Antiglioma Natural Products from the Marine-Associated Fungus Penicillium sp. ZZ1750.

Marine-derived Penicillium fungi are one of the most important sources for the discovery of new bioactive natural products. This study characterized the isolation, structures, and antiglioma activities of twelve compounds, including three novel ones-penipyridinone B (1), 11S-(-)-penilloid A (2), and 11R,14E-(+)-penilloid A (3)-from the marine fungus Penicillium sp. ZZ1750. The structures of the novel compounds were determined via extensive nuclear magnetic resonance (NMR) spectroscopic analyses, high-resolution electrospray ionization mass spectroscopy (HRESIMS) data, Mosher's method, optical rotation (OR) calculations, and electronic circular dichroism (ECD) calculations. Penipyridinone B represents the first example of its structural type and showed potent antiglioma activity, with IC50 values of 2.45 µM for U87MG cells and 11.40 µM for U251 cells. The known compounds of questiomycin A (9) and xanthocillin X (10) also showed antiproliferative activity against both U87MG and U251 cells, with IC50 values of 13.65 µM to 22.56 µM. The antiglioma activity of questiomycin A and xanthocillin X may be related to the promotion of reactive oxygen species (ROS) production, the reduction of mitochondrial membrane potential (MMP), and the enhancement of caspase-3 enzyme activity.

New Antiproliferative Compounds against Glioma Cells from the Marine-Sourced Fungus Penicillium sp. ZZ1750.

Seven novel compounds, namely peniresorcinosides A-E (1-5), penidifarnesylin A (6), and penipyridinone A (7), together with the 11 known ones 8-17, were isolated from a culture of the marine-associated fungus Penicillium sp. ZZ1750 in rice medium. The structures of the new compounds were established based on their high-resolution electrospray ionization mass spectroscopy (HRESIMS) data, extensive nuclear magnetic resonance (NMR) spectroscopic analyses, chemical degradation, Mosher's method, 13C-NMR calculations, electronic circular dichroism (ECD) calculations, and single crystal X-ray diffraction. Peniresorcinosides A (1) and B (2) are rare glycosylated alkylresorcinols and exhibited potent antiglioma activity, with IC50 values of 4.0 and 5.6 µM for U87MG cells and 14.1 and 9.8 µM for U251 cells, respectively.

Virtual reality-based adaptive dose assessment method for arbitrary geometries in nuclear facility decommissioning.

This paper presents an improved and efficient virtual reality-based adaptive dose assessment method (VRBAM) applicable to the cutting and dismantling tasks in nuclear facility decommissioning. The method combines the modeling strength of virtual reality with the flexibility of adaptive technology. The initial geometry is designed using three-dimensional computer-aided design tools, and a hybrid model composed of cuboids and a point-cloud is generated automatically according to the virtual model of the object. In order to improve the efficiency of dose calculation while retaining accuracy, the hybrid model is converted to a weighted point-cloud model, and the point kernels are generated by adaptively simplifying the weighted point-cloud model according to the detector position, an approach that is suitable for arbitrary geometries. The dose rates are calculated using the point kernel method. To account for radiation scattering effects, buildup factors are calculated using the geometric progression formula in the fitting function. The geometric modeling capability of VRBAM was verified by simulating basic geometries, which included a convex surface, a concave surface, a flat surface and their combination. The simulation results show that the VRBAM is more flexible and superior to other approaches in modeling complex geometries. In this paper, the computation time and dose rate results obtained from the proposed method were also compared with those obtained using the MCNP code and an earlier virtual reality-based method developed by the same authors.

A fast simulation method for radiation maps using interpolation in a virtual environment.

In nuclear decommissioning, virtual simulation technology is a useful tool to achieve an effective work process by using virtual environments to represent the physical and logical scheme of a real decommissioning project. This technology is cost-saving and time-saving, with the capacity to develop various decommissioning scenarios and reduce the risk of retrofitting. The method utilises a radiation map in a virtual simulation as the basis for the assessment of exposure to a virtual human. In this paper, we propose a fast simulation method using a known radiation source. The method has a unique advantage over point kernel and Monte Carlo methods because it generates the radiation map using interpolation in a virtual environment. The simulation of the radiation map including the calculation and the visualisation were realised using UNITY and MATLAB. The feasibility of the proposed method was tested on a hypothetical case and the results obtained are discussed in this paper.

Streptonaphthyridine A, a new naphthyridine analogue with antiproliferative activity against human glioma cells from mariana trench-associated actinomycete Streptomyces sp. SY2111.

A new naphthyridine analogue, named streptonaphthyridine A (1), together with eight previously reported compounds (2-9), were isolated from a Mariana Trench sediment-associated actinomycete Streptomyces sp. SY2111. Planar structure of streptonaphthyridine A was established by analyses of its HRESIMS data and extensive NMR spectra and its absolute configuration was determined by a combination of single crystal X-ray diffraction analysis and optical rotation calculations. Streptonaphthyridine A (1) had antiproliferative activity against human glioma U87MG and U251 cells with IC50 values of 7.9 ± 1.3 and 13.4 ± 2.7 µM, respectively, and the known compound monomethylsulochrin (7) showed more potent activity with IC50 values of 0.6 ± 0.1 µM for U87MG cells and 0.1 ± 0.0 µM for U251 cells.

Antimicrobial metabolites from the Indonesian mangrove sediment-derived fungus Penicillium chrysogenum sp. ZZ1151.

A total of 14 compounds including a novel tetrasubstituted benzene derivative peniprenylphenol A were isolated from a scaled-up culture of the Indonesian mangrove sediment-derived fungus Penicillium chrysogenum ZZ1151 in rice medium. Structures of the isolated compounds were determined based on their NMR spectroscopic analyses, HRESIMS data, optical rotation calculations and comparison with the reported data. New peniprenylphenol A (1) was found to have antimicrobial activities against human pathogenic methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli and Candida albicans with MIC values of 6, 13, and 13 µg/mL, respectively. The known compounds of penicimumide (2), preparaherquamide (5), uridine (6), thymine (7), 1,2-seco-trypacidin (8) communol G (9), clavatol (10), 4-hydroxybenzeneacetic acid methyl ester (11), 2,5-dihydroxyphenylacetic acid methyl ester (12), 2-hydroxyphenylacetic acid methyl ester (13) and 4-hydroxyphenylethanone (14) showed antimicrobial activity against at least one of the three tested pathogens with MIC values of 3-25 µg/mL.

New Hygrocins K-U and Streptophenylpropanamide A and Bioactive Compounds from the Marine-Associated Streptomyces sp. ZZ1956.

Marine-derived Streptomyces actinomycetes are one of the most important sources for the discovery of novel bioactive natural products. This study characterized the isolation, structural elucidation and biological activity evaluation of thirty compounds, including twelve previously undescribed compounds, namely hygrocins K-U (5-13, 17 and 18) and streptophenylpropanamide A (23), from the marine-associated actinomycete Streptomyces sp. ZZ1956. Structures of the isolated compounds were determined by a combination of extensive NMR spectroscopic analyses, HRESIMS data, the Mosher's method, ECD calculations, single crystal X-ray diffraction and comparison with reported data. Hygrocins C (1), D (2), F (4), N (8), Q (11) and R (12), 2-acetamide-6-hydroxy-7-methyl-1,4-naphthoquinone (22), echoside C (27), echoside A (28) and 11,11'-O-dimethylelaiophylin (30) had antiproliferative activity (IC50: 0.16-19.39 µM) against both human glioma U87MG and U251 cells with hygrocin C as the strongest active compound (IC50: 0.16 and 0.35 µM, respectively). The analysis of the structure-activity relationship indicated that a small change in the structures of the naphthalenic ansamycins had significant influence on their antiglioma activities. Hygrocins N (8), O (9), R (12), T (17) and U (18), 2-amino-6-hydroxy-7-methyl-1,4-naphthoquinone (21), 2-acetamide-6-hydroxy-7-methyl-1,4-naphthoquinone (22), 3'-methoxy(1,1',4',1″-terphenyl)-2',6'-diol (26), echoside C (27) and echoside A (28) showed antibacterial activity against methicillin-resistant Staphylococcus aureus and Escherichia coli with MIC values of 3-48 µg/mL.

[Correlation between distributions of pathogenic bacteria on hands and the position of funeral staffs].

OBJECTIVE: This study aims to investigate the bacteria contamination on hands of funeral staffs in different positions. METHODS: Bacterial samples were collected from the hands of 105 funeral staffs in different positions (including 90 frontline staffs and 15 administrative workers) from 13 funeral parlors nationwide, and were subsequently tested by bacterium inspection. RESULTS: In total, 1783 strains of bacteria were isolated, including 1027 Gram-positive bacteria, most of which were Staphylococcus; and 756 Gram-negative bacteria, most of which were Pseudomonas. Out of the 1783 strains of bacteria, 570 pathogens and opportunistic pathogens were isolated, accounted to 31.96%. The isolated ratio of pathogens and conditional pathogens in embalmed/cosmetologist of cadavers was 35.67% (370/1037), which was higher than those in the funeral workers in other positions, such as cremators, pick-up and administrative workers, whose ratios were 24.42% (95/389), 22.41% (52/232) and 10.40% (12/125), respectively (χ(2) were 13.682, 10.967 and 32.263, respectively; P values were all < 0.05). And the isolated ratios of pathogens and conditional pathogens in cremators and pick-up workers were significantly higher than that in administrative workers (χ(2) were 11.206 and 7.873, respectively; P values were all < 0.05). CONCLUSION: Lots of bacteria were found in the samples from hands of funeral staffs. The isolated ratio of pathogens and conditional pathogens was different between the funeral staffs in different positions; while the highest was from embalmed/cosmetologist of cadavers and the lowest was from administrators.

Remaining useful life prediction techniques for electric valves based on convolution auto encoder and long short term memory.

To optimize the operation and maintenance of nuclear power systems, this study presents a remaining useful life (RUL) prediction method for electric valves by combining convolutional auto-encoder (CAE) and long short term memory (LSTM). CAE can extract deeper features and LSTM is efficient in dealing with time-series data. Moreover, by designing a parallel structure between the outputs of CAE and the original data, features fed into the LSTM are enriched. Also, network structure and corresponding hyper-parameters are compared to obtain a more suitable model. Moreover, the accuracy of the proposed method is tested and compared with other machine learning algorithms. This work also serves as a critical innovation to enhance the safety and economic operation of nuclear plants and other complex systems.

A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants.

The safety and public health during nuclear power plant operation can be enhanced by accurately recognizing and diagnosing potential problems when a malfunction occurs. However, there are still obvious technological gaps in fault diagnosis applications, mainly because adopting a single fault diagnosis method may reduce fault diagnosis accuracy. In addition, some of the proposed solutions rely heavily on fault examples, which cannot fully cover future possible fault modes in nuclear plant operation. This paper presents the results of a research in hybrid fault diagnosis techniques that utilizes support vector machine (SVM) and improved particle swarm optimization (PSO) to perform further diagnosis on the basis of qualitative reasoning by knowledge-based preliminary diagnosis and sample data provided by an on-line simulation model. Further, SVM has relatively good classification ability with small samples compared to other machine learning methodologies. However, there are some challenges in the selection of hyper-parameters in SVM that warrants the adoption of intelligent optimization algorithms. Hence, the major contribution of this paper is to propose a hybrid fault diagnosis method with a comprehensive and reasonable design. Also, improved PSO combined with a variety of search strategies are achieved and compared with other current optimization algorithms. Simulation tests are used to verify the accuracy and interpretability of research findings presented in this paper, which would be beneficial for intelligent execution of nuclear power plant operation.