Detecting shifts in nonlinear dynamics using Empirical Dynamic Modeling with Nested-Library Analysis.

Abrupt changes in system states and dynamical behaviors are often observed in natural systems; such phenomena, named regime shifts, are explained as transitions between alternative steady states (more generally, attractors). Various methods have been proposed to detect regime shifts from time series data, but a generic detection method with theoretical linkage to underlying dynamics is lacking. Here, we provide a novel method named Nested-Library Analysis (NLA) to retrospectively detect regime shifts using empirical dynamic modeling (EDM) rooted in theory of attractor reconstruction. Specifically, NLA determines the time of regime shift as the cutting point at which sequential reduction of the library set (i.e., the time series data used to reconstruct the attractor for forecasting) optimizes the forecast skill of EDM. We illustrate this method on a chaotic model of which changing parameters present a critical transition. Our analysis shows that NLA detects the change point in the model system and outperforms existing approaches based on statistical characteristics. In addition, NLA empirically detected a real-world regime shift event revealing an abrupt change of Pacific Decadal Oscillation index around the mid-1970s. Importantly, our method can be easily generalized to various systems because NLA is equation-free and requires only a single time series.

EPC-K1 Prevents ONOO(-)-induced Apoptosis in Cerebellar Granule Neurons.

The cytotoxic effect of peroxynitrite on cerebellar granule neurons was studied. Exposure of cerebellar granule neurons to 10 &mgr;mol/L peroxynitrite triggered apoptosis in vitro, which was confirmed by both morphological (nuclear morphology observed by fluorescence microscopy) and biochemical evidence (DNA fragmentation detected by ELISA). Using ESR spin labeling technique, the alteration of biophysical characteristics of neuronal cell membrane during the apoptotic process was studied. The results indicate that after treatment with peroxynitrite, the fluidity of both the surface layer and the deep layer of the neuronal cell membrane decreased markedly, and the S/W ratio of the membrane protein thiol groups increased significantly. Pre-treating cerebellar granule neurons with antioxidant EPC-K1, a novel water-soluble derivative of vitamin C and vitamin E, alleviated the oxidative injury and prevented cells from apoptosis.