Laustenskov4312

The endless introduction of toxic heavy metals through industrialization has worsened the heavy metal pollution in the environment. find more Thus, the need for its effective removal has become more crucial than before. Studies on graphene-based nanomaterials and their use in removing heavy metals are gaining tremendous traction over the past decade. The properties of graphene oxide (GO), such as large surface areas, desired functional groups and excellent mechanical properties are advantageous. Nevertheless, due to its tendency to agglomerate and difficulty in phase separation after treatment, the functionalization of GO using various materials of different surface functional groups is an ongoing study. The surface modification of GO is done by using various materials to introduce heteroatoms, which have high affinity for heavy metals. This review summarizes the utilization of different surface functional groups, such as oxygen-containing, nitrogen-containing, and sulphur-containing functionalized graphene oxide composites in the adsorption of cationic and oxyanionic heavy metals. The toxicity of these heavy metals is also addressed. Furthermore, the interactions between adsorbents and heavy metals which are influenced by pH and surface functional groups, are also discussed in detail. This is followed by the review in adsorption isotherms and kinetics. Future research needs are also offered. Lead (Pb) affects the growth and productivity of rice negatively through soil-Pb-plant interactions. A pot experiment was conducted to assess the Pb uptake and its distributive pattern in different fragrant rice cultivars i.e., Meixiangzhan-2 (MXZ-2), Xiangyaxiangzhan (XYXZ), Guixiangzhan (GXZ), Basmati-385 (B-385), and Nongxiang-18 (NX-18) and relationship of Pb uptake with grain Pb-contents and rice yield and related traits i.e., productive tillers hill-1, spikelets panicle-1, filled grain percentage, and 1000-grain weight. Lead as Pb(NO3)2 was applied at 0 (control), 400 (Pb1), 800 (Pb2) and 1200 mg kg-1 (Pb3) of soil in solution form. Results showed that all rice cultivars accumulated different concentration of Pb, with the highest in roots and the lowest in grains. The translocation factors (TF) from stems to leaves were higher than root to stems and leaves to ears/grains. The grain Pb contents have significant positive associations with ear Pb contents and TF of Pb from leaves to ear at reproductive stage. Moreover, relative changes (RC) in grain yields have significant correlations with the RC in some yield attributes i.e., productive tillers per hill, spikelets per panicle, and filled grain percentage under Pb toxicity. Overall, grain Pb contents are affected mainly by the transference of leaves Pb contents to ears/grains (an index to determine final grain Pb contents) whereas RC in rice yields suggested its relationships with some agronomic attributes of fragrant rice under Pb stress. Control of risks caused by disinfection by-products (DBPs) requires pre-knowledge of their levels in drinking water. In this study, a radial basis function (RBF) artificial neural network (ANN) was proposed to predict the concentrations of haloacetic acids (HAAs, one dominant class of DBPs) in actual distribution systems. To train and verify the RBF ANN, a total of 64 samples taken from a typical region (Jinhua region) in China were characterized in terms of water characteristics (dissolved organic carbon (DOC), ultraviolet absorbance at 254 nm (UVA254), NO2--N level, NH4+-N level, Br- and pH), temperature and the prevalent HAAs concentrations. Compared with multiple linear/log linear regression (MLR) models, predictions done by RBF ANNs showed rather higher regression coefficients and accuracies, indicating the high capability of RBF ANNs to depict complicated and non-linear relationships between HAAs formation and various factors. Meanwhile, it was found that, predictions of HAAs formation done by RBF ANNs were efficient and allowed to further improve the prediction accuracy. This is the first study to systematically explore feasibility of RBF ANNs in prediction of DBPs. Accurate predictions by RBF ANNs provided great potential application of DBPs monitoring in actual distribution system. Malachite green is an N-methylated diaminophenylmethane dye that has generated much concern over its suggestive carcinogenic nature. After its excessive use in aquaculture industry as an effective ectoparasitide, much debate was raised over its toxicological effects leading to scientific studies conducted on animal models. Even after several bans, malachite green is still easily available in many parts of the world and unscrupulously even used to give green vegetables a fresher look. This study aims to address this concern by systematically studying the toxicological effects of malachite green through bioimaging in plant and animal cell and tissue. Sandalwood-derived carbon quantum dots have been used as a bioimaging tool since they are non-cytotoxic and show excellent fluorescence properties. Onion tissues demonstrate the translocation of the dye inside cells having high affinity for the nuclei and cell walls. Toxicological effects on the growth of Vigna radiata (mung beans) have been studied methodically. Bioimaging of the transverse cross-section of the dye-treated plant root shows a significant difference from the control. In animal cells, dose-dependent decrease in cell viability of MG-63 cells was observed with MG. CQD showed good fluorescence in both cytoplasm and nucleus of MG63 cells. In addition, CQDs were employed as a great tool for bioimaging of the histopathologically adverse effects of MG in Golden hamster animal model. This study showed CQDs could be used as an alternative non-site specific fluorescent probe for cell and tissue imaging for better visualization of cell and tissue architectural changes. Natural colloids can influence the binding mechanisms between nano-hydroxyapatite (nHAP) and Cd(II). In this study, the effects of organic and inorganic natural colloids on Cd(II) sorption onto nHAP were compared. Different experimental approaches combined with the additivity model and the Extended-Derjaguin-Landau-Verwey-Overbeek model were used to quantify the distribution of Cd(II) in the systems of nHAP and natural colloid, and the interaction energy between particles. The results showed that both fulvic acid (FA) and montmorillonite colloid (MONT) had the promotion and inhibition effects on Cd(II) sorption onto nHAP. Coexistence of FA or MONT could stabilize nHAP particles. FA could adsorb onto nHAP particle surface via carboxylic and phenolic groups, which increased nHAP electronegativity and formed steric resistance effect. Coexistence of MONT mainly increased nHAP electronegativity. These effects prevented the reduction of the specific surface area of nHAP particles and increased the Cd(II) sorption onto nHAP.