Spirotetramat, a member of tetronic and tetramic acid derivatives, is a unique insecticide and acaricide. Although the effect on zebrafish embryos lipid biosynthesis of spirotetramat has been characterized, the energy metabolism and toxic effect mechanism warrant further investigation. To investigate the toxic mechanism of spirotetramat on energy metabolism, zebrafish embryos were exposed to 100, 500 and 1000 µg/L of spirotetramat for 4 days. Untargeted metabolomics showed the synthesis and degradation of ketone pathway metabolites (R)-3-Hydroxybutyric acid and Acetoacetate significantly decreased, as well as increasing the abundance of Anti-Acetyl Coenzyme A Carboxylase protein (ACC1). Down-regulation of the genes related to ß-oxidation and the tricarboxylic acid cycle in the embryos show decreased energy metabolism. Carnitine palmitoyltransferase 1 (CPT- I) significantly decreased while citrate synthase (CS) significantly increased. Additionally, mitochondrial lesions in embryos were found using electron microscopy. Our study provides novel and robust perspectives, which show that spirotetramat treatment in embryos leads to metabolic disturbances that adversely affect cellular energy homeostasis.

Chemical pollutants, such as pesticides, often leach into aquatic environments and impact non-target organisms. Marine invertebrates have complex life cycles with multiple life-history stages. Exposure to pesticides during one life-history stage potentially influences subsequent stages; a process known as a carry-over effect. Here, we investigated carry-over effects on the jellyfish Aurelia coerulea. We exposed polyps to individual and combined concentrations of atrazine (2.5 μg/L) and chlorpyrifos (0.04 μg/L) for four weeks, after which they were induced to strobilate. The resultant ephyrae were then redistributed and exposed to either the same conditions as their parent-polyps or to filtered seawater to track potential carry-over effects. The percentage of deformities, ephyrae size, pulsation and respiration rates, as well as the metabolic profile of the ephyrae, were measured. We detected a subtle carry-over effect in two metabolites, acetoacetate and glycerophosphocholine, which are precursors of the neurotransmitter acetylcholine, important for energy metabolism and osmoregulation of the ephyrae. Although these carry-over effects were not reflected in the other response variables in the short-term, a persistent reduction of these two metabolites could have negative physiological consequences on A. coerulea jellyfish in the long-term. Our results highlight the importance of considering more than one life-history stage in ecotoxicology, and measuring a range of variables with different sensitivities to detect sub-lethal effects caused by anthropogenic stressors. Furthermore, since we identified few effects when using pesticides concentrations corresponding to Australian water quality guidelines, we suggest that future studies consider concentrations detected in the environment, which are higher than the water quality guidelines, to obtain a more realistic scenario by possible risk from pesticide exposure.

A solid polymer, poly[(sodium methacrylate)-co-2-(methacryloyloxy)ethyl acetoacetate], p(MAA-co-MEAA) was synthesized and then grafted onto carbon nanotubes to prepare poly(MAA-co-MEAA)-grafted carbon nanotubes [CNT-g-p(MAA-co-MEAA)]. NMR, TGA, and FT-IR characterized the synthesized polymers and adsorbents. SEM-EDX was used to investigate the surface characteristics of the adsorbents. Pb²⁺ was removed from the aqueous solution using the CNT-g-p(MAA-co-MEAA). A batch adsorption experiment was performed at different Pb²⁺ concentrations (1, 10, 25, 50 mg/L), pH (4 and 6.75), temperature (25 and 35 °C), and contact periods (1, 5, 20, 60, and 1440 min) to study the adsorption kinetics and isotherm. The adsorbent dose of 2.5 g/L could effectively lower the initial Pb²⁺ concentration of 1000 to 2 ppb. The maximum adsorption capacity of the adsorbent was found to be 1178 mg/g. In addition, the adsorbents have been shown to effectively reduce the coexisting metal ion concentrations from industrial wastewater, which indicated the potential of the proposed adsorbent in removing metal ions from coexisting metals containing wastewater. To predict the adsorption efficiency of Pb²⁺, various linear, non-linear, and neural network models were established. An additional data set, not incorporated in model training, was used to validate the models. A number of models showed excellent performance with R² in the range of 0.89–0.98. In model validation studies, the correlation coefficients (r) ranged from 0.94 to 0.99. The novel adsorbent and models will most likely aid in the development of a robust treatment technique for removing Pb²⁺ ions from water and wastewater.