RESUMO
Cadinanes are a class of bicyclic sesquiterpenes with complex stereochemistry and broad pharmacological activities, such as antibacterial, anti-inflammatory, and hypoglycemic activities. To date, structurally diverse and bioactive cadinane sesquiterpenes have been isolated and identified from a variety of plants and microorganisms. Moreover, deeper understandings on cadinane sesquiterpene synthases have been made. This article categorized the 124 new cadinanes which were published in the literatures in the past four years (2017-2020) into five structural types, and presented their pharmacological activities. We also illustrated the elucidation of the biosynthetic pathways for typical cadinanes, summarized the research progress on cadinane sesquiterpene synthases. Finally, current challenges and future prospects were proposed and discussed.
Assuntos
Anti-Inflamatórios , Sesquiterpenos Policíclicos , SesquiterpenosRESUMO
The objective is to deal with brain effective connectivity among epilepsy electroencephalogram (EEG) signals recorded by use of depth electrodes in the cerebral cortex of patients suffering from refractory epilepsy during their epileptic seizures. The Wiener-Granger Causality Index (WGCI) is a well-known effective measure that can be useful to detect causal relations of interdependence in these kinds of EEG signals. It is based on the linear autoregressive model, and the issue of the estimation of the model parameters plays an important role in the calculation accuracy and robustness of WGCI to do research on brain effective connectivity. Focusing on this issue, a modified Akaike's information criterion algorithm is introduced in the computation of the WGCI to estimate the orders involved in the underlying models and in order to advance the performance of WGCI to detect brain effective connectivity. Experimental results support the interesting performance of the proposed algorithm to characterize the information flow both in a linear stochastic system and a physiology-based model.