Four New Diterpenoid Alkaloids from The Roots of Aconitum coreanum

Four new hetisine‐type C₂₀‐diterpenoid alkaloids, named as coreanines A–D ( 1 – 4 ), were isolated from the roots of Aconitum coreanum, together with thirteen known alkaloids ( 5 – 17 ). Their structures were elucidated by extensive spectroscopic methods including IR, HR‐ESI‐MS and NMR techniques. All the isolated compounds were screened for the acetylcholinesterase (AChE) inhibitory effects, and none of them showed considerable inhibitory activity.     

Genetic diversity and population structure of Swertia tetraptera (Gentianaceae), an endemic species of Qinghai-Tibetan Plateau

Swertia tetraptera Maxim is an annual alpine herb endemic to the Qinghai-Tibetan Plateau (QTP). Its populations are locally scattered as isolated patches throughout this region. Genetic variation within and among thirty-four populations of this species was assessed using ISSR fingerprinting with 10 primers. High levels of genetic diversity exist within species (P = 98.9%, I = 0.3475; He = 0.2227), while the within-population diversity is low (P = 32.7%, I = 0.177; He = 0.12). High levels of genetic differentiation were detected among populations based on various statistics, including Nei’s genetic diversity analysis (G_ST = 0.4608), Bayesian analysis (θ^B = 0.476) and AMOVA (F_ST = 0.57). That is, populations shared low levels of genetic identity (I = 0.2622–0.0966). This genetic structure was probably due to severe genetic drift, breeding system and limited gene flow. The observed genetic structure of the populations implies that different populations across the distribution range of the species should be sampled to maintain high genetic diversity when a conservation strategy is implemented.     

Characterization of MnpC, a Hydroquinone Dioxygenase Likely Involved in the meta-Nitrophenol Degradation by Cupriavidus necator JMP134

Cupriavidus necator JMP134 utilizes meta-nitrophenol (MNP) as the sole source of carbon, nitrogen, and energy. The metabolic reconstruction of MNP degradation performed in silico suggested that MnpC might have played an important role in MNP degradation. In order to experimentally confirm the prediction, we have now characterized the mnpC-encoded (amino)hydroquinone dioxygenase involved in the ring-cleavage reaction of MNP degradation. Real-time PCR analysis indicated that mnpC played an essential role in MNP degradation. MnpC was purified to homogeneity as an N-terminal six-His-tagged fusion protein, and it was proved to be a dimer as demonstrated by gel filtration. MnpC was a Fe²⁺- and Mn²⁺-dependent dioxygenase, catalyzing the ring-cleavage of hydroquinone to 4-hydroxymuconic semialdehyde in vitro and proposed as an aminohydroquinone dioxygenase involved in MNP degradation in vivo. Phylogenetic analysis suggested that MnpC diverged from the other (chloro)hydroquinone dioxygenases at an earlier point, which might result in the preference for its physiological substrate.     

Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.