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14 pages, 2602 KiB  
Article
Roles of Mature Domain Targeting Signals (MTSs) for Protein Translocation and Secretion in Lactococcus lactis
by Mai Ngoc Hoang and Clemens Peterbauer
Int. J. Mol. Sci. 2025, 26(1), 219; https://doi.org/10.3390/ijms26010219 - 30 Dec 2024
Viewed by 527
Abstract
Lactococcus lactis is a potential bacterial cell factory to develop delivery systems for vaccines and therapeutic proteins. Much progress has been made in applications using engineered L. lactis against, e.g., inflammatory bowel disease and cervical cancer, but the improvement of secretion and cell [...] Read more.
Lactococcus lactis is a potential bacterial cell factory to develop delivery systems for vaccines and therapeutic proteins. Much progress has been made in applications using engineered L. lactis against, e.g., inflammatory bowel disease and cervical cancer, but the improvement of secretion and cell anchoring efficacy is still desirable. A double-labeling method based on biarsenical hairpin binding and nickel–polyhistidine affinity was used for visualization of protein trafficking and the quantification of targeted proteins on the cell surface and in the cytoplasm. To investigate the importance of mature domain targeting signals (MTSs), we generated truncated constructs encoding 126, 66, and 26 amino acid residues from the N-terminus of the basic membrane protein A (BmpA) and fused those with the gene for the human papillomavirus serotype 16 (HPV16) E7 oncoprotein. Overexpression of fusion proteins was observed to come at the cost of cell proliferation. L. lactis cells produced and displayed the shortest fusion protein only with difficulty, suggesting that the entire absence of a homologous sequence containing MTSs significantly impedes the export and surface anchoring of fusion proteins. With 40 amino acids following the signal peptide and containing one MTS, effective translocation was possible. Mutations of MTSs towards increased hydrophobicity resulted in increased secreted and surface-displayed fusion protein, suggesting the potential to design rationally improved constructs. Full article
(This article belongs to the Section Molecular Microbiology)
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Figure 1

Figure 1
<p>Growth profile of <span class="html-italic">L. lactis</span> carrying homologous proteins and fusion proteins. Optical density (OD) at 600 nm wavelength was measured after 3-, 9- and 24-h post-induction.</p>
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<p>Quantitative comparison on surface and intracellular fluorescence expression of <span class="html-italic">L. lactis</span> carrying homologous and fusion proteins over three time points (3, 9, 24 h post induction). Color of columns: blue—3 h, orange—9 h, gray—24 h. (<b>a</b>) Surface fluorescence, y-axis: corrected fluorescence intensity of Ni-NTA-Atto 488 (His-tag); (<b>b</b>) intracellular fluorescence, y-axis: corrected average cell fluorescence of ReAsH (Tetra-cysteine tag).</p>
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<p>Hydropathy plot of BmpA and fusion proteins. (<b>a</b>) BmpA conjugated C-terminally with hexa-histidine and tetra-cysteine tags, 366 amino acids in length. (<b>b</b>) BE1, BE2, and BE3 (126, 66, and 26 amino acids at the N-terminus of BmpA fused with HPV16 E7 and C-terminally tagged with hexa-histidine and tetra-cysteine), window size = 5. Red line: threshold +1.6. Graph was created by ProtScale Expasy.</p>
Full article ">Figure 4
<p>Site-directed designation for mutations. (<b>a</b>) Sequence map of BE1 fusion construct. Hydrophobic patches (signal peptide—H1, H2, H3, H4) were identified by Kyte–Doolittle hydropathy evaluation and annotated accordingly. (<b>b</b>) List of mutations created using site-directed mutagenesis.</p>
Full article ">Figure 5
<p>Quantitative comparison on surface and intracellular fluorescence protein expression of alanine variants at 3, 9, and 24 h are included. (<b>a</b>) Quantitative comparison of surface expression and (<b>b</b>) quantitative comparison of intracellular expression: blue bar—three hours; orange bar—nine hours; light gray bar—24 h.</p>
Full article ">Figure 6
<p>Maps of plasmid constructs. (<b>a</b>) pNZ8150 with the gene for the membrane-anchored protein BmpA. (<b>b</b>) pNZ8150 with the sequence encoding the first 126 N-terminal amino acids of BmpA fused with the gene for the heterologous oncoprotein E7 from HPV-16. (<b>c</b>, <b>d</b>) Truncated constructs of the insert from the plasmid in b, containing the first 66 N-terminal amino acids of BmpA, or only the first 26 amino acids (the signal peptide) of BmpA, and E7.</p>
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21 pages, 797 KiB  
Review
Association Between Serum Concentrations of (Certain) Metals and Type 2 Diabetes Mellitus
by Magdalena Tyczyńska, Gabriela Hunek, Weronika Kawecka, Adam Brachet, Marta Gędek, Kinga Kulczycka, Katarzyna Czarnek, Jolanta Flieger and Jacek Baj
J. Clin. Med. 2024, 13(23), 7443; https://doi.org/10.3390/jcm13237443 - 6 Dec 2024
Viewed by 908
Abstract
The findings regarding trace element concentrations in patients diagnosed with type 2 diabetes and healthy controls are inconsistent, and therefore, we determined to gather them in the form of a review to further indicate the need for more advanced knowledge development. In our [...] Read more.
The findings regarding trace element concentrations in patients diagnosed with type 2 diabetes and healthy controls are inconsistent, and therefore, we determined to gather them in the form of a review to further indicate the need for more advanced knowledge development. In our study, we reviewed articles and studies that involved the topics of micronutrient and metal associations with the occurrence and development of type 2 diabetes. We mainly included works regarding human-based studies, but with limited research results, animal-based research was also taken into account. With some newer studies, we reached for initial assumptions of previous statements. The results indicated that higher serum levels of lead, cadmium, arsenic, bromine, barium, strontium, nickel, aluminum, calcium, copper, and ferritin are positively associated with diabetic prevalence. Both too-low and too-high levels of zinc, selenium, and magnesium may be connected to the development of diabetes. Chromium has the capability of insulin response modulation, with enhanced insulin-cell binding, and thus, lower serum levels of chromium can be found in diabetic patients. There are contradictory discoveries regarding manganese. Its supplementation can possibly cease the development of insulin resistance and type 2 diabetes. On the contrary, other studies reported that there is no such connection. Our work indicates that, as micronutrients play a significant role in the pathogenesis of metabolic disorders, more research regarding their bodily homeostasis and type 2 diabetes should be conducted. Full article
(This article belongs to the Special Issue Type 2 Diabetes and Complications: From Diagnosis to Treatment)
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<p>The description of known associations between the pathogenesis of metabolic disturbance in type 2 diabetes mellitus and selected metals, with the inclusion of the most affected organs and metabolic values.</p>
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15 pages, 6312 KiB  
Article
Environmentally Friendly Nanoporous Polymeric Gels for Sustainable Wastewater Treatment
by Tarek M. Madkour, Rasha E. Elsayed and Rasha A. Azzam
Gels 2024, 10(12), 756; https://doi.org/10.3390/gels10120756 - 22 Nov 2024
Viewed by 563
Abstract
Environmentally friendly nanoporous gels are tailor-designed and employed in the adsorption of toxic organic pollutants in wastewater. To ensure the maximum adsorption of the contaminant molecules by the gels, molecular modeling techniques were used to evaluate the binding affinity between the toxic organic [...] Read more.
Environmentally friendly nanoporous gels are tailor-designed and employed in the adsorption of toxic organic pollutants in wastewater. To ensure the maximum adsorption of the contaminant molecules by the gels, molecular modeling techniques were used to evaluate the binding affinity between the toxic organic contaminants such as methylene blue (MB) and Congo red (CR) and various biopolymers. To generate nanopores in the matrix of the polymeric gels, salt crystals were used as porogen. The pores were then used to accommodate catalytic nickel (Ni0) nanoparticles. Under UV irradiation, the nanoparticles demonstrated the effective adsorption and photocatalytic degradation of both the methylene blue and Congo red dyes, achieving removal efficiencies of up to 90% for MB and 80% for CR. The thermodynamic analysis suggested a spontaneous endothermic dissociative adsorption mechanism, which implies the oxidative catalytic degradation of the dyes. The kinetic modeling suggested a pseudo-second-order model, while the model for intra-particle diffusion revealed that Congo red diffuses faster than methylene blue. MB adsorption followed a Langmuir isotherm, while CR adsorption followed a linear isotherm. The results confirm that dye molecules initially undergo physisorption and subsequent dissociative adsorption. The products of the catalytic degradation of methylene blue continue to be absorbed on the surface of the nanoparticles, while those of Congo red switch to preferential desorption. Full article
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Graphical abstract

Graphical abstract
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<p>Snapshots of the molecular simulations of (<b>a</b>) the polymer blend mixed with MB dye molecules and (<b>b</b>) the polymer blend mixed with CR dye molecules. Each cell has a triclinic lattice with a side length of 19.7064 Å and an angle of 90°.</p>
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<p>Enthalpy of mixing MB (<b>a</b>) and CR (<b>b</b>) with the different polymeric blends at different dye mole fractions.</p>
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<p>(<b>a</b>) SEM image for the unloaded gel, (<b>b</b>) SEM image for the Ni-loaded gel, (<b>c</b>) TGA for the unloaded gel, and (<b>d</b>) TGA for the Ni-loaded gel.</p>
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<p>BET isotherms of the unloaded gel (<b>a</b>) and the Ni<sup>0</sup>-loaded gel (<b>b</b>).</p>
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<p>The uptake capacity and percent removal of methylene blue and Congo red at equilibrium at various initial concentrations of the dye solutions (<b>a</b>), used dose of the adsorbent (<b>b</b>), and operating temperature (<b>c</b>).</p>
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<p>Plots of van’t Hoff (<b>a</b>) and equilibrium isotherms (<b>b</b>) for MB and CR adsorption.</p>
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<p>The kinetic plots of the removal of methylene blue and Congo red dyes (<b>a</b>), linear isotherms estimated using the pseudo-first-order model (<b>b</b>), linear isotherms estimated using the pseudo-second-order model (<b>c</b>), and linear isotherms estimated using the intra-particle diffusion model (<b>d</b>).</p>
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<p>Schematic diagram for the preparation of in situ impregnated polymeric gels.</p>
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24 pages, 8710 KiB  
Article
Structural, Antioxidant, and Protein/DNA-Binding Properties of Sulfate-Coordinated Ni(II) Complex with Pyridoxal-Semicarbazone (PLSC) Ligand
by Violeta Jevtovic, Luka Golubović, Odeh A. O. Alshammari, Munirah Sulaiman Alhar, Tahani Y. A. Alanazi, Aleksandra Radulović, Đura Nakarada, Jasmina Dimitrić Marković, Aleksandra Rakić and Dušan Dimić
Inorganics 2024, 12(11), 280; https://doi.org/10.3390/inorganics12110280 - 30 Oct 2024
Cited by 1 | Viewed by 762
Abstract
The pyridoxal-semicarbazone (PLSC) ligand and its transition metal complexes have shown significant biological activity. In this contribution, a novel nickel(II)-PLSC complex, [Ni(PLSC)(SO4)(H2O)2], was obtained, and its structure was determined by X-ray crystallographic analysis, FTIR, and UV-VIS spectroscopy. [...] Read more.
The pyridoxal-semicarbazone (PLSC) ligand and its transition metal complexes have shown significant biological activity. In this contribution, a novel nickel(II)-PLSC complex, [Ni(PLSC)(SO4)(H2O)2], was obtained, and its structure was determined by X-ray crystallographic analysis, FTIR, and UV-VIS spectroscopy. The sulfate ion is directly coordinated to the central metal ion. The intermolecular stabilization interactions were examined using Hirshfeld surface analysis. The crystal structure was optimized by a B3LYP functional using two pseudopotentials for nickel(II) (LanL2DZ and def2-TZVP) together with a 6-311++G(d,p) basis set for non-metallic atoms. The experimental and theoretical bond lengths and angles were compared, and the appropriate level of theory was determined. The stabilization interactions within the coordination sphere were investigated by the Quantum Theory of Atoms in Molecules (QTAIM). The antioxidant activity towards hydroxyl and ascorbyl radicals was measured by EPR spectroscopy. The interactions between Human Serum Albumin (HSA) and the complex were examined by spectrofluorimetric titration and a molecular docking study. The mechanism of binding to DNA was analyzed by complex fluorescence quenching, potassium iodide quenching, and ethidium bromide displacement studies in conjunction with molecular docking simulations. Full article
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<p>Different binding modes of PLSC ligand.</p>
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<p>(<b>a</b>) Molecular diagram of [Ni(PLSC)(SO<sub>4</sub>)(H<sub>2</sub>O)<sub>2</sub>], with non-hydrogen atoms represented by 50% displacement ellipsoids and hydrogen atoms as spheres of arbitrary size. (<b>b</b>) The ball and stick representation shows part of the hydrogen bonding between the molecules. (Hydrogen-white, carbon-gray, nitrogen-blue, oxygen-red, sulfur-lilac, nickel-light blue).</p>
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<p>Cell packing is viewed down the b-axis, and the 3D hydrogen-bonded network is shown as comprising parallel layers of the Ni(PLSC) structural units.</p>
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<p>(<b>a</b>) Hirshfeld surface and (<b>b</b>) optimized structure (hydrogen atoms are omitted for clarity) at the B3LYP/6-311++G(d,p)(H,C,N,O,S)/LanL2DZ(Ni) level of theory of [Ni(PLSC)(SO<sub>4</sub>)(H<sub>2</sub>O)<sub>2</sub>]. (Hydrogen—white, carbon—gray, nitrogen—blue, oxygen—red, sulfur—yellow, nickel—light blue).</p>
Full article ">Figure 5
<p>The EPR spectra of the (<b>a</b>) DEPMPO-HO<sup>•</sup> adduct and (<b>b</b>) ascorbyl radical in the absence (black line) and presence of different concentrations of [Ni(PLSC)(SO<sub>4</sub>)(H<sub>2</sub>O)<sub>2</sub>].</p>
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<p>The fluorescence emission spectra of HSA for the titration with various concentrations of [Ni(PLSC)(SO<sub>4</sub>)(H<sub>2</sub>O)<sub>2</sub>] at (<b>a</b>) 27°, (<b>b</b>) 32°, and (<b>c</b>) 37 °C, and (<b>d</b>) the van ’t Hoff plot for the binding process.</p>
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<p>HSA molecule (PDB ID: 1AO6) with bound ligands: [Ni(PLSC)(H<sub>2</sub>O)<sub>2</sub>(SO<sub>4</sub>)] complex and HPO<sub>4</sub><sup>2−</sup> anion, occupying FA9 and FA8 binding sites, respectively. Ligands and tryptophane are depicted using ball representation; each is colored distinctly. HPO<sub>4</sub><sup>2−</sup> ion from buffer solution is colored by element, Ni(II) complex is shown in light green, and Trp213 is represented in dark grey.</p>
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<p>A 3D representation of the supramolecular interactions of [Ni(PLSC)(H<sub>2</sub>O)<sub>2</sub>(SO<sub>4</sub>)] located in the FA8 binding site. Only the interacting parts of the amino acids are shown, with colors corresponding to their respective regions of the HSA molecule: yellow for subdomain IB, green for subdomain IIA, interdomain region between subdomains IIA and IIB is light grey, and subdomain IA is violet. For the representation of nickel(II), complex sticks colored by the element were used. Supramolecular interactions are represented by dashed lines colored according to the type of interaction denoted in the figure’s legend.</p>
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<p>Fluorescence emission spectra of [Ni(PLSC)(H<sub>2</sub>O)<sub>2</sub>(SO<sub>4</sub>)] for the titration with various concentrations of CT-DNA at (<b>a</b>) 27°, (<b>b</b>) 32°, and (<b>c</b>) 37 °C, and (<b>d</b>) the van ’t Hoff plot for the binding process.</p>
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<p>Fluorescence emission spectra of [Ni(PLSC)(H<sub>2</sub>O)<sub>2</sub>(SO<sub>4</sub>)] without CT-DNA (<b>a</b>) and with CT-DNA (<b>b</b>) in the presence of different concentrations of KI, and (<b>c</b>) the Stern–Volmer plots for the complex fluorescence quenching by KI.</p>
Full article ">Figure 11
<p>(<b>a</b>) Fluorescence emission spectra of CT-DNA-EB for the titration with the complex at 27 °C and (<b>b</b>) the double-log Stern–Volmer dependency of intensity on the concentration of [Ni(PLSC)(H<sub>2</sub>O)<sub>2</sub>(SO<sub>4</sub>)].</p>
Full article ">Figure 12
<p>Binding of square planar Ni(II) complex with PLSC ligand at two distinct sites: intercalation site (depicted in dark green, ball-and-stick representation) and minor groove (shown in pink, ball-and-stick representation). DNA molecule is colored yellow. Experimentally determined binding energy (ΔG<sub>exp</sub>), best-calculated binding energy (ΔG1), and fifth calculated binding energy value (ΔG<sub>5</sub>) are also indicated.</p>
Full article ">Figure 13
<p>The supramolecular interactions of the square planar Ni(II) complex in (<b>a</b>) the intercalation site and (<b>b</b>) the major groove. Only the interacting parts of the nucleobases are shown colored in yellow. For the representation of the square planar Ni(II) complex, sticks colored by element were used. Supramolecular interactions are represented by dashed lines colored according to the type of interaction denoted in the figure’s legend. The experimentally determined binding energy (ΔG<sub>exp</sub>) and the calculated binding energy values are also indicated.</p>
Full article ">
38 pages, 16780 KiB  
Review
An Evaluation of Metal Binding Constants to Cell Surface Receptors in Freshwater Organisms, and Their Application in Biotic Ligand Models to Predict Metal Toxicity
by Paul L. Brown and Scott J. Markich
Water 2024, 16(20), 2999; https://doi.org/10.3390/w16202999 - 21 Oct 2024
Viewed by 998
Abstract
Biotic ligand models (BLMs) predict the toxicity of metals in aquatic environments by accounting for metal interactions with cell surface receptors (biotic ligands) in organisms, including water chemistry (metal speciation) and competing cations. Metal binding constants (log KMBL values), which indicate the [...] Read more.
Biotic ligand models (BLMs) predict the toxicity of metals in aquatic environments by accounting for metal interactions with cell surface receptors (biotic ligands) in organisms, including water chemistry (metal speciation) and competing cations. Metal binding constants (log KMBL values), which indicate the affinity of metals for cell surface receptors, are fundamental to BLMs, but have only been reported for a few commonly investigated metals and freshwater species. This review evaluated literature toxicity and uptake data for seven key metals (cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), lead (Pb), uranium (U), and zinc (Zn)) and four key competing cations (protons (H), calcium (Ca), magnesium (Mg), and sodium (Na)), to derive average metal binding constants for freshwater organisms/taxa. These constants will improve current BLMs for Cd, Cu, Ni, Pb, and Zn, and aid in developing new BLMs for Co and U. The derived metal binding constants accurately predicted metal toxicity for a wide range of freshwater organisms (75–88% of data were within a factor of two and 88–98% of data were within a factor of three of the ideal 1:1 agreement line), when considering metal speciation, competing cations and the fraction of cell receptors ((fC)M50%) occupied by the metal at the median (50%) effect concentration (EC50). For many organisms, toxicity occurs when 50% of cell surface receptors are occupied by the metal, though this threshold can vary. Some organisms exhibit toxicity with less than 50% receptor occupancy, while others with protective mechanisms show reduced toxicity, even with similar log KMBL values. For Cu, U, and Pb, the toxic effect of the metal hydroxide (as MOH+) must be considered in addition to the free metal ion (M2+), as these metals hydrolyse in circumneutral freshwaters (pH 5.5 to 8.5), contributing to toxicity. Full article
(This article belongs to the Special Issue Ecotoxicity of Pollutants on Aquatic Species)
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Figure 1
<p>A schematic overview of the biotic ligand model (BLM) for divalent metals, demonstrating the binding of the free metal ion (M<sup>2+</sup>) and metal hydroxide (MOH<sup>+</sup>) to receptors (transporters) on the cell membrane surface of aquatic organisms. These metal ions may enter the cell, potentially inducing toxicity. The metal binding constant (log <span class="html-italic">K</span><sub>MBL</sub>) represents the binding affinity of metals with cell surface receptors. The M<sup>2+</sup> and MOH<sup>+</sup> attached to purple spheres represent extracellular (or surface-bound) metal (not taken up by cells), typically removed by chemical extraction prior to measuring intracellular (internal) metal. The key cations (H<sup>+</sup>, Ca<sup>2+</sup>, Mg<sup>2+</sup>, and Na<sup>+</sup>) that may ameliorate the binding of M<sup>2+</sup> and MOH<sup>+</sup> at the cell surface receptor are also shown.</p>
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<p>An illustration of the “cascade of effects” leading to metal toxicity in aquatic organisms. Each stage of the cascade highlights the appearance of the terms {M–X–cell} (metal bound to a receptor site on the cell surface), [M] (free metal ion) and (<span class="html-italic">f<sub>C</sub></span>)<sub>M</sub><sup>50%</sup> (the fraction of receptor sites bound by a metal at its median toxic effect concentration (TR<sub>50</sub>)), in both the numerator and denominator on the right-hand side of the equation.</p>
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<p>The predictive capacity of the biotic ligand model for (<b>a</b>) zinc (Zn) with seven freshwater species (13 studies) and 142 water quality scenarios (all values expressed as dissolved Zn in mg/L), (<b>b</b>) nickel (Ni) with ten freshwater species (14 studies) and 256 water quality scenarios (all values expressed as dissolved Ni in mg/L), (<b>c</b>) cadmium (Cd) with six freshwater species (seven studies) and 83 water quality scenarios (all values expressed as dissolved Cd in mg/L) and (<b>d</b>) cobalt (Co) with nine freshwater species (four studies) and 12 water quality scenarios (all values expressed as dissolved Co in mg/L). The solid lines indicate ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Nys et al. (2016) [<a href="#B40-water-16-02999" class="html-bibr">40</a>], Keithly et al. (2004) [<a href="#B42-water-16-02999" class="html-bibr">42</a>], Kozlova et al. (2009) [<a href="#B44-water-16-02999" class="html-bibr">44</a>], Clifford and McGeer (2010) [<a href="#B45-water-16-02999" class="html-bibr">45</a>], Stubblefield et al. (2020) [<a href="#B47-water-16-02999" class="html-bibr">47</a>], Bringolf et al. (2006) [<a href="#B54-water-16-02999" class="html-bibr">54</a>], De Schamphelaere and Janssen (2004) [<a href="#B55-water-16-02999" class="html-bibr">55</a>], De Schamphelaere and Janssen (2004) [<a href="#B56-water-16-02999" class="html-bibr">56</a>], Heijerick et al. (2005) [<a href="#B57-water-16-02999" class="html-bibr">57</a>], Cooper et al. (2009) [<a href="#B58-water-16-02999" class="html-bibr">58</a>], Van Regenmortal et al. (2017) [<a href="#B59-water-16-02999" class="html-bibr">59</a>], Clifford and McGeer (2009) [<a href="#B60-water-16-02999" class="html-bibr">60</a>], Heijerick et al. (2002) [<a href="#B61-water-16-02999" class="html-bibr">61</a>], Hyne et al. (2005) [<a href="#B62-water-16-02999" class="html-bibr">62</a>], Paulauskis and Winner (1988) [<a href="#B63-water-16-02999" class="html-bibr">63</a>], Cusimano et al. (1986) [<a href="#B64-water-16-02999" class="html-bibr">64</a>], Stauber et al. (2023) [<a href="#B65-water-16-02999" class="html-bibr">65</a>], Deleebeek et al. (2008) [<a href="#B66-water-16-02999" class="html-bibr">66</a>], Schlekat et al. (2010) [<a href="#B67-water-16-02999" class="html-bibr">67</a>], Deleebeek et al. (2009) [<a href="#B68-water-16-02999" class="html-bibr">68</a>], Deleebeek et al. (2007) [<a href="#B69-water-16-02999" class="html-bibr">69</a>], Mano and Shinohara (2020) [<a href="#B70-water-16-02999" class="html-bibr">70</a>], Meyer et al. (1999) [<a href="#B71-water-16-02999" class="html-bibr">71</a>], Schroeder (2008) [<a href="#B72-water-16-02999" class="html-bibr">72</a>], Nys et al. (2016) [<a href="#B73-water-16-02999" class="html-bibr">73</a>], Hoang et al. (2004) [<a href="#B74-water-16-02999" class="html-bibr">74</a>], He et al. (2023) [<a href="#B75-water-16-02999" class="html-bibr">75</a>], Chan (2013) [<a href="#B76-water-16-02999" class="html-bibr">76</a>], Niyogi et al. (2008) [<a href="#B77-water-16-02999" class="html-bibr">77</a>], Tan and Wang (2011) [<a href="#B78-water-16-02999" class="html-bibr">78</a>], Kallqvist (2009) [<a href="#B79-water-16-02999" class="html-bibr">79</a>], Clifford (2009) [<a href="#B80-water-16-02999" class="html-bibr">80</a>], Jackson et al. (2000) [<a href="#B81-water-16-02999" class="html-bibr">81</a>], Marr et al. (1998) [<a href="#B82-water-16-02999" class="html-bibr">82</a>], dos Reis et al. (2024) [<a href="#B83-water-16-02999" class="html-bibr">83</a>] and Alsop and Wood (2000) [<a href="#B84-water-16-02999" class="html-bibr">84</a>].</p>
Full article ">Figure 3 Cont.
<p>The predictive capacity of the biotic ligand model for (<b>a</b>) zinc (Zn) with seven freshwater species (13 studies) and 142 water quality scenarios (all values expressed as dissolved Zn in mg/L), (<b>b</b>) nickel (Ni) with ten freshwater species (14 studies) and 256 water quality scenarios (all values expressed as dissolved Ni in mg/L), (<b>c</b>) cadmium (Cd) with six freshwater species (seven studies) and 83 water quality scenarios (all values expressed as dissolved Cd in mg/L) and (<b>d</b>) cobalt (Co) with nine freshwater species (four studies) and 12 water quality scenarios (all values expressed as dissolved Co in mg/L). The solid lines indicate ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Nys et al. (2016) [<a href="#B40-water-16-02999" class="html-bibr">40</a>], Keithly et al. (2004) [<a href="#B42-water-16-02999" class="html-bibr">42</a>], Kozlova et al. (2009) [<a href="#B44-water-16-02999" class="html-bibr">44</a>], Clifford and McGeer (2010) [<a href="#B45-water-16-02999" class="html-bibr">45</a>], Stubblefield et al. (2020) [<a href="#B47-water-16-02999" class="html-bibr">47</a>], Bringolf et al. (2006) [<a href="#B54-water-16-02999" class="html-bibr">54</a>], De Schamphelaere and Janssen (2004) [<a href="#B55-water-16-02999" class="html-bibr">55</a>], De Schamphelaere and Janssen (2004) [<a href="#B56-water-16-02999" class="html-bibr">56</a>], Heijerick et al. (2005) [<a href="#B57-water-16-02999" class="html-bibr">57</a>], Cooper et al. (2009) [<a href="#B58-water-16-02999" class="html-bibr">58</a>], Van Regenmortal et al. (2017) [<a href="#B59-water-16-02999" class="html-bibr">59</a>], Clifford and McGeer (2009) [<a href="#B60-water-16-02999" class="html-bibr">60</a>], Heijerick et al. (2002) [<a href="#B61-water-16-02999" class="html-bibr">61</a>], Hyne et al. (2005) [<a href="#B62-water-16-02999" class="html-bibr">62</a>], Paulauskis and Winner (1988) [<a href="#B63-water-16-02999" class="html-bibr">63</a>], Cusimano et al. (1986) [<a href="#B64-water-16-02999" class="html-bibr">64</a>], Stauber et al. (2023) [<a href="#B65-water-16-02999" class="html-bibr">65</a>], Deleebeek et al. (2008) [<a href="#B66-water-16-02999" class="html-bibr">66</a>], Schlekat et al. (2010) [<a href="#B67-water-16-02999" class="html-bibr">67</a>], Deleebeek et al. (2009) [<a href="#B68-water-16-02999" class="html-bibr">68</a>], Deleebeek et al. (2007) [<a href="#B69-water-16-02999" class="html-bibr">69</a>], Mano and Shinohara (2020) [<a href="#B70-water-16-02999" class="html-bibr">70</a>], Meyer et al. (1999) [<a href="#B71-water-16-02999" class="html-bibr">71</a>], Schroeder (2008) [<a href="#B72-water-16-02999" class="html-bibr">72</a>], Nys et al. (2016) [<a href="#B73-water-16-02999" class="html-bibr">73</a>], Hoang et al. (2004) [<a href="#B74-water-16-02999" class="html-bibr">74</a>], He et al. (2023) [<a href="#B75-water-16-02999" class="html-bibr">75</a>], Chan (2013) [<a href="#B76-water-16-02999" class="html-bibr">76</a>], Niyogi et al. (2008) [<a href="#B77-water-16-02999" class="html-bibr">77</a>], Tan and Wang (2011) [<a href="#B78-water-16-02999" class="html-bibr">78</a>], Kallqvist (2009) [<a href="#B79-water-16-02999" class="html-bibr">79</a>], Clifford (2009) [<a href="#B80-water-16-02999" class="html-bibr">80</a>], Jackson et al. (2000) [<a href="#B81-water-16-02999" class="html-bibr">81</a>], Marr et al. (1998) [<a href="#B82-water-16-02999" class="html-bibr">82</a>], dos Reis et al. (2024) [<a href="#B83-water-16-02999" class="html-bibr">83</a>] and Alsop and Wood (2000) [<a href="#B84-water-16-02999" class="html-bibr">84</a>].</p>
Full article ">Figure 3 Cont.
<p>The predictive capacity of the biotic ligand model for (<b>a</b>) zinc (Zn) with seven freshwater species (13 studies) and 142 water quality scenarios (all values expressed as dissolved Zn in mg/L), (<b>b</b>) nickel (Ni) with ten freshwater species (14 studies) and 256 water quality scenarios (all values expressed as dissolved Ni in mg/L), (<b>c</b>) cadmium (Cd) with six freshwater species (seven studies) and 83 water quality scenarios (all values expressed as dissolved Cd in mg/L) and (<b>d</b>) cobalt (Co) with nine freshwater species (four studies) and 12 water quality scenarios (all values expressed as dissolved Co in mg/L). The solid lines indicate ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Nys et al. (2016) [<a href="#B40-water-16-02999" class="html-bibr">40</a>], Keithly et al. (2004) [<a href="#B42-water-16-02999" class="html-bibr">42</a>], Kozlova et al. (2009) [<a href="#B44-water-16-02999" class="html-bibr">44</a>], Clifford and McGeer (2010) [<a href="#B45-water-16-02999" class="html-bibr">45</a>], Stubblefield et al. (2020) [<a href="#B47-water-16-02999" class="html-bibr">47</a>], Bringolf et al. (2006) [<a href="#B54-water-16-02999" class="html-bibr">54</a>], De Schamphelaere and Janssen (2004) [<a href="#B55-water-16-02999" class="html-bibr">55</a>], De Schamphelaere and Janssen (2004) [<a href="#B56-water-16-02999" class="html-bibr">56</a>], Heijerick et al. (2005) [<a href="#B57-water-16-02999" class="html-bibr">57</a>], Cooper et al. (2009) [<a href="#B58-water-16-02999" class="html-bibr">58</a>], Van Regenmortal et al. (2017) [<a href="#B59-water-16-02999" class="html-bibr">59</a>], Clifford and McGeer (2009) [<a href="#B60-water-16-02999" class="html-bibr">60</a>], Heijerick et al. (2002) [<a href="#B61-water-16-02999" class="html-bibr">61</a>], Hyne et al. (2005) [<a href="#B62-water-16-02999" class="html-bibr">62</a>], Paulauskis and Winner (1988) [<a href="#B63-water-16-02999" class="html-bibr">63</a>], Cusimano et al. (1986) [<a href="#B64-water-16-02999" class="html-bibr">64</a>], Stauber et al. (2023) [<a href="#B65-water-16-02999" class="html-bibr">65</a>], Deleebeek et al. (2008) [<a href="#B66-water-16-02999" class="html-bibr">66</a>], Schlekat et al. (2010) [<a href="#B67-water-16-02999" class="html-bibr">67</a>], Deleebeek et al. (2009) [<a href="#B68-water-16-02999" class="html-bibr">68</a>], Deleebeek et al. (2007) [<a href="#B69-water-16-02999" class="html-bibr">69</a>], Mano and Shinohara (2020) [<a href="#B70-water-16-02999" class="html-bibr">70</a>], Meyer et al. (1999) [<a href="#B71-water-16-02999" class="html-bibr">71</a>], Schroeder (2008) [<a href="#B72-water-16-02999" class="html-bibr">72</a>], Nys et al. (2016) [<a href="#B73-water-16-02999" class="html-bibr">73</a>], Hoang et al. (2004) [<a href="#B74-water-16-02999" class="html-bibr">74</a>], He et al. (2023) [<a href="#B75-water-16-02999" class="html-bibr">75</a>], Chan (2013) [<a href="#B76-water-16-02999" class="html-bibr">76</a>], Niyogi et al. (2008) [<a href="#B77-water-16-02999" class="html-bibr">77</a>], Tan and Wang (2011) [<a href="#B78-water-16-02999" class="html-bibr">78</a>], Kallqvist (2009) [<a href="#B79-water-16-02999" class="html-bibr">79</a>], Clifford (2009) [<a href="#B80-water-16-02999" class="html-bibr">80</a>], Jackson et al. (2000) [<a href="#B81-water-16-02999" class="html-bibr">81</a>], Marr et al. (1998) [<a href="#B82-water-16-02999" class="html-bibr">82</a>], dos Reis et al. (2024) [<a href="#B83-water-16-02999" class="html-bibr">83</a>] and Alsop and Wood (2000) [<a href="#B84-water-16-02999" class="html-bibr">84</a>].</p>
Full article ">Figure 4
<p>The predictive capacity of the biotic ligand model for (<b>a</b>) copper (Cu) with 12 freshwater species (15 studies) and 383 water quality scenarios (all values expressed as dissolved Cu in μg/L), (<b>b</b>) uranium (UO<sub>2</sub>) with ten freshwater species (six studies) and 52 water quality scenarios (all values expressed as dissolved U in μg/L) and (<b>c</b>) lead (Pb) with five freshwater species (eight studies) and 110 water quality scenarios (all values expressed as dissolved Pb in μg/L). The solid line indicates ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Di Toro et al. (2001) [<a href="#B5-water-16-02999" class="html-bibr">5</a>], De Schampheleare and Janssen (2002) [<a href="#B9-water-16-02999" class="html-bibr">9</a>], Meyer et al. (1999) [<a href="#B39-water-16-02999" class="html-bibr">39</a>], Cooper et al. (2009) [<a href="#B58-water-16-02999" class="html-bibr">58</a>], Cusimano et al. (1986) [<a href="#B64-water-16-02999" class="html-bibr">64</a>], Long et al. (2004) [<a href="#B85-water-16-02999" class="html-bibr">85</a>], Crémazy et al. (2017) [<a href="#B86-water-16-02999" class="html-bibr">86</a>], Erickson et al. (1996) [<a href="#B87-water-16-02999" class="html-bibr">87</a>], De Schampheleare et al. (2007) [<a href="#B88-water-16-02999" class="html-bibr">88</a>], De Schampheleare et al. (2002) [<a href="#B89-water-16-02999" class="html-bibr">89</a>], Ryan et al. (2009) [<a href="#B90-water-16-02999" class="html-bibr">90</a>], Villavicencio et al. (2005) [<a href="#B91-water-16-02999" class="html-bibr">91</a>], Welsh et al. (1996) [<a href="#B92-water-16-02999" class="html-bibr">92</a>], Sciera et al. (2004) [<a href="#B93-water-16-02999" class="html-bibr">93</a>], Kramer et al. (2004) [<a href="#B94-water-16-02999" class="html-bibr">94</a>], Goulet et al. (2015) [<a href="#B95-water-16-02999" class="html-bibr">95</a>], Semaan et al. (2001) [<a href="#B96-water-16-02999" class="html-bibr">96</a>], Markich (2013) [<a href="#B97-water-16-02999" class="html-bibr">97</a>], Trenfield et al. (2011) [<a href="#B98-water-16-02999" class="html-bibr">98</a>], Charles et al. (2002) [<a href="#B99-water-16-02999" class="html-bibr">99</a>], Franklin et al. (2001) [<a href="#B100-water-16-02999" class="html-bibr">100</a>], De Schampheleare et al. (2014) [<a href="#B101-water-16-02999" class="html-bibr">101</a>], Esbaugh et al. (2011) [<a href="#B102-water-16-02999" class="html-bibr">102</a>], Mager et al. (2011) [<a href="#B103-water-16-02999" class="html-bibr">103</a>], Antunes and Kreager (2014) [<a href="#B104-water-16-02999" class="html-bibr">104</a>], Nys et al. (2014) [<a href="#B105-water-16-02999" class="html-bibr">105</a>], Grosell et al. (2006) [<a href="#B106-water-16-02999" class="html-bibr">106</a>], Bircneau et al. (2008) [<a href="#B107-water-16-02999" class="html-bibr">107</a>] and McDonald et al. (2002) [<a href="#B108-water-16-02999" class="html-bibr">108</a>].</p>
Full article ">Figure 4 Cont.
<p>The predictive capacity of the biotic ligand model for (<b>a</b>) copper (Cu) with 12 freshwater species (15 studies) and 383 water quality scenarios (all values expressed as dissolved Cu in μg/L), (<b>b</b>) uranium (UO<sub>2</sub>) with ten freshwater species (six studies) and 52 water quality scenarios (all values expressed as dissolved U in μg/L) and (<b>c</b>) lead (Pb) with five freshwater species (eight studies) and 110 water quality scenarios (all values expressed as dissolved Pb in μg/L). The solid line indicates ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Di Toro et al. (2001) [<a href="#B5-water-16-02999" class="html-bibr">5</a>], De Schampheleare and Janssen (2002) [<a href="#B9-water-16-02999" class="html-bibr">9</a>], Meyer et al. (1999) [<a href="#B39-water-16-02999" class="html-bibr">39</a>], Cooper et al. (2009) [<a href="#B58-water-16-02999" class="html-bibr">58</a>], Cusimano et al. (1986) [<a href="#B64-water-16-02999" class="html-bibr">64</a>], Long et al. (2004) [<a href="#B85-water-16-02999" class="html-bibr">85</a>], Crémazy et al. (2017) [<a href="#B86-water-16-02999" class="html-bibr">86</a>], Erickson et al. (1996) [<a href="#B87-water-16-02999" class="html-bibr">87</a>], De Schampheleare et al. (2007) [<a href="#B88-water-16-02999" class="html-bibr">88</a>], De Schampheleare et al. (2002) [<a href="#B89-water-16-02999" class="html-bibr">89</a>], Ryan et al. (2009) [<a href="#B90-water-16-02999" class="html-bibr">90</a>], Villavicencio et al. (2005) [<a href="#B91-water-16-02999" class="html-bibr">91</a>], Welsh et al. (1996) [<a href="#B92-water-16-02999" class="html-bibr">92</a>], Sciera et al. (2004) [<a href="#B93-water-16-02999" class="html-bibr">93</a>], Kramer et al. (2004) [<a href="#B94-water-16-02999" class="html-bibr">94</a>], Goulet et al. (2015) [<a href="#B95-water-16-02999" class="html-bibr">95</a>], Semaan et al. (2001) [<a href="#B96-water-16-02999" class="html-bibr">96</a>], Markich (2013) [<a href="#B97-water-16-02999" class="html-bibr">97</a>], Trenfield et al. (2011) [<a href="#B98-water-16-02999" class="html-bibr">98</a>], Charles et al. (2002) [<a href="#B99-water-16-02999" class="html-bibr">99</a>], Franklin et al. (2001) [<a href="#B100-water-16-02999" class="html-bibr">100</a>], De Schampheleare et al. (2014) [<a href="#B101-water-16-02999" class="html-bibr">101</a>], Esbaugh et al. (2011) [<a href="#B102-water-16-02999" class="html-bibr">102</a>], Mager et al. (2011) [<a href="#B103-water-16-02999" class="html-bibr">103</a>], Antunes and Kreager (2014) [<a href="#B104-water-16-02999" class="html-bibr">104</a>], Nys et al. (2014) [<a href="#B105-water-16-02999" class="html-bibr">105</a>], Grosell et al. (2006) [<a href="#B106-water-16-02999" class="html-bibr">106</a>], Bircneau et al. (2008) [<a href="#B107-water-16-02999" class="html-bibr">107</a>] and McDonald et al. (2002) [<a href="#B108-water-16-02999" class="html-bibr">108</a>].</p>
Full article ">Figure 5
<p>The predictive capacity of the biotic ligand model for uranium (UO<sub>2</sub>) with ten freshwater species (six studies) and 52 water quality scenarios (all values expressed as dissolved U in μg/L) when only UO<sub>2</sub><sup>2+</sup> is considered responsible for toxicity. The solid line indicates ideal (1:1) agreement between the measured and predicted EC/LC<sub>50</sub> values, the dashed lines represent ratios of ½ and 2 between the measured and predicted EC/LC<sub>50</sub> values and the dotted and dashed lines represent ratios of ⅓ and 3. Within the legend, the values in parentheses denote the number of data points from each study. References: Goulet et al. (2015) [<a href="#B95-water-16-02999" class="html-bibr">95</a>], Semaan et al. (2001) [<a href="#B96-water-16-02999" class="html-bibr">96</a>], Markich (2013) [<a href="#B97-water-16-02999" class="html-bibr">97</a>], Trenfield et al. (2011) [<a href="#B98-water-16-02999" class="html-bibr">98</a>], Charles et al. (2002) [<a href="#B99-water-16-02999" class="html-bibr">99</a>] and Franklin et al. (2001) [<a href="#B100-water-16-02999" class="html-bibr">100</a>].</p>
Full article ">Figure 6
<p>Linear regressions between (<span class="html-italic">f</span><sub>C</sub>)<sub>M</sub><sup>50%</sup> and their corresponding EC/LC<sub>50</sub> values for nickel (Ni–green) and copper (Cu–blue). The red dashed lines represent the expected behaviour of Zn (red stars), despite no significant (<span class="html-italic">p</span> &gt; 0.05) linear relationship, and are roughly parallel to the fitted regressions for Ni and Cu (aligning with both the upper and lower observed Zn values).</p>
Full article ">Figure 7
<p>Linear regressions between log <span class="html-italic">K</span><sub>MBL</sub> (metal binding affinity) and log (1/[M]) (a measure of metal toxicity) for (<b>a</b>) <span class="html-italic">Ceriodaphnia dubia</span> and <span class="html-italic">Daphnia magna</span> (crustaceans), and (<b>b</b>) <span class="html-italic">Oncorhynchus mykiss</span> (fish). <span class="html-italic">For O. mykiss</span>, Cd<sup>2+</sup> values were added as an overlay using both the uncorrected (0.216; open red circle) and corrected (i.e., × (1 − 0.216)/0.216); open purple circle) (<span class="html-italic">f<sub>C</sub></span>)<sub>M</sub><sup>50%</sup> value. The correction brings Cd<sup>2+</sup> in line with the other six metals (see <a href="#sec5-water-16-02999" class="html-sec">Section 5</a>).</p>
Full article ">
17 pages, 3768 KiB  
Article
Distribution Characteristics and Pollution Assessment of Soil Aggregates of Cr, Ni, and Cu in a Region of Northern Hebei Province
by Sha Xie, Jie Zhang, Zhijun Liu, Xiaofei Guo, Yuebing Sun and Qingqing Huang
Agronomy 2024, 14(10), 2408; https://doi.org/10.3390/agronomy14102408 - 17 Oct 2024
Viewed by 661
Abstract
In order to understand the distribution, occurrence forms, and influencing factors of chromium (Cr), nickel (Ni), and copper (Cu) in soil aggregates, a five-step extraction method was used to determine their forms in soil aggregates of different sizes in a mountainous area of [...] Read more.
In order to understand the distribution, occurrence forms, and influencing factors of chromium (Cr), nickel (Ni), and copper (Cu) in soil aggregates, a five-step extraction method was used to determine their forms in soil aggregates of different sizes in a mountainous area of northern Hebei Province. The ecological risk was evaluated using the geo-accumulation index (Igeo) and primary and secondary comparison value method (RSP). Redundancy analysis (RDA) was used to identify the main factors affecting the distribution and morphology of Cr, Ni, and Cu in soil. The results showed that in vertical distribution, Cr, Ni, and Cu were concentrated in the surface soil, but there was no clear relationship between soil depth and heavy metal content. The distribution characteristics revealed that Cr, Ni, and Cu in soils mainly existed in relatively stable Fe-Mn oxides and residue states, and their morphology in aggregates did not vary considerably with particle size. Furthermore, the RSP results showed that the pollution risk of Cr, Ni, and Cu was higher, with Cr and Ni posing the highest risk in the 0.5–1 mm and 1–2 mm particle size ranges. The RDA results showed that available phosphorus and soil organic matter (SOM) were the main factors that caused the characteristic difference of 1–2 mm aggregate components. Additionally, hydrolyzed nitrogen, cation exchange capacity (CEC), and calcium exchange have positive effects on the residual state of Cr. For Ni, SOM, CEC and exchangeable calcium have positive effects on the binding state of Fe and Mn oxides and carbonate. For Cu, CEC and exchangeable calcium are the key factors that cause the morphological differences of aggregates. Based on the above results, a theoretical basis has been provided for the prevention and control of pollution in the subsequent research area. Full article
(This article belongs to the Special Issue Soil Evolution, Management, and Sustainable Utilization)
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<p>Layout of sampling points in the research area.</p>
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<p>Spatial distribution of heavy metals Cr, Cu, and Ni in the study area.</p>
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<p>Distribution of Cr, Cu and Ni contents in different soil layers. Note: Numbers 1–8 represent different plots in the study area, “S” represents topsoil and “P” represents subsurface soil (20–50 cm), the red part represents that the value exceeds the threshold in the Soil environmental quality-Risk control standard for soil contamination of agricultural land (GB15618-2018).</p>
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<p>Speciation distribution of Cr (<b>a</b>), Cu (<b>b</b>), and Ni (<b>c</b>) in different polluted areas. Note: 1, 7, and 8 are the names of different plots; a, b, c, and d represent aggregates with particle size ranges of &lt;0.25 mm, 0.25–0.5 mm, 0.5–1 mm, and 1–2 mm, respectively.</p>
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<p>Evaluation results of Cr (<b>a</b>), Cu (<b>b</b>), and Ni (<b>c</b>) <span class="html-italic">I</span><sub>geo</sub> and RSP in soil aggregates of different particle sizes.</p>
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<p>Evaluation results of Cr (<b>a</b>), Cu (<b>b</b>), and Ni (<b>c</b>) <span class="html-italic">I</span><sub>geo</sub> and RSP in soil aggregates of different particle sizes.</p>
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<p>RDA analysis of heavy metal content and physicochemical properties in soil aggregates of different particle sizes. Note: Different colors of circles represent different particle sizes, and F1–F5 are Tessier five-step forms, respectively. The red line represents the value of Tessier’s five-step form, and the blue line represents the values of various physical and chemical properties of soil.</p>
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<p>Correlation analysis of total amount and available state content for heavy metals and physicochemical properties. * The correlation is significant when the confidence level (both sides) is 0.05; a deeper color of red indicates stronger correlation, and a deeper color of blue indicates weaker correlation.</p>
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17 pages, 8396 KiB  
Article
A New Process for Efficient Non-Destructive Metal-Activated Composite Plating of Ni-P-Al2O3 on Titanium Base and Its Performance Research
by Kaifang Cui, Jin Gao, Siqi Li, Xue Leng, Liang Zhong and Rongming Qiang
Coatings 2024, 14(9), 1203; https://doi.org/10.3390/coatings14091203 - 19 Sep 2024
Viewed by 1044
Abstract
A new high efficient and non-destructive mental activation process of electroless composite plating was proposed. The process utilized electromagnetic induction equipment to heat the titanium alloy substrate and used its energy to complete the activation process, which could successfully attach the nickel nanoparticles [...] Read more.
A new high efficient and non-destructive mental activation process of electroless composite plating was proposed. The process utilized electromagnetic induction equipment to heat the titanium alloy substrate and used its energy to complete the activation process, which could successfully attach the nickel nanoparticles firmly to the surface of the titanium alloy; at the same time, the process pre-activated Al2O3 nanoparticles and added the activated nanoparticles to the plating solution. In the process of plating, the activated titanium substrate was used as the catalytic center of electroless nickel plating (ENP) for electroless composite plating. The new activation process avoided complicated traditional processes such as acid etching and zinc dipping. Such traditional processes require huge doses of chemicals, including various strong acids, so improper waste liquid treatment will cause harm to the environment. The important parameters of the process were optimized by orthogonal experiments. A scanning electron microscope (SEM), an X-ray photoelectron spectroscopy (XPS), an energy dispersive spectrometer (EDS), thermal shock experiments and friction and wear experiments were used to characterize and analyze the surface morphology, composition, binding force and friction coefficient of the coating, and analyze the coating quality by measuring the plating rate and the thickness of the coating. The results showed that the rate of electroless composite plating increased with the increase in Al2O3 nanoparticle concentration. When the concentration of Al2O3 nanoparticles reached 1.5 g/L, the ENP rate decreased with the increase in Al2O3 nanoparticle concentration. The adhesion of the sample was evaluated by the scratch test, which showed that the binding grade of the sample was 0, and the Vickers hardness was 688.5 HV. Results showed that the coating produced by this new process has excellent performance. Therefore, the process is an environmentally friendly and fast activation composite plating process. Full article
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<p>Flow diagram of the electroless composite plating Ni-P/Al<sub>2</sub>O<sub>3</sub> process.</p>
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<p>Electromagnetic induction heating principle schematic diagram.</p>
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<p>(<b>a</b>,<b>b</b>) SEM images of the surface before and after degreasing. (<b>c</b>,<b>d</b>) Images of water contact angle.</p>
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<p>Temperature curve over time.</p>
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<p>SEM and EDS of the surface of the activated sample.</p>
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<p>XRD of the surface after activation of the specimen.</p>
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<p>(<b>a</b>) Full spectrum of the activated sample surface; (<b>b</b>) Ni spectrum of the activated sample surface.</p>
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<p>SEM and EDS of Al<sub>2</sub>O<sub>3</sub> nanoparticles after activation.</p>
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<p>Full spectrum of nanoparticles after pre-activation.</p>
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<p>Effect of Al<sub>2</sub>O<sub>3</sub> nanoparticles on deposition rate.</p>
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<p>SEM and EDS of Ni-P/Al<sub>2</sub>O<sub>3</sub> composite coating surface.</p>
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<p>XRD image of the substrate after composite plating.</p>
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<p>(<b>a</b>) SEM cross-section of composite plating; (<b>b</b>) coating scratch diagram of new process; (<b>c</b>) coating scratch diagram of zinc dipping.</p>
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<p>Variation curves of surface friction coefficient (<b>a</b>) and wear morphology (<b>b</b>) of titanium alloy substrate and its electroless Ni-P/Al<sub>2</sub>O<sub>3</sub> composite plating.</p>
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<p>Scan of surface roughness after composite plating.</p>
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18 pages, 3144 KiB  
Article
Theoretical Study of the Effects of Different Coordination Atoms (O/S/N) on Crystal Structure, Stability, and Protein/DNA Binding of Ni(II) Complexes with Pyridoxal-Semi, Thiosemi, and Isothiosemicarbazone Ligand Systems
by Violeta Jevtovic, Aleksandra Rakić, Odeh A. O. Alshammari, Munirah Sulaiman Alhar, Tahani Alenezi, Violeta Rakic and Dušan Dimić
Inorganics 2024, 12(9), 251; https://doi.org/10.3390/inorganics12090251 - 17 Sep 2024
Cited by 1 | Viewed by 957
Abstract
Nickel transition metal complexes have shown various biological activities that depend on the ligands and geometry. In this contribution, six Ni(II) nitrate complexes with pyridoxal-semi, thiosemi, and isothiosemicarbazone ligands were examined using theoretical chemistry methods. The structures of three previously reported complexes ([Ni(PLSC)(H [...] Read more.
Nickel transition metal complexes have shown various biological activities that depend on the ligands and geometry. In this contribution, six Ni(II) nitrate complexes with pyridoxal-semi, thiosemi, and isothiosemicarbazone ligands were examined using theoretical chemistry methods. The structures of three previously reported complexes ([Ni(PLSC)(H2O)3]∙2NO3, [Ni(PLTSC)2] ∙2NO3∙H2O, and [Ni(PLITSC)(H2O)3]∙2NO3) were investigated based on Hirshfeld surface analysis, and the most important stabilization interactions in the crystal structures were outlined. These structures were optimized at the B3LYP/6-311++G(d,p)(H,C,N,O,(S))/LanL2DZ(Ni) level of theory, and the applicability was checked by comparing theoretical and experimental bond lengths and angles. The same level of theory was applied for the optimization of three additional structures, ([Ni(PLSC)2]2+, [Ni(PLTSC)(H2O)3]2+, and [Ni(PLITSC)2]2+). The interactions between selected ligands and Ni(II) were examined using the Natural Bond Orbital (NBO) and Quantum Theory of Atoms in Molecules (QTAIM) approaches. Particular emphasis was placed on interactions between oxygen, sulfur, and nitrogen donor atoms and Ni(II). Human Serum Albumin (HSA) and the DNA-binding properties of these complex cations were assessed using molecular docking simulations. The presence of water molecules and various substituents in the thermodynamics of the processes was demonstrated. The results showed significant effects of structural parameters on the stability and reactivity towards important biomolecules. Full article
(This article belongs to the Special Issue Metal Complexes Diversity: Synthesis, Conformations, and Bioactivity)
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<p>Complexation modes of neutral PLSC, PLTSC, and PLITSC ligands.</p>
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<p>Hirshfeld surfaces of different nickel(II) nitrate complexes included in this study.</p>
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<p>Optimized structures (at the B3LYP/6-311++G(d,p)(H,C,N,O,(S)/LanL2DZ(Ni) level of theory) of selected octahedral Ni(II) complexes. Carbon—gray; nitrogen—blue; oxygen—red; sulfur—yellow; nickel—teal; hydrogen atoms have been omitted for clarity.</p>
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<p>Structure of HSA with subdomains: IA in reddish, IB in yellow, IIA in green, IIB in orange, IIIA in lilac, and IIIB in pink. The active positions FA1–FA8 are denoted with the representation of myristic acids (yellow CPK model), commonly bound in the structures. The position of a fluorescent amino acid, Trp214, is depicted as dark green CPK balls, while [Ni(PLSC)<sub>2</sub>]<sup>2+</sup> is presented as purple CPK balls.</p>
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<p>The most important interactions between HSA and [Ni(PLSC)(H<sub>2</sub>O)<sub>3</sub>]<sup>2+</sup> (<b>left</b>) and [Ni(PLSC)<sub>2</sub>]<sup>2+</sup> (<b>right</b>) complexes, as obtained in the molecular docking simulations.</p>
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<p>The most important interactions between DNA and [Ni(PLSC)(H<sub>2</sub>O)<sub>3</sub>]<sup>2+</sup> (<b>left</b>) and [Ni(PLSC)<sub>2</sub>]<sup>2+</sup> (<b>right</b>) complexes, as obtained via the molecular docking simulations.</p>
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22 pages, 7074 KiB  
Article
Characterization and Cytotoxic Assessment of Bis(2-hydroxy-3-carboxyphenyl)methane and Its Nickel(II) Complex
by Ayman H. Ahmed, Ibrahim O. Althobaiti, Ebtsam K. Alenezy, Yazeed M. Asiri, Sobhy Ghalab and Omar A. Hussein
Molecules 2024, 29(17), 4239; https://doi.org/10.3390/molecules29174239 - 6 Sep 2024
Viewed by 868
Abstract
A condensation reaction of salicylic acid with formaldehyde in the presence of sulfuric acid led to the synthesization of the bis(2-hydroxy-3-carboxyphenyl)methane (BHCM) ligand, which was subsequently allowed to bind with nickel (II) ions. In light of the information obtained from the elemental analyses [...] Read more.
A condensation reaction of salicylic acid with formaldehyde in the presence of sulfuric acid led to the synthesization of the bis(2-hydroxy-3-carboxyphenyl)methane (BHCM) ligand, which was subsequently allowed to bind with nickel (II) ions. In light of the information obtained from the elemental analyses (C, H, and M), spectral (IR, MS, 1H-NMR, and UV–Vis) and thermal and magnetic measurements, the most likely structures of the ligand and complex have been identified. It has been suggested that the BHCM coordinates in a tetradentate manner with two Ni(II) ions to produce an octahedral binuclear complex. The SEM and TEM morphology of the compounds showed spherical shapes. An X-ray diffraction analysis indicated a considerable difference in the diffraction patterns between BHCM (crystalline) and Ni–BHCM (amorphous), and the Scherrer equation was used to calculate the crystallite size. Some optical characteristics were estimated from UV–Vis spectra. The ligand and its nickel(II) complex underlie the range of semiconductors. It was verified that for human lung (A-549) cancer, the BHCM compound displayed a significant barrier to the proliferation test in noncancerous cells (human lung fibroblasts, WI-38), which was also undertaken. To demonstrate the binding affinities of the chosen compounds (BHCM and Ni–BHCM) in the receptor protein’s active site [PDB ID: 5CAO], a molecular docking (MD) study was carried out. Full article
(This article belongs to the Special Issue Advances in Coordination Chemistry 2.0)
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<p>BHCM and Ni–BHCM morphological pictures.</p>
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<p>XRD graph of Ni–BHCM.</p>
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<p>Changes in the nickel complex’s optical parameters include (<b>a</b>) transmittance—T, (<b>b</b>) band gap energy—E<sub>g</sub>, (<b>c</b>) refractive index—n, (<b>d</b>) optical conductivity—σ<sub>opt</sub> and (<b>e</b>) penetration depth—W.</p>
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<p>Changes in the nickel complex’s optical parameters include (<b>a</b>) transmittance—T, (<b>b</b>) band gap energy—E<sub>g</sub>, (<b>c</b>) refractive index—n, (<b>d</b>) optical conductivity—σ<sub>opt</sub> and (<b>e</b>) penetration depth—W.</p>
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<p>Changes in the nickel complex’s optical parameters include (<b>a</b>) transmittance—T, (<b>b</b>) band gap energy—E<sub>g</sub>, (<b>c</b>) refractive index—n, (<b>d</b>) optical conductivity—σ<sub>opt</sub> and (<b>e</b>) penetration depth—W.</p>
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<p>HOMO and LUMO transition, energy and optimized lowest energy structure of the ligand and nickel(II) complex. BHCM: [MM2 Minimization: Stretch: 2.1471, Bend: 8.8211, Stretch-Bend: −0.1542, Torsion: −16.3849, Non-1,4 VDW: −9.7095, 1,4 VDW: 12.6725, Dipole/Dipole: 0.3568, Total Energy: −2.2511 kcal/mol] and [MMFF94 Minimization: Final Energy: 36.2527 kcal/mol]. Ni–BHCM: [MM2 Minimization: Stretch: 118.3621, Bend: 331.6871, Stretch-Bend: −0.2150, Torsion: −9.8166, Non-1,4 VDW: −58.7081, 1,4 VDW: 4.6860, Dipole/Dipole: −62.5274, Total Energy: 323.4682 kcal/mol] and [MMFF94 Minimization: Final Energy: 683.54 kcal/mol].</p>
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<p>IC<sub>50</sub> and assessment of BHCM’s cytotoxicity on the human lung carcinoma (A-549) and fibroblast normal cells (WI-38).</p>
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<p>Interaction of BHCM with 5CAO as a receptor.</p>
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<p>Interaction of the Ni–BHCM complex with 5CAO as a receptor.</p>
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<p>FT-IR spectrum of Ni–BHCM complex.</p>
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<p>Electronic spectrum of Ni–BHCM.</p>
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<p>TGA of Ni–BHCM.</p>
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<p>Diagram illustrating the Ni–BHCM creation.</p>
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22 pages, 5371 KiB  
Article
Experimental and Theoretical Studies on DNA Binding and Anticancer Activity of Nickel(II) and Zinc(II) Complexes with N– (8–Quinolyl) Salicylaldimine Schiff Base Ligands
by Bussaba Pinchaipat, Ratanon Chotima, Malinee Promkatkaew, Sunan Kitjaruwankul, Kittipong Chainok and Teerawat Khudkham
Chemistry 2024, 6(4), 618-639; https://doi.org/10.3390/chemistry6040037 - 28 Jul 2024
Cited by 1 | Viewed by 2171
Abstract
Transition metal complexes of nickel(II) with 5–bromo–N–(8–quinolyl)salicylaldimine (HqsalBr, HL1); [Ni(qsalBr)2] (1) and 3,5–dibromo–N–(8–quinolyl)salicylaldimine (HqsalBr2, HL2); [Ni(qsalBr2)2] (3) including zinc(II) complex with HL1, [Zn(qsalBr)2] [...] Read more.
Transition metal complexes of nickel(II) with 5–bromo–N–(8–quinolyl)salicylaldimine (HqsalBr, HL1); [Ni(qsalBr)2] (1) and 3,5–dibromo–N–(8–quinolyl)salicylaldimine (HqsalBr2, HL2); [Ni(qsalBr2)2] (3) including zinc(II) complex with HL1, [Zn(qsalBr)2] (2), have been synthesized and successfully characterized using various techniques, namely IR, NMR, mass spectrometry, thermogravimetric analysis (TGA), and single crystal X–ray crystallography. DFT calculations were employed to examine the structural and electronic parameters of the complexes at their optimized geometries. The complexes showed strong DNA-binding activities, assessed by UV-Vis and fluorescence spectroscopy, primarily through intercalation. Molecular docking investigations were carried out to provide profound insights into the interaction mechanisms of these complexes with DNA and lung cancer cells. These computational studies revealed that [Ni(qsalBr2)2] (3) exhibits the most favorable negative binding energies, −9.1 kcal/mol with DNA and −9.3 kcal/mol with cancer cells, facilitated by hydrogen bonding and hydrophobic interactions. Furthermore, the in vitro anticancer activity was evaluated against the A549 human lung adenocarcinoma cell line, with [Zn(qsalBr)2] (2) exhibiting the highest potency against this cancer cell line. Full article
(This article belongs to the Section Bioinorganics)
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<p>UV–Vis spectra of HL<sup>1</sup>, HL<sup>2</sup>, and complexes <b>1</b>–<b>3</b> in THF.</p>
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<p>Thermogravimetric analysis (TGA) of Schiff base ligand and complexes.</p>
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<p>Crystal structure with thermal ellipsoid of complex <b>3</b>.</p>
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<p>Optimized structures of HL<sup>1</sup> and HL<sup>2</sup> binding with nickel(II) and zinc(II).</p>
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<p>HOMO and LUMO charge density maps and the energy gaps (ΔE) of the HL<sup>1</sup> ligand and its nickel(II) and zinc(II) complexes.</p>
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<p>HOMO and LUMO charge density maps and the energy gaps (ΔE) of the HL<sup>2</sup> ligand and its nickel(II) complex.</p>
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<p>Electronic absorption spectra of Schiff base complexes in the absence and presence of increasing amount of CT–DNA. (<b>a</b>) [Ni(qsalBr)<sub>2</sub>] (1); (<b>b</b>) [Zn(qsalBr)<sub>2</sub>] (2); (<b>c</b>) [Ni(qsalBr<sub>2</sub>)<sub>2</sub>] (3).</p>
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<p>Fluorescence quenching spectra (λ<sub>ex</sub> = 525 nm) of EB–DNA in the absence and presence of increasing amounts of the complexes. (a) [Ni(qsalBr)<sub>2</sub>] (1); (b) [Zn(qsalBr)<sub>2</sub>] (2); (c) [Ni(qsalBr<sub>2</sub>)<sub>2</sub>] (3).</p>
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<p>Molecular docking with 2D and 3D interactions of the complexes into the B–DNA (PDB id: 1bna).</p>
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<p>Molecular docking with 2D and 3D interactions of the complexes into the EGFR kinase domain (PDB id: 7ukv).</p>
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<p>Preparation of Schiff base ligands.</p>
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<p>Preparation of zinc(II) and nickel(II) complexes.</p>
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16 pages, 4889 KiB  
Article
Fabrication and Characterization of Graphene–Mesoporous Carbon–Nickel–Poly(Vinyl Alcohol)-Coated Mandrel-Coiled TCPFLNR Artificial Muscle
by Pawandeep Singh Matharu, Yuyang Song, Umesh Gandhi and Yonas Tadesse
Biomimetics 2024, 9(8), 458; https://doi.org/10.3390/biomimetics9080458 - 26 Jul 2024
Viewed by 1020
Abstract
This study investigates the performance enhancement of mandrel-coiled twisted and coiled polymer fibers with a nichrome heater (TCPFLNR) by coating with a solution of graphene–mesoporous carbon–nickel–polyvinyl alcohol. The coating process involved a one-pot synthesis utilizing graphene powder, Ni nanoparticles, mesoporous [...] Read more.
This study investigates the performance enhancement of mandrel-coiled twisted and coiled polymer fibers with a nichrome heater (TCPFLNR) by coating with a solution of graphene–mesoporous carbon–nickel–polyvinyl alcohol. The coating process involved a one-pot synthesis utilizing graphene powder, Ni nanoparticles, mesoporous carbon, and PVA as a binding agent. The coating was performed by manually shaking the TCPFLNR and the subsequent annealing process, which results in improved thermal conductivity and actuation behavior of the TCPFLNR. Experimental results on a 60 mm long actuator demonstrated significant enhancements in actuation displacement and actuation strain (20% to 42%) under various loads with an input current of 0.27 A/power 2.16 W. The blocked stress is ~10 MPa under this 2.16 W power input and the maximum strain is 48% at optimum load of 1.4 MPa. The observed actuation strain correlated directly with the input power. The coated TCPFLNR exhibited better thermal contacts, facilitating enhanced heat transfer, and reducing power consumption by 6% to 9% compared to non-coated actuators. It was found that the nanomaterial coating helps the TCP actuator to be reliable for more than 75,000 actuation cycles at 0.1 Hz in air due to improved thermal conductivity. These findings highlight the potential for further research to optimize electrothermally operated TCP actuators and unlock advancements in this field. Full article
(This article belongs to the Special Issue Bioinspired Structures for Soft Actuators)
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<p>Overview of graphene–mesoporous C–Ni–PVA-coated mandrel-coiled TCP<sub>FL</sub><sup>NR</sup> artificial muscles. The maximum actuation strain at ~2 MPa load was 48% at 4 W power input and it could sustain 75,000 cyclic response at 0.1 Hz frequency.</p>
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<p>The mandrel-coiled TCP<sub>FL</sub><sup>NR</sup> actuator fabrication. (<b>a</b>) Twist insertion, (<b>b</b>) nichrome wire incorporation process, and (<b>c</b>) mandrel coiling process.</p>
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<p>Synthesis of graphene-mesoporous C-Ni-PVA solution.</p>
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<p>(<b>a</b>–<b>d</b>) Coating process of TCP<sub>FL</sub><sup>NR</sup> actuator. (<b>e</b>) Optical microscopy image of artificial muscle after completing lifecycle tests.</p>
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<p>Characterization setup (schematic).</p>
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<p>Characterization comparison of graphene-mesoporous C-Ni-PVA coated TCP<sub>FL</sub><sup>NR</sup> actuator and conventional TCP<sub>FL</sub><sup>NR</sup> actuator at 0.0285 Hz actuation frequency at different loads until 500 g. (<b>a</b>) Schematic diagram of training and characterization setup. (<b>b</b>) (Comparison of actuation strain with loaded length at different loads at similar input current for both actuators.) Comparison of actuation strain (% of loaded length) vs. different loads in grams of graphene-mesoporous C-Ni-PVA coated TCP<sub>FL</sub><sup>NR</sup> actuator (0.27 A, 15.8 V) and conventional TCP<sub>FL</sub><sup>NR</sup> actuator (0.27 A, 17.4 V) of 60 mm length each. (<b>c</b>) (Comparison of actuation displacement with loaded length at different loads at similar input current for both actuators.) Comparison of y-axis displacement with loaded length (mm) vs. different loads in grams of graphene-mesoporous C-Ni-PVA coated TCP<sub>FL</sub><sup>NR</sup> actuator (0.27 A, 15.8 V) and conventional TCP<sub>FL</sub><sup>NR</sup> actuator (0.27 A, 17.4 V) of 60 mm length each. The fishing line precursor fiber is 80 lb capacity and is 0.8 mm in diameter.</p>
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<p>Dynamic actuation comparison of graphene-mesoporous C-Ni-PVA-coated TCP<sub>FL</sub><sup>NR</sup> actuator and conventional TCP<sub>FL</sub><sup>NR</sup> actuator at 0.0285 Hz actuation frequency at three different loads (70 g, 100 g, 150 g) for tensile actuation vs. time and y-axis displacement vs. time plots. (<b>a</b>) 70 g, (<b>b</b>) 100 g, (<b>c</b>) 150 g.</p>
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<p>Dynamic actuation comparison of graphene-mesoporous C-Ni-PVA-coated TCP<sub>FL</sub><sup>NR</sup> actuator and conventional TCP<sub>FL</sub><sup>NR</sup> actuator at 0.0285 Hz actuation frequency at three different loads (70 g, 100 g, 150 g) for tensile actuation vs. time and y-axis displacement vs. time plots. (<b>a</b>) 70 g, (<b>b</b>) 100 g, (<b>c</b>) 150 g.</p>
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<p>Comparison of power consumed (W) vs. time (s). Plots for coated and non-coated mandrel-coiled TCP<sub>FL</sub><sup>NR</sup> at different input currents, (<b>a</b>) 0.25 A, (<b>b</b>) 0.27 A, and (<b>c</b>) 0.29 A, at 0.0285 Hz (15 s on, 20 s off) frequency.</p>
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<p>Comparison of power consumed (W) vs. time (s). Plots for coated and non-coated mandrel-coiled TCP<sub>FL</sub><sup>NR</sup> at different input currents, (<b>a</b>) 0.25 A, (<b>b</b>) 0.27 A, and (<b>c</b>) 0.29 A, at 0.0285 Hz (15 s on, 20 s off) frequency.</p>
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<p>Comparison of temperature variation (°C) vs. time (s). Results for coated and non-coated mandrel-coiled TCP<sub>FL</sub><sup>NR</sup> at different input currents, (<b>a</b>) 0.25 A, (<b>b</b>) 0.27 A, and (<b>c</b>) 0.29 A, at 0.0285 Hz (15 s on, 20 s off) frequency.</p>
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<p>Tested lifecycle of graphene–mesoporous C–Ni–PVA-coated TCP<sub>FL</sub><sup>NR</sup> at 0.1 Hz and 0.27 A input current.</p>
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<p>Proposed work showing the difference in performance of the TCP fishing line actuator; (<b>a</b>) non-coated, (<b>b</b>) single-layer graphene–mesoporous C–Ni–PVA-coated, (<b>c</b>) double-layer graphene–mesoporous C–Ni–PVA-coated.</p>
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20 pages, 2081 KiB  
Article
C(P)XCG Proteins of Haloferax volcanii with Predicted Zinc Finger Domains: The Majority Bind Zinc, but Several Do Not
by Deniz Üresin, Jonathan Schulte, Nina Morgner and Jörg Soppa
Int. J. Mol. Sci. 2024, 25(13), 7166; https://doi.org/10.3390/ijms25137166 - 28 Jun 2024
Viewed by 1240
Abstract
In recent years, interest in very small proteins (µ-proteins) has increased significantly, and they were found to fulfill important functions in all prokaryotic and eukaryotic species. The halophilic archaeon Haloferax volcanii encodes about 400 µ-proteins of less than 70 amino acids, 49 of [...] Read more.
In recent years, interest in very small proteins (µ-proteins) has increased significantly, and they were found to fulfill important functions in all prokaryotic and eukaryotic species. The halophilic archaeon Haloferax volcanii encodes about 400 µ-proteins of less than 70 amino acids, 49 of which contain at least two C(P)XCG motifs and are, thus, predicted zinc finger proteins. The determination of the NMR solution structure of HVO_2753 revealed that only one of two predicted zinc fingers actually bound zinc, while a second one was metal-free. Therefore, the aim of the current study was the homologous production of additional C(P)XCG proteins and the quantification of their zinc content. Attempts to produce 31 proteins failed, underscoring the particular difficulties of working with µ-proteins. In total, 14 proteins could be produced and purified, and the zinc content was determined. Only nine proteins complexed zinc, while five proteins were zinc-free. Three of the latter could be analyzed using ESI-MS and were found to contain another metal, most likely cobalt or nickel. Therefore, at least in haloarchaea, the variability of predicted C(P)XCG zinc finger motifs is higher than anticipated, and they can be metal-free, bind zinc, or bind another metal. Notably, AlphaFold2 cannot correctly predict whether or not the four cysteines have the tetrahedral configuration that is a prerequisite for metal binding. Full article
(This article belongs to the Special Issue Metalloproteins: How Metals Shape Protein Structure and Function)
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<p>(<b>A</b>) Affinity purification of protein HVO_B0212 using nickel chelating sepharose. Aliquots of the following fractions were analyzed on a tricine SDS-PAGE: L—cell lysate, F—flow through, W—wash fractions, and E—elution fractions. (<b>B</b>) Tricine SDS-PAGE of the different fractions of an attempt to affinity purify protein HVO_2391A. (<b>C</b>) Chromatogram of a size exclusion chromatography of the elution fractions of the affinity isolation shown in (<b>A</b>). (<b>D</b>) Chromatogram of a size exclusion chromatography of the elution fractions of the affinity isolation shown in (<b>B</b>). The red arrow indicates the elution volume of a protein of the size of HVO_2391A-NHis.</p>
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<p>Zinc content of the 14 characterized H. volcanii C(P)XCG µ-proteins. A quantitative assay with the highly zinc-specific fluorophore ZnAF-2F was applied. Mean values of at least three biological replicates and standard deviations are shown. The results of previous studies [<a href="#B30-ijms-25-07166" class="html-bibr">30</a>,<a href="#B31-ijms-25-07166" class="html-bibr">31</a>] are included and marked in yellow.</p>
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<p>ESI mass spectra of different zinc finger µ-proteins after treatment with EDTA (red) and without treatment (black). (<b>A</b>) Analysis of positive control protein HVO_0758. (<b>B</b>) Analysis of protein HVO_0489. (<b>C</b>) Analysis of protein HVO_1670A. (<b>D</b>) Analysis of protein HVO_A0254A.</p>
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<p>(<b>A</b>) Comparison between zinc-binding pocket 2 (ZBP2) of HVO_2753, AlphaFold structure prediction (blue), and the NMR solution structure (green) (PDB: 6YDH). (<b>B</b>) Structure comparison of ZBP1 of HVO_2753 between the AlphaFold structure prediction (blue) and the NMR structure (green) (PDB: 6YDH). (<b>C</b>) AlphaFold structure predictions of HVO_0546 (left) and HVO_B0212 (right), zoomed into the putative ZBP formed by the C(P)XCG-related motifs. (<b>D</b>) AlphaFold structure predictions of the putative zinc-binding pockets of HVO_A0511 (left) and a version of HVO_A0511 in which all four cysteines had been replaced by alanines (right).</p>
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11 pages, 3309 KiB  
Article
Biomining of ‘Heavy’ Metals and Lanthanides from Red Mud of a Former Lignite Mines by Sorption on Chitin
by Felix Blind and Stefan Fränzle
Polysaccharides 2024, 5(2), 158-168; https://doi.org/10.3390/polysaccharides5020012 - 14 Jun 2024
Viewed by 1258
Abstract
In times of increasing demand for resources, processing various waste materials is becoming more economically and ecologically viable. Red mud is a waste material that originates from the bauxite process, also known as the Bayer process. Red mud, due to its high alkalinity [...] Read more.
In times of increasing demand for resources, processing various waste materials is becoming more economically and ecologically viable. Red mud is a waste material that originates from the bauxite process, also known as the Bayer process. Red mud, due to its high alkalinity and heavy metal content, is often stored in landfills, which can lead to accidents such as those in Brazil or Hungary, especially if the storage takes place above ground. Red mud contains not only iron and aluminum residues but also other economically valuable metals such as manganese, titanium, cadmium, or cobalt. Currently, only 4 million tons of the annual production of 150 million tons are utilized in various industries, which is a relatively small amount. Typically, only the iron content is further processed, leaving other potential resources untapped. Chitin has a high binding capacity for various trivalent and divalent metal ions, making it a suitable material for separating red mud into its components. It has been demonstrated that chitin can effectively remove aluminum, barium, cadmium, cobalt, copper, manganese, iron, nickel, lead, strontium, and various lanthanides from a red mud-like sludge. The elements bound to chitin can be easily removed using wet chemistry. Biologically compatible substances are predominantly used in this process, with few exceptions. The removal of elements from red sludge or other mining wastewater using chitin is a viable alternative to traditional mining methods. Full article
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<p>Natural red mud-like slugged in a small pound near Zittau, Saxony, Germany. <b>Left</b>: Spring area. <b>Right</b>: Part of a stream from the spring to a small lake. (S. Fränzle 2024©).</p>
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<p>A section of a chitin molecule is presented, along with the potential binding sites for divalent metal ions here using Fe<sup>2+</sup>-Ions as an example.</p>
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<p>(<b>a</b>–<b>c</b>): Measured concentration of the tested elements in red mud-like sludges from the riverbed and the water surface in relation to the concentration of these elements in the water body. (Blanks meaning the measured concentration was lower than the detection limit).</p>
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<p>(<b>a</b>,<b>b</b>): Comparison of the concentration for the tested elements in both red mud-like sludges with the concentration in the desorption media after desorption from chitin. (Blanks meaning the measured concentration was lower than the detection limit).</p>
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<p>Recovery rate for the tested elements after desorption from chitin by DMF and formic acid. (For Cd, Ni and Pb, no value could be given due to the fact that the concentration of these elements in both red mud-like sludges were lower than the detection limit).</p>
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<p>Schematic representation of a possible design of a plant for biomining various elements from red mud with chitin. a: red sludge heap; b: first desorption basin for removing the elements bound to chitin (e.g., LiCl in DMF); c: second desorption basin for removing the elements bound to chitin (e.g., formic acid); d: conveyor belt coated with chitin; e deflection rollers.</p>
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17 pages, 10384 KiB  
Article
In Situ Thermal Interactions of Cu-Based Anti-Corrosion Coatings on Steel Implemented by Surface Alloying
by Huda Hanif Khan, Tong Wang, Lihong Su, Huijun Li, Qiang Zhu, Ana Yang, Zigang Li, Wei Wang and Hongtao Zhu
Coatings 2024, 14(6), 722; https://doi.org/10.3390/coatings14060722 - 5 Jun 2024
Cited by 1 | Viewed by 1393
Abstract
Incorporating expensive alloying elements into bulk steel for corrosion protection is undesirable, considering that only the surfaces are exposed to aggressive environments. Therefore, this work focused on developing and optimizing a new surface functioning technology through in situ observation of thermal interactions between [...] Read more.
Incorporating expensive alloying elements into bulk steel for corrosion protection is undesirable, considering that only the surfaces are exposed to aggressive environments. Therefore, this work focused on developing and optimizing a new surface functioning technology through in situ observation of thermal interactions between the metallic powders at elevated temperatures. The study revealed that the Cu-Ni powder mixture, with 12.5 wt% Ni, began to melt at 1099.5 °C and was fully melted at 1175 °C, significantly different from the Cu-Ni solid solution and bulk Cu or Ni. As a result of high-temperature reactions, copper penetration of up to 35 µm for pure copper and 55 µm for copper-chromium composite coatings occurred due to liquid metal corrosion. In contrast, the copper-nickel composite coating exhibited a cupronickel solution microstructure with FeNi dendrites and a nickel-rich transition layer. This cupronickel coating, with a chemical composition of 89.3 wt% Cu, 6.2 wt% Ni, and 4.5 wt% Fe, demonstrated uniform thickness, superior surface morphology, and continuous coverage on the steel substrate. Furthermore, the Ni-rich transition layer played a vital role in preventing copper penetration along the grain boundary of the steel matrix while forming a chemical binding between the coating and the substrate. The practicality of the coating was further confirmed through the hot-rolling procedure and subsequent electrochemical corrosion tests, which resulted in a 44% improvement in corrosion resistance. Full article
(This article belongs to the Special Issue Surface Science of Degradation and Surface Protection)
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<p>Cu-Ni binary phase diagram calculated by Thermo-Calc software.</p>
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<p>Thermal setup of (<b>a</b>) pure Cu, (<b>b</b>) Cu-Ni, and Cu–Cr coatings for HTCLSM experiments.</p>
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<p>Melting and solidification process of pure Cu-coated sample. (<b>a</b>) Cu powder on the surface, (<b>b</b>) Melting started, (<b>c</b>) Fully melted, (<b>d</b>) Solidification.</p>
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<p>Solidification process of Cu–Cr coating. (<b>a</b>) Liquid pool with undissolved solid particles, (<b>b</b>) a combination of the solid and liquid phases, (<b>c</b>) solidified coating with the lesser residual liquid left.</p>
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<p>Melting process of Cu-Ni powders. (<b>a</b>) Metallic powders started to melt, (<b>b</b>) Solid powders with some molten liquid, (<b>c</b>) Liquid pool started to form with fewer solid powders left, (<b>d</b>) fully melt.</p>
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<p>Solidification process of Cu-Ni coating. (<b>a</b>) Fully molten state, (<b>b</b>) solidification started, (<b>c</b>) solidified coating with less molten liquid, (<b>d</b>) fully solidified.</p>
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<p>Surface morphologies and secondary electron images of coated samples, (<b>a</b>,<b>b</b>) pure Cu; (<b>c</b>,<b>d</b>) Cu–Cr; and (<b>e</b>,<b>f</b>) Cu-Ni.</p>
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<p>Cross-section of the coating layers at the center of coated samples, (<b>a</b>,<b>d</b>) pure Cu; (<b>b</b>,<b>e</b>) Cu–Cr; (<b>c</b>,<b>f</b>) Cu-Ni.</p>
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<p>Pure Cu coating structure (<b>a</b>) Secondary Electron Image, (<b>b</b>) EDS layered map, and its Cu and Fe elemental maps.</p>
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<p>Cu–Cr coating structure (<b>a</b>) Back-scattered Electron Microscopic Image, (<b>b</b>) EDS layered map of the surface region. (<b>c</b>) Back-scattered electron image and (<b>d</b>) EDS layered map of the interface region. Cu, Cr, and Fe elemental maps for (<b>b</b>,<b>d</b>) are shown on the right side of respective EDS layered maps.</p>
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<p>Cu-Ni coating structure (<b>a</b>) Back-scattered Electron Image, (<b>b</b>) EDS layered map and Elemental maps of Cu, Ni, and Fe at Site 1 (Ni-rich dendritic structure), (<b>c</b>) Back-scattered Electron Image of Site 2 (Ni-rich interface); (<b>d</b>) EDS layered map and Elemental maps of Cu, Ni, and Fe at Site 2 (Ni-rich interface); (<b>e</b>–<b>g</b>) Elemental spectrums of Point scan 1 (coating region), (<b>f</b>) point scan 2 (dendrite), (<b>g</b>) point scan 3 (interface). In (<b>a</b>), an overlapping region between Site 1 and Site 2 is highlighted by the red dashed rectangular boxes in the EDS mapping shown in (<b>b</b>,<b>d</b>).</p>
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<p>(<b>a</b>) Cu-Ni coated sample cross-section after practical hot rolling and (<b>b</b>) line-scan of the cross-section.</p>
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<p>Electrochemical corrosion test results in 3.5% salt solution.</p>
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17 pages, 3676 KiB  
Article
Coordination Compounds of Nickel(II) with 3,5–Dibromo–Salicylaldehyde: Structure and Interaction with Biomolecules
by Georgios I. Psarras, Ariadni Zianna, Antonios G. Hatzidimitriou and George Psomas
Inorganics 2024, 12(5), 138; https://doi.org/10.3390/inorganics12050138 - 10 May 2024
Viewed by 1293
Abstract
Three neutral nickel(II) complexes of 3,5–dibromo–salicylaldehyde (3,5–diBr–saloH) were synthesized in the presence or absence of 1,10–phenanthroline (phen) or its derivative 2,9–dimethyl–1,10–phenanthroline (neoc) as co–ligands, namely [Ni(3,5–diBr–salo)2(neoc)] (complex 1), [Ni(3,5–diBr–salo)2(phen)] (complex 2) and [Ni(3,5–diBr–salo)2(H2O) [...] Read more.
Three neutral nickel(II) complexes of 3,5–dibromo–salicylaldehyde (3,5–diBr–saloH) were synthesized in the presence or absence of 1,10–phenanthroline (phen) or its derivative 2,9–dimethyl–1,10–phenanthroline (neoc) as co–ligands, namely [Ni(3,5–diBr–salo)2(neoc)] (complex 1), [Ni(3,5–diBr–salo)2(phen)] (complex 2) and [Ni(3,5–diBr–salo)2(H2O)2] (complex 3), and were characterized by various techniques. The crystal structure of [Ni(3,5–diBr–salo)2(neoc)] was determined by single-crystal X-ray crystallography. According to employed studying techniques, the complexes interact tightly with calf-thymus DNA by an intercalative fashion. Furthermore, compounds 1–3 bind tightly and reversibly to human and bovine serum albumin. Full article
(This article belongs to the Special Issue Metal-Based Compounds: Relevance for the Biomedical Field)
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Graphical abstract

Graphical abstract
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<p>Syntax formula of (<b>A</b>) 3,5–dibromo–salicylaldehyde (3,5–diBr–saloH), (<b>B</b>) 2,9–dimethyl–1,10–phenanthroline (neoc), and (<b>C</b>) 1,10–phenanthroline (phen).</p>
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<p>Synthetic routine and proposed structures for complexes <b>1–3</b>.</p>
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<p>Molecular structure of [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>). Aromatic hydrogen and methyl hydrogen atoms have been omitted for clarity.</p>
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<p>UV–vis spectra of a DMSO solution of [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>) and [Ni(3,5–diBr–salo)<sub>2</sub>(phen)] (complex <b>2</b>) (1 × 10<sup>−4</sup> M) in the presence of increasing amounts of CT DNA. The arrows show the changes upon increasing amounts of CT DNA.</p>
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<p>Relative viscosity (η/η<sub>0</sub>)<sup>1/3</sup> of CT DNA (0.1 mM) in buffer solution (150 mM of NaCl and 15 mM of trisodium citrate at pH 7.0) in the presence of complexes <b>1–3</b> at increasing amounts (r = [complex]/[DNA]).</p>
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<p>(<b>A</b>) Fluorescence emission spectra (λ<sub>excitation</sub> = 540 nm) for EB–DNA adduct ([EB] = 20 µM, [DNA] = 26 µM) in buffer solution (150 mM of NaCl and 15 mM of trisodium citrate at pH = 7.0) in the presence of increasing amounts of [Ni(3,5–diBr–salo)<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>] (complex <b>3</b>). (<b>B</b>) Plot of relative EB–DNA fluorescence emission intensity at λ<sub>emission</sub> = 594 nm (I/Io, %) <span class="html-italic">vs</span>. r (r = [complex]/[DNA]) in the presence of complexes <b>1–3</b> (up to 45.2% of the initial EB–DNA fluorescence for [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>), 48.2% for [Ni(3,5–diBr–salo)<sub>2</sub>(phen)] (complex <b>2</b>), and 41.3% for [Ni(3,5–diBr–salo)<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>] (complex <b>3</b>)).</p>
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<p>(<b>A</b>) Fluorescence emission spectra (λ<sub>excitation</sub> = 295 nm) of BSA (3 µM) in buffer solution (150 mM of NaCl and 15 mM of trisodium citrate at pH = 7.0) in the absence and presence of increasing amounts of [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>)<b>.</b> (<b>B</b>) Plot of relative BSA-fluorescence emission intensity at λ<sub>em,max</sub> = 345 nm (I/Io, %) <span class="html-italic">vs</span>. r (r = [complex]/[BSA]) for complexes <b>1–3</b> (up to 14.4% of the initial BSA fluorescence for [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>), 10.3% for [Ni(3,5–diBr–salo)<sub>2</sub>(phen)] (complex <b>2</b>), and 16.0% for [Ni(3,5–diBr–salo)<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>] (complex <b>3</b>)). (<b>C</b>) Fluorescence emission spectra (λ<sub>excitation</sub> = 295 nm) of HSA (3 µM) in buffer solution (150 mM of NaCl and 15 mM of trisodium citrate at pH = 7.0) in the absence and presence of increasing amounts of [Ni(3,5–diBr–salo)<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>] (complex <b>3</b>). (<b>D</b>) Plot of relative HSA-fluorescence emission intensity at λ<sub>em,max</sub> = 340 nm (I/Io,%) <span class="html-italic">vs</span>. r (r = [complex]/[HSA]) for complexes <b>1–3</b> (up to 31.0% of the initial HSA fluorescence for [Ni(3,5–diBr–salo)<sub>2</sub>(neoc)] (complex <b>1</b>), 20.9% for [Ni(3,5–diBr–salo)<sub>2</sub>(phen)] (complex <b>2</b>), and 26.2% for [Ni(3,5–diBr–salo)<sub>2</sub>(H<sub>2</sub>O)<sub>2</sub>] (complex <b>3</b>)).</p>
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