Passive States for Essential Observers

The aim of this note is to present a unified approach to the results given in \cite{bb99} and \cite{bs04} which also covers examples of models not presented in these two papers (e.g. $d$-dimensional Minkowski space-time for $d\geq 3$). Assuming that a state is passive for an observer travelling along certain (essential) worldlines, we show that this state is invariant under the isometry group, is a KMS-state for the observer at a temperature uniquely determined by the structure constants of the Lie algebra involved and fulfills (a variant of) the Reeh-Schlieder property. Also the modular objects associated to such a state and the observable algebra of an observer are computed and a version of weak locality is examined.Comment: 27 page

Snf1 Dependent Destruction of Med13 is Required for Programmed Cell Death Following Oxidative Stress in Yeast

All eukaryotic cells, when faced with unfavorable environmental conditions, have to decide whether to mount a survival or cell death response. The conserved cyclin C and its kinase partner Cdk8 play a key role in this decision. Both are members of the Cdk8 kinase module that, along with Med12 and Med13, associate with the core mediator complex of RNA polymerase II. In S. cerevisiae, oxidative stress triggers Med13 destruction1, which thereafter releases cyclin Ci nto the cytoplasm. Cytoplasmic cyclin C associates with mitochondria where it induces hyper-fragmentation and programmed cell death2. This suggests a model in which oxidative stress mediated destruction o fMed13 represents a key molecular switch which commits the cell to programmed cell death. Thus it is important to decipher the precise molecular mechanisms that control Med13 destruction following exposure to oxidative stress

Semi-parametric modeling of SARS-CoV-2 transmission in Orange County, California using tests, cases, deaths, and seroprevalence data

Mechanistic modeling of SARS-CoV-2 transmission dynamics and frequently estimating model parameters using streaming surveillance data are important components of the pandemic response toolbox. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, we propose a Bayesian modeling framework that integrates multiple surveillance data streams. Our model uses both SARS-CoV-2 diagnostics test and mortality time series to estimate our model parameters, while also explicitly integrating seroprevalence data from cross-sectional studies. Importantly, our data generating model for incidence data takes into account changes in the total number of tests performed. We model transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparameterically. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March, 2020 and March, 2021 and find that 33-62% of the Orange County residents experienced SARS-CoV-2 infection by the end of February, 2021. Despite this high number of infections, our results show that the abrupt end of the winter surge in January, 2021, was due to both behavioral changes and a high level of accumulated natural immunity.Comment: 37 pages, 16 pages of main text, including 5 figures, 1 tabl

The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks

<p>Abstract</p> <p>Background</p> <p>Currently, there is a gap between purely theoretical studies of the topology of large bioregulatory networks and the practical traditions and interests of experimentalists. While the theoretical approaches emphasize the global characterization of regulatory systems, the practical approaches focus on the role of distinct molecules and genes in regulation. To bridge the gap between these opposite approaches, one needs to combine 'general' with 'particular' properties and translate abstract topological features of large systems into testable functional characteristics of individual components. Here, we propose a new topological parameter – the pairwise disconnectivity index of a network's element – that is capable of such bridging.</p> <p>Results</p> <p>The pairwise disconnectivity index quantifies how crucial an individual element is for sustaining the communication ability between connected pairs of vertices in a network that is displayed as a directed graph. Such an element might be a vertex (i.e., molecules, genes), an edge (i.e., reactions, interactions), as well as a group of vertices and/or edges. The index can be viewed as a measure of topological redundancy of regulatory paths which connect different parts of a given network and as a measure of sensitivity (robustness) of this network to the presence (absence) of each individual element. Accordingly, we introduce the notion of a path-degree of a vertex in terms of its corresponding incoming, outgoing and mediated paths, respectively. The pairwise disconnectivity index has been applied to the analysis of several regulatory networks from various organisms. The importance of an individual vertex or edge for the coherence of the network is determined by the particular position of the given element in the whole network.</p> <p>Conclusion</p> <p>Our approach enables to evaluate the effect of removing each element (i.e., vertex, edge, or their combinations) from a network. The greatest potential value of this approach is its ability to systematically analyze the role of every element, as well as groups of elements, in a regulatory network.</p

Cryptococcus neoformans Mediator Protein Ssn8 Negatively Regulates Diverse Physiological Processes and Is Required for Virulence

Cryptococcus neoformans is a ubiquitously distributed human pathogen. It is also a model system for studying fungal virulence, physiology and differentiation. Light is known to inhibit sexual development via the evolutionarily conserved white collar proteins in C. neoformans. To dissect molecular mechanisms regulating this process, we have identified the SSN8 gene whose mutation suppresses the light-dependent CWC1 overexpression phenotype. Characterization of sex-related phenotypes revealed that Ssn8 functions as a negative regulator in both heterothallic a-α mating and same-sex mating processes. In addition, Ssn8 is involved in the suppression of other physiological processes including invasive growth, and production of capsule and melanin. Interestingly, Ssn8 is also required for the maintenance of cell wall integrity and virulence. Our gene expression studies confirmed that deletion of SSN8 results in de-repression of genes involved in sexual development and melanization. Epistatic and yeast two hybrid studies suggest that C. neoformans Ssn8 plays critical roles downstream of the Cpk1 MAPK cascade and Ste12 and possibly resides at one of the major branches downstream of the Cwc complex in the light-mediated sexual development pathway. Taken together, our studies demonstrate that the conserved Mediator protein Ssn8 functions as a global regulator which negatively regulates diverse physiological and developmental processes and is required for virulence in C. neoformans