A Systemic Receptor Network Triggered by Human cytomegalovirus Entry

Virus entry is a multistep process that triggers a variety of cellular pathways interconnecting into a complex network, yet the molecular complexity of this network remains largely unsolved. Here, by employing systems biology approach, we reveal a systemic virus-entry network initiated by human cytomegalovirus (HCMV), a widespread opportunistic pathogen. This network contains all known interactions and functional modules (i.e. groups of proteins) coordinately responding to HCMV entry. The number of both genes and functional modules activated in this network dramatically declines shortly, within 25 min post-infection. While modules annotated as receptor system, ion transport, and immune response are continuously activated during the entire process of HCMV entry, those for cell adhesion and skeletal movement are specifically activated during viral early attachment, and those for immune response during virus entry. HCMV entry requires a complex receptor network involving different cellular components, comprising not only cell surface receptors, but also pathway components in signal transduction, skeletal development, immune response, endocytosis, ion transport, macromolecule metabolism and chromatin remodeling. Interestingly, genes that function in chromatin remodeling are the most abundant in this receptor system, suggesting that global modulation of transcriptions is one of the most important events in HCMV entry. Results of in silico knock out further reveal that this entire receptor network is primarily controlled by multiple elements, such as EGFR (Epidermal Growth Factor) and SLC10A1 (sodium/bile acid cotransporter family, member 1). Thus, our results demonstrate that a complex systemic network, in which components coordinating efficiently in time and space contributes to virus entry.Comment: 26 page

Optimization of extraction condition for phytic acid from peanut meal by response surface methodology

Phytic acid (PA), a molecule with high commercial value, is one of the important component in peanutmeal. However, PA has not yet been isolated from peanut meal and played its role. This paper reportedthe extraction conditions of PA from peanut meal after removed protein. The independent variables werehydrochloric acid (HCl) concentration, solid to liquid ratio, extraction time and extraction temperature.Response surface methodology (RSM) was used to optimize the extraction conditions based on the extractionyield of PA. The results show that the second-order polynomial models derived from responseswell with the experimental (R2 = 0.9783). The optimal extraction condition was obtained with solid toliquid ratio of 1:16 (g:mL), HCl concentration of 0.02 mol/L, extraction time of 105 min, and extractiontemperature of 30 °C. At this condition, PA with higher purity were obtained. the extraction ratio was6.12%, and the content of PA was 182.7 mg/g dry PA extract. The experimental values under optimal conditionwere in good consistent with the predicted values. The PA extracted from peanut meal was verifiedqualitatively by IR spectra. The extraction technology of PA from peanut meal has a strong potential forrealized high-value utilization of peanut meal

Distributed Consensus of Linear Multi-Agent Systems with Adaptive Dynamic Protocols

This paper considers the distributed consensus problem of multi-agent systems with general continuous-time linear dynamics. Two distributed adaptive dynamic consensus protocols are proposed, based on the relative output information of neighboring agents. One protocol assigns an adaptive coupling weight to each edge in the communication graph while the other uses an adaptive coupling weight for each node. These two adaptive protocols are designed to ensure that consensus is reached in a fully distributed fashion for any undirected connected communication graphs without using any global information. A sufficient condition for the existence of these adaptive protocols is that each agent is stabilizable and detectable. The cases with leader-follower and switching communication graphs are also studied.Comment: 17 pages, 5 figue

Top Quark Forward-Backward Asymmetry and Same-Sign Top Quark Pairs

The top quark forward-backward asymmetry measured at the Tevatron collider shows a large deviation from standard model expectations. Among possible interpretations, a non-universal $Z^\prime$ model is of particular interest as it naturally predicts a top quark in the forward region of large rapidity. To reproduce the size of the asymmetry, the couplings of the $Z^\prime$ to standard model quarks must be large, inevitably leading to copious production of same-sign top quark pairs at the energies of the Large Hadron Collider (LHC). We explore the discovery potential for $tt$ and $ttj$ production in early LHC experiments at 7-8 TeV and conclude that if {\it no} $tt$ signal is observed with 1 fb$^{-1}$ of integrated luminosity, then a non-universal $Z^\prime$ alone cannot explain the Tevatron forward-backward asymmetry.Comment: Tevatron limit from same-sign tt search adde

Understanding bias in the evaporative damping of El Niño–Southern Oscillation events in CMIP5 models

This study examines the extent of the Pacific double–intertropical convergence zone (ITCZ) bias in an ensemble of CMIP5 coupled general circulation models and the relationship between this common bias and equatorial Pacific evaporative heat flux feedbacks involved in El Niño–Southern Oscillation (ENSO). A feedback decomposition method, based on the latent heat flux bulk formula, is implemented to enable identification of underlying causes of feedback bias and diversity from dynamical and thermodynamical processes. The magnitude of mean precipitation south of the equator in the east Pacific (an indicator of the extent of the double-ITCZ bias in a model) is linked to the mean meridional surface wind speed and direction in the region and is consequently linked to diversity in the strength of the wind speed response during the ENSO cycle. The ENSO latent heat flux damping is weak in almost all models and shows a relatively large range in strength in the CMIP5 ensemble. While both humidity gradient and wind speed feedbacks are important drivers of the damping, the wind speed feedback is an underlying cause of the overall damping bias for many models and is ultimately more dominant in driving interensemble variation. Feedback biases can also persist in atmosphere-only (AMIP) runs, suggesting that the atmosphere model plays an important role in latent heat flux damping and double-ITCZ bias and variation. Improvements to coupled model simulation of both mean precipitation and ENSO may be accelerated by focusing on the atmosphere component

Diagnosing relationships between mean state biases and El Niño shortwave feedback in CMIP5 models

The rate of damping of tropical Pacific sea surface temperature anomalies (SSTAs) associated with El Niño events by surface shortwave heat fluxes has significant biases in current coupled climate models [phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. Of 33 CMIP5 models, 16 have shortwave feedbacks that are weakly negative in comparison to observations, or even positive, resulting in a tendency of amplification of SSTAs. Two biases in the cloud response to El Niño SSTAs are identified and linked to significant mean state biases in CMIP5 models. First, cool mean SST and reduced precipitation are linked to comparatively less cloud formation in the eastern equatorial Pacific during El Niño events, driven by a weakened atmospheric ascent response. Second, a spurious reduction of cloud driven by anomalous surface relative humidity during El Niño events is present in models with more stable eastern Pacific mean atmospheric conditions and more low cloud in the mean state. Both cloud response biases contribute to a weak negative shortwave feedback or a positive shortwave feedback that amplifies El Niño SSTAs. Differences between shortwave feedback in the coupled models and the corresponding atmosphere-only models (AMIP) are also linked to mean state differences, consistent with the biases found between different coupled models. Shortwave feedback bias can still persist in AMIP, as a result of persisting weak shortwave responses to anomalous cloud and weak cloud responses to atmospheric ascent. This indicates the importance of bias in the atmosphere component to coupled model feedback and mean state biases