Parthenolide attenuates LPS-induced activation of NF-κB in a time-dependent manner in rat myocardium.

Parthenolide (PTN), a selective nuclear factor kappa B (NF-κB) inhibitor, has been used extensively to inhibit NF-κB activation. The duration of the inhibitory effect of PTN on NF-κB in vivo remains unclear. This study was to determine whether a lipopolysaccharide (LPS) challenge 6, 12 and 24 h after the administration of PTN could activate NF-κB. Rats were devided into five groups. The rats in the PTN, PTN+LPS and DMSO groups were injected intraperitoneally with PTN or DMSO. After 6, 12 or 24 h, LPS was administered in LPS and PTN+LPS groups. The expressions of NF-κB p50, IκBα and p-IκBα were inhibited in both PTN and PTN+LPS group at end of 6 and 12 h and no effects at 24 h. In summary, myocardial NF-κB expression occurs 1 h after the administration of LPS. PTN blocks this effect given at 6 h and no inhibitory effect 24 h after administration in vivo

Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions

3D action recognition has broad applications in human-computer interaction and intelligent surveillance. However, recognizing similar actions remains challenging since previous literature fails to capture motion and shape cues effectively from noisy depth data. In this paper, we propose a novel two-layer Bag-of-Visual-Words (BoVW) model, which suppresses the noise disturbances and jointly encodes both motion and shape cues. First, background clutter is removed by a background modeling method that is designed for depth data. Then, motion and shape cues are jointly used to generate robust and distinctive spatial-temporal interest points (STIPs): motion-based STIPs and shape-based STIPs. In the first layer of our model, a multi-scale 3D local steering kernel (M3DLSK) descriptor is proposed to describe local appearances of cuboids around motion-based STIPs. In the second layer, a spatial-temporal vector (STV) descriptor is proposed to describe the spatial-temporal distributions of shape-based STIPs. Using the Bag-of-Visual-Words (BoVW) model, motion and shape cues are combined to form a fused action representation. Our model performs favorably compared with common STIP detection and description methods. Thorough experiments verify that our model is effective in distinguishing similar actions and robust to background clutter, partial occlusions and pepper noise

A proof of Mader's conjecture on large clique subdivisions in C4C_4-free graphs

Given any integers $s,t\geq 2$, we show there exists some $c=c(s,t)>0$ such that any $K_{s,t}$-free graph with average degree $d$ contains a subdivision of a clique with at least $cd^{\frac{1}{2}\frac{s}{s-1}}$ vertices. In particular, when $s=2$ this resolves in a strong sense the conjecture of Mader in 1999 that every $C_4$-free graph has a subdivision of a clique with order linear in the average degree of the original graph. In general, the widely conjectured asymptotic behaviour of the extremal density of $K_{s,t}$-free graphs suggests our result is tight up to the constant $c(s,t)$.Comment: 25 pages, 1 figur