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A number of studies have demonstrated that endophytic fungi have the potential to produce antitumor active substances with novel structures and significant activities. In our previous studies, we isolated a Fusarium strain from the stem of the medicinal plant Nothapodytes pittosporoides (Oliv.). In this study, we identified this strain as Fusarium solani and found that its crude extract has significant antitumor activity against human alveolar adenocarcinoma cells (A549). We overexpressed the global regulatory factor VeA in F. solani (VeAOE), resulting in a significant increase in antitumor activity. The MTT assay results showed that the inhibition rate of the VeAOE mutant extract on A549 cancer cells was significantly higher than that of the WT extract, as the IC50 decreased from 369.22 to 285.89 μg/mL, and the apoptosis ratio was significantly increased by approximately 4.86-fold. In VeAOE, accumulation of alkaloids, terpenoids, carboxylic acid derivatives, phenols and flavonoid metabolites with potential antitumor activity was significantly increased compared with WT based on metabolomic analysis. Additionally, transcriptome analysis found that the expression patterns of 48 genes related to antitumor activity were significantly changed in VeAOE, mainly involving glycosyl hydrolases, the Zn(2)-Cys(6) class, cytochrome P450 monooxygenase, 3-isopropylmalate dehydratase, and polyketide synthases. These results suggested that VeA mediated the antitumor activity of the metabolites in F. solani HB1-J1 by regulating multiple metabolic pathways. [ABSTRACT FROM AUTHOR]

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Odor released from the sewage sludge composting process often has a negative impact on the sewage sludge treatment facility and becomes a hindrance to promoting compost technology. This study investigated the effect of adding KNO3 on the emissions of volatile sulfur compounds, such as hydrogen sulfide (H2S), dimethyl sulfide (DMS), and carbon disulfide (CS2), during sewage sludge composting and on the physicochemical properties of compost products, such as arylsulfatase activity, available sulfur, total sulfur, moisture content, and germination index. The results showed that the addition of KNO3 could inhibit the emissions of volatile sulfur compounds during composting. KNO3 can also increase the heating rate and peak temperature of the compost pile and reduce the available sulfur loss. The addition of 4% and 8% KNO3 had the best effect on H2S emissions, and it reduced the emissions of H2S during composting by 19.5% and 20.0%, respectively. The addition of 4% KNO3 had the best effect on DMS and CS2 emissions, and it reduced the emissions of DMS and CS2 by 75.8% and 63.0%, respectively. Furthermore, adding 4% KNO3 had the best effect from the perspective of improving the germination index of the compost. [ABSTRACT FROM AUTHOR]

For small signal stability analysis of power systems, computing eigenvalues of the state space model is a widely used method, but still worthy of study due to computational issues in practical application. For large-scale power systems, high dimension of state space model, unknown distribution of eigenvalues and requirement on computing speed make computation of eigenvalues a challenging task. A computationally efficient method is proposed with utilizing synchronous parallelization for finding eigenvalues of concern in a flexibly specified area on the s -plane. The designed parallel framework achieves exact workload balance among computing units, which is attributed to the kernel eigenvalue solver implemented by Krylov–Schur factorization with fixing subspace dimension and discarding restart process. Satisfactory parallel speedup and numerical stability are obtained. Reliability for finding all target eigenvalues and parallel scalability of the parallelization are validated by numerical experiments on three power systems with different scales. • Parallel scalability by scheduling computing tasks in synchronous parallelization. • Computational reliability on finding all wanted eigenvalues with enough accuracy. • Numerical stability with discarding restart process of Krylov-Schur factorization. [ABSTRACT FROM AUTHOR]

Microwave heating is a promising technique for heterogeneous catalytic reactions in plastic decomposition. The microwave-insensitive plastic material requires microwave-absorbing catalysts to facilitate catalytic-assisted decomposition and synergistic heating. However, the heating characteristics of catalyst particles within the microwave system is still unclear. In this study, the effects of particle size, particle arrangement direction, and particle shape on the microwave heating behavior of particles was investigated, and the model was experimentally validated and analyzed using infrared temperature data. The simulation results indicated that the heating rate increased as the particle size enlarged, with an average heating rate of 5.56 °C/s for the particle with a radius of 5 mm in comparison to 4.29 °C/s for that of 1 mm. Additionally, when particles were aligned parallel to the applied electric field, the electric field was intensely focused at the interparticle area, with a maximum electric field strength difference of 2.2 × 104 V/m in the samples. In contrast, the horizontal placement resulted in reduced electric field intensity (4.7 × 103 V/m) and lower temperatures (62 °C) near the areas adjacent to the particles compared to the maximum values in the particles. With respect to particle shape, cylindrical particles possessing larger aspect ratios exhibited superior heating performance due to the extended span of intraparticle microwave transmission aligned with the electric field direction but also resulted in increased thermal field distribution inhomogeneity. The research offers theoretical guidance to prevent catalyst sintering and promote microwave-assisted catalytic plastic decomposition. • The interrelation of electromagnetic field, power loss and temperature is revealed. • Two opposite interaction principles for particles arrangement are explored. • Local cold spots occur near the horizontal interparticle region. • The effect of particle shape on heating performance and homogeneity is studied. [ABSTRACT FROM AUTHOR]

Microorganisms have developed mechanisms to adapt to environmental stress, but how microbial communities adapt to long-term and combined heavy-metal contamination under natural environmental conditions remains unclear. Specifically, this study analyzed the characteristics of heavy metal composition, microbial community, and heavy metal resistance genes (MRGs) in sediments along Mang River, a tributary of the Yellow River, which has been heavily polluted by industrial production for more than 40 years. The results showed that the concentrations of Cr, Zn, Pb, Cu and As in most sediments were higher than the ambient background values. Bringing the heavy metals speciation and concentration into the risk evaluation method, two-thirds of the sediment samples were at or above the moderate risk level, and the ecological risk of combined heavy metals in the sediments decreased along the river stream. The high ecological risk of heavy metals affected the microbial community structure, metabolic pathways and MRG distribution. The formation of a HM-resistant microbiome possibly occurred through the spread of insertion sequences (ISs) carrying multiple MRGs, the types of ISs carrying MRGs outnumber those of plasmids, and the quantity of MRGs on ISs is also higher than that on plasmids. These findings could improve our understanding of the adaptation mechanism of microbial communities to long-term combined heavy metal contamination. [Display omitted] • Various HMs pollution decreased from upstream to downstream in Mang River sediments. • HMs and nutrients altered the microbial communities in Mang River sediments. • HM-resistant microbiome possibly formed through the spread of MRGs carried by ISs. • Mang River inflow barely increased the MRG content of the Yellow River. [ABSTRACT FROM AUTHOR]