Minimum Cost Flows in Graphs with Unit Capacities

We consider the minimum cost flow problem on graphs with unit capacities and its special cases. In previous studies, special purpose algorithms exploiting the fact that capacities are one have been developed. In contrast, for maximum flow with unit capacities, the best bounds are proven for slight modifications of classical blocking flow and push-relabel algorithms. In this paper we show that the classical cost scaling algorithms of Goldberg and Tarjan (for general integer capacities) applied to a problem with unit capacities achieve or improve the best known bounds. For weighted bipartite matching we establish a bound of O(sqrt{rm}log C) on a slight variation of this algorithm. Here r is the size of the smaller side of the bipartite graph, m is the number of edges, and C is the largest absolute value of an arc-cost. This simplifies a result of [Duan et al. 2011] and improves the bound, answering an open question of [Tarjan and Ramshaw 2012]. For graphs with unit vertex capacities we establish a novel O(sqrt{n}mlog(nC)) bound. We also give the first cycle canceling algorithm for minimum cost flow with unit capacities. The algorithm naturally generalizes the single source shortest path algorithm of [Goldberg 1995]

Attractive instability of oppositely charged membranes induced by charge density fluctuations

We predict the conditions under which two oppositely charged membranes show a dynamic, attractive instability. Two layers with unequal charges of opposite sign can repel or be stable when in close proximity. However, dynamic charge density fluctuations can induce an attractive instability and thus facilitate fusion. We predict the dominant instability modes and timescales and show how these are controlled by the relative charge and membrane viscosities. These dynamic instabilities may be the precursors of membrane fusion in systems where artificial vesicles are engulfed by biological cells of opposite charge

酸化物ガラスの塩基度と XPS による O1s 化学シフトの相関に関する考察

O1s binding energy measured by X-ray photoelectron spectroscopy (XPS) is candidate as a new tool to determine a new scale of Lewis basicity of oxide ions in glass. Some mathematical expressions for the basicity or XPS chemical shift, such as charge parameter and optical basicity, were compared with the experimental O1s binding energy in binary alkali oxide glasses. The expressions so far in use needed some modification in parameters. A new empirical expression introduced in this paper gives a new concept and universal scale of basicity

Partially Annealed Disorder and Collapse of Like-Charged Macroions

Charged systems with partially annealed charge disorder are investigated using field-theoretic and replica methods. Charge disorder is assumed to be confined to macroion surfaces surrounded by a cloud of mobile neutralizing counterions in an aqueous solvent. A general formalism is developed by assuming that the disorder is partially annealed (with purely annealed and purely quenched disorder included as special cases), i.e., we assume in general that the disorder undergoes a slow dynamics relative to fast-relaxing counterions making it possible thus to study the stationary-state properties of the system using methods similar to those available in equilibrium statistical mechanics. By focusing on the specific case of two planar surfaces of equal mean surface charge and disorder variance, it is shown that partial annealing of the quenched disorder leads to renormalization of the mean surface charge density and thus a reduction of the inter-plate repulsion on the mean-field or weak-coupling level. In the strong-coupling limit, charge disorder induces a long-range attraction resulting in a continuous disorder-driven collapse transition for the two surfaces as the disorder variance exceeds a threshold value. Disorder annealing further enhances the attraction and, in the limit of low screening, leads to a global attractive instability in the system.Comment: 21 pages, 2 figure

Small nucleoli are a cellular hallmark of longevity

Animal lifespan is regulated by conserved metabolic signalling pathways and specific transcription factors, but whether these pathways affect common downstream mechanisms remains largely elusive. Here we show that NCL-1/TRIM2/Brat tumour suppressor extends lifespan and limits nucleolar size in the major C. elegans longevity pathways, as part of a convergent mechanism focused on the nucleolus. Long-lived animals representing distinct longevity pathways exhibit small nucleoli, and decreased expression of rRNA, ribosomal proteins, and the nucleolar protein fibrillarin, dependent on NCL-1. Knockdown of fibrillarin also reduces nucleolar size and extends lifespan. Among wildtype C. elegans, individual nucleolar size varies, but is highly predictive for longevity. Long-lived dietary restricted fruit flies and insulin-like-peptide mutants exhibit small nucleoli and fibrillarin expression, as do long-lived dietary restricted and IRS1 knockout mice. Furthermore, human muscle biopsies from individuals who underwent modest dietary restriction coupled with exercise also display small nucleoli. We suggest that small nucleoli are a cellular hallmark of longevity and metabolic health conserved across taxa

Quantum-enhanced absorption refrigerators

Thermodynamics is a branch of science blessed by an unparalleled combination of generality of scope and formal simplicity. Based on few natural assumptions together with the four laws, it sets the boundaries between possible and impossible in macroscopic aggregates of matter. This triggered groundbreaking achievements in physics, chemistry and engineering over the last two centuries. Close analogues of those fundamental laws are now being established at the level of individual quantum systems, thus placing limits on the operation of quantum-mechanical devices. Here we study quantum absorption refrigerators, which are driven by heat rather than external work. We establish thermodynamic performance bounds for these machines and investigate their quantum origin. We also show how those bounds may be pushed beyond what is classically achievable, by suitably tailoring the environmental fluctuations via quantum reservoir engineering techniques. Such superefficient quantum-enhanced cooling realises a promising step towards the technological exploitation of autonomous quantum refrigerators

Development of an In Vitro Model for the Multi-Parametric Quantification of the Cellular Interactions between Candida Yeasts and Phagocytes

We developed a new in vitro model for a multi-parameter characterization of the time course interaction of Candida fungal cells with J774 murine macrophages and human neutrophils, based on the use of combined microscopy, fluorometry, flow cytometry and viability assays. Using fluorochromes specific to phagocytes and yeasts, we could accurately quantify various parameters simultaneously in a single infection experiment: at the individual cell level, we measured the association of phagocytes to fungal cells and phagocyte survival, and monitored in parallel the overall phagocytosis process by measuring the part of ingested fungal cells among the total fungal biomass that changed over time. Candida albicans, C. glabrata, and C. lusitaniae were used as a proof of concept: they exhibited species-specific differences in their association rate with phagocytes. The fungal biomass uptaken by the phagocytes differed significantly according to the Candida species. The measure of the survival of fungal and immune cells during the interaction showed that C. albicans was the more aggressive yeast in vitro, destroying the vast majority of the phagocytes within five hours. All three species of Candida were able to survive and to escape macrophage phagocytosis either by the intraphagocytic yeast-to-hyphae transition (C. albicans) and the fungal cell multiplication until phagocytes burst (C. glabrata, C. lusitaniae), or by the avoidance of phagocytosis (C. lusitaniae). We demonstrated that our model was sensitive enough to quantify small variations of the parameters of the interaction. The method has been conceived to be amenable to the high-throughput screening of mutants in order to unravel the molecular mechanisms involved in the interaction between yeasts and host phagocytes

Qualitative prediction of blood–brain barrier permeability on a large and refined dataset

The prediction of blood–brain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on blood–brain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with blood–brain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (ntrees = 5) based on only four descriptors yields a validated accuracy of 88%

Sphingomyelin Functions as a Novel Receptor for Helicobacter pylori VacA

The vacuolating cytotoxin (VacA) of the gastric pathogen Helicobacter pylori binds and enters epithelial cells, ultimately resulting in cellular vacuolation. Several host factors have been reported to be important for VacA function, but none of these have been demonstrated to be essential for toxin binding to the plasma membrane. Thus, the identity of cell surface receptors critical for both toxin binding and function has remained elusive. Here, we identify VacA as the first bacterial virulence factor that exploits the important plasma membrane sphingolipid, sphingomyelin (SM), as a cellular receptor. Depletion of plasma membrane SM with sphingomyelinase inhibited VacA-mediated vacuolation and significantly reduced the sensitivity of HeLa cells, as well as several other cell lines, to VacA. Further analysis revealed that SM is critical for VacA interactions with the plasma membrane. Restoring plasma membrane SM in cells previously depleted of SM was sufficient to rescue both toxin vacuolation activity and plasma membrane binding. VacA association with detergent-resistant membranes was inhibited in cells pretreated with SMase C, indicating the importance of SM for VacA association with lipid raft microdomains. Finally, VacA bound to SM in an in vitro ELISA assay in a manner competitively inhibited by lysenin, a known SM-binding protein. Our results suggest a model where VacA may exploit the capacity of SM to preferentially partition into lipid rafts in order to access the raft-associated cellular machinery previously shown to be required for toxin entry into host cells