Dietary assessment of ochratoxin A in Chinese dark tea and inhibitory effects of tea polyphenols on ochratoxigenic Aspergillus niger.

In recent years, there has been an increasingly heated debate on whether Chinese dark tea is contaminated with mycotoxins and whether it poses health risks to consumers. In this study, a rapid method based on high-performance liquid chromatography was used to detect ochratoxin A (OTA) in Chinese dark tea samples from different regions of China and different years. Of the 228 Chinese dark tea samples tested, 21 were detected for OTA contamination, with a concentration ranging from 2.51 ± 0.16 to 12.62 ± 0.72 µg/kg. Subsequently, a dark tea drinking risk assessment was conducted, and the hazard quotient for each group was far below the acceptable level of 1.0. Of the 12 Aspergillus spp. strains isolated, one strain of Aspergillus niger had the ability to produce OTA. We also found that tea polyphenols and epigallocatechin gallate inhibited the growth of ochratoxin-producing Aspergillus niger and the expression of non-ribosomal peptide synthetase (NRPS), a key gene for ochratoxin synthesis. Thus, OTA contamination of dark tea is at an acceptable risk level, and the inhibition of ochratoxigenic Aspergillus niger by polyphenols provides new insights into the safety of dark tea consumption.

Application of the Monte Carlo Library Least-Squares (MCLLS) approach for chromium quantitative analysis in aqueous solution.

In the present work, a new in-situ prompt gamma-ray neutron activation analysis (PGNAA) setup was developed for the quantitative measurement of chromium (Cr) in aqueous solutions which consists of a 4" × 4″ inch Bismuth Germanate detector and a 300 mCi 241Americium-beryllium neutron source. A series of standard samples were prepared by dissolving Cr compounds in deionized water of analytical pure grade and measured using the in situ PGNAA setup. Quantitative spectrum analysis was conducted using Monte Carlo Library Least-Squares approach (MCLLS). Simulates of elemental library spectra were in silico modeled using the CEARCPG code, which was developed by Prof. Robin Gardner research group in North Carolina State University. The fitted spectra presented were in excellent agreement with the total experimental spectrum, and the correlation coefficients were all nearly 1. After applying the MCLLS approach, the minimum detectable concentration of Cr was 301.5 mg/L, better than that obtained with other setups, and the relative deviation of the Cr quantitative analysis accuracy was less than 4.09%.

Study on the PGNAA measurement of heavy metals in aqueous solution by the Monte Carlo-Library Least-Squares (MCLLS) approach.

In the present work, a prompt gamma neutron activation analysis (PGNAA) setup, which consists of a 300mCi 241Americium-Beryllium (Am-Be) neutron source and a 4 × 4-in. Bismuth germanium oxide (BGO) detector, was developed for heavy metal detection in aqueous solutions. A series of standard samples with analytical purity were prepared by dissolving heavy metals in deionized water. Quantitative spectrum analysis was performed by the Monte Carlo-Least-Squares (MCLLS) approach to measure the standard samples. The detector response functions of 4 × 4-in. BGO detector were generated by using the CEARDRF code. The element libraries were simulated in silico by the CEARCPG code, which was developed by Dr. Gardner. The simulation results presented were in very good agreement with the experimental results. The correlation coefficients were very close to 1 when the fitted spectrum was compared with the experimental spectrum. By applying the MCLLS approach, the relative deviation of the measurement accuracy was less than 2.27% for Ni, Mn, and Cu and up to 69.33% for Pb.

Monte Carlo simulation of moderator and reflector in coal analyzer based on a D-T neutron generator.

Coal is one of the most popular fuels in the world. The use of coal not only produces carbon dioxide, but also contributes to the environmental pollution by heavy metals. In prompt gamma-ray neutron activation analysis (PGNAA)-based coal analyzer, the characteristic gamma rays of C and O are mainly induced by fast neutrons, whereas thermal neutrons can be used to induce the characteristic gamma rays of H, Si, and heavy metals. Therefore, appropriate thermal and fast neutrons are beneficial in improving the measurement accuracy of heavy metals, and ensure that the measurement accuracy of main elements meets the requirements of the industry. Once the required yield of the deuterium-tritium (d-T) neutron generator is determined, appropriate thermal and fast neutrons can be obtained by optimizing the neutron source term. In this article, the Monte Carlo N-Particle (MCNP) Transport Code and Evaluated Nuclear Data File (ENDF) database are used to optimize the neutron source term in PGNAA-based coal analyzer, including the material and shape of the moderator and neutron reflector. The optimized targets include two points: (1) the ratio of the thermal to fast neutron is 1:1 and (2) the total neutron flux from the optimized neutron source in the sample increases at least 100% when compared with the initial one. The simulation results show that, the total neutron flux in the sample increases 102%, 102%, 85%, 72%, and 62% with Pb, Bi, Nb, W, and Be reflectors, respectively. Maximum optimization of the targets is achieved when the moderator is a 3-cm-thick lead layer coupled with a 3-cm-thick high-density polyethylene (HDPE) layer, and the neutron reflector is a 27-cm-thick hemispherical lead layer.