Intergenerational toxic effects of parental exposure to [Cn mim]NO3 (n = 2,4,6) on nervous and skeletal development in zebrafish offspring.

Ionic liquids (ILs) are thought to have negative effects on human health. Researchers have explored the effects of ILs on zebrafish development during the early stages, but the intergenerational toxicity of ILs on zebrafish development has rarely been reported. Herein, parental zebrafish were exposed to different concentrations (0, 12.5, 25, and 50 mg/L) of [Cn mim]NO3 (n = 2, 4, 6) for 1 week. Subsequently, the F1 offspring were cultured in clean water for 96 h. [Cn mim]NO3 (n = 2, 4, 6) exposure inhibited spermatogenesis and oogenesis in F0 adults, even causing obvious lacunae in the testis and atretic follicle oocytes in ovary. After parental exposure to [Cn mim]NO3 (n = 2, 4, 6), the body length and locomotor behavior were measured in F1 larvae at 96 hours post-fertilization (hpf). The results showed that the higher the concentration of [Cn mim]NO3 (n = 2, 4, 6), the shorter the body length and swimming distance, and the longer the immobility time. Besides, a longer alkyl chain length of [Cn mim]NO3 had a more negative effect on body length and locomotor behavior. RNA-seq analysis revealed several downregulated differentially expressed genes (DEGs)-grin1b, prss1, gria3a, and gria4a-enriched in neurodevelopment-related pathways, particularly the pathway for neuroactive ligand-receptor interaction. Moreover, several upregulated DEGs, namely col1a1a, col1a1b, and acta2, were mainly associated with skeletal development. Expression of DEGs was tested by RT-qPCR, and the outcomes were consistent with those obtained from RNA-Seq. We provide evidence showing the effects of parental exposure to ILs on the regulation of nervous and skeletal development in F1 offspring, demonstrating intergenerational effects.

Nanopolystyrene size effect and its combined acute toxicity with halogenated PAHs on Daphnia magna.

Nanoplastics (NPs, diameter <1 µm) not only have toxicity but also change the toxicity of other pollutants in water. To date, the nanopolystyrene (nano-PS) size effect and its combined toxicity with halogenated polycyclic aromatic hydrocarbons (HPAHs) remain unclear. In this study, the single toxicity, combined toxicity, and mode of action of the binary mixture of polystyrene (PS) and HPAH were examined. At the same time, the nano-PS size effect on combined toxicity was also discussed. According to our results, the 48 h acute toxicity test results showed that 30 nm PS was highly toxic (EC50-48 h = 1.65 mg/L), 200 nm PS was moderately toxic (EC50-48 h = 17.8 mg/L), and 1 µm PS was lowly toxic (EC50-48 h = 189 mg/L). The NP toxicity decreased with increasing size. HPAHs were highly toxic substances to Daphnia magna (EC50-48 h = 0.12-0.22 mg/L). The mode of action of PS and HPAHs was antagonistic according to the toxicity unit method (TU), additive index method (AI), and mixture toxicity index method (MTI). The size effect of nano-PS operates via two mechanisms: the inherent toxicity of nano-PS and the sorption of pollutants by nano-PS. The former impacts the combined toxicity more than the latter. In the binary mixed system, the larger the particle size and the higher the proportion of NPs in the system, the less toxic the system was. Linear interpolation analysis can be used to predict the combined toxicity of a mixed system with any mixing ratio.

Proteolysis modification targeting protein corona affects ultrasound-induced membrane homeostasis of saccharomyces cerevisiae: Analysis of lipid relative contributions on membrane properties.

Introduction: Protein corona (PCN) adsorbed on the surface of nanoparticles has brought new research perspectives for the interaction between nanoparticles and microorganisms. In this study, the responses of saccharomyces cerevisiae' membrane lipid composition, the average length of the fatty acyl chains and the average number of unsaturation of fatty acids to ultrasound combined with nano-Fe3O4@PCN with time-limited proteolysis (nano-Fe3O4@TLP-PCN) was investigated. Methods: Lipidomic data was obtained using Ultra-high performance liquid chromatography coupled with a Q-Exactive plus mass spectrometer. The membrane potential, proton motive force assay and the membrane lipid oxidation were measured using Di-BAC4(3), DISC3(5) and C11-BODIPY581/591 as the probes. Combined with the approach of feasible virtual samples generation, the back propagation artificial neural network (BP-ANN) model was adopted to establish the mapping relationship between lipids and membrane properties. Results: The time-limited proteolysis targeting wheat PCN-coated Fe3O4 nanoparticles resulted in regular changes of hydrodynamic diameters, ζ-potentials, and surface hydrophobicity. In addition, with the prolongation of PCN proteolysis time, disturbances of 3 S.cerevisiae membrane characteristics, and membrane lipidomic remodeling in response to ultrasound+ nano-Fe3O4@PCN were observed. The analysis of relative importance which followed revealed that ergosterol, phosphatidylserine, and phosphatidylinositol phosphate had the greatest influence on membrane potential. For membrane lipid oxidation, ceramide, phosphatidylethanolamine, and sitosterol ester contribute 16.2, 14.9, and 13.1%, respectively. The relative contributions of six lysolecithins to the dissipation of proton motive force remained limited. Discussion: An adaptation mechanism of cell membrane to proteolyzed PCN, wherein lipidome remodeling could preserved functional membrane phenotypes was revealed. Furthermore, it is highlighted that the relative importances of SiE, Cer, PE and PIP in determining membrane potential, PMF dissipation and membrane lipid oxidation by establishing FVSG-BP-ANN model.

Sensitive sensing of Hg(II) based on lattice B and surface F co-doped CeO2: Synergies of catalysis and adsorption brought by doping site engineering.

Transition metal oxides are widely used in the detection of heavy metal ions (HMIs), and the co-doping strategy that introducing a variety of different dopant atoms to modify them can obtain a better detection performance. However, there is very little research on the co-doped transition metal oxides by non-metallic elements for electrochemical detection. Herein, boron (B) and fluorine (F) co-doped CeO2 nanomaterial (BFC) is constructed to serve as the electrochemically sensitive interface for the detection of Hg(II). B and F affect the sensitivity of CeO2 to HMIs when they were introduced at different doping sites. Through a variety of characterization, it is proved that B is successfully doped into the lattice and F is doped on the surface of the material. Through the improvement of the catalytic properties and adsorption capacity of CeO2 by different doping sites, this B and F co-doped CeO2 exhibits excellent square wave anodic stripping voltammetry (SWASV) current responses to Hg(II). Both the high sensitivity of 906.99 µA µM-1 cm-2 and the low limit of detection (LOD) of 0.006 µM are satisfactory. Besides, this BFC glassy carbon electrode (GCE) also has good anti-interference property, which has been successfully used in the detection of Hg(II) in actual water. This discovery provides a useful strategy for designing a variety of non-metallic co-doped transition metal oxides to construct trace heavy metal ion-sensitive interfaces.

Proteolysis Degree of Protein Corona Affect Ultrasound-Induced Sublethal Effects on Saccharomyces cerevisiae: Transcriptomics Analysis and Adaptive Regulation of Membrane Homeostasis.

Protein corona (PC) adsorbed on the surface of nanoparticles brings new research perspectives on the interaction between nanoparticles and fermentative microorganisms. Herein, the proteolysis of wheat PC adsorbed on a nano-Se surface using cell-free protease extract from S. cerevisiae was conducted. The proteolysis caused monotonic changes of ζ-potentials and surface hydrophobicity of PC. Notably, the innermost PC layer was difficult to be proteolyzed. Furthermore, when S. cerevisiae was stimulated by ultrasound + 0.1 mg/mL nano-Se@PC, the proportion of lethal and sublethal injured cells increased as a function of the proteolysis time of PC. The transcriptomics analysis revealed that 34 differentially expressed genes which varied monotonically were related to the plasma membrane, fatty acid metabolism, glycerolipid metabolism, etc. Significant declines in the membrane potential and proton motive force disruption of membrane were found with the prolonged proteolysis time; meanwhile, higher membrane permeability, membrane oxidative stress levels, membrane lipid fluidity, and micro-viscosity were triggered.

The joint effect of ultrasound and magnetic Fe3O4 nanoparticles on the yield of 2,6-dimethoxy-ρ-benzoquinone from fermented wheat germ: Comparison of evolutionary algorithms and interactive analysis of paired-factors.

2,6-Dimethoxy-ρ-benzoquinone (DMBQ) is a potential anti-tumor substance found in the fermented wheat germ. In this study, ultrasound and Fe3O4 nanoparticles were used to improve the DMBQ yield. An artificial neural network (ANN) embedded separately with the back-propagation algorithm (BP), genetic algorithm (GA), particle swarm optimized algorithm (PSO), ant colony optimized algorithm (ACO), GA-ACO, GA-PSO and PSO-ACO, were used to establish the relationship between 11 factors and DMBQ yield. The robustness and generalization of PSO-ACO-ANN, which gave the minimum mean squared error and mean absolute percentage error for the training and test dataset, was superior to the others. Next, a modified Garson's algorithm and mixed partial derivatives algorithm indicated that the most influential paired-parameters were ultrasonic power and concentration of nanoparticles. Finally, the factors were optimized by six optimization algorithms, and confirmatory experimental results indicated that the optimum DMBQ yield was 0.213 ±â€¯0.007 mg/g, which was 161.2% higher than the control.

Artificial neural network - Genetic algorithm to optimize wheat germ fermentation condition: Application to the production of two anti-tumor benzoquinones.

Methoxy-ρ-benzoquinone (MBQ) and 2, 6-dimethoxy-ρ-benzoquinone (DMBQ) are two potential anticancer compounds in fermented wheat germ. In present study, modeling and optimization of added macronutrients, microelements, vitamins for producing MBQ and DMBQ was investigated using artificial neural network (ANN) combined with genetic algorithm (GA). A configuration of 16-11-1 ANN model with Levenberg-Marquardt training algorithm was applied for modeling the complicated nonlinear interactions among 16 nutrients in fermentation process. Under the guidance of optimized scheme, the total contents of MBQ and DMBQ was improved by 117% compared with that in the control group. Further, by evaluating the relative importance of each nutrient in terms of the two benzoquinones' yield, macronutrients and microelements were found to have a greater influence than most of vitamins. It was also observed that a number of interactions between nutrients affected the yield of MBQ and DMBQ remarkably.