeneration. In our study, the impact of Matn2 on hepatocarcinogenesis was investigated in Matn2(-/-) mice comparing them with wild-type (WT) mice in a diethylnitrosamine (DEN) model. The liver tissue was analyzed macroscopically, histologically and immunohistochemically, at protein level by Proteome Profiler Arrays and Western blot analysis. Matn2(-/-) mice exhibited higher susceptibility to hepatocarcinogenesis compared to wild-type mice. In the liver of Matn2(-/-) mice, spontaneous microscopic tumor foci were detected without DEN treatment. After 15 mu g/g body weight DEN treatment, the liver of Matn2(-/-) mice contained macroscopic tumors of both larger number and size than the WT liver. In contrast with the WT liver, spontaneous phosphorylation of EGFR, Erk1/2 GSK-3 alpha/beta and retinoblastoma protein (p-Rb), decrease in p21/CIP1 level, and increase in beta-Catenin protein expression were detected in Matn2(-/-) livers. Focal Ki-67 positivity of these samples provided additional support to our presumption that the lack of Matn2 drives the liver into a pro-proliferatory state, making it prone to tumor development. This enhanced proliferative capacity was further increased in the tumor nodules of DEN-treated Matn2(-/-) livers. Our study suggests that Matn2 functions as a tumor suppressor in hepatocarcinogenesis, and in this process activation of EGFR together with that of Erk1/2, as well as inactivation of GSK-3 beta, play strategic roles