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12 pages, 6474 KiB  
Article
A Novel Magnetic Flux Leakage Method Incorporating TMR Sensors for Detecting Zinc Dross Defects on the Surface of Hot-Dip Galvanized Sheets
by Bo Wang, San Zhang, Jie Wang, Liqin Jing and Feilong Mao
Magnetochemistry 2024, 10(12), 101; https://doi.org/10.3390/magnetochemistry10120101 - 10 Dec 2024
Viewed by 563
Abstract
Surface quality control of hot-dip galvanized sheets is a critical research topic in the metallurgical industry. Zinc dross, the most common surface defect in the hot-dip galvanizing process, significantly affects the sheet’s service performance. In this manuscript, a novel magnetic flux leakage (MFL) [...] Read more.
Surface quality control of hot-dip galvanized sheets is a critical research topic in the metallurgical industry. Zinc dross, the most common surface defect in the hot-dip galvanizing process, significantly affects the sheet’s service performance. In this manuscript, a novel magnetic flux leakage (MFL) detection method was proposed to detect zinc dross defects on the surface of hot-dip galvanized steel sheets. Instead of using exciting coils in traditional methods, a tiny permanent magnet with a millimeter magnitude was employed to reduce the size and weight of the equipment. Additionally, a high-precision tunnel magnetoresistance (TMR) sensor with a sensitivity of 300 mV/V/Oe was selected to achieve higher detection accuracy. The experimental setup was established, and the x-axis direction (sample movement direction) was determined as the best measurement axis by vector analysis through experiments and numerical simulation. The detection results indicate that this novel MFL detection method could detect industrial zinc dross with an equivalent size of 400 μm, with high signal repeatability and signal-to-noise ratio. In the range of 0–1200 mm/s, the detection speed has almost no effect on the measurement signal, which indicates that this novel method has higher adaptability to various conditions. The multi-path scanning method with a single probe was used to simulate the array measurement to detect a rectangular area of 30 × 60 mm. Ten zinc dross defects were detected across eight measurement paths with 4 mm intervals, and the positions of these zinc dross defects were successfully reconstructed. The research results indicate that this novel MFL detection method is simple and feasible. Furthermore, the implementation of array measurements provides valuable guidance for subsequent in-depth research and potential industrial applications in the future. Full article
(This article belongs to the Section Applications of Magnetism and Magnetic Materials)
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Figure 1

Figure 1
<p>Principle sketch of the novel MFL method: (<b>a</b>) defect near, (<b>b</b>) leave the permanent magnet, and (<b>c</b>) characteristic of the signal.</p>
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<p>Evolution of magnetic lines when a ferromagnetic material with defect passes through a permanent magnet: (<b>a</b>) defect near, (<b>b</b>) underneath, and (<b>c</b>) leave the PM.</p>
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<p>Hot-dip galvanized sheet specimen.</p>
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<p>Micrographs of zinc dross defects in hot-dip galvanized sheet specimen: (<b>a</b>) defect 1; (<b>b</b>) defect 2; and (<b>c</b>) defect 3.</p>
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<p>Experimental device: (<b>a</b>) overall layout and (<b>b</b>) device details.</p>
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<p>Numerical model of vector analysis of galvanized sheet.</p>
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<p>The vector analysis results of (<b>a</b>) experimental and (<b>b</b>) numerical study.</p>
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<p>Measuring results of galvanized sheet specimen: (<b>a</b>) defect 1; (<b>b</b>) defect 2; and (<b>c</b>) defect 3.</p>
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<p>Relationship between the moving velocity of the galvanized sheet and the amplitudes of the measuring signals.</p>
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<p>Schematic diagram of area scanning paths using a single sensor.</p>
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<p>Area scanning results using a single sensor: (<b>a</b>) path 1 and 2; (<b>b</b>) path 3 and 4; (<b>c</b>) path 5 and 6; (<b>d</b>) path 7 and 8.</p>
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<p>Area scanning results using a single sensor: (<b>a</b>) path 1 and 2; (<b>b</b>) path 3 and 4; (<b>c</b>) path 5 and 6; (<b>d</b>) path 7 and 8.</p>
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<p>Reappearance of zinc dross in a galvanized sheet.</p>
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<p>Schematic diagram of scanning a galvanized sheet by staggered multi-row array sensors.</p>
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21 pages, 1158 KiB  
Article
Optimizing Light Intensity and Salinity for Sustainable Kale (Brassica oleracea) Production and Potential Application in Marine Aquaponics
by Christopher Pascual, Lirong Xiang, Ricardo Hernandez and Steven Hall
Sustainability 2024, 16(23), 10516; https://doi.org/10.3390/su162310516 - 30 Nov 2024
Viewed by 1006
Abstract
With rising populations and increasing food consumption, the demand for food is placing significant strain on freshwater resources. Exploring crops that can thrive under saline conditions is crucial to ensuring food security. Although brackish and seawater is abundant, it is generally unsuitable for [...] Read more.
With rising populations and increasing food consumption, the demand for food is placing significant strain on freshwater resources. Exploring crops that can thrive under saline conditions is crucial to ensuring food security. Although brackish and seawater is abundant, it is generally unsuitable for irrigation. However, some plants exhibit tolerance to moderate levels of salinity. This study investigated the effects of varying light intensities (150 and 250 photosynthetic photon flux densities) and salinity levels (<1.5, 5, 10, and 17 parts per thousand, equivalent to <26, 86, 171, and 291 millimolars) on the growth and nutrient composition of Russian kale (Brassica oleracea) grown in indoor hydroponics. The experiment was conducted over five months, from September 2023 to January 2024. The results revealed that a light intensity of 250 PPFD and salinity levels of <1.5–5 ppt (<26–86 mM) were optimal for maximizing the biomass yield of the kale, whereas a significant reduction in the yield was observed at salinity levels exceeding 10 ppt (171 mM). In contrast, the dry matter percentage was significantly higher at 17 ppt (291 mM). The macronutrient contents, particularly the total Kjeldahl nitrogen (TKN), total phosphorus (TP), and magnesium (Mg), were consistent across both light intensities (150–250 PPFDs) and at salinity levels between <1.5 and 10 ppt (<26–171 mM) but were reduced at 17 ppt (291 mM). The micronutrient concentrations, such as those of copper (Cu), iron (Fe), and zinc (Zn), were higher at the lower light intensity (150 PPFD) across the salinity levels. These findings suggest that optimizing the light conditions is essential for enhancing the nutritional value of kale in saline environments. These outcomes are particularly vital for improving agricultural productivity and resilience in salt-affected regions, thereby supporting broader food security and sustainability goals. Full article
(This article belongs to the Special Issue Sustainability in Aquaculture Systems)
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Figure 1
<p>The plant growth parameters of kale measured over time from 0 to 112 DAT under treatment combinations of light intensities (150 and 250 PPFDs) and salinity levels (&lt;1.5, 5, 10, and 17 ppt, equivalent to &lt;26, 86, 171, and 291 mM) with three replications each: (<b>a</b>) plant height; (<b>b</b>) leaf length; (<b>c</b>) leaf width; and (<b>d</b>) stem diameter.</p>
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<p>The yield parameters of kale gathered throughout a 112-day experiment under treatment combinations of light intensities (150 and 250 PPFDs) and salinity levels (&lt;1.5, 5, 10, and 17 ppt, equivalent to &lt;26, 86, 171, and 291 mM) with three replications each: (<b>a</b>) number of leaves harvested; (<b>b</b>) fresh biomass; (<b>c</b>) dry biomass; and (<b>d</b>) dry matter percentage. Error bars represent standard errors. Means with the same superscript letters on each plot were not significantly different at <span class="html-italic">p</span> &lt; 0.05 using Tukey’s HSD test.</p>
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<p>The water consumption and water productivity of kale plants under different light intensities (150 and 250 PPFDs) and salinity levels (&lt;1.5, 5, 10, and 17 ppt, equivalent to &lt;26, 86, 171, and 291 mM): (<b>a</b>) total water consumption per plant after 112 DAT (L/plant); (<b>b</b>) water productivity (g/L). Error bars represent standard errors. Means with the same superscript letters on each plot are not significantly different at <span class="html-italic">p</span> &lt; 0.05 using Tukey’s HSD test.</p>
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<p>The macronutrient contents of kale leaves under different light intensities (150 and 250 PPFDs) and salinity levels (&lt;1.5, 5, 10, and 17 ppt, equivalent to &lt;26, 86, 171, and 291 mM): (<b>a</b>) total Kjeldahl nitrogen (TKN); (<b>b</b>) potassium; (<b>c</b>) total phosphorus (TP); (<b>d</b>) magnesium (Mg); (<b>e</b>) sodium (Na); (<b>f</b>) calcium (Ca). Error bars represent standard errors. Means with the same superscript letters on each plot were not significantly different at <span class="html-italic">p</span> &lt; 0.05 using Tukey’s HSD test.</p>
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<p>The micronutrients of the kale plants’ leaves under treatment combinations of light intensities (150 and 250 PPFDs) and salinity levels (&lt;1.5, 5, 10, and 17 ppt, equivalent to &lt;26, 86, 171, and 291 mM): (<b>a</b>) copper; (<b>b</b>) zinc; (<b>c</b>) iron; (<b>d</b>) manganese. Error bars represent standard errors. Means with the same superscript letters on each plot were not significantly different at <span class="html-italic">p</span> &lt; 0.05 using Tukey’s HSD test.</p>
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11 pages, 2374 KiB  
Article
Investigation of a Magnetic Levitation Architecture with a Ferrite Core for Energy Harvesting
by Igor Nazareno Soares, Ruy Alberto Corrêa Altafim, Ruy Alberto Pisani Altafim, Melkzedekue de Moraes Alcântara Calabrese Moreira, Felipe Schiavon Inocêncio de Sousa, José A. Afonso, João Paulo Carmo and Rogério de Andrade Flauzino
Energies 2024, 17(21), 5315; https://doi.org/10.3390/en17215315 - 25 Oct 2024
Viewed by 947
Abstract
This work presents the development of a magnetic levitation system with a ferrite core, designed for electromagnetic energy harvesting from mechanical vibrations. The system consists of a fixed enamel-coated copper coil and five neodymium-iron-boron permanent magnets housed within a PVC spool. To enhance [...] Read more.
This work presents the development of a magnetic levitation system with a ferrite core, designed for electromagnetic energy harvesting from mechanical vibrations. The system consists of a fixed enamel-coated copper coil and five neodymium-iron-boron permanent magnets housed within a PVC spool. To enhance magnetic flux concentration, a manganese-zinc ferrite (Mn-Zn) ring was employed within the spool. Experimental tests were conducted at frequencies up to 20 Hz, demonstrating the device’s potential for harvesting energy from small vibrations, such as those generated by human biomechanical movements, achieving operating voltages up to 3 V. Additionally, the architecture is scalable for larger systems and allows for the integration of multiple transducers without magnetic field interference, independent of the frequency or excitation phase of each transducer. Full article
(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)
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<p>General linear electromagnetic energy harvester scheme.</p>
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<p>Linear electromagnetic energy harvester model.</p>
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<p>Linear EM energy harvesting architectures: (<b>a</b>) spring-mass with moving coil; (<b>b</b>) spring-mass with moving magnet; (<b>c</b>) free impact mass frequency-up converter; (<b>d</b>) magnetic levitation; and (<b>e</b>) double spring-mass with moving magnet.</p>
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<p>Non-resonant EM energy harvesters: (<b>a</b>) rotational, steady torque conversion (<b>b</b>) hybrid, converts linear to rotational movement.</p>
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<p>(<b>a</b>) Schematic of the developed energy harvester: coil with an air core, ferrite, four levitating magnets, and one fixed magnet; (<b>b</b>) final assembly.</p>
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<p>(<b>a</b>) Schematic of the full-wave rectifier circuit; (<b>b</b>) in-series association of full-wave rectifier circuits.</p>
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<p>System built for the mechanical stimulation of the transducers.</p>
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<p>Signal generated by the energy harvester when excited with a harmonic signal of 10 Hz frequency, with a selected segment of the signal.</p>
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<p>Voltage measurements at the output capacitor of the rectifier circuit connected to the energy harvester for input signals with frequencies from 5 to 20 Hz.</p>
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11 pages, 4947 KiB  
Article
Growth of Hg0.7Cd0.3Te on Van Der Waals Mica Substrates via Molecular Beam Epitaxy
by Shuo Ma, Wenwu Pan, Xiao Sun, Zekai Zhang, Renjie Gu, Lorenzo Faraone and Wen Lei
Molecules 2024, 29(16), 3947; https://doi.org/10.3390/molecules29163947 - 21 Aug 2024
Viewed by 3764
Abstract
In this paper, we present a study on the direct growth of Hg0.7Cd0.3Te thin films on layered transparent van der Waals mica (001) substrates through weak interface interaction through molecular beam epitaxy. The preferred orientation for [...] Read more.
In this paper, we present a study on the direct growth of Hg0.7Cd0.3Te thin films on layered transparent van der Waals mica (001) substrates through weak interface interaction through molecular beam epitaxy. The preferred orientation for growing Hg0.7Cd0.3Te on mica (001) substrates is found to be the (111) orientation due to a better lattice match between the Hg0.7Cd0.3Te layer and the underlying mica substrate. The influence of growth parameters (mainly temperature and Hg flux) on the material quality of epitaxial Hg0.7Cd0.3Te thin films is studied, and the optimal growth temperature and Hg flux are found to be approximately 190 °C and 4.5 × 104 Torr as evidenced by higher crystalline quality and better surface morphology. Hg0.7Cd0.3Te thin films (3.5 µm thick) grown under these optimal growth conditions present a full width at half maximum of 345.6 arc sec for the X-ray diffraction rocking curve and a root-mean-square surface roughness of 6 nm. However, a significant number of microtwin defects are observed using cross-sectional transmission electron microscopy, which leads to a relatively high etch pit density (mid-107 cm2) in the Hg0.7Cd0.3Te thin films. These findings not only facilitate the growth of HgCdTe on mica substrates for fabricating curved IR sensors but also contribute to a better understanding of growth of traditional zinc-blende semiconductors on layered substrates. Full article
(This article belongs to the Special Issue Recent Advances in Epitaxial Growth: Materials and Methods)
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<p>(<b>a</b>) Representative RHEED patterns for mica substrate surface just before and after starting <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> growth; (<b>b</b>) representative RHEED patterns for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> surface under an optimal growth temperature (190 °C, sample Mica003) and other non-optimal growth temperatures (180 °C, 185 °C, and 195 °C, samples Mica001, Mica002, and Mica004) at the end of growth run; (<b>c</b>) photograph of 3.5 µm thick <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> thin films grown on mica for 2 h and a ruler as reference; (<b>d</b>) representative <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ω</mi> <mo>−</mo> <mn>2</mn> <mi mathvariant="sans-serif">θ</mi> </mrow> </semantics></math> scan HRXRD curve of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> thin films grown on mica; (<b>e</b>) normalized XRD rocking curves of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> thin films grown on mica at different growth temperatures.</p>
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<p>Top-view SEM and AFM images of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> thin films grown on mica with different growth temperatures: 180 °C (<b>a</b>,<b>e</b>), 185 °C (<b>b</b>,<b>f</b>), 190 °C (<b>c</b>,<b>g</b>), and 195 °C (<b>d</b>,<b>h</b>), respectively.</p>
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<p>XRD rocking curves of 3.5 µm thick <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> samples grown on mica with different Hg fluxes.</p>
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<p>Top-view SEM and AFM images of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">H</mi> <mi mathvariant="normal">g</mi> </mrow> <mrow> <mn>0.7</mn> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">d</mi> </mrow> <mrow> <mn>0.3</mn> </mrow> </msub> <mi mathvariant="normal">T</mi> <mi mathvariant="normal">e</mi> </mrow> </semantics></math> thin films grown on mica with different Hg fluxes: 3 × <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </mrow> </semantics></math> Torr (<b>a</b>,<b>e</b>), 4.5 × <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </mrow> </semantics></math> (<b>b</b>,<b>f</b>), 6 × <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </mrow> </semantics></math> (<b>c</b>,<b>g</b>), and 7 × <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </mrow> </semantics></math> (<b>d</b>,<b>h</b>), respectively.</p>
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<p>(<b>a</b>) Low-magnification cross-sectional TEM image of sample Mica003; (<b>b</b>) cross-sectional TEM image and (<b>c</b>) HRTEM image of the interface region “1. Good area” as indicated in (<b>a</b>); (<b>d</b>) SAED patterns of HgCdTe in (<b>c</b>); (<b>e</b>) SAED patterns of mica in (<b>c</b>); (<b>f</b>) cross-sectional TEM image and (<b>g</b>) HRTEM image of the interface region “2. Twins area” as indicated in (<b>a</b>); (<b>h</b>) SAED patterns of mica in (<b>g</b>).</p>
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<p>Selected region for TEM specimen preparation and low-magnification cross-sectional TEM image of (<b>a</b>) sample Mica003 and (<b>b</b>) sample Mica004; (<b>c</b>) TEM image of HgCdTe twins area in (<b>b</b>).</p>
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<p>Surface SEM image of sample Mica003 after EPD etching.</p>
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15 pages, 13437 KiB  
Article
Integrative Analysis of Transcriptomic Profiles and Physiological Responses Provide New Insights into Drought Stress Tolerance in Oil Palm (Elaeis guineensis Jacq.)
by Fernan Santiago Mejía-Alvarado, Arley Fernando Caicedo-Zambrano, David Botero-Rozo, Leonardo Araque, Cristihian Jarri Bayona-Rodríguez, Seyed Mehdi Jazayeri, Carmenza Montoya, Iván Ayala-Díaz, Rodrigo Ruiz-Romero and Hernán Mauricio Romero
Int. J. Mol. Sci. 2024, 25(16), 8761; https://doi.org/10.3390/ijms25168761 - 12 Aug 2024
Cited by 3 | Viewed by 1471
Abstract
Oil palm (Elaeis guineensis Jacq.) is a highly productive crop economically significant for food, cosmetics, and biofuels. Abiotic stresses such as low water availability, salt accumulation, and high temperatures severely impact oil palm growth, physiology, and yield by restricting water flux among [...] Read more.
Oil palm (Elaeis guineensis Jacq.) is a highly productive crop economically significant for food, cosmetics, and biofuels. Abiotic stresses such as low water availability, salt accumulation, and high temperatures severely impact oil palm growth, physiology, and yield by restricting water flux among soil, plants, and the environment. While drought stress’s physiological and biochemical effects on oil palm have been extensively studied, the molecular mechanisms underlying drought stress tolerance remain unclear. Under water deficit conditions, this study investigates two commercial E. guineensis cultivars, IRHO 7001 and IRHO 2501. Water deficit adversely affected the physiology of both cultivars, with IRHO 2501 being more severely impacted. After several days of water deficit, there was a 40% reduction in photosynthetic rate (A) for IRHO 7001 and a 58% decrease in IRHO 2501. Further into the drought conditions, there was a 75% reduction in A for IRHO 7001 and a 91% drop in IRHO 2501. Both cultivars reacted to the drought stress conditions by closing stomata and reducing the transpiration rate. Despite these differences, no significant variations were observed between the cultivars in stomatal conductance, transpiration, or instantaneous leaf-level water use efficiency. This indicates that IRHO 7001 is more tolerant to drought stress than IRHO 2501. A differential gene expression and network analysis was conducted to elucidate the differential responses of the cultivars. The DESeq2 algorithm identified 502 differentially expressed genes (DEGs). The gene coexpression network for IRHO 7001 comprised 274 DEGs and 46 predicted HUB genes, whereas IRHO 2501’s network included 249 DEGs and 3 HUB genes. RT-qPCR validation of 15 DEGs confirmed the RNA-Seq data. The transcriptomic profiles and gene coexpression network analysis revealed a set of DEGs and HUB genes associated with regulatory and transcriptional functions. Notably, the zinc finger protein ZAT11 and linoleate 13S-lipoxygenase 2-1 (LOX2.1) were overexpressed in IRHO 2501 but under-expressed in IRHO 7001. Additionally, phytohormone crosstalk was identified as a central component in the response and adaptation of oil palm to drought stress. Full article
(This article belongs to the Special Issue Recent Research in Plant Abiotic Stress)
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Figure 1
<p>Physical appearance of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation for three weeks (drought stress).</p>
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<p>Predawn leaf water potential (Ψleaf) of two oil palm cultivars, Deli × La Mé (IRHO 7001 and IRHO 2501), in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Each box corresponds to the mean ± SD (<span class="html-italic">n</span> = 6).</p>
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<p>Physiological response of two oil palm cultivars, Deli × La Mé, IRHO 7001 (7001) and IRHO 2501 (2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Each box corresponds to the mean ± SD. (<span class="html-italic">n</span> = 6). (<b>A</b>). photosynthetic rate (<span class="html-italic">A</span>), (<b>B</b>). stomatal conductance (<span class="html-italic">gs</span>), (<b>C</b>). transpiration rate (E), and (<b>D</b>). instantaneous leaf-level water use efficiency (WUE).</p>
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<p>DEGs of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. (<b>A</b>) Heatmap of the RNA-Seq samples. A tendency toward red indicates under-expression, while a tendency toward blue indicates overexpression. (<b>B</b>) Unique and shared DEGs between two contrasting oil palm genotypes and drought stress conditions. The color key scale corresponds to the L2FC, tendency to blue correspond to underexpressed genes, while tendency to red indicates overexpressed.</p>
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<p>Gene coexpression networks of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. (<b>A</b>) General; (<b>B</b>) IRHO 7001; and (<b>C</b>) IRHO 2501. The igraph R package was used to construct the general and specific cultivar coexpression networks under drought stress. Each node (sphere or bead-like shape) represents a gene, and groups of nodes highlighted with the same color indicate a module of genes. The black edges represent direct correlations between genes, and the red lines represent inverse correlations. The size of each node is proportional to the mean expression level of the gene represented by the node.</p>
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<p>Relative quantification of 15 genes by RT–qPCR compared against RNA-Seq in two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Yellow bars indicate the relative expression value obtained by RT-qPCR. Lite blue diamonds indicate the RNA-Seq value. (<b>A</b>) WRKY transcription factor 51; (<b>B</b>) NAC transcription factor NAM-B2-like_ NAM-B2; (<b>C</b>) beta-xylosidase alpha-L-arabinofuranosidase 2-like OsI_08964_ BXL1; (<b>D</b>) Leucine-rich repeat receptor-like serine_ At1g17230; (<b>E</b>) Calcium-binding protein CML42; (<b>F</b>) Ser/threo-protein phosphatase 6 regulatory ankyrin repeat subunit B; (<b>G</b>) Pectinesterase-like; (<b>H</b>) Pentatricopeptide repeat-containing protein_ At5g39980; (<b>I</b>) Multiple C2 and transmembrane domain-containing protein 2-like, (<b>J</b>) Non-specific lipid-transfer protein 2-like; (<b>K</b>) Transcription factor bHLH35-like isoform X1; (<b>L</b>) Mitogen-activated protein kinase kinase kinase 2-like; (<b>M</b>) Bidirectional sugar transporter SWEET14-like; (<b>N</b>) Galactinol synthase 1-like_ GOLS1; and (<b>O</b>) Xyloglucan endotransglucosylase/hydrolase protein 22-like XTH22.</p>
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<p>Phytohormone crosstalk and signal cascades of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. The numbers indicate the step-by-step signaling cascade response in oil palms under drought stress. Numbers 1 and 2 indicate the stimulus and signal perception. 3 indicates signal transduction. 4, 5, and 6 indicate phytohormone metabolism and TFs activation/ inactivation. 7 and 8 indicate drought stress-induced genes and ROS metabolism balance. Gene expression levels are indicated for each cultivar, where 7001 = IRHO 7001 and 2501 = IRHO 2501. The square color corresponds to the gene expression color scale in the L2FC bar. The question mark indicates no gene expression. Arrows colors indicate flux of water (blue), ABA (green), and ROS (red) from soil or roots to leaves. The figure was partly generated using plant icon adaptations licensed and created by Guillaume Lobet (<a href="https://figshare.com/authors/Plant_Illustrations/3773596" target="_blank">https://figshare.com/authors/Plant_Illustrations/3773596</a> is licensed under CC-BY 4.0 Unported <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a>, accessed on 16 April 2024).</p>
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14 pages, 1676 KiB  
Article
Metabolic Shift in Porcine Spermatozoa during Sperm Capacitation-Induced Zinc Flux
by Tyler Weide, Kayla Mills, Ian Shofner, Matthew W. Breitzman and Karl Kerns
Int. J. Mol. Sci. 2024, 25(14), 7919; https://doi.org/10.3390/ijms25147919 - 19 Jul 2024
Cited by 1 | Viewed by 1563
Abstract
Mammalian spermatozoa rely on glycolysis and mitochondrial oxidative phosphorylation for energy leading up to fertilization. Sperm capacitation involves a series of well-regulated biochemical steps that are necessary to give spermatozoa the ability to fertilize the oocyte. Additionally, zinc ion (Zn2+) fluxes [...] Read more.
Mammalian spermatozoa rely on glycolysis and mitochondrial oxidative phosphorylation for energy leading up to fertilization. Sperm capacitation involves a series of well-regulated biochemical steps that are necessary to give spermatozoa the ability to fertilize the oocyte. Additionally, zinc ion (Zn2+) fluxes have recently been shown to occur during mammalian sperm capacitation. Semen from seven commercial boars was collected and analyzed using image-based flow cytometry before, after, and with the inclusion of 2 mM Zn2+ containing in vitro capacitation (IVC) media. Metabolites were extracted and analyzed via Gas Chromatography-Mass Spectrometry (GC-MS), identifying 175 metabolites, with 79 differentially abundant across treatments (p < 0.05). Non-capacitated samples showed high levels of respiration-associated metabolites including glucose, fructose, citric acid, and pyruvic acid. After 4 h IVC, these metabolites significantly decreased, while phosphate, lactic acid, and glucitol increased (p < 0.05). With zinc inclusion, we observed an increase in metabolites such as lactic acid, glucitol, glucose, fructose, myo-inositol, citric acid, and succinic acid, while saturated fatty acids including palmitic, dodecanoic, and myristic acid decreased compared to 4 h IVC, indicating regulatory shifts in metabolic pathways and fatty acid composition during capacitation. These findings underscore the importance of metabolic changes in improving artificial insemination and fertility treatments in livestock and humans. Full article
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<p>Image-based flow cytometry validation of in vitro capacitation. (<b>a</b>–<b>c</b>) Histogram overlays between 0 h (shown in red, filled in solid) and 4 h IVC (shown in green, not filled in), showing changes in the fluorescence of biomarkers between the two treatments. (<b>a</b>) FluoZin 3 AM intensity reporting zinc ion localization, (<b>b</b>) PI intensity reflecting plasma membrane integrity/remodeling, and (<b>c</b>) lectin PNA conjugated to AlexaFluor 647 intensity reflecting acrosomal integrity/remodeling. Boar #2 is displayed here for illustrative purposes. (<b>d</b>–<b>g</b>) Images taken from the Cytek<sup>®</sup> Amnis<sup>®</sup> ImageStream<sup>®X</sup> MkII image-based flow cytometer (Fremont, CA, USA) validating capacitation status. Columns are denoted by channel number and fluorescent probe/target, and rows are single-cell images of different spermatozoa. Channels used: (1) Brightfield (BF), (2) FluoZin 3 AM reflecting zinc (Zn) ion localization, (4) propidium iodide (PI), (7) Hoescht 33342 nuclear stain, and (11) lectin peanut agglutin (PNA)-Alexa Fluor 647™. Examples of (<b>d</b>) zinc signature 1 spermatozoa, (<b>e</b>) zinc signature 2, (<b>f</b>) zinc signature 3, and (<b>g</b>) zinc signature 4. Total percentages of sperm per biomarker classification are in <a href="#app1-ijms-25-07919" class="html-app">Table S1</a>.</p>
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<p>Changes in abundance in key metabolites associated with cellular respiration after in vitro capacitation. A total of 79 metabolites involved in cellular respiration pathways were identified as differentially abundant following capacitation (<span class="html-italic">p</span> &lt; 0.05; complete heatmap of those identified displayed in <a href="#app1-ijms-25-07919" class="html-app">Figure S2</a>). Eight of the well-known metabolites that are represented here are integral to well-known cellular respiration processes. Non-capacitated (0 h) is shown on the left in red, capacitated (4 h) is shown in the middle in green, and capacitated +2 mM zinc (4 h + Zn) is shown on the right in blue, for each respective metabolite.</p>
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<p>Heat map representing top 25 differentially abundant metabolites in sperm metabolome of all sires individually across treatments. Fold change is illustrated by a gradient from dark blue (negative) to dark red (positive). 0 h (non-capacitated) are in red, 4 h IVC are in green, and 4 h IVC + 2 mM zinc are in blue, by class. Metabolites starting with the name “RI=” are unidentified features that have been given a retention-index-based name for tracking purposes. Total 79 statistically significant metabolites are reported in <a href="#app1-ijms-25-07919" class="html-app">Figure S2</a>.</p>
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<p>Principal component analysis. PCA analysis was employed to visualize the metabolic differentiation between non-capacitated spermatozoa (red triangles), capacitated spermatozoa (green squares), and capacitated spermatozoa supplemented with 2 mM zinc (blue circles). Each symbol represents an individual sample plotted against the first two principal components. Colored ellipses represent confidence regions, indicating the clustering of samples within each group, with each color corresponding to a different treatment.</p>
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<p>Volcano plots representing top 25 differentially abundant metabolites in sperm metabolome across treatments. Fold change (log2(FC)) is represented on the <span class="html-italic">X</span>-axis, and the statistical significance (−log10(<span class="html-italic">p</span>-value)) is represented on the <span class="html-italic">Y</span>-axis. Metabolites with labels are the top 25 differentially abundant within treatment groups. Varying size in circles in (<b>a</b>,<b>b</b>) represents the relative abundance of each metabolite (<b>a</b>) Comparison before and after 4 h of in vitro capacitation: 23 metabolites were less abundant and 19 metabolites were more abundant after 4 h of IVC. (<b>b</b>) Changes in sperm metabolome abundances between 4 h IVC and 4 h IVC + 2 mM Zinc: 6 metabolites were less abundant and 13 metabolites were more abundant after 4 h of IVC + 2 mM zinc inclusion. Metabolites starting with the name “RI=” are unidentified features that have been given a retention-index-based name for tracking purposes.</p>
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23 pages, 6685 KiB  
Article
Evaluation of Pigment-Modified Clear Binders and Asphalts: An Approach towards Sustainable, Heat Harvesting, and Non-Black Pavements
by Gul Badin, Naveed Ahmad, Ying Huang and Yasir Mahmood
Infrastructures 2024, 9(5), 88; https://doi.org/10.3390/infrastructures9050088 - 17 May 2024
Cited by 3 | Viewed by 1782
Abstract
Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder [...] Read more.
Pavement construction practices have evolved due to increasing environmental impact and urban heat island (UHI) effects, as pavements, covering over 30% of urban areas, contribute to elevated air temperatures. This study introduces heat-reflective pavements, by replacing conventional black bitumen with a clear binder and pigment-modified clear binders. Titanium dioxide white, zinc ferrite yellow, and iron oxide red pigments are used to give asphalt corresponding shades. The asphalt and bitumen specimens were subjected to thermal analysis in heat sinks, under varying solar fluxes. The pigment dosage was maintained at 4%, according to the weight of the total mix, for all pigment types. The samples were heated and cooled for 3 h and 2 h, respectively. Mechanical testing was conducted to ascertain the impact of temperature variations on both the neat clear binder (C.B) and pigmented C.B and asphalt mixture samples. Wheel tracking and dynamic modulus tests were conducted to evaluate their performance under high temperatures. The results indicate that non-black asphalt mixtures exhibit significant temperature reductions, up to 9 °C, which are further enhanced by pigmented binders, up to 11 °C. It was found that asphalt with a clear or transparent binder demonstrated lower temperatures and faster heat dissipation in extreme conditions. Moreover, C.B asphalt mixtures displayed a rut resistance of 15%, with the pigmented C.B asphalt mixture showing a remarkable rut resistance of 73%, outperforming conventional asphalt. Non-black mixtures, especially C.B + zinc ferrite, showed improved resistance to permanent deformation in dynamic modulus tests. Full article
(This article belongs to the Special Issue Sustainable and Digital Transformation of Road Infrastructures)
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<p>(<b>a</b>) Thin layer of CB poured onto steel surface [<a href="#B1-infrastructures-09-00088" class="html-bibr">1</a>]; (<b>b</b>) mid-point gradation curve.</p>
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<p>Steps involved in the preparation of binders and asphalt mixtures for thermal analysis. (<b>a</b>) TiO<sub>2</sub> being mixed with dry aggregates. (<b>b</b>) Binder poured into the TiO<sub>2</sub> blended aggregates. (<b>c</b>) Placement of a silicon heater at the base of the heat sink. (<b>d</b>) Heat sink inside the fiber block insulation, with installed thermocouples and heater. (<b>e</b>) White pigmented (TiO<sub>2</sub>) clear binder poured into a container. (<b>f</b>) TiO<sub>2</sub>-modified CB under experimentation. (<b>g</b>) Conventional asphalt inside the large heat sink, with installed thermocouples and heater. (<b>h</b>) White pigmented asphalt mixture before the start of the test.</p>
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<p>Steps involved in the preparation of binders and asphalt mixtures for thermal analysis. (<b>a</b>) TiO<sub>2</sub> being mixed with dry aggregates. (<b>b</b>) Binder poured into the TiO<sub>2</sub> blended aggregates. (<b>c</b>) Placement of a silicon heater at the base of the heat sink. (<b>d</b>) Heat sink inside the fiber block insulation, with installed thermocouples and heater. (<b>e</b>) White pigmented (TiO<sub>2</sub>) clear binder poured into a container. (<b>f</b>) TiO<sub>2</sub>-modified CB under experimentation. (<b>g</b>) Conventional asphalt inside the large heat sink, with installed thermocouples and heater. (<b>h</b>) White pigmented asphalt mixture before the start of the test.</p>
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<p>Schematics of laboratory setup.</p>
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<p>Three dimensional views, with labeled dimensions (mm), of (<b>a</b>) larger heat sink, and (<b>b</b>) smaller heat sink.</p>
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<p>Heating and cooling temperature curves at 1200 flux for: (<b>a</b>) conventional asphalt mixture; (<b>b</b>) asphalt mixture prepared with neat clear binder; (<b>c</b>) asphalt mixture prepared with titanium dioxide-blended clear binder; and (<b>d</b>) asphalt mixture prepared with zinc ferrite-blended clear binder.</p>
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<p>Mean temperature of 50 mm thick asphalt mixtures at (<b>a</b>) 1000 W/m<sup>2</sup> and (<b>b</b>) 800 W/m<sup>2</sup>.</p>
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<p>Heating and cooling temperature curves at 1200 flux for: (<b>a</b>) conventional black bitumen, (<b>b</b>) neat clear binder, (<b>c</b>) clear binder-modified with titanium dioxide pigments, and (<b>d</b>) clear binder-modified with zinc ferrite pigments.</p>
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<p>Mean temperature of 25 mm thick bituminous samples at (<b>a</b>) 1000 W/m<sup>2</sup> and (<b>b</b>) 800 W/m<sup>2</sup>.</p>
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<p>Heat map against Avg. curve of the asphalt mixtures, showing (<b>a</b>) heating time from 45–50 °C and (<b>b</b>) cooling time from 50–45 °C.</p>
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<p>Heat map against Avg. curve of bituminous binders, showing (<b>a</b>) heating time from 45–55 °C and (<b>b</b>) cooling time from 55–45 °C.</p>
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<p>Heat map showing the temperature variations over time for (<b>a</b>) asphalt mixtures and (<b>b</b>) bituminous binders.</p>
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<p>Cooper wheel tracking test (CWTT) of asphalt mixtures at 55 °C.</p>
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<p>Dynamic modulus of asphalt mixtures at (<b>a</b>) 55 °C and (<b>b</b>) 40 °C.</p>
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<p>Dynamic modulus samples (<b>a</b>) after core cutting and (<b>b</b>) before core cutting.</p>
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<p>(<b>a</b>) Normal probability plot. (<b>b</b>) Line fit plot for neat C.B asphalt. (<b>c</b>) Line fit plot for C.B + ZnFe<sub>2</sub>O<sub>4</sub>. (<b>d</b>) Line fit plot for C.B + TiO<sub>2</sub> with conventional black asphalt.</p>
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10 pages, 1869 KiB  
Article
Zinc Ionophore Pyrithione Mimics CD28 Costimulatory Signal in CD3 Activated T Cells
by Jana Jakobs and Lothar Rink
Int. J. Mol. Sci. 2024, 25(8), 4302; https://doi.org/10.3390/ijms25084302 - 12 Apr 2024
Viewed by 1092
Abstract
Zinc is an essential trace element that plays a crucial role in T cell immunity. During T cell activation, zinc is not only structurally important, but zinc signals can also act as a second messenger. This research investigates zinc signals in T cell [...] Read more.
Zinc is an essential trace element that plays a crucial role in T cell immunity. During T cell activation, zinc is not only structurally important, but zinc signals can also act as a second messenger. This research investigates zinc signals in T cell activation and their function in T helper cell 1 differentiation. For this purpose, peripheral blood mononuclear cells were activated via the T cell receptor-CD3 complex, and via CD28 as a costimulatory signal. Fast and long-term changes in intracellular zinc and calcium were monitored by flow cytometry. Further, interferon (IFN)-γ was analyzed to investigate the differentiation into T helper 1 cells. We show that fast zinc fluxes are induced via CD3. Also, the intracellular zinc concentration dramatically increases 72 h after anti-CD3 and anti-CD28 stimulation, which goes along with the high release of IFN-γ. Interestingly, we found that zinc signals can function as a costimulatory signal for T helper cell 1 differentiation when T cells are activated only via CD3. These results demonstrate the importance of zinc signaling alongside calcium signaling in T cell differentiation. Full article
(This article belongs to the Section Biochemistry)
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<p>PBMCs were stained with (<b>a</b>) Fluo-4 to detect intracellular free calcium or (<b>b</b>) with FluoZin-3 to detect intracellular free zinc. Then, cells were stimulated with uncoated beads (control), soluble anti-CD28- and/or anti-CD3 coated beads and with thapsigargin or pyrithione as positive control. Signals were measured 10 min after stimulation with flow cytometry, and subsequently calcium and zinc concentrations were calculated for gated lymphocytes. Data are presented as mean + SEM with <span class="html-italic">n</span> = 4 (<b>a</b>) and <span class="html-italic">n</span> = 5 (<b>b</b>) experiments. Statistical significance to the control was determined by one-way ANOVA with Dunnett’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Zinc and calcium signaling kinetics after CD3 stimulation were measured. For this, PBMCs were stained with Fluo-4 (calcium) or with FluoZin-3 (zinc) and a baseline fluorescent signal was measured for 55 s with flow cytometry. Then, cells were stimulated with anti-CD3 beads (CD3<sub>B</sub>), while fast signals were immediately measured for at least 250 s. (<b>a</b>) An exemplary forward and side scatter density plot before stimulation with CD3<sub>B</sub> is shown. The colors from red to yellow, green and blue indicate the decreasing density of events, with red representing the highest density. (<b>b</b>) After stimulation with CD3<sub>B</sub>, two additional populations are seen in the forward and side scatter density plot showing lymphocyte-bead complexes. Lymphocytes and lymphocyte-bead complexes were gated. (<b>c</b>) As a control, PBMCs were stimulated with uncoated beads (Control<sub>B</sub>). (<b>d</b>) Then, lymphocytes bound to anti-CD3 beads (CD3<sub>B</sub><sup>+</sup>) were distinguished from lymphocytes not bound to anti-CD3 beads (CD3<sub>B</sub><sup>−</sup>) due to an autofluorescence of the beads over 670 nm. (<b>e</b>) Exemplary calcium and (<b>f</b>) zinc kinetics are shown for CD3<sub>B</sub><sup>+</sup> and CD3<sub>B</sub><sup>−</sup>. The mean fluorescent signal of (<b>g</b>) Fluo-4 or (<b>h</b>) FluoZin-3 200–250 s after stimulation with anti-CD3 beads was compared between CD3<sub>B</sub><sup>+</sup> and CD3<sub>B</sub><sup>−</sup>. (<b>i</b>) Exemplary calcium and (<b>j</b>) zinc kinetics for 600 s (10 min) are shown of <span class="html-italic">n</span> = 2 experiments. Data are presented as exemplary experiments (<b>a</b>–<b>f</b>,<b>i</b>,<b>j</b>) or as mean + SEM with <span class="html-italic">n</span> = 7 (<b>g</b>) and <span class="html-italic">n</span> = 8 (<b>h</b>) experiments. Statistical significance to the control was determined by paired t-test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>PBMCs were stimulated with immobile anti-CD3 and/or soluble anti-CD28 and incubated for 24, 48 or 72 h. After the respective incubation times, intracellular free (<b>a</b>) calcium and (<b>b</b>) zinc were measured by Fluo-4 and FluoZin-3, respectively, with flow cytometry. Data are presented as mean + SEM with <span class="html-italic">n</span> = 4–5 (<b>a</b>) and <span class="html-italic">n</span> = 4 (<b>b</b>) experiments. Statistical significance to the control was determined by two-way ANOVA with Dunnett’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>PBMCs were stimulated with immobile anti-CD3 and/or soluble anti-CD28 and 0.35 µM pyrithione (Pyr). After 72 h, IFN-γ (<b>a</b>), IL-10 (<b>b</b>) and IL-17 (<b>c</b>) were measured in the supernatant by ELISA. Data are presented as mean + SEM with <span class="html-italic">n</span> = 10 (<b>a</b>) and <span class="html-italic">n</span> = 9 (<b>b</b>,<b>c</b>) experiments. Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparisons test (<b>a</b>,<b>c</b>) or a Friedman test with Dunn’s multiple comparisons test (<b>b</b>). Significantly different results (<span class="html-italic">p</span> &lt; 0.05) have no common identification letter.</p>
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16 pages, 9653 KiB  
Article
[SBP]BF4 Additive Stabilizing Zinc Anode by Simultaneously Regulating the Solvation Shell and Electrode Interface
by Xingyun Zhang, Kailimai Su, Yue Hu, Kaiyuan Xue, Yan Wang, Minmin Han and Junwei Lang
Batteries 2024, 10(3), 102; https://doi.org/10.3390/batteries10030102 - 14 Mar 2024
Cited by 1 | Viewed by 2100
Abstract
The zinc anode mainly faces technical problems such as short circuits caused by the growth of dendrite, low coulomb efficiency, and a short cycle life caused by side reactions, which impedes the rapid development of aqueous zinc-ion batteries (AZIBs). Herein, a common ionic [...] Read more.
The zinc anode mainly faces technical problems such as short circuits caused by the growth of dendrite, low coulomb efficiency, and a short cycle life caused by side reactions, which impedes the rapid development of aqueous zinc-ion batteries (AZIBs). Herein, a common ionic liquid, 1,1-Spirobipyrrolidinium tetrafluoroborate ([SBP]BF4), is selected as a new additive for pure ZnSO4 electrolyte. It is found that this additive could regulate the solvation sheath of hydrated Zn2+ ions, promote the ionic mobility of Zn2+, homogenize the flux of Zn2+, avoid side reactions between the electrolyte and electrode, and inhibit the production of zinc dendrites by facilitating the establishment of an inorganic solid electrolyte interphase layer. With the 1% [SBP]BF4-modified electrolyte, the Zn||Zn symmetric cell delivers an extended plating/stripping cycling life of 2000 h at 1 mA cm−2, which is much higher than that of the cell without additives (330 h). As a proof of concept, the Zn‖V2O5 battery using the [SBP]BF4 additive shows excellent cycling stability, maintaining its specific capacity at 97 mAh g−1 after 2000 cycles at 5 A g−1, which is much greater than the 46 mAh g−1 capacity of the non-additive battery. This study offers zinc anode stabilization through high-efficiency electrolyte engineering. Full article
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<p>The schematic diagram of the Zn deposition process in the electrolyte (<b>a</b>) without and (<b>b</b>) with [SBP]BF<sub>4</sub> additive.</p>
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<p>(<b>a</b>) XRD patterns of the original zinc foil and the zinc foil after 70 cycles in electrolytes with [SBP]BF<sub>4</sub> and without [SBP]BF<sub>4</sub>. FTIR spectra (<b>b</b>–<b>d</b>) and Raman spectra (<b>e</b>,<b>f</b>) of electrolytes containing different proportions of [SBP]BF<sub>4</sub>.</p>
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<p>The XPS spectra of the Zn foils after 140 h cycles in (<b>a</b>) pure ZnSO<sub>4</sub> and (<b>b</b>) ZnSO<sub>4</sub> + 1wt% [SBP]BF<sub>4</sub> electrolytes.</p>
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<p>SEM images and optical microscope images of zinc electrode after 140 h cycling in (<b>a</b>,<b>c</b>) pure ZnSO<sub>4</sub> electrolyte and (<b>b</b>,<b>d</b>) electrolyte containing [SBP]BF<sub>4</sub>. AFM images of (<b>e</b>) the original Zn foil and (<b>f</b>,<b>g</b>) Zn foil after 140 h cycling in different electrolytes.</p>
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<p>(<b>a</b>) The potentiodynamic polarization curves of the zinc anode in three-electrode system in electrolyte with 1wt% [SBP]BF<sub>4</sub> and without [SBP]BF<sub>4</sub>. (<b>b</b>–<b>e</b>) The constant current charge and discharge cycle performance of Zn||Zn symmetrical battery using electrolytes with different proportions of [SBP]BF<sub>4</sub> additive at 1 mA cm<sup>−2</sup>.</p>
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<p>(<b>a</b>) The coulombic efficiency and (<b>b</b>) the voltage–time curves of Zn||Cu batteries using electrolytes with and without additives. Nyquist plots tested of the graphite paper||graphite paper batteries (<b>c</b>) without [SBP]BF<sub>4</sub> additive and (<b>d</b>) with additive in the electrolyte. The chronoamperometry curves of Zn||Zn cells (<b>e</b>) without and (<b>f</b>) with 1wt% [SBP]BF<sub>4</sub> additives in the electrolyte (insets give the corresponding Nyquist plots at initial and steady states after fitting).</p>
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<p>In the study of the electrochemical performance of Zn||V<sub>2</sub>O<sub>5</sub> fuel cells, it was determined that the active material loading on the positive electrode sheet is between 1 and 2 mg cm<sup>−2</sup>: (<b>a</b>) the CV cures at a scan rate of 1 mV s<sup>−1</sup> in electrolytes with and without [SBP]BF<sub>4</sub> additives; (<b>b</b>) rate performance in electrolytes with and without [SBP]BF<sub>4</sub> additives; charge/discharge profiles in electrolytes of (<b>c</b>) without and (<b>d</b>) with [SBP]BF<sub>4</sub> additive; (<b>e</b>) cyclic stabilities and efficiencies in electrolytes with and without [SBP]BF<sub>4</sub> additives at 5 A g<sup>−1</sup>.</p>
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14 pages, 3515 KiB  
Article
Integrating Chlorophyll a Fluorescence and Enzymatic Profiling to Reveal the Wheat Responses to Nano-ZnO Stress
by Shengdong Li, Yujia Liu, Zongshuai Wang, Tianhao Liu, Xiangnan Li and Peng Zhang
Plants 2023, 12(22), 3808; https://doi.org/10.3390/plants12223808 - 9 Nov 2023
Viewed by 1377
Abstract
It has been shown that increased concentrations of zinc oxide nanoparticles (nano-ZnO) in the soil are harmful to plant growth. However, the sensitivity of different wheat cultivars to nano-ZnO stress is still unclear. To detect the physiological response process of wheat varieties with [...] Read more.
It has been shown that increased concentrations of zinc oxide nanoparticles (nano-ZnO) in the soil are harmful to plant growth. However, the sensitivity of different wheat cultivars to nano-ZnO stress is still unclear. To detect the physiological response process of wheat varieties with different tolerance to nano-ZnO stress, four wheat cultivars (viz., cv. TS1, ZM18, JM22, and LM6) with different responses to nano-ZnO stress were selected, depending on previous nano-ZnO stress trials with 120 wheat cultivars in China. The results found that nano-ZnO exposure reduced chlorophyll concentrations and photosynthetic electron transport efficiency, along with the depressed carbohydrate metabolism enzyme activities, and limited plant growth. Meanwhile, the genotypic variation in photosynthetic carbon assimilation under nano-ZnO stress was found in wheat plants. Wheat cv. JM22 and LM6 possessed relatively lower Zn concentrations and higher leaf nitrogen per area, less reductions in their net photosynthetic rate, a maximum quantum yield of the PS II (Fv/Fm), electron transport flux per cross-section (ETo/CSm), trapped energy flux per cross-section (TRo/CSm), and total soluble sugar and sucrose concentrations under nano-ZnO stress, showing a better tolerance to nano-ZnO stress than wheat cv. TS1 and ZM18. In addition, the chlorophyll a fluorescence parameters Fv/Fm, ETo/CSm, and TRo/CSm could be used to rapidly screen wheat varieties resistant to nano-ZnO stress. The results here provide a new approach for solving the issues of crop yield decline in regions polluted by heavy metal nanoparticles and promoting the sustainable utilization of farmland with heavy metal pollution. Full article
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Graphical abstract
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<p>Net photosynthetic rate (An, (<b>a</b>)) and relative chlorophyll content (SPAD, (<b>b</b>)) in different wheat cultivars as affected by zinc oxide nanoparticles (nano-ZnO). Vertical bars indicate mean ± SE (<span class="html-italic">n</span> = 3). Non-nano-ZnO stress, Control; nano-ZnO stress, Nano-ZnO; wheat cultivars, <span class="html-italic">TS1</span>, <span class="html-italic">ZM18</span>, <span class="html-italic">JM22</span>, and <span class="html-italic">LM6</span>; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001; ns, no significant difference.</p>
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<p>Changes in the maximum quantum yield of the PS II (Fv/Fm, (<b>a</b>)), electron transport flux per cross-section (ETo/CSm, (<b>b</b>)), trapped energy flux per cross-section (TRo/CSm, (<b>c</b>)), and performance index on absorption basis (PIabs, (<b>d</b>)) in different wheat cultivars as affected by zinc oxide nanoparticles (nano-ZnO). Vertical bars indicate mean ± SE (<span class="html-italic">n</span> = 3). Non-nano-ZnO stress, Control; nano-ZnO stress, Nano-ZnO; wheat cultivars, <span class="html-italic">TS1</span>, <span class="html-italic">ZM18, JM22</span>, and <span class="html-italic">LM6</span>; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, and <span class="html-italic">p</span> &lt; 0.001; ns, no significant difference.</p>
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<p>Activities of initial Rubisco (<b>a</b>) and total Rubisco (<b>b</b>), Rubisco activation (<b>c</b>), activities of Ca<sup>2+</sup>-ATPase (<b>d</b>) and Mg<sup>2+</sup>-ATPase (<b>e</b>), and ATP concentration (<b>f</b>) in different wheat cultivars as affected by zinc oxide nanoparticles (nano-ZnO). Vertical bars indicate mean ± SE (<span class="html-italic">n</span> = 3). Non-nano-ZnO stress, Control; nano-ZnO stress, Nano-ZnO; and wheat cultivars, <span class="html-italic">TS1</span>, <span class="html-italic">ZM18</span>, <span class="html-italic">JM22</span>, and <span class="html-italic">LM6</span>; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001; ns, no significant difference.</p>
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<p>Heat map of key carbohydrate metabolism enzyme activities in different wheat cultivars as affected by zinc oxide nanoparticles (nano-ZnO). The difference in activity for a given enzyme among the different treatments was normalized and converted to a color scale. Vertical bars indicate mean ± SE (<span class="html-italic">n</span> = 3). Non-nano-ZnO stress, Control; nano-ZnO stress, Nano-ZnO; wheat cultivars, <span class="html-italic">TS1</span>, <span class="html-italic">ZM18</span>, <span class="html-italic">JM22</span>, and <span class="html-italic">LM6</span>; cytoplasmic invertase, cytInv; hexokinase, HXK; fructokinase, FK; phosphoglucomutase, PGM; UDP-glucose pyrophosphyorylase, UGPase; ADP-glucose pyrophosphorylase, AGPase; glucose-6-phosphate dehydrogenase, G6PDH; phosphoglucoisomerase, PGI; phosphofructokinase, PFK; sucrose synthase, Susy; cell wall invertase, cwInv; aldolase, Ald; and vacuolar invertase, vacInv.</p>
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<p>The concentrations of leaf nitrogen per area (<b>a</b>), leaf total soluble sugar (<b>b</b>), shoot dry matter (Shoot DM, (<b>c</b>)), leaf Zn (<b>d</b>), leaf sucrose (<b>e</b>), and root dry matter (Root DM, (<b>f</b>)) in different wheat cultivars as affected by zinc oxide nanoparticles (nano-ZnO). Vertical bars indicate mean ± SE (<span class="html-italic">n</span> = 3). Non-nano-ZnO stress, Control; nano-ZnO stress, Nano-ZnO; and wheat cultivars, <span class="html-italic">TS1</span>, <span class="html-italic">ZM18</span>, <span class="html-italic">JM22</span>, <span class="html-italic">LM6</span>; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001; ns, no significant difference.</p>
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<p>A comprehensive description of the response of wheat plants (e.g., <span class="html-italic">ZM18</span>) to nano-ZnO stress. The green up and red down arrows indicate positive and negative effects of nano-ZnO on the physiological processes of wheat plants. Hexokinase, HXK; phosphoglucoisomerase, PGI; glucose-6-phosphate dehydrogenase, G6PDH; fructokinasem, FK; phosphofructokinase, PFK; phosphoglucomutase, PGM; UDP-glucose, pyrophosphyorylase, UGPase; aldolase, Ald; ADP-glucose pyrophosphorylase, AGPase; net photosynthetic rate, An; stomatal conductance, g<sub>s</sub>; maximum quantum efficiency of photosystem II, F<sub>v</sub>/F<sub>m</sub>; photosystem I, PSI; photosystem II, PS II; ribulose-1,5-bisphosphate, RuBP; adenosine diphosphate, ADP; adenosine triphosphate, ATP; and nicotinamide adenine dinucleotide phosphate, NADPH.</p>
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17 pages, 2390 KiB  
Article
Different Source Contributions of Bioactive Trace Metals in Sinking Particles in the Northern South China Sea
by Weiying Li, Jingjing Zhang, Hongliang Li, Zezhou Wu, Xingju He, Lihua Ran, Martin G. Wiesner and Jianfang Chen
J. Mar. Sci. Eng. 2023, 11(11), 2125; https://doi.org/10.3390/jmse11112125 - 7 Nov 2023
Viewed by 1417
Abstract
Time-series samples intercepted via three synchronized moored sediment traps, deployed at 1000 m, 2150 m, and 3200 m in the northern South China Sea (NSCS) during June 2009–May 2010, were analyzed to quantify the bioactive trace metal fluxes in sinking particles and investigate [...] Read more.
Time-series samples intercepted via three synchronized moored sediment traps, deployed at 1000 m, 2150 m, and 3200 m in the northern South China Sea (NSCS) during June 2009–May 2010, were analyzed to quantify the bioactive trace metal fluxes in sinking particles and investigate their different source contributions. Iron (Fe) primarily originated from lithogenic sources. Manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), and zinc (Zn) exhibited various degrees of enrichment over their continental crustal ratios. Since the sources of bioactive trace metals in sinking particles can be divided into lithogenic, biogenic, and excess fractions, mass conservation calculations were used to quantify the contribution of each source. The results showed that Fe, Mn, and Co had extremely low biogenic proportions (0.1–3.3%), while Ni, Cu, and Zn had higher proportions (2.7–17.3%), with the biogenic fraction decreasing with the depth. Moreover, excess sources accounted for a significant proportion of Mn (68–75%), Co (34–54%), Ni (60–62%), Cu (59–74%), and Zn (56–65%) in sinking particles at the three sampling depths. The excess fractions of Mn, Co, and Cu in sinking particles can be affected by authigenic particles. This is supported by their similar scavenging-type behavior, as observed via the increase in their fluxes and enrichment patterns with the increasing depth. Furthermore, the excess fractions of Ni, Cu, and Zn may have significant contributions from anthropogenic sources. The variability of Fe in sinking particles was mainly controlled via lithogenic matter. Notably, organic matter and opal were found to be pivotal carriers in the export of excess bioactive trace metals (Mn, Co, Ni, and Cu) via the water column, accompanied with the elevated ballast effect of lithogenic matter with the depth. However, the transportation of excess Zn was more complicated due to the intricate processes involved in Zn dynamics. These findings contribute to our understanding of the sources and transport mechanisms of bioactive trace metals in the marine environment. Full article
(This article belongs to the Special Issue Biogeochemistry of Trace Elements in the Marine Environment)
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<p>The locations of the SCS-N sediment trap mooring station (red circle, 18.5° N, 116° E, water depth 3736 m) and the adjacent South East Asian Time-series Study (SEATS) station (blue square, 18° N, 116° E, water depth 3783 m). On the right of the map is the diagram of the three synchronized traps array at the SCS-N station.</p>
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<p>Correlations of bioactive trace metal fluxes with Al fluxes in sinking particles. The ratios of bioactive trace metal to Al in crust and aerosols are shown in <a href="#app1-jmse-11-02125" class="html-app">Table S1</a>.</p>
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<p>Enrichment factor values of varying bioactive trace metals in sinking particles collected from &lt;160 m [<a href="#B33-jmse-11-02125" class="html-bibr">33</a>], 1000 m, 2150 m, and 3200 m in the NSCS. The ends of the box, the ends of the whiskers, and the line across each box indicate the 25th and 75th percentiles, the 5th and 95th percentiles, and the median, respectively; the open squares and the filled diamonds indicate the arithmetic mean and the data outliers, respectively.</p>
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<p>The results of principal components analysis of total trace metal concentrations and major component concentrations in sinking particles at (<b>a</b>) 1000 m, (<b>b</b>) 2150 m, and (<b>c</b>) 3200 m depths. Factor 1 (lithogenic matter) and Factor 2 (organic matter) for the first two major components.</p>
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<p>Bioactive trace metal fluxes in sinking particles at 1000 m, 2150 m, and 3200 m from lithogenic (Litho.), biogenic (Bio.), and excess (Exc.) sources.</p>
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<p>Schematic depiction of the transportation of bioactive trace metals in the northern South China Sea.</p>
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24 pages, 4615 KiB  
Article
Influences of Yogurt with Functional Ingredients from Various Sources That Help Treat Leaky Gut on Intestinal Barrier Dysfunction in Caco-2 Cells
by Ricardo S. Aleman, Ryan Page, Roberto Cedillos, Ismael Montero-Fernández, Jhunior Abraham Marcia Fuentes, Douglas W. Olson and Kayanush Aryana
Pharmaceuticals 2023, 16(11), 1511; https://doi.org/10.3390/ph16111511 - 24 Oct 2023
Cited by 5 | Viewed by 2182
Abstract
The impact of yogurts made with starter culture bacteria (L. bulgaricus and S. thermophilus) and supplemented with ingredients (maitake mushrooms, quercetin, L-glutamine, slippery elm bark, licorice root, N-acetyl-D-glucosamine, zinc orotate, and marshmallow root) that can help treat leaky gut were investigated [...] Read more.
The impact of yogurts made with starter culture bacteria (L. bulgaricus and S. thermophilus) and supplemented with ingredients (maitake mushrooms, quercetin, L-glutamine, slippery elm bark, licorice root, N-acetyl-D-glucosamine, zinc orotate, and marshmallow root) that can help treat leaky gut were investigated using the Caco-2 cell monolayer as a measure of intestinal barrier dysfunction. Milk from the same source was equally dispersed into nine pails, and the eight ingredients were randomly allocated to the eight pails. The control had no ingredients. The Caco-2 cells were treated with isoflavone genistein (negative control) and growth media (positive control). Inflammation was stimulated using an inflammatory cocktail of cytokines (interferon-γ, tumor necrosis factor-α, and interleukin-1β) and lipopolysaccharide. The yogurt without ingredients (control yogurt) was compared to the yogurt treatments (yogurts with ingredients) that help treat leaky gut. Transepithelial electrical resistance (TEER) and paracellular permeability were measured to evaluate the integrity of the Caco-2 monolayer. Transmission electron microscopy (TEM), immunofluorescence microscopy (IM), and real-time quantitative polymerase chain reaction (RTQPCR) were applied to measure the integrity of tight junction proteins. The yogurts were subjected to gastric and intestinal digestion, and TEER was recorded. Ferrous ion chelating activity, ferric reducing potential, and DPPH radical scavenging were also examined to determine the yogurts’ antioxidant capacity. Yogurt with quercetin and marshmallow root improved the antioxidant activity and TEER and had the lowest permeability in fluorescein isothiocyanate (FITC)–dextran and Lucifer yellow flux among the yogurt samples. TEM, IM, and RTQPCR revealed that yogurt enhanced tight junction proteins’ localization and gene expression. Intestinal digestion of the yogurt negatively impacted inflammation-induced Caco-2 barrier dysfunction, while yogurt with quercetin, marshmallow root, maitake mushroom, and licorice root had the highest TEER values compared to the control yogurt. Yogurt fortification with quercetin, marshmallow root, maitake mushroom, and licorice root may improve functionality when dealing with intestinal barrier dysfunction. Full article
(This article belongs to the Section Natural Products)
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<p>(<b>a</b>) Caco-2 cell proliferation during incubation with different ratios of yogurt powder diluted with water. There were no significant (<span class="html-italic">p</span> &lt; 0.05) differences among treatments or over time in one-way ANOVA. Control yogurt = PY. Caco-2 cells treated with phosphate-buffered saline (PBS) were used as negative control (black bars). (<b>b</b>) Effect of powdered yogurt dilutions on barrier function for differentiated Caco-2. Powdered yogurt was resuspended in growth media at 1:25, 1:50, 1:75, and 1:100 dilutions before application to cell monolayers. TEER was measured after 48 h. <sup>ABC</sup> Different letters indicate significant (<span class="html-italic">p</span> &lt; 0.05) differences among treatments for TEER values in one-way ANOVA followed by Tukey test.</p>
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<p>Yogurt samples (Ys) raise the TEER of Caco-2 cell monolayers exposed to an inflammatory stimulus. Caco-2 cells were treated with a control (growth media), and an inflammatory stimulus (I) consisting of interleukin-1β (IL-1β, 25 ng mL<sup>−1</sup>), tumor necrosis factor-α (TNF-α, 50 ng mL<sup>−1</sup>), and interferon-gamma (IFN-γ, 50 ng mL<sup>−1</sup>) or I and Ys from 0 to 72 h. Zn = zinc orotate, Q = quercetin, NAG = N-acetyl-D-glucosamine, MM = maitake mushrooms, LG = L-glutamine, SEB = slippery elm bark, PY = control Yogurt, MR = marshmallow root, and LR = licorice root.</p>
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<p>The flux of (<b>A</b>) fluorescein isothiocyanate–dextran (FD) and (<b>B</b>) Lucifer yellow (LY) in differentiated Caco-2 cells exposed to vehicle control (C), inflammatory stimulus (I), or inflammatory stimulus and CYs for 15 h. LG = L-glutamine, LR = licorice root, MM = maitake mushrooms, SEB = slippery elm bark, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, PY = control yogurt, Q = quercetin, and Zn = zinc orotate.</p>
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<p>TEM micrographs of yogurt samples, inflammatory stimulus (IS), and growth media (C) in differentiated Caco-2 cells after 48 h. Pictures were taken under approximately 90 nm<sup>2</sup>. Yogurt samples: Q = quercetin, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, LG = L-glutamine, ZN = zinc orotate, MM = maitake mushrooms, LR = licorice root, SEB = slippery elm bark, and CY = control yogurt. Red arrow indicates the black streaks (tight junctions).</p>
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<p>ZO-1 immunofluorescence microscopy pictures of yogurt samples, inflammatory stimulus (IS), and growth media (C) in differentiated Caco-2 cells after 48 h. Pictures are taken under approximately 70 nm<sup>2</sup>. Yogurt samples: Q = quercetin, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, LG = L-glutamine, ZN = zinc orotate, MM = maitake mushrooms, LR = licorice root, SEB = slippery elm bark, and CY = control yogurt. Red arrow indicates the green pattern (ZO-1 tight junction).</p>
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<p>Occludin-1 immunofluorescence microscopy pictures of yogurt samples, inflammatory stimulus (IS), and growth media (C) in differentiated Caco-2 cells after 48 h. Pictures are taken under approximately 70 nm<sup>2</sup>. Yogurt samples: Q = quercetin, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, LG = L-glutamine, ZN = zinc orotate, MM = maitake mushrooms, LR = licorice root, SEB = slippery elm bark, and CY = control yogurt. Red arrow indicates the green pattern (occludin-1 tight junction).</p>
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<p>Immunofluorescence pictures of claudin-1 yogurt samples, inflammatory stimulus (IS), and growth media (C) in differentiated Caco-2 cells after 48 h. Pictures are taken under approximately 70 nm<sup>2</sup>. Yogurt samples: Q = quercetin, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, LG = L-glutamine, ZN = zinc orotate, MM = maitake mushrooms, LR = licorice root, SEB = slippery elm bark, and CY = control yogurt. Red arrow indicates the green pattern (claudin-1 tight junction).</p>
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<p>(<b>A</b>) ZO-1, (<b>B</b>) occludin, and (<b>C</b>) claudin-1 relative intensity/cell of control (healthy and untreated cells with no inflammatory stimulus) and inflammatory stimulus (IS) (cells treated with only IL-1β, TNF-α, IFN-γ, LPS, and isoflavone genistein) yogurt samples: Q = quercetin, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, LG = L-glutamine, ZN = zinc orotate, MM = maitake mushrooms, LR = licorice root, SEB = slippery elm bark, and C = control yogurt with IS. <sup>a–c</sup> Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05 among control yogurt and C samples in one-way ANOVA followed by Tukey test.</p>
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<p>Relative expression of ZO-1, claudin-1, and occludin in different yogurt samples with growth media (C) and inflammation stimulus (IS). Yogurt samples were treated with IS and the following ingredients: LG = L-glutamine, LR = licorice root, MM = maitake mushrooms, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, PY = control yogurt, Q = quercetin, SEB = slippery elm bark, and Zn = zinc orotate. <sup>ABC</sup> Occludin relative expression means across the various ingredients not containing a common letter were significantly different (<span class="html-italic">p</span> &lt; 0.05). <sup>ABCD</sup> Claudin-1 relative expression means across the various ingredients not containing a common letter were significantly different (<span class="html-italic">p</span> &lt; 0.05). <sup>AB</sup> ZO-1 relative expression means across the various ingredients not containing a common letter were significantly different (<span class="html-italic">p</span> &lt; 0.05) in one-way ANOVA followed by Tukey test.</p>
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<p>In vitro simulated (<b>A</b>) gastric digestion and (<b>B</b>) intestinal digestion of yogurt. Differentiated Caco-2 cells were treated with a vehicle control (C), inflammatory stimulus (I) (25 ng mL<sup>−1</sup> IL-1β, 50 ng mL<sup>−1</sup> TNF-α, 50 ng mL<sup>−1</sup> IFN-γ, and 1 μg mL<sup>−1</sup> LPS) 0.03 g mL<sup>−1</sup>, and yogurt samples for 48 h. Yogurt samples were treated with IS and the following ingredients: LG = L-glutamine, LR = licorice root, MM = maitake mushrooms, MR = marshmallow root, NAG = N-acetyl-D-glucosamine, PY = control yogurt, Q = quercetin, SEB = slippery elm bark, and Zn = zinc orotate. Values are means ± SD, with n = 7 for each treatment. <sup>abcd</sup> Means not containing a common letter were significantly different, as determined via one-way ANOVA followed by Tukey-HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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17 pages, 3600 KiB  
Article
Engineering of Multifunctional Nanocomposite Membranes for Wastewater Treatment: Oil/Water Separation and Dye Degradation
by Hamouda M Mousa, Mostafa M. Sayed, Ibrahim M. A. Mohamed, M. S. Abd El-sadek, Emad Abouel Nasr, Mohamed A. Mohamed and Mohamed Taha
Membranes 2023, 13(10), 810; https://doi.org/10.3390/membranes13100810 - 25 Sep 2023
Cited by 2 | Viewed by 2105
Abstract
Multifunctional membrane technology has gained tremendous attention in wastewater treatment, including oil/water separation and photocatalytic activity. In the present study, a multifunctional composite nanofiber membrane is capable of removing dyes and separating oil from wastewater, as well as having antibacterial activity. The composite [...] Read more.
Multifunctional membrane technology has gained tremendous attention in wastewater treatment, including oil/water separation and photocatalytic activity. In the present study, a multifunctional composite nanofiber membrane is capable of removing dyes and separating oil from wastewater, as well as having antibacterial activity. The composite nanofiber membrane is composed of cellulose acetate (CA) filled with zinc oxide nanoparticles (ZnO NPs) in a polymer matrix and dipped into a solution of titanium dioxide nanoparticles (TiO2 NPs). Membrane characterization was performed using transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), and Fourier transform infrared (FTIR), and water contact angle (WCA) studies were utilized to evaluate the introduced membranes. Results showed that membranes have adequate wettability for the separation process and antibacterial activity, which is beneficial for water disinfection from living organisms. A remarkable result of the membranes’ analysis was that methylene blue (MB) dye removal occurred through the photocatalysis process with an efficiency of ~20%. Additionally, it exhibits a high separation efficiency of 45% for removing oil from a mixture of oil–water and water flux of 20.7 L.m−2 h−1 after 1 h. The developed membranes have multifunctional properties and are expected to provide numerous merits for treating complex wastewater. Full article
(This article belongs to the Special Issue Development and Application of Membrane Separation Processes)
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<p>Illustrative diagram shows nanocomposite membrane fabrication steps: electrospinning setup component, dip coating of TiO<sub>2</sub> NPs, membrane drying, and calcination.</p>
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<p>FESEM analyses show membrane morphology: (<b>a</b>) CA, (<b>b</b>) CA/ZnO NPs, (<b>c</b>) CA/ZnO @ TiO<sub>2</sub> NPs, and (<b>d</b>) calcined CA/ZnO @ TiO<sub>2</sub> NPs.</p>
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<p>(<b>a</b>,<b>b</b>) Characterization of CA/ZnO @ TiO<sub>2</sub> NPs membrane of single nanofiber, (<b>c</b>,<b>d</b>) calcined CA/ZnO @ TiO<sub>2</sub> NPs showed TEM images of composite nanoparticles and EDS mapping.</p>
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<p>FTIR analysis of the different developed membranes’ conditions.</p>
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<p>(<b>i</b>) Membrane wettability using WCA: (<b>a</b>) CA, (<b>b</b>) CA/ZnO NPs, and (<b>c</b>) CA/ZnO @ TiO<sub>2</sub> NP. (<b>ii</b>) antibacterial test of the control and CA/ZnO @ TiO<sub>2</sub> NPs membrane.</p>
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<p>Membranes’ photocatalytic performance using MB dye. Control is referring to MB degradation without any catalyst materials.</p>
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<p>Plots of ln(C/C0) versus time for the prepared photocatalyst membrane against degradation of MB.</p>
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<p>Photocatalytic process and electron transport of a composite CA/ZnO @ TiO<sub>2</sub> membrane under direct sunlight.</p>
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<p>Membrane’s water flux and oil separation efficiency of modified CA/ZnO @ TiO<sub>2</sub> NPs membrane.</p>
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<p>Optical microscope photographs of oily wastewater before and after separation were recorded for three distinct membranes. (<b>a</b>) oil/water emulsion before separation (<b>b</b>) CA, (<b>c</b>) CA/ZnO NPs, and (<b>d</b>) CA/ZnO @ TiO<sub>2</sub> NPs. Microscopic images at a magnification of 10×.</p>
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12 pages, 5595 KiB  
Article
Bioavailability of Cd in Agricultural Soils Evaluated by DGT Measurements and the DIFS Model in Relation to Uptake by Rice and Tea Plants
by Yubo Wen, Yuanyuan Wang, Chunjun Tao, Wenbing Ji, Shunsheng Huang, Mo Zhou and Xianqiang Meng
Agronomy 2023, 13(9), 2378; https://doi.org/10.3390/agronomy13092378 - 13 Sep 2023
Cited by 1 | Viewed by 1548
Abstract
The elevated accumulation of cadmium (Cd) in rice (Oryza sativa L.) and tea (Camellia sinensis L.) grown in agricultural soils may lead to a variety of adverse health effects. This study collected and analyzed crop samples along with paired rhizosphere soil [...] Read more.
The elevated accumulation of cadmium (Cd) in rice (Oryza sativa L.) and tea (Camellia sinensis L.) grown in agricultural soils may lead to a variety of adverse health effects. This study collected and analyzed crop samples along with paired rhizosphere soil samples from 61 sites in Cd-contaminated regions in Anhui Province, China. The findings revealed that both the diffusive gradients in thin-films (DGT) and soil solution were capable of effectively predicting Cd contents in crops. Conventional chemical extraction methods were inappropriate to evaluate the bioavailability of Cd. However, the effective concentrations (CE) corrected by the DGT-induced fluxes in soils (DIFS) model exhibited the strongest correlation with crop Cd contents. Except for CE, various measurement methods yielded better results for predicting Cd bioavailability in tea compared to rice. Pearson’s correlation analysis and the random forest (RF) model identified the key influencing factors controlling Cd uptake by rice and tea, including pH, soil texture, and contents of zinc (Zn) and selenium (Se) in soils, which antagonize Cd. To reduce the potential health risk from rice and tea, the application of soil liming and/or Se-oxidizing bacteria was expected to be an effective management strategy. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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<p>Location of 61 sampling sites in Shitai County, China.</p>
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<p>Distributions of Cd concentrations in (<b>a</b>) F1–F7 fractions by sequential extractions from soils, and in (<b>b</b>) rice grains and tea leaves.</p>
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<p>Relationships between Cd concentrations in rice grains/tea leaves and (<b>a</b>) soil solution Cd (<span class="html-italic">C</span><sub>solu</sub>), (<b>b</b>) effective concentration of Cd (<span class="html-italic">C</span><sub>E</sub>) in soils.</p>
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<p>Factor importance derived from the random forest (RF) model for bioconcentration of Cd concentrations in (<b>a</b>) rice grains (<span class="html-italic">BCF</span><sub>rice</sub>) and (<b>b</b>) tea leaves (<span class="html-italic">BCF</span><sub>tea</sub>).</p>
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17 pages, 3394 KiB  
Article
Photosynthetic Efficiency of Marchantia polymorpha L. in Response to Copper, Iron, and Zinc
by Carlo Sorce, Erika Bellini, Florinda Bacchi and Luigi Sanità di Toppi
Plants 2023, 12(15), 2776; https://doi.org/10.3390/plants12152776 - 26 Jul 2023
Cited by 5 | Viewed by 1636
Abstract
Metal micronutrients are essential for plant nutrition, but their toxicity threshold is low. In-depth studies on the response of light-dependent reactions of photosynthesis to metal micronutrients are needed, and the analysis of chlorophyll a fluorescence transients is a suitable technique. The liverwort Marchantia [...] Read more.
Metal micronutrients are essential for plant nutrition, but their toxicity threshold is low. In-depth studies on the response of light-dependent reactions of photosynthesis to metal micronutrients are needed, and the analysis of chlorophyll a fluorescence transients is a suitable technique. The liverwort Marchantia polymorpha L., a model organism also used in biomonitoring, allowed us to accurately study the effects of metal micronutrients in vivo, particularly the early responses. Gametophytes were treated with copper (Cu), iron (Fe) or zinc (Zn) for up to 120 h. Copper showed the strongest effects, negatively affecting almost the entire light phase of photosynthesis. Iron was detrimental to the flux of energy around photosystem II (PSII), while the acceptor side of PSI was unaltered. The impact of Fe was milder than that of Cu and in both cases the structures of the photosynthetic apparatus that resisted the treatments were still able to operate efficiently. The susceptibility of M. polymorpha to Zn was low: although the metal affected a large part of the electron transport chain, its effects were modest and short-lived. Our results may provide a contribution towards achieving a more comprehensive understanding of response mechanisms to metals and their evolution in plants, and may be useful for supporting the development of biomonitoring techniques. Full article
(This article belongs to the Special Issue Heavy Metal Tolerance in Plants and Algae)
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Figure 1
<p>Effects of the exposure to 200 µM Cu for 6 (<b>a</b>,<b>b</b>), 14 (<b>c</b>,<b>d</b>), 24 (<b>g</b>,<b>h</b>), 72 (<b>i</b>,<b>j</b>) and 120 h (<b>k</b>,<b>l</b>), and to 80 µM Cu for 24 h (<b>e</b>,<b>f</b>) in dark-adapted <span class="html-italic">M. polymorpha</span> gametophytes. Induction transients of ChlF (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>) and spider plots (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>l</b>) of parameters of JIP test (described in <a href="#plants-12-02776-t001" class="html-table">Table 1</a>), normalized to the values of the control, which were set as one. Black lines = control; red lines = 200 µM Cu; orange line = 80 µM Cu. Only those parameters that differed significantly from the control (<span class="html-italic">p</span> &lt; 0.05) are shown. All values are the mean of nine replications.</p>
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<p>Effects of the exposure to 300 µM Fe for 6 (<b>a</b>,<b>b</b>), 14 (<b>c</b>,<b>d</b>), 24 (<b>e</b>,<b>f</b>), 72 (<b>g</b>,<b>h</b>) and 120 h (<b>i</b>,<b>j</b>), in dark-adapted <span class="html-italic">M. polymorpha</span> gametophytes. Induction transients of ChlF (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>) and spider plots (<b>d</b>,<b>h</b>,<b>j</b>) or bar charts (<b>b</b>,<b>f</b>) of parameters of JIP test (described in <a href="#plants-12-02776-t001" class="html-table">Table 1</a>); values in spider plots were normalized to those of the control, which were set as one. Black lines (or bars) = control; red lines (or bars) = 300 µM Fe. Only those parameters that differed significantly from the control (*, <span class="html-italic">p</span> &lt; 0.05) are shown. All values are the mean of nine replications.</p>
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<p>Effects of the exposure to 200 µM Fe for 24 (<b>a</b>,<b>b</b>) and 72 (<b>c</b>,<b>d</b>) h, in dark-adapted <span class="html-italic">M. polymorpha</span> gametophytes. Induction transients of ChlF (<b>a</b>,<b>c</b>) and spider plot (<b>b</b>) or bar chart (<b>d</b>) of parameters of JIP test (described in <a href="#plants-12-02776-t001" class="html-table">Table 1</a>); values in spider plot were normalized to those of the control, which were set as one. Black line (or bar) = control; orange line (or bar) = 200 µM Fe. Only those parameters that differed significantly from the control (*, <span class="html-italic">p</span> &lt; 0.05) are shown. All values are the mean of nine replications.</p>
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<p>Effects of the exposure to 80 µM Zn for 72 h (<b>a</b>,<b>b</b>) and to 200 µM Zn for 24 h (<b>c</b>,<b>d</b>), in dark-adapted <span class="html-italic">M. polymorpha</span> gametophytes. Induction transients of ChlF (<b>a</b>,<b>c</b>) and spider plot (<b>b</b>) or bar chart (<b>d</b>) of parameters of JIP test (described in <a href="#plants-12-02776-t001" class="html-table">Table 1</a>); values in spider plot were normalized to those of the control, which were set as one. Black line (or white bar) = control; pale blue line = 80 µM Zn; dark blue bar = 200 µM Zn. Only those parameters that differed significantly from the control (*, <span class="html-italic">p</span> &lt; 0.05) are shown. All values are the mean of nine replications.</p>
Full article ">Figure 5
<p>Heat map representing relative variability of the analyzed photosynthesis-related parameters, following treatment of <span class="html-italic">M. polymorpha</span> gametophytes with 200 µM Cu. Red is for lower values and green for the highest values. All data were first normalized to bring the value of the parameters in the range 1–100.</p>
Full article ">Figure 6
<p>Heat map representing relative variability of the analyzed photosynthesis-related parameters, following treatment of <span class="html-italic">M. polymorpha</span> gametophytes with 300 µM Fe. Red is for lower values and green for the highest values. All data were first normalized to bring the value of the parameters in the range 1–100.</p>
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