Inhibition of Fungal Aflatoxin B1 Biosynthesis by Diverse Botanically-Derived Polyphenols

Purpose: To identify and characterize the capacity of diverse botanically-derived polyphenols to inhibit aflatoxin B1 (AFB1) production by Aspergillus flavus.Methods: A tea-derived polyphenol mixture and numerous individual polyphenols were tested for their effects on A. flavus growth and AFB1 production. Fungal spores were cultured for 60 h with polyphenols (range 0 ‒ 1,000 μg/mL). The fungi were enumerated by hemocytometry, and AFB1 in culture supernatants was quantified by high-performance liquid chromatography (HPLC).Results: Neither the tea-derived polyphenol mixture nor individual polyphenol compound, except quercetin, inhibited A. flavus growth. Quercetin detectably inhibited growth at 800 μg/mL; none of the remaining polyphenols inhibited fungal proliferation, even at 1,000 μg/mL. However, catechin mixture and all individual polyphenols differentially inhibited fungal AFB1 biosynthesis. Non-ester catechin derivatives revealed stronger inhibitory activity than ester derivatives.Conclusion: Quercetin exhibits the strongest inhibitory effect on AFB1 production and is the only test compound that also inhibits fungal proliferation. Botanically-derived polyphenols are, therefore, promising reagents for controlling fungal contamination and associated toxic aflatoxin deposition in harvested crops and in food processing operations.Keywords: Polyphenols, Quercetin, Aflatoxin B1, Inhibition, Antioxidatio

Exploiting Magnetic Resonance Angiography Imaging Improves Model Estimation of BOLD Signal

The change of BOLD signal relies heavily upon the resting blood volume fraction () associated with regional vasculature. However, existing hemodynamic data assimilation studies pretermit such concern. They simply assign the value in a physiologically plausible range to get over ill-conditioning of the assimilation problem and fail to explore actual . Such performance might lead to unreliable model estimation. In this work, we present the first exploration of the influence of on fMRI data assimilation, where actual within a given cortical area was calibrated by an MR angiography experiment and then was augmented into the assimilation scheme. We have investigated the impact of on single-region data assimilation and multi-region data assimilation (dynamic cause modeling, DCM) in a classical flashing checkerboard experiment. Results show that the employment of an assumed in fMRI data assimilation is only suitable for fMRI signal reconstruction and activation detection grounded on this signal, and not suitable for estimation of unobserved states and effective connectivity study. We thereby argue that introducing physically realistic in the assimilation process may provide more reliable estimation of physiological information, which contributes to a better understanding of the underlying hemodynamic processes. Such an effort is valuable and should be well appreciated

Changing planar thin film growth into self-assembled island formation by adjusting experimental conditions

Illustrated in this paper are two examples of altering planar growth into self-assembled island formation by adapting experimental conditions. Partial oxidation, undersaturated solution and high temperature change Frank-Van der Merwe (FM) growth of Al0.3Ga0.7As in liquid phase epitaxy (LPE) into isolated island deposition. Low growth speed, high temperature and in situ annealing in molecular beam epitaxy (MBE) cause the origination of InAs/GaAs quantum dots (QDs) to happen while the film is still below critical thickness in Stranski-Krastanow (SK) mode. Sample morphologies are characterized by scanning electron microscopy (SEM) or atomic force microscopy (AFM). It is suggested that such achievements are of value not only to fundamental researches but also to spheres of device applications as well. (c) 2004 Elsevier B.V. All rights reserved

The Second Transmembrane Domain of P2X7 Contributes to Dilated Pore Formation

Activation of the purinergic receptor P2X7 leads to the cellular permeability of low molecular weight cations. To determine which domains of P2X7 are necessary for this permeability, we exchanged either the C-terminus or portions of the second transmembrane domain (TM2) with those in P2X1 or P2X4. Replacement of the C-terminus of P2X7 with either P2X1 or P2X4 prevented surface expression of the chimeric receptor. Similarly, chimeric P2X7 containing TM2 from P2X1 or P2X4 had reduced surface expression and no permeability to cationic dyes. Exchanging the N-terminal 10 residues or C-terminal 14 residues of the P2X7 TM2 with the corresponding region of P2X1 TM2 partially restored surface expression and limited pore permeability. To further probe TM2 structure, we replaced single residues in P2X7 TM2 with those in P2X1 or P2X4. We identified multiple substitutions that drastically changed pore permeability without altering surface expression. Three substitutions (Q332P, Y336T, and Y343L) individually reduced pore formation as indicated by decreased dye uptake and also reduced membrane blebbing in response to ATP exposure. Three others substitutions, V335T, S342G, and S342A each enhanced dye uptake, membrane blebbing and cell death. Our results demonstrate a critical role for the TM2 domain of P2X7 in receptor function, and provide a structural basis for differences between purinergic receptors. © 2013 Sun et al

Selecting control genes for RT-QPCR using public microarray data

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable

Bulk properties of the system formed in Au+Au collisions at sNN =14.5 GeV at the BNL STAR detector

We report systematic measurements of bulk properties of the system created in Au+Au collisions at sNN=14.5 GeV recorded by the STAR detector at the Relativistic Heavy Ion Collider (RHIC). The transverse momentum spectra of π±, K±, and p(p) are studied at midrapidity (|y|<0.1) for nine centrality intervals. The centrality, transverse momentum (pT), and pseudorapidity (η) dependence of inclusive charged particle elliptic flow (v2), and rapidity-odd charged particles directed flow (v1) results near midrapidity are also presented. These measurements are compared with the published results from Au+Au collisions at other energies, and from Pb+Pb collisions at sNN=2.76 TeV. The results at sNN=14.5 GeV show similar behavior as established at other energies and fit well in the energy dependence trend. These results are important as the 14.5-GeV energy fills the gap in μB, which is of the order of 100 MeV, between sNN=11.5 and 19.6 GeV. Comparisons of the data with UrQMD and AMPT models show poor agreement in general