Increment entropy as a measure of complexity for time series

Entropy has been a common index to quantify the complexity of time series in a variety of fields. Here, we introduce increment entropy to measure the complexity of time series in which each increment is mapped into a word of two letters, one letter corresponding to direction and the other corresponding to magnitude. The Shannon entropy of the words is termed as increment entropy (IncrEn). Simulations on synthetic data and tests on epileptic EEG signals have demonstrated its ability of detecting the abrupt change, regardless of energetic (e.g. spikes or bursts) or structural changes. The computation of IncrEn does not make any assumption on time series and it can be applicable to arbitrary real-world data.Comment: 12pages,7figure,2 table

The Loss of Hh Responsiveness by a Non-Ciliary Gli2 Variant

Hedgehog signaling is crucial for vertebrate development and physiology. Gli2, the primary effector of Hedgehog signaling, localizes to the tip of the primary cilium, but the importance of its ciliary localization remains unclear. We address the roles of Gli2 ciliary localization by replacing endogenous Gli2 with Gli2ΔCLR, a Gli2 variant not localizing to the cilium. The resulting Gli2ΔCLRKI and Gli2ΔCLRKI;Gli3 double mutants resemble Gli2-null and Gli2;Gli3 double mutants, respectively, suggesting the lack of Gli2ΔCLR activation in development. Significantly, Gli2ΔCLR cannot be activated either by pharmacochemical activation of Smo in vitro or by loss of Ptch1 in vivo. Finally,Gli2ΔCLR exhibits strong transcriptional activator activity in the absence of Sufu, suggesting that the lack of its activation in vivo results from a specific failure in relieving the inhibitory function of Sufu. Our results provide strong evidence that the ciliary localization of Gli2 is crucial for cilium-dependent activation of Hedgehog signaling

System Structure Risk Metric Method Based on Information Flow

Part 5: Modelling and SimulationInternational audienceThe measurement of structure risk aims to analysis and evaluate the not occurred, potential, and the objectively exist risk in system structure. It is an essential way to validate system function and system quality. This paper proposes the risk metric model and algorithm based on information flow and analysis risk trend between traditional tree structure and network-centric structure

RNase L contributes to lipid metabolism

Macrophage-derived foam cell formation is a milestone of the atherosclerotic lesion initiation and progression, leading to cardiovascular diseases and stroke. Foam cells are formed from the disruption of a homeostatic mechanism that manipulates the uptake, intracellular metabolism and efflux of cholesterol within macrophages. Although studies have yielded much information about the homeostatic mechanism, the molecular basis of foam cell formation remains to be fully understood. We recently found that deficiency of RNase L attenuated macrophage functions including macrophage migration and its endocytic activity. Furthermore, RNase L markedly impacted the expression of certain pro- and anti-foam cell genes in macrophages. Most interestingly we have revealed that lack of RNase L significantly increased the formation of foam cells from bone marrow derived macrophages (BMMs). The increase of foam cell formation was associated with up-regulation of the expression of scavenger receptors such as CD36, SR-A, and PPAR-g. These studies provide new insights into foam cell formation and novel therapeutic strategies for atherosclerosis may be designed through activation/up-regulation of RNase L.https://engagedscholarship.csuohio.edu/u_poster_2014/1001/thumbnail.jp

Tumour Suppressor Function of RNase L in A Mouse Model

RNase L is one of the key enzymes involved in the molecular mechanisms of interferon (IFN) actions. Upon binding with its activator, 5′-phosphorylated, 2′-5′ oligoadenylates (2-5A), RNase L plays an important role in the antiviral and anti-proliferative functions of IFN, and exerts proapoptotic activity independent of IFN. In this study, we have found that RNase L retards proliferation in an IFN-dependent and independent fashion. To directly measure the effect of RNase L on tumour growth in the absence of other IFN-induced proteins, human RNase L cDNA was stably expressed in P-57 cells, an aggressive mouse fibrosarcoma cell line. Three clonal cell lines were isolated in which the overexpression of RNase L was 15–20-fold of the endogenous level. Groups of five nude mice were injected subcutaneously with either the human RNase L overexpressing clones (P-RL) or control cells transfected with an empty vector (P-Vec). Tumour growth by the two cell lines was monitored by measuring tumour volumes. In the P-RL group, tumour formation was significantly delayed and the tumours grew much slower compared to the control group. Morphologically, the P-RL tumour appeared to have more polygonal cells and increased single cell tumour necrosis. Interestingly, P-RL tumours eventually started to grow. Further analysis revealed, however, that these tumours no longer expressed ectopic RNase L. Our findings suggest that RNase L plays a critical role in the inhibition of fibrosarcoma growth in nude mice