Five new unusual citrinin-derived alkaloids with a tetracyclic core, citrinidines A–E (1–5), two new amide alkaloids, methyl (2S,8E)-1′-(2-methyl-3-oxodec-8-enamido) butanoate (6) and (2S,8E)-2-methyl-3-oxodec-8-enamide (7), a new unusual citrinin trimer, tricitrinol C (8), a new citrinin acetal-ketal derivative, citrininol (9), together with four known citrinin monomers (10–13), and three known citrinin dimers (14–16), were isolated from the fermentation of hydrothermal vent-associated fungus Penicillium citrinum TW132-59. Their structures were unambiguously determined by nuclear magnetic resonance (NMR), mass spectrometry, Mosher′s method, 13C NMR calculation in combination with DP4+, and ECD calculations. A plausible biosynthetic pathway of all new compounds (1–9) was proposed. Citrinin trimer (8) exhibited potent cytotoxicity activity with an IC50 value of 1.34 ± 0.11 μM, and compounds 1 and 15 showed moderate cytotoxicity with IC50 values of 17.50 ± 1.43 and 9.45 ± 0.55 μM, respectively, against A549 cell line.

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We report the discovery of talaropeptins A (1) and B (2), tripeptides with an unusual 5/6/5 heterocyclic scaffold and an N-trans-cinnamoyl moiety, which were identified from the marine-derived fungus Talaromyces purpureogenus CX11. A bioinformatic analysis of the genome of T. purpureogenus CX11 and gene inactivation revealed that the biosynthesis of talaropeptins involves a nonribosomal peptide synthase gene cluster. Their chemical structures were elucidated using a combination of 1D and 2D NMR spectroscopy and mass spectrometry. The absolute configurations of 1 and 2 were established by electronic circular dichroism calculations and Marfey’s method. The plausible biosynthesis of 1 and 2 is also proposed on the basis of gene deletion, substrate feeding, and heterologous expression. Compounds 1 and 2 showed moderate antifungal activity against phytopathogenic fungus Fusarium oxysporum with MIC values of 12.5 and 25 μg/mL, respectively.

Quantifying the complexity of physiologic time series has long attracted interest from researchers. The multiscale entropy (MSE) algorithm is a prevailing method to quantify the complexity of signals in a variety of research fields. However, the MSE method assigns increased complexity to the mixed signal of a physiologic time series added with white noise, although the mixed signal should become less complex due to the broken correlation. In addition, the MSE method needs users to visually examine its scale dependence (shape) to better characterize the complexity of a physiologic process, which is sometimes not feasible. In this paper, we proposed a new method, namely the power-law exponent modulated multiscale entropy (pMSE), as a complexity measure for physiologic time series. We tested the pMSE method on simulated data and real-world physiologic interbeat interval time series and demonstrated that it could solve the above two difficulties of the MSE method. We expect that the proposed pMSE method or its future variants could serve as a useful complement to the MSE method for the complexity analysis of physiologic time series. INDEX TERMS Time series, multiscale entropy, complexity, power-law, self-similarity