OBDD-Based Representation of Interval Graphs

A graph $G = (V,E)$ can be described by the characteristic function of the edge set $\chi_E$ which maps a pair of binary encoded nodes to 1 iff the nodes are adjacent. Using \emph{Ordered Binary Decision Diagrams} (OBDDs) to store $\chi_E$ can lead to a (hopefully) compact representation. Given the OBDD as an input, symbolic/implicit OBDD-based graph algorithms can solve optimization problems by mainly using functional operations, e.g. quantification or binary synthesis. While the OBDD representation size can not be small in general, it can be provable small for special graph classes and then also lead to fast algorithms. In this paper, we show that the OBDD size of unit interval graphs is $O(\ | V \ | /\log \ | V \ |)$ and the OBDD size of interval graphs is $O(\ | V \ | \log \ | V \ |)$which both improve a known result from Nunkesser and Woelfel (2009). Furthermore, we can show that using our variable order and node labeling for interval graphs the worst-case OBDD size is$\Omega(\ | V \ | \log \ | V \ |)$. We use the structure of the adjacency matrices to prove these bounds. This method may be of independent interest and can be applied to other graph classes. We also develop a maximum matching algorithm on unit interval graphs using$O(\log \ | V \ |)$operations and a coloring algorithm for unit and general intervals graphs using$O(\log^2 \ | V \ |)$ operations and evaluate the algorithms empirically.Comment: 29 pages, accepted for 39th International Workshop on Graph-Theoretic Concepts 201

Propriedades tecnológicas de bactérias ácido lácticas e staphilococcaceae isoladas da microbiota de embutidos cárneos artesanais na região Sul/Brasil.

Projeto/Plano de Ação: 03.08.06.009

Surface atomic geometry of Si(001)-(2X1): A low-energy electron-diffraction structure analysis

The reconstruction of the Si(001)-2×1 surface consists of asymmetric and buckled Si dimers. The vertical separation between the up and the down atom within the dimer is about 0.72±0.05 Å and the dimer bond length of 2.24±0.08 Å has been found to be slightly smaller than the Si-Si distance in the bulk. The tilt of the dimer is 19±2°. The formation of Si dimers induces pronounced distortions in the substrate that were detectable down to the fifth Si layer. The structure determination is based on two independent low-energy electron-diffraction data sets taken in two different laboratories. The structural results agree well within the error limits, though noticeable differences occur between the experimental data sets. These differences in the experimental data can possibly be attributed to different preparation procedures

A non-autonomous stochastic discrete time system with uniform disturbances

The main objective of this article is to present Bayesian optimal control over a class of non-autonomous linear stochastic discrete time systems with disturbances belonging to a family of the one parameter uniform distributions. It is proved that the Bayes control for the Pareto priors is the solution of a linear system of algebraic equations. For the case that this linear system is singular, we apply optimization techniques to gain the Bayesian optimal control. These results are extended to generalized linear stochastic systems of difference equations and provide the Bayesian optimal control for the case where the coefficients of these type of systems are non-square matrices. The paper extends the results of the authors developed for system with disturbances belonging to the exponential family

A census of cell types and paracrine interactions in colorectal cancer

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue. To define differences in cellular composition between the normal colon and colorectal cancer, and to map potential cellular interactions between tumor cells and their microenvironment, we profiled transcriptomes of >50,000 single cells from tumors and matched normal tissues of eight colorectal cancer patients. We find that tumor formation is accompanied by changes in epithelial, immune and stromal cell compartments in all patients. In the epithelium, we identify a continuum of five tumor-specific stem cell and progenitor-like populations, and persistent multilineage differentiation. We find multiple stromal and immune cell types to be consistently expanded in tumor compared to the normal colon, including cancer-associated fibroblasts, pericytes, monocytes, macrophages and a subset of T cells. We identify epithelial tumor cells and cancer-associated fibroblasts as relevant for assigning colorectal cancer consensus molecular subtypes. Our survey of growth factors in the tumor microenvironment identifies cell types responsible for increased paracrine EGFR, MET and TGF-β signaling in tumor tissue compared to the normal colon. We show that matched colorectal cancer organoids retain cell type heterogeneity, allowing to define a distinct differentiation trajectory encompassing stem and progenitor-like tumor cells. In summary, our single-cell analyses provide insights into cell types and signals shaping colorectal cancer cell plasticity

Deciphering the Role of Humoral and Cellular Immune Responses in Different COVID-19 Vaccines - A Comparison of Vaccine Candidate Genes in Roborovski Dwarf Hamsters

With the exception of inactivated vaccines, all SARS-CoV-2 vaccines currently used for clinical application focus on the spike envelope glycoprotein as a virus-specific antigen. Compared to other SARS-CoV-2 genes, mutations in the spike protein gene are more rapidly selected and spread within the population, which carries the risk of impairing the efficacy of spike-based vaccines. It is unclear to what extent the loss of neutralizing antibody epitopes can be compensated by cellular immune responses, and whether the use of other SARS-CoV-2 antigens might cause a more diverse immune response and better long-term protection, particularly in light of the continued evolution towards new SARS-CoV-2 variants. To address this question, we explored immunogenicity and protective effects of adenoviral vectors encoding either the full-length spike protein (S), the nucleocapsid protein (N), the receptor binding domain (RBD) or a hybrid construct of RBD and the membrane protein (M) in a highly susceptible COVID-19 hamster model. All adenoviral vaccines provided life-saving protection against SARS-CoV-2-infection. The most efficient protection was achieved after exposure to full-length spike. However, the nucleocapsid protein, which triggered a robust T-cell response but did not facilitate the formation of neutralizing antibodies, controlled early virus replication efficiently and prevented severe pneumonia. Although the full-length spike protein is an excellent target for vaccines, it does not appear to be the only option for future vaccine design

Temporal omics analysis in Syrian hamsters unravel cellular effector responses to moderate COVID-19

In COVID-19, immune responses are key in determining disease severity. However, cellular mechanisms at the onset of inflammatory lung injury in SARS-CoV-2 infection, particularly involving endothelial cells, remain ill-defined. Using Syrian hamsters as a model for moderate COVID-19, we conduct a detailed longitudinal analysis of systemic and pulmonary cellular responses, and corroborate it with datasets from COVID-19 patients. Monocyte-derived macrophages in lungs exert the earliest and strongest transcriptional response to infection, including induction of pro-inflammatory genes, while epithelial cells show weak alterations. Without evidence for productive infection, endothelial cells react, depending on cell subtypes, by strong and early expression of anti-viral, pro-inflammatory, and T cell recruiting genes. Recruitment of cytotoxic T cells as well as emergence of IgM antibodies precede viral clearance at day 5 post infection. Investigating SARS-CoV-2 infected Syrian hamsters thus identifies cell type-specific effector functions, providing detailed insights into pathomechanisms of COVID-19 and informing therapeutic strategies

Mitogen-activated protein kinase activity drives cell trajectories in colorectal cancer

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue lacking visible organization. We sought to define transcriptional states of colorectal cancer cells and signals controlling their development by performing single-cell transcriptome analysis of tumors and matched non-cancerous tissues of twelve colorectal cancer patients. We defined patient-overarching colorectal cancer cell clusters characterized by differential activities of oncogenic signaling pathways such as mitogen-activated protein kinase and oncogenic traits such as replication stress. RNA metabolic labeling and assessment of RNA velocity in patient-derived organoids revealed developmental trajectories of colorectal cancer cells organized along a mitogen-activated protein kinase activity gradient. This was in contrast to normal colon organoid cells developing along graded Wnt activity. Experimental targeting of EGFR-BRAF-MEK in cancer organoids affected signaling and gene expression contingent on predictive KRAS/BRAF mutations and induced cell plasticity overriding default developmental trajectories. Our results highlight directional cancer cell development as a driver of non-genetic cancer cell heterogeneity and re-routing of trajectories as a response to targeted therapy