Gene silencing H-NS paralogue StpA forms a rigid protein filament along DNA that blocks DNA accessibility

Nucleoid-associated proteins are bacterial proteins that are responsible for chromosomal DNA compaction and global gene regulation. One such protein is Escherichia coli Histone-like nucleoid structuring protein (H-NS) which functions as a global gene silencer. Whereas the DNA-binding mechanism of H-NS is well-characterized, its paralogue, StpA which is also able to silence genes is less understood. Here we show that StpA is similar to H-NS in that it is able to form a rigid filament along DNA. In contrast to H-NS, the StpA filament interacts with a naked DNA segment to cause DNA bridging which results in simultaneous stiffening and bridging of DNA. DNA accessibility is effectively blocked after the formation of StpA filament on DNA, suggesting rigid filament formation is the important step in promoting gene silencing. We also show that >1 mM magnesium promotes higher order DNA condensation, suggesting StpA may also play a role in chromosomal DNA packaging

Parametric Formula for Stress Concentration Factor of Fillet Weld Joints with Spline Bead Profile

The existing parametric formulae to calculate the notch stress concentration factor of fillet welds often result in reduced accuracy due to an oversimplification of the real weld geometry. The present work proposes a parametric formula for the evaluation of the notch SCF based on the spline weld model that offers a better approximation of the real shape of the fillet weld. The spline model was adopted in FE analyses on T-shape joints and cruciform joints models, under different loading conditions, to propose a parametric formula for the calculation of the SCF by regression analysis. In addition, the precision of parametric formulae based on the line model was examined. The magnitude of the stress concentration was also analyzed by means of its probability distribution. The results show that the line model is not accurate enough to calculate the SCF of fillet weld if the weld profile is considered. The error of the SCF by the proposed parametric formulae is proven to be smaller than 5% according to the testing data system. The stress concentration of cruciform joints under tensile stress represents the worst case scenario if assessed by the confidence interval of 95% survival probability

Core Index of Perfect Matching Polytope for a 2-Connected Cubic Graph

For a 2-connected cubic graph G, the perfect matching polytope P(G) of G contains a special point xc=(13,13,…,13)$x^c = \left( {{1 \over 3},{1 \over 3}, \ldots ,{1 \over 3}} \right)$ . The core index ϕ(P(G)) of the polytope P(G) is the minimum number of vertices of P(G) whose convex hull contains xc. The Fulkerson’s conjecture asserts that every 2-connected cubic graph G has six perfect matchings such that each edge appears in exactly two of them, namely, there are six vertices of P(G) such that xc is the convex combination of them, which implies that ϕ(P(G)) ≤ 6. It turns out that the latter assertion in turn implies the Fan-Raspaud conjecture: In every 2-connected cubic graph G, there are three perfect matchings M1, M2, and M3 such that M1 ∩ M2 ∩ M3 = ∅. In this paper we prove the Fan-Raspaud conjecture for ϕ(P(G)) ≤ 12 with certain dimensional conditions

Removable Edges in Near-bricks

For a brick apart from a few small graphs, Lovász (1987) proposed a conjecture on the existence of an edge whose deletion results in a graph with only one brick in its tight cut decomposition. Carvalho, Lucchesi, and Murty (2002) confirmed this conjecture by showing the existence of such two edges. This paper generalizes the result obtained by Carvalho et al. to the case of irreducible near-brick, where a graph is irreducible if it contains no induced odd path of length 3 or more. Meanwhile, a lower bound on the number of removable edges of matching-covered bipartite graphs is presented

An Improved Algorithm for a Bicriteria Batching Scheduling Problem

This note is concerned with the bicriteria scheduling problem on a series-batching machine to minimize maximum cost and makespan. An O(n5) algorithm has been established previously. Here is an improved algorithm which solves the problem in O(n3) time