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15 pages, 9791 KiB  
Article
Synthesis of BiOCl Colloidal Particles by Laser Ablation of Solids in Liquids
by Abril Vázquez Francisco, Armando Pérez-Centeno, Laura P. Rivera and José G. Quiñones-Galván
Surfaces 2024, 7(4), 864-878; https://doi.org/10.3390/surfaces7040057 (registering DOI) - 15 Oct 2024
Abstract
Colloidal bismuth nanoparticles (NPs) were synthesized in sodium chloride (NaCl) solutions at different concentrations using the laser ablation of solids in liquids technique. The obtained materials were characterized using various techniques. The morphology, size, and crystalline phases were determined through scanning electron microscopy [...] Read more.
Colloidal bismuth nanoparticles (NPs) were synthesized in sodium chloride (NaCl) solutions at different concentrations using the laser ablation of solids in liquids technique. The obtained materials were characterized using various techniques. The morphology, size, and crystalline phases were determined through scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and Fourier-transform infrared spectroscopy (FTIR). The optical properties were studied using UV–visible spectroscopy, employing the Tauc method to determine the band gap of the particles. Two types of materials were identified depending on the NaCl concentration: spherical nanoparticles of α-Bi2O3 and the coexistence of α-Bi2O3 and BiOCl particles with irregular morphology. NaCl concentrations higher than 11.6% enable the coexistence of α-Bi2O3 and BiOCl. The photocatalytic response of the colloids was evaluated by the degrading rhodamine B under visible light irradiation. The sample synthesized at a NaCl concentration of 31.6% showed the best photocatalytic activity. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Schematic illustration of the synthesis process and (<b>b</b>) nanoparticle colloidal solution obtained.</p>
Full article ">Figure 2
<p>Bismuth nanoparticles after the synthesis: (<b>a</b>) SEM micrograph, (<b>b</b>) TEM micrograph, and (<b>c</b>) UV–vis spectrum.</p>
Full article ">Figure 3
<p>UV–vis spectra (<b>a</b>) and Tauc plots (<b>b</b>) of the samples synthesized at different concentrations of NaCl.</p>
Full article ">Figure 4
<p>(<b>a</b>) SEM and (<b>b</b>) TEM micrographs of bismuth NPs in 3% NaCl solution.</p>
Full article ">Figure 5
<p>(<b>a</b>) SEM and (<b>b</b>) TEM micrographs of bismuth NPs in 11.6% NaCl solution.</p>
Full article ">Figure 6
<p>(<b>a</b>) SEM and (<b>b</b>) TEM micrographs of bismuth NPs in 31.6% NaCl solution.</p>
Full article ">Figure 6 Cont.
<p>(<b>a</b>) SEM and (<b>b</b>) TEM micrographs of bismuth NPs in 31.6% NaCl solution.</p>
Full article ">Figure 7
<p>Survey XPS spectra of the samples synthesized with 3%, 11.6%, and 31.6% NaCl.</p>
Full article ">Figure 8
<p>High resolution XPS spectra of Bi 4f.</p>
Full article ">Figure 9
<p>High resolution XPS spectra of Cl 2p.</p>
Full article ">Figure 10
<p>High resolution XPS spectra of O 1s.</p>
Full article ">Figure 11
<p>Raman spectra of the samples synthesized at different NaCl concentrations showing the following: (<b>a</b>) the full Raman spectrum, (<b>b</b>) magnification of the Raman bands for Bi<sub>2</sub>O<sub>3</sub>, and BiOCl.</p>
Full article ">Figure 12
<p>FT-IR spectra of the samples.</p>
Full article ">Figure 13
<p>Rhodamine B+Bi NPS solutions: (<b>a</b>) before being irradiated with visible light, (<b>b</b>) after 720 min of irradiation.</p>
Full article ">Figure 14
<p>Photocatalytic degradation of rhodamine B using bismuth NPs synthesized in 3%, 11.6%, and 31.6% of NaCl, under visible light radiation.</p>
Full article ">
26 pages, 2596 KiB  
Article
A Parameter-Adaptive Method for Primary Frequency Regulation of Grid-Forming Direct-Drive Wind Turbines
by Siqi Hu, Keqilao Meng and Zikai Wu
Sensors 2024, 24(20), 6651; https://doi.org/10.3390/s24206651 (registering DOI) - 15 Oct 2024
Abstract
When wind turbines contribute to system frequency support using virtual synchronous generator (VSG) control, conventional VSG methods often fall short of meeting operational demands, particularly in terms of inertia and frequency support. In this study, considering both the frequency regulation and dynamic performance [...] Read more.
When wind turbines contribute to system frequency support using virtual synchronous generator (VSG) control, conventional VSG methods often fall short of meeting operational demands, particularly in terms of inertia and frequency support. In this study, considering both the frequency regulation and dynamic performance of VSG, a novel parameter design method that enhances frequency modulation capabilities is proposed in this paper. Initially, VSG control is integrated into the grid-side converter of a direct-drive permanent magnet synchronous generator (D-DPMSG) wind turbine. A small-signal model of the D-DPMSG-VSG active power is then formulated to analyze how the moment of inertia and damping coefficient impact system stability. Subsequently, ensuring that system parameter constraints are met, the key parameters of VSG are adaptively designed to dynamically adjust the system’s frequency and output power during transient responses. Finally, simulation results based on D-DPMSG-VSG in MATLAB/Simulink validated the feasibility, effectiveness, and advantages of the proposed parameter-adaptive VSG control strategy for enhancing the frequency modulation (FM) performance of wind turbines. Full article
(This article belongs to the Section Industrial Sensors)
21 pages, 5922 KiB  
Article
A Size Effect Model Combining Both Surface Effects and the Fracture Process Zone (FPZ) for Rocks under Uniaxial Compression
by Yang Liu, Xiaoyu Liu, Huimei Zhang and Fengbo Zhu
Appl. Sci. 2024, 14(20), 9413; https://doi.org/10.3390/app14209413 (registering DOI) - 15 Oct 2024
Abstract
Developing a size effect model that can encompass the surface effect and the fracture process zone (FPZ) is still challenging. Here, a combined size effect model (CSE model) is formulated by integrating the surface effect size model and the size effect model of [...] Read more.
Developing a size effect model that can encompass the surface effect and the fracture process zone (FPZ) is still challenging. Here, a combined size effect model (CSE model) is formulated by integrating the surface effect size model and the size effect model of fracture mechanics (SEFM model) associated with the FPZ for rocks under compression. Parametric studies indicate that an increased volume fraction of the interior zone as the sample size increases is responsible for the anomalous size effect (ASE). The normal size effect (NSE) is a result of the decrease in the surface layer’s volume fraction and the interior zone’s nominal strength as the sample size increases. Moreover, the mixed type ASE–NSE is caused by the competition among the reduced surface volume fraction, the weakened interior zone strength, and the increased interior zone volume fraction as the sample size increases. A validation study demonstrates that the CSE model accurately predicts the ASE, the NSE, and the mixed type ASE–NSE. It was observed that the determination coefficient R2 of the CSE model is greater than that of the SEFM model for the NSE, equivalent to that of the size effect model of surface effects for the ASE and close to that of the improved USEL (IUSEL) for the mixed type ASE–NSE. Full article
(This article belongs to the Section Civil Engineering)
Show Figures

Figure 1

Figure 1
<p>The relationship between height–diameter ratio and nominal UCS under different friction coefficients [<a href="#B75-applsci-14-09413" class="html-bibr">75</a>].</p>
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<p>A schematic illustration of a rock consisting of an interior zone coated by a free surface layer under uniaxial compression.</p>
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<p>Macroscopic failure characteristics of Gosford sandstone samples of different sizes under uniaxial compression [<a href="#B12-applsci-14-09413" class="html-bibr">12</a>].</p>
Full article ">Figure 4
<p>Stress–strain curves of Gosford sandstone samples of different sizes under uniaxial compression: (<b>a</b>) 25 mm, (<b>b</b>) 50 mm, and (<b>c</b>) 96 mm [<a href="#B12-applsci-14-09413" class="html-bibr">12</a>].</p>
Full article ">Figure 5
<p>The size effect model of fracture mechanics considering the surface effect and the FPZ of the interior zone for a rock sample under uniaxial compression.</p>
Full article ">Figure 6
<p>Effect of <span class="html-italic">k</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">m</span> = 0.1, (<b>b</b>) <span class="html-italic">m</span> = 0.1, (<b>c</b>) <span class="html-italic">m</span> = 1.0, and (<b>d</b>) <span class="html-italic">m</span> = 100.</p>
Full article ">Figure 6 Cont.
<p>Effect of <span class="html-italic">k</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">m</span> = 0.1, (<b>b</b>) <span class="html-italic">m</span> = 0.1, (<b>c</b>) <span class="html-italic">m</span> = 1.0, and (<b>d</b>) <span class="html-italic">m</span> = 100.</p>
Full article ">Figure 7
<p>The effect of <span class="html-italic">t</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 0.1; (<b>b</b>) <span class="html-italic">k</span> = 1.0 and <span class="html-italic">m</span> = 0.1; (<b>c</b>) k = 2.0 and <span class="html-italic">m</span> = 0.1; and (<b>d</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 1.0.</p>
Full article ">Figure 7 Cont.
<p>The effect of <span class="html-italic">t</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 0.1; (<b>b</b>) <span class="html-italic">k</span> = 1.0 and <span class="html-italic">m</span> = 0.1; (<b>c</b>) k = 2.0 and <span class="html-italic">m</span> = 0.1; and (<b>d</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 1.0.</p>
Full article ">Figure 8
<p>Size effect of compressive strength of wastewater concrete under different numbers of freeze–thaw cycles: (<b>a</b>) <span class="html-italic">N</span> = 0 and (<b>b</b>) <span class="html-italic">N</span> = 50 [<a href="#B87-applsci-14-09413" class="html-bibr">87</a>].</p>
Full article ">Figure 9
<p>The effect of <span class="html-italic">a</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 0.1; (<b>b</b>) <span class="html-italic">k</span> = 1.0 and <span class="html-italic">m</span> = 0.1; (<b>c</b>) k = 2.0 and <span class="html-italic">m</span> = 0.1; and (<b>d</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 1.0.</p>
Full article ">Figure 9 Cont.
<p>The effect of <span class="html-italic">a</span> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 0.1; (<b>b</b>) <span class="html-italic">k</span> = 1.0 and <span class="html-italic">m</span> = 0.1; (<b>c</b>) k = 2.0 and <span class="html-italic">m</span> = 0.1; and (<b>d</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 1.0.</p>
Full article ">Figure 10
<p>The effect of <span class="html-italic">D</span><sub>0</sub> on the CSE model [Equation (17)] when (<b>a</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 0.1; (<b>b</b>) <span class="html-italic">k</span> = 1.0 and <span class="html-italic">m</span> = 0.1; (<b>c</b>) k = 2.0 and <span class="html-italic">m</span> = 0.1; and (<b>d</b>) <span class="html-italic">k</span> = 0.1 and <span class="html-italic">m</span> = 1.0.</p>
Full article ">Figure 11
<p>Comparison of the CSE model and the SEFM model for the no-flaw samples with data on the NSE: coal.</p>
Full article ">Figure 12
<p>Comparison of the CSE model and the size effect model of surface effects [Equation (4)] with data on the ASE: simulated granite.</p>
Full article ">Figure 13
<p>Comparison of the IUSEL and the CSE model with data on the mixed type ASE–NSE: (<b>a</b>) Gosford sandstone, (<b>b</b>) Pilton sandstone, (<b>c</b>) Pennant sandstone, (<b>d</b>) Burrington oolite limestone, (<b>e</b>) Hollington sandstone, (<b>f</b>) Gambier limestone, (<b>g</b>) artificial rock, (<b>h</b>) high-strength gypsum, and (<b>i</b>) limestone.</p>
Full article ">Figure 13 Cont.
<p>Comparison of the IUSEL and the CSE model with data on the mixed type ASE–NSE: (<b>a</b>) Gosford sandstone, (<b>b</b>) Pilton sandstone, (<b>c</b>) Pennant sandstone, (<b>d</b>) Burrington oolite limestone, (<b>e</b>) Hollington sandstone, (<b>f</b>) Gambier limestone, (<b>g</b>) artificial rock, (<b>h</b>) high-strength gypsum, and (<b>i</b>) limestone.</p>
Full article ">
22 pages, 1264 KiB  
Article
The Association between Gut Microbiota and Serum Biomarkers in Children with Atopic Dermatitis
by Irina G. Kalashnikova, Alexandra I. Nekrasova, Anna V. Korobeynikova, Maria M. Bobrova, German A. Ashniev, Sirozhdin Yu. Bakoev, Angelica V. Zagainova, Mariya V. Lukashina, Larisa R. Tolkacheva, Ekaterina S. Petryaikina, Alexander S. Nekrasov, Sergey I. Mitrofanov, Tatyana A. Shpakova, Lidiya V. Frolova, Natalya V. Bulanova, Ekaterina A. Snigir, Vladimir E. Mukhin, Vladimir S. Yudin, Valentin V. Makarov, Anton A. Keskinov and Sergey M. Yudinadd Show full author list remove Hide full author list
Biomedicines 2024, 12(10), 2351; https://doi.org/10.3390/biomedicines12102351 (registering DOI) - 15 Oct 2024
Abstract
Background. Currently, it is known that the gut microbiota plays an important role in the functioning of the immune system, and a rebalancing of the bacterial community can arouse complex immune reactions and lead to immune-mediated responses in an organism, in particular, the [...] Read more.
Background. Currently, it is known that the gut microbiota plays an important role in the functioning of the immune system, and a rebalancing of the bacterial community can arouse complex immune reactions and lead to immune-mediated responses in an organism, in particular, the development of atopic dermatitis (AD). Cytokines and chemokines are regulators of the innate and adaptive immune response and represent the most important biomarkers of the immune system. It is known that changes in cytokine profiles are a hallmark of many diseases, including atopy. However, it remains unclear how the bacterial imbalance disrupts the function of the immune response in AD. Objectives. We attempted to determine the role of gut bacteria in modulating cytokine pathways and their role in atopic inflammation. Methods. We sequenced the 16S rRNA gene from 50 stool samples of children aged 3–12 years who had confirmed atopic dermatitis, and 50 samples from healthy children to serve as a control group. To evaluate the immune status, we conducted a multiplex immunofluorescence assay and measured the levels of 41 cytokines and chemokines in the serum of all participants. Results. To find out whether changes in the composition of the gut microbiota were significantly associated with changes in the level of inflammatory cytokines, a correlation was calculated between each pair of bacterial family and cytokine. In the AD group, 191 correlations were significant (Spearman’s correlation coefficient, p ≤ 0.05), 85 of which were positive and 106 which were negative. Conclusions. It has been demonstrated that intestinal dysbiosis is associated with alterations in cytokine profiles, specifically an increase in proinflammatory cytokine concentrations. This may indicate a systemic impact of these conditions, leading to an imbalance in the immune system’s response to the Th2 type. As a result, atopic conditions may develop. Additionally, a correlation between known AD biomarkers (IL-5, IL-8, IL-13, CCL22, IFN-γ, TNF-α) and alterations in the abundance of bacterial families (Pasteurellaceae, Barnesiellaceae, Eubacteriaceae) was observed. Full article
21 pages, 18833 KiB  
Article
Mitigating Hyperglycaemic Oxidative Stress in HepG2 Cells: The Role of Carica papaya Leaf and Root Extracts in Promoting Glucose Uptake and Antioxidant Defence
by Mthokozisi Bongani Nxumalo, Nosipho Ntanzi, Hezekiel Mathambo Kumalo and Rene Bernadette Khan
Nutrients 2024, 16(20), 3496; https://doi.org/10.3390/nu16203496 (registering DOI) - 15 Oct 2024
Abstract
Background/Objectives: Diabetes often goes undiagnosed, with 60% of people in Africa unaware of their condition. Type 2 diabetes mellitus (T2DM) is associated with insulin resistance and is treated with metformin, despite the undesirable side effects. Medicinal plants with therapeutic potential, such as Carica [...] Read more.
Background/Objectives: Diabetes often goes undiagnosed, with 60% of people in Africa unaware of their condition. Type 2 diabetes mellitus (T2DM) is associated with insulin resistance and is treated with metformin, despite the undesirable side effects. Medicinal plants with therapeutic potential, such as Carica papaya, have shown promising anti-diabetic properties. This study explored the role of C. papaya leaf and root extracts compared to metformin in reducing hyperglycaemia-induced oxidative stress and their impact on liver function using HepG2 as a reference. Methods: The cytotoxicity was assessed through the MTT assay. At the same time, glucose uptake and metabolism (ATP and ∆Ψm) in HepG2 cells treated with C. papaya aqueous leaf and root extract were evaluated using a luminometry assay. Additionally, antioxidant properties (SOD2, GPx1, GSH, and Nrf2) were measured using qPCR and Western blot following the detection of MDA, NO, and iNOS, indicators of free radicals. Results: The MTT assay showed that C. papaya extracts did not exhibit toxicity in HepG2 cells and enhanced glucose uptake compared to the hyperglycaemic control (HGC) and metformin. The glucose levels in C. papaya-treated cells increased ATP production (p < 0.05), while the ∆Ψm was significantly increased in HGR1000-treated cells (p < 0.05). Furthermore, C. papaya leaf extract upregulated GPx1 (p < 0.05), GSH, and Nrf2 gene (p < 0.05), while SOD2 and Nrf2 proteins were reduced (p > 0.05), ultimately lowering ROS (p > 0.05). Contrarily, the root extract stimulated SOD2 (p > 0.05), GPx1 (p < 0.05), and GSH levels (p < 0.05), reducing Nrf2 gene and protein expression (p < 0.05) and resulting in high MDA levels (p < 0.05). Additionally, the extracts elevated NO levels and iNOS expression (p < 0.05), suggesting potential RNS activation. Conclusion: Taken together, the leaf extract stimulated glucose metabolism and triggered ROS production, producing a strong antioxidant response that was more effective than the root extract and metformin. However, the root extract, particularly at high concentrations, was less effective at neutralising free radicals as it did not stimulate Nrf2 production, but it did maintain elevated levels of SOD2, GSH, and GPx1 antioxidants. Full article
(This article belongs to the Section Phytochemicals and Human Health)
Show Figures

Figure 1

Figure 1
<p>The effects of <span class="html-italic">C. papaya</span> leaf and root extracts on cell viability and cytotoxicity in HepG2 cells induced with NG and hyperglycaemia. <span class="html-italic">C. papaya</span> leaf extract had fluctuating effects on cell viability, ranging from 85% to 103%, in both NG and hyperglycaemia (HG) treated cells (<b>A</b>,<b>B</b>), respectively. However, cell viability remained similar to the control (100%) in NG cells treated with <span class="html-italic">C. papaya</span> root (<b>C</b>). In contrast, the viability was increased to 110% in HG-treated cells (<b>D</b>). All experiments were conducted in triplicates.</p>
Full article ">Figure 2
<p>In hyperglycemic conditions, the concentration of <span class="html-italic">C. papaya</span> leaf and root extracts at 500 and 1000 µg/mL maintained cell viability similar to normal and HG controls. Metformin slightly reduced it to 81%.</p>
Full article ">Figure 3
<p>The levels of glucose in HGMet- and HGL500-treated cells were non-significantly decreased in relation to the HGC-treated cells, while were increased significantly in the HGL1000-, HGR500-, and HGR1000-treated cells (##, *** <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">Figure 4
<p>The effect of <span class="html-italic">C. papaya</span> on hyperglycaemia-induced HepG2 was shown through two measures: mitochondrial membrane potential and ATP activity levels. <span class="html-italic">C. papaya</span> treatment showed a slight increase in ∆Ψm except for HGR1000, where a significant increase was observed (<b>A</b>). Also, ATP levels in HG-treated HepG2 cells were significantly higher compared to HG-control (<b>B</b>) (###, *, **, ***, <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">Figure 5
<p>The effect of <span class="html-italic">C. papaya</span> leaf and root extracts on lipid peroxidation induced by HG (<b>A</b>) and nitrate/nitrite concentrations (<b>B</b>). Results showed that HGMet treatment led to a decrease in MDA levels, while <span class="html-italic">C. papaya</span> treatment resulted in an increased MDA concentration (<b>A</b>). Moreover, HGMet treatment significantly lowered nitrate/nitrile levels in cells, whereas <span class="html-italic">C. papaya</span> treatment led to a significant increase in nitrate/nitrile levels in HepG2 cells (<b>B</b>) (*, **, *** <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">Figure 6
<p>The presence of hyperglycaemia significantly reduced GSH levels from normal glucose to HGC. However, treatments effectively restored intracellular GSH levels above the HGC (<b>A</b>). The GSH/GSSG ratio decreased in HGMet-treated cells. At the same time, it increased in HG-induced cells treated with <span class="html-italic">C. papaya</span> leaf and root extracts, indicating the antioxidant effect of <span class="html-italic">C. papaya</span> extracts on GSH/GSSG in HG HepG2 cells (<b>B</b>) (##, ** <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">Figure 7
<p>The effects of <span class="html-italic">C. papaya</span> on the iNOS, SOD2, and GPx1 protein expression of hyperglycaemia-induced HepG2 cells (<b>A</b>) shows a non-significant increase in iNOS protein expression from the NG-control to the HG-control; however, a significant increase in the protein expression was seen in HGMet and <span class="html-italic">C. papaya</span>-treated cells compared to the HG-control. (<b>B</b>) SOD2 expression was upregulated in HG cells treated with metformin but downregulated in <span class="html-italic">C. papaya</span> HGL500 and HGL1000. SOD2 expression remained slightly higher in HGR-treated cells compared to HGC. (<b>C</b>) GPx1 protein expression decreased in HG-control when compared to the NG-control, while it was increased in HGMet and <span class="html-italic">C. papaya</span>-treated HepG2 (##, *, **, *** <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">Figure 8
<p>The gene expression of <span class="html-italic">Nrf2</span> was found to be lower in HGC compared to NGC, while its protein expression was significantly higher in HGC. However, when metformin, HGL500, and HGL1000 were administered, there was an increase in the gene expression of <span class="html-italic">Nrf2</span>, while the protein expression decreased as a result of the same treatments (<b>A</b>). On the other hand, treating hyperglycemic HepG2 cells with <span class="html-italic">C. papaya</span> root extract led to a downregulation of the Nrf2 gene expression, while HGR500 increased the protein expression. However, the protein expression was significantly reduced in cells treated with HGR1000 (<b>B</b>) (##, *, **, *** <span class="html-italic">p</span> &lt; 0.05, unpaired student <span class="html-italic">t</span>-test with Welch’s correction).</p>
Full article ">
22 pages, 2402 KiB  
Article
Chronic Low-Dose-Rate Radiation-Induced Persistent DNA Damage and miRNA/mRNA Expression Changes in Mouse Hippocampus and Blood
by Hong Wang, Salihah Lau, Amanda Tan and Feng Ru Tang
Cells 2024, 13(20), 1705; https://doi.org/10.3390/cells13201705 (registering DOI) - 15 Oct 2024
Abstract
Our previous study demonstrated that the acute high-dose-rate (3.3 Gy/min) γ-ray irradiation (γ-irradiation) of postnatal day-3 (P3) mice with 5 Gy induced depression and drastic neuropathological changes in the dentate gyrus of the hippocampus of adult mice. The present study investigated the effects [...] Read more.
Our previous study demonstrated that the acute high-dose-rate (3.3 Gy/min) γ-ray irradiation (γ-irradiation) of postnatal day-3 (P3) mice with 5 Gy induced depression and drastic neuropathological changes in the dentate gyrus of the hippocampus of adult mice. The present study investigated the effects of chronic low-dose-rate (1.2 mGy/h) γ-irradiation from P3 to P180 with a cumulative dose of 5 Gy on animal behaviour, hippocampal cellular change, and miRNA and mRNA expression in the hippocampus and blood in female mice. The radiation exposure did not significantly affect the animal’s body weight, and neuropsychiatric changes such as anxiety and depression were examined by neurobehavioural tests, including open field, light-dark box, elevated plus maze, tail suspension, and forced swim tests. Immunohistochemical staining did not detect any obvious loss of mature and immature neurons (NeuN and DCX) or any inflammatory glial response (IBA1, GFAP, and PDGFRα). Nevertheless, γH2AX foci in the stratum granulosum of the dentate gyrus were significantly increased, suggesting the chronic low-dose-rate irradiation induced persistent DNA damage foci in mice. miRNA sequencing and qRT-PCR indicated an increased expression of miR-448-3p and miR-361-5p but decreased expression of miR-193a-3p in the mouse hippocampus. Meanwhile, mRNA sequencing and qRT-PCR showed the changed expression of some genes, including Fli1, Hs3st5, and Eif4ebp2. Database searching by miRDB and TargetScan predicted that Fli1 and Hs3st5 are the targets of miR-448-3p, and Eif4ebp2 is the target of miR-361-5p. miRNA/mRNA sequencing and qRT-PCR results in blood showed the increased expression of miR-6967-3p and the decreased expression of its target S1pr5. The interactions of these miRNAs and mRNAs may be related to the chronic low-dose-rate radiation-induced persistent DNA damage. Full article
(This article belongs to the Section Cells of the Nervous System)
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<p>Weight measurement indicates that chronic irradiation with a dose rate of 1.2 mGy/h did not affect weight gain from 2 weeks during irradiation until 64 weeks after the first irradiation started. Animal weight gain increased significantly during the first week of irradiation. The Student’s <span class="html-italic">t</span>-test was used to compare the body weight between control and exp groups (1.2 mGy/h) at different time points. * <span class="html-italic">p</span> &lt; 0.05. Control: n = 9; Exp (1.2 mGy/h): n = 15. W: week; C: control; E: exp (1.2 mGy/h); 1W-C means control mice in 1 week.</p>
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<p>Neurobehavioural tests did not show chronic irradiation-induced anxiety and depression behavioral changes. Time spent (<b>A</b>) and distance travelled (<b>B</b>) in each area in the open field test; time spent (<b>C</b>) in the light and dark box and distance travelled (<b>D</b>) in the light box in the light–dark box test; time spent (<b>E</b>) and distance travelled (<b>F</b>) in three areas in the elevated plus maze; (<b>G</b>) time immobile in the tail suspension test and forced swim test. TST: tail suspension test; FST: forced swim test. The Student’s <span class="html-italic">t</span>-test was used to compare the data between the control and exp groups (1.2 mGy/h). Control: n = 9; exp group: n = 15.</p>
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<p>Immunohistochemical staining of the dentate gyrus of the hippocampus in the control and experiment mice. (<b>A1</b>–<b>A3</b>): NeuN immunopositive mature neurons (arrow); (<b>B1</b>–<b>B3</b>): GFAP immunopositive astrocytes (arrow); (<b>C1</b>–<b>C3</b>): PDGFRα immunopositive oligodendrocyte precursor cells (arrow) in the hilus; (<b>D1</b>–<b>D3</b>): IBA1 immunopositive microglia (arrow) in the hilus and the granule cell layer; (<b>E1</b>–<b>E3</b>): DCX immunopositive immature neurons (arrow) in the subgranular zone; (<b>F1</b>–<b>F3</b>): γH2AX immunostaining shows DNA damage foci in the granule cells. Scale bar = 100 μm in (<b>A1</b>) applies to (<b>B1</b>–<b>E1</b>) and (<b>A2</b>–<b>E2</b>). Scale bar = 50 μm in (<b>F1</b>) applies to (<b>F2</b>). (<b>A3</b>–<b>F3</b>): statistical results. <span class="html-italic">* p</span> &lt; 0.05. Control: n = 8; exp group: n = 7.</p>
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<p>Immunohistochemical staining of the dentate gyrus of the hippocampus in the control and experiment mice. (<b>A1</b>–<b>A3</b>): NeuN immunopositive mature neurons (arrow); (<b>B1</b>–<b>B3</b>): GFAP immunopositive astrocytes (arrow); (<b>C1</b>–<b>C3</b>): PDGFRα immunopositive oligodendrocyte precursor cells (arrow) in the hilus; (<b>D1</b>–<b>D3</b>): IBA1 immunopositive microglia (arrow) in the hilus and the granule cell layer; (<b>E1</b>–<b>E3</b>): DCX immunopositive immature neurons (arrow) in the subgranular zone; (<b>F1</b>–<b>F3</b>): γH2AX immunostaining shows DNA damage foci in the granule cells. Scale bar = 100 μm in (<b>A1</b>) applies to (<b>B1</b>–<b>E1</b>) and (<b>A2</b>–<b>E2</b>). Scale bar = 50 μm in (<b>F1</b>) applies to (<b>F2</b>). (<b>A3</b>–<b>F3</b>): statistical results. <span class="html-italic">* p</span> &lt; 0.05. Control: n = 8; exp group: n = 7.</p>
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<p>Low-dose-rate irradiation-induced hippocampal mRNA changes: (<b>A</b>) Heatmap of mRNA changes from mRNA sequencing in the control and experiment (Exp) mice. (<b>B</b>) qRT-PCR indicates a significant down-regulation of <span class="html-italic">Ccn1</span>, <span class="html-italic">Fli1</span>, <span class="html-italic">Fosb</span>, <span class="html-italic">Ets1</span>, <span class="html-italic">Hs3st5,</span> and <span class="html-italic">Eif4ebp2</span> genes, and up-regulation of <span class="html-italic">Cort</span>, <span class="html-italic">Foxh1</span>, and <span class="html-italic">Opalin</span> genes. * <span class="html-italic">p</span> &lt; 0.05. Control: n = 3; Exp group: n = 3. FH: female hippocampus; FH1, FH2, FH3 are controls; FH4, FH5, FH6 are exp mice (1.2 mGy/h); TPM: transcript per million.</p>
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<p>Low-dose-rate irradiation-induced hippocampal miRNA changes: (<b>A</b>) Heatmap of miRNA changes from miRNA sequencing in the control and experiment mice; (<b>B</b>) qRT-PCR indicates a significant down-regulation of miR-193a-3p and up-regulation of miR-448-3p and miR-361-5p in the irradiated mice (* <span class="html-italic">p</span> &lt; 0.05), but no changes for other miRNA investigated (<span class="html-italic">p</span> &gt; 0.05). Control: n = 3; Exp group: n = 3. FH: female hippocampus; FH1, FH2, FH3 are controls; FH4, FH5, FH6 are exp (irradiated with 1.2 mGy/h).</p>
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<p>Low-dose-rate irradiation-induced blood mRNA changes: (<b>A</b>) Heatmap of mRNA sequencing results in the blood of control and experiment mice; (<b>B</b>) qRT-PCR indicates a significant down-regulation of <span class="html-italic">Tppp3</span>, <span class="html-italic">S1pr5</span>, and <span class="html-italic">Rbpms</span> and up-regulation of <span class="html-italic">Lepr</span> genes (* <span class="html-italic">p</span> &lt; 0.05) but no changes of other mRNAs in the blood of the control and irradiated mice. Control: n = 3; exp group: n = 3. FB: female blood; FB1, FB2, and FB3 are controls; FB4, FB5, and FB6 are exp mice (1.2 mGy/h); TPM: transcript per million.</p>
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<p>Low-dose-rate irradiation-induced blood miRNA changes: (<b>A</b>) Heatmap of miRNA sequencing results in the blood of control and experiment mice; (<b>B</b>) qRT-PCR indicates a significant down-regulation of miR-296-5p and up-regulation of miR-6967-3p (* <span class="html-italic">p</span> &lt; 0.05) but no changes of other miRNAs in the blood of the control and irradiated mice. The Student’s <span class="html-italic">t</span>-test was used to compare the data between control and exp mice (1.2 mGy/h). Control: n = 3; exp group: n = 3. FB: female blood; FB1, FB2, FB3 are controls; FB4, FB5, FB6 are exp (1.2 mGy/h).</p>
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<p>Low-dose-rate irradiation-induced differentially expressed miRNAs and mRNAs in both the blood and hippocampus. (<b>A</b>,<b>B</b>): Venn diagram of 18 differentially expressed miRNAs (<b>A</b>) and two mRNAs (<b>B</b>) in both the blood and hippocampus of irradiated mice compared to the control; (<b>C</b>) table list of 18 miRNAs differentially expressed in both the blood and hippocampus; (<b>D</b>) table list of two mRNAs differentially expressed in both the blood and hippocampus.</p>
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15 pages, 799 KiB  
Article
Challenges in Maritime Cybersecurity Training and Compliance
by Divine C. Chupkemi and Konstantinos Mersinas
J. Mar. Sci. Eng. 2024, 12(10), 1844; https://doi.org/10.3390/jmse12101844 (registering DOI) - 15 Oct 2024
Abstract
The implementation of cybersecurity standards and directives in the maritime sector plays a crucial role in protecting critical maritime infrastructures from cyber threats. The level of protection depends heavily on humans. However, the effectiveness of cybersecurity training and compliance programmes, an essential component [...] Read more.
The implementation of cybersecurity standards and directives in the maritime sector plays a crucial role in protecting critical maritime infrastructures from cyber threats. The level of protection depends heavily on humans. However, the effectiveness of cybersecurity training and compliance programmes, an essential component of these standards, is often hindered by challenges related to the sector’s environment, including the established technologies, practices, and norms. This paper aims to identify these challenges through a literature review and set the basis for more effective human risk minimization, responses, and training. We identify 17 challenges and validate them with an online survey (N = 205) capturing real-world perspectives from maritime-related stakeholders. Our findings contribute to enhancing the effectiveness of maritime cybersecurity training and compliance programmes, ultimately strengthening the maritime cybersecurity posture. Full article
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<p>How convenient is the training delivery method used by the company?</p>
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<p>What would you say is the biggest obstacle to taking cybersecurity training?</p>
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13 pages, 471 KiB  
Article
Implications of Traditional Cooking on Air Quality and Female Health: An In-Depth Analysis of Particulate Matter, Carbon Monoxide, and Carbon Dioxide Exposure in a Rural Community
by Kenia González-Pedraza, Arturo Figueroa-Montaño, Martha Orozco-Medina, Felipe Lozano-Kasten and Valentina Davydova Belitskaya
Atmosphere 2024, 15(10), 1232; https://doi.org/10.3390/atmos15101232 (registering DOI) - 15 Oct 2024
Abstract
Indoor air pollution, particularly in rural communities, is a significant health determinant, primarily due to the prevalence of traditional cooking practices. The WHO estimates 4.3 million annual deaths related to household air pollution. This study quantifies indoor pollutants and assesses health impacts and [...] Read more.
Indoor air pollution, particularly in rural communities, is a significant health determinant, primarily due to the prevalence of traditional cooking practices. The WHO estimates 4.3 million annual deaths related to household air pollution. This study quantifies indoor pollutants and assesses health impacts and perceptions regarding traditional cooking. Using Extech air quality monitoring equipment, the study measured particulate matter (PM), carbon monoxide (CO), and carbon dioxide (CO2) in 48 rural homes. A survey of 39 women gathered insights on their use of wood for cooking and perceptions of air quality. This dual approach analyzed both environmental and social dimensions. Findings showed fine particulate matter (0.3, 0.5, 1.0, and 2.5 μm) exceeded safety limits by threefold, while coarser particulates (5.0 and 10 µm) were concerning but less immediate. CO levels were mostly acceptable, but high concentrations posed risks. CO2 levels indicated good ventilation. Survey responses highlighted reliance on wood and poor air quality perceptions demonstrating little awareness of health risks. Common symptoms included eye discomfort, respiratory issues, and headaches. The study emphasizes the need for interventions to reduce exposure to indoor pollutants and increase awareness of health risks to encourage cleaner cooking practices in rural communities. Full article
(This article belongs to the Special Issue Exposure Assessment of Air Pollution (2nd Edition))
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<p>The community of Agua Caliente is located along the shore of Lake Chapala, Jalisco, Mexico.</p>
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15 pages, 1946 KiB  
Article
Comprehensive Analysis of BrDUF506 Genes across the Brassica rapa Genome Uncovers Potential Functions in Sexual Reproduction and Abiotic Stress Tolerance
by Guangqi Zhu, Jingxuan Wang, Shuang He, Kexin Liang, Renyi Zhang, Jiabao Huang, Xueqin Yang and Xiaojing Zhang
Int. J. Mol. Sci. 2024, 25(20), 11087; https://doi.org/10.3390/ijms252011087 (registering DOI) - 15 Oct 2024
Abstract
The Domain of Unknown Function 506 (DUF506) belongs to the PD-(D/E) XK nuclease superfamily and has been reported to play critical roles in growth and development as well as responses to abiotic stresses. However, the function of DUF506 genes in Brassica rapa ( [...] Read more.
The Domain of Unknown Function 506 (DUF506) belongs to the PD-(D/E) XK nuclease superfamily and has been reported to play critical roles in growth and development as well as responses to abiotic stresses. However, the function of DUF506 genes in Brassica rapa (B. rapa) remains unclear. In this study, a total of 18 BrDUF506 genes were identified and randomly distributed across eight chromosomes, categorized into four subfamilies. Analyzing their promoter sequences has uncovered various stress-responsive elements, such as those for drought, methyl jasmonate (MeJA), and abscisic acid (ABA). Bra000098 and Bra017099 exhibit significantly enhanced expression in response to heat and drought stress. Protein interaction predictions indicate that Bra000098 homolog, At2g38820, is interacting with ERF012 and PUB48 and is involved in abiotic stress regulation. Furthermore, gene expression profiling has identified Bra026262 with a high expression level in flowers and significantly decreased in female sterile mutants. Protein interaction prediction further revealed that its homolog, At4g32480, interacts with MYB and AGL proteins, suggesting the potential roles in female gametophyte development. The current study enhances our understanding of the functional roles of BrDUF506s, providing significant insights that are valuable in investigating sexual reproduction and abiotic stress responses in B. rapa. Full article
(This article belongs to the Collection Advances in Molecular Plant Sciences)
20 pages, 6111 KiB  
Article
Preliminary Study on Multi-Scale Modeling of Asphalt Materials: Evaluation of Material Behavior through an RVE-Based Approach
by Ahmed Ibrahim Hassanin Mohamed, Oliver Giraldo-Londoño, Baolin Deng, Zhen Chen, Punyaslok Rath and William G. Buttlar
Materials 2024, 17(20), 5041; https://doi.org/10.3390/ma17205041 (registering DOI) - 15 Oct 2024
Abstract
This study employs a microstructure-based finite element modeling approach to understand the mechanical behavior of asphalt mixtures across different length scales. Specifically, this work aims to develop a multi-scale modeling approach employing representative volume elements (RVEs) of optimal size; this is a key [...] Read more.
This study employs a microstructure-based finite element modeling approach to understand the mechanical behavior of asphalt mixtures across different length scales. Specifically, this work aims to develop a multi-scale modeling approach employing representative volume elements (RVEs) of optimal size; this is a key issue in asphalt modeling for high-fidelity fracture modeling of heterogeneous asphalt mixtures. To determine the optimal RVE size, a convergence analysis of homogenized elastic properties is conducted using two types of RVEs, one made with polydisperse spherical inclusions, and another made with polydisperse truncated cylindrical inclusions, each aligned with the American Association of State Highway and Transportation Official’s maximum density gradation curve for a 12.5 mm Nominal Maximum Aggregate Size (NMAS). The minimum RVE lengths for this NMAS were found to be in the range of 32–34 mm. After the optimal RVE size for each inclusion shape is obtained, computational models of heterogeneous Indirect Tensile Asphalt Cracking Test samples are then generated. These models include the components of viscoelastic mastic, linear elastic aggregates, and cohesive zone modeling to simulate the rate-dependent failure evolution from micro- to macro-cracking. Examination of load-displacement responses at multiple loading rates shows that both heterogeneous models replicate experimentally measured data satisfactorily. Through micro- and macro-level analyses, this study enhances our understanding of the composition-performance relationships in asphalt pavement materials. The procedure proposed in this study allows us to identify the optimal RVE sizes that preserve computational efficiency without significantly compromising their ability to capture the asphalt material behavior under specific operational conditions. Full article
(This article belongs to the Special Issue Mechanical Property Research of Advanced Asphalt-Based Materials)
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<p>Scheme of multi-scale modeling through RVE based approach.</p>
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<p>Mechanical characterization of periodic unit cell: load in extension-compression (<b>left</b>) and loading in shear (<b>right</b>).</p>
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<p>Types of inclusions considered in this study: (<b>a</b>) Polydisperse spherical particles and (<b>b</b>) truncated cylindrical particles.</p>
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<p>Presentation of each inclusion size in the two selected RVEs.</p>
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<p>Gradation of RVE particle distribution based on 0.45 power gradation chart.</p>
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<p>Engineering constants for the two types of RVEs vs. RVE side length for various aggregate volume fractions: (<b>a</b>) Young’s modulus, (<b>b</b>) Shear modulus, and (<b>c</b>) Poisson’s ratio.</p>
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<p>Creation of IDEAL CT full-scale model: (<b>a</b>) replicating unit RVE to extend model domain beyond 150 mm × 150 mm × 62 mm, (<b>b</b>) slicing cylindrical specimen from extended model domain, (<b>c</b>) generated full scale models, and (<b>d</b>) applying boundary conditions.</p>
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<p>Schematic illustration of a full-scale model depicting the level of damage on the symmetry plane.</p>
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<p>Element size in relation to peak load and maximum displacement.</p>
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<p>Numerical simulation vs. experiment for load-displacement relation at different loading rates: (<b>a</b>) 0.8 mm/s, (<b>b</b>) 1.6 mm/s, (<b>c</b>) 3.2 mm/s, and (<b>d</b>) total deformation (in mm) at the peak load for all loading rates.</p>
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<p>Root mean squared error comparison between the two proposed models vs. the applied loading rates.</p>
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20 pages, 29919 KiB  
Article
The Synergistic Effect of the Same Climatic Factors on Water Use Efficiency Varies between Daily and Monthly Scales
by Guangchao Li, Zhaoqin Yi, Liqin Han, Ping Hu, Wei Chen, Xuefeng Ye and Zhen Yang
Sustainability 2024, 16(20), 8925; https://doi.org/10.3390/su16208925 (registering DOI) - 15 Oct 2024
Abstract
The coupled processes of ecosystem carbon and water cycles are usually evaluated using the water use efficiency (WUE), and improving WUE is crucial for maintaining the sustainability of ecosystems. However, it remains unclear whether the WUE in different ecosystem responds synchronously to the [...] Read more.
The coupled processes of ecosystem carbon and water cycles are usually evaluated using the water use efficiency (WUE), and improving WUE is crucial for maintaining the sustainability of ecosystems. However, it remains unclear whether the WUE in different ecosystem responds synchronously to the synergistic effect of the same climate factors at daily and monthly scales. Therefore, we employed a machine learning-driven factor analysis method and a geographic detector model, and we quantitatively evaluated the individual effects and the synergistic effect of climate factors on the daily mean water use efficiency (WUED) and monthly mean water use efficiency (WUEM) in different ecosystems in China. Our results showed that (1) among the 10 carbon flux monitoring sites in China, WUED and WUEM exhibited the highest positive correlations with the near-surface air humidity and the highest negative correlation with solar radiation. The correlation between WUEM and climate factors was generally greater than that between WUED and climate factors. (2) There were significant differences in the order of importance and degree of impact of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the near-surface air humidity imposed the greatest influence on the WUED and WUEM changes, followed by the near-surface water vapor pressure. (3) There were significant differences in the synergistic effects of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the WUED variability was most sensitive to the synergistic effect of solar radiation and photosynthetically active radiation, while the WUEM variability was most sensitive to the synergistic effect of the near-surface air humidity and soil moisture. The research results indicated that synchronous responses of the WUE in very few ecosystems to the same climate factors and their synergistic effect occurred at daily and monthly scales. This finding enhances the understanding of sustainable water resource use and the impact of climate change on water use efficiency, providing crucial insights for improving climate-adaptive ecosystem management and sustainable water resource utilization across different ecosystems. Full article
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<p>(<b>a</b>) Spatial distribution of the climate zones and ChinaFLUX sites and (<b>b</b>) spatial distribution of the land use types in 2010.</p>
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<p>Synergistic effect of climate variables on the ecosystem WUE at different time scales.</p>
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<p>Multiyear daily mean variations in the GPP (orange line), ET (green line) and WUE (blue line) in the different ecosystems in China.</p>
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<p>Multiyear monthly mean variations in the GPP, ET and WUE.</p>
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<p>Pearson’s correlation coefficients between the WUE and climate factors at the different time scales at the 10 carbon flux monitoring stations in China. Cyan indicates a negative correlation between the WUE and each climate variable, and orange indicates a positive correlation between the WUE and each climate variable. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Summary of the XGBoost SHAP value (impact on model output) results for WUE<sub>D</sub> at the 10 carbon flux monitoring sites in China.</p>
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<p>Relative importance (impact on model output) of the different drivers at the 10 carbon flux monitoring stations in China for WUE<sub>D</sub>.</p>
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<p>Summary of the XGBoost SHAP value (impact on model output) results for WUE<sub>M</sub> at the 10 carbon flux monitoring sites in China.</p>
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<p>Relative importance (impact on model output) of the different drivers of the 10 carbon flux monitoring stations in China for WUE<sub>M</sub>.</p>
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<p>Synergistic effect of the climate factors on WUE<sub>D</sub> at the 10 flux monitoring sites.</p>
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<p>Synergistic effect of the climate factors on WUE<sub>M</sub> at the 10 flux monitoring sites.</p>
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8 pages, 928 KiB  
Brief Report
Modifications in Immune Response Patterns Induced by Kynurenine and One-Residue-Substituted T Cell Epitopes in SARS-CoV-2-Specific Human T Cells
by Mieko Tokano, Rie Takagi and Sho Matsushita
COVID 2024, 4(10), 1676-1683; https://doi.org/10.3390/covid4100116 (registering DOI) - 15 Oct 2024
Abstract
Peptide p176-190, derived from the SARS-CoV-2 spike protein, is one of the major T cell epitopes that elicits the HLA-DR-restricted IL-8 response of human CD4+ T cells. Using PBMCs from a healthy individual primed with an S-protein-based SARS-CoV-2 vaccine, we established a [...] Read more.
Peptide p176-190, derived from the SARS-CoV-2 spike protein, is one of the major T cell epitopes that elicits the HLA-DR-restricted IL-8 response of human CD4+ T cells. Using PBMCs from a healthy individual primed with an S-protein-based SARS-CoV-2 vaccine, we established a CD4+ T cell line (TM45) and cloned T cells (TM45.2) specific for the peptide. We showed that (i) co-incubation with kynurenine leads to increased IL-8; (ii) T cells incubated in the absence of kynurenine recovered the original levels of cytokine production; and (iii) peptide p176-190 substituted at 176 Leucine for neutral hydrophilic serine completely abolished the cytokine responses of TM45.2 cells, thereby suggesting that 176 L is the first anchor residue for binding to HLA-DR. These observations collectively indicate that (i) enhanced IL-8 responses can be induced by kynurenine, which is produced under infectious conditions in COVID-19; (ii) the response is not a permanent change in the T cell phenotype; and (iii) IL-8 responses associated with harmful neutrophil extracellular traps can be abrogated by a single amino acid substitution of the viral antigens. These findings may shed light on a novel strategy for designing vaccines for viral infections that are accompanied by increased kynurenine production. Full article
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<p>TM45 cells were incubated in the presence of irradiated (30 Gy) autologous PBMCs prepulsed with the peptide p176-190 and human rIL-2 (50 U/mL), with or without kynurenine. After 7 days, TM45 cells (1 × 10<sup>4</sup>/well) were cultured in 96-well flat-bottom culture plates in the presence of irradiated autologous PBMCs (1 × 10<sup>5</sup>/well) and 5 μM peptide p176-190 in R10H medium. Four days later, the culture supernatant fluid was collected for IL-8 (<b>A</b>) and GM-CSF (<b>B</b>) ELISAs (n = 6). Values obtained by subtracting the IL-8 concentration in the absence of peptide (Δpg/mL) are shown. * <span class="html-italic">p</span> &lt; 0.05, compared to ΔIL-8 with peptide p176-190 in the absence of kynurenine. (<b>C</b>) TM45 cells were incubated in the presence of irradiated (30 Gy) autologous PBMCs prepulsed with the peptide p176-190, human rIL-2 (50 U/mL), with or without kynurenine. After 7 days, TM45 cells (1 × 10<sup>4</sup>/well) were cultured in 96-well flat-bottom culture plates in the presence of irradiated autologous PBMCs (1 × 10<sup>5</sup>/well) and 5 μM peptide p176-190 using R10H medium. A portion of TM45 cells was maintained for an additional 7 days. Four days later, culture supernatant fluid was collected for an IL-8 ELISA (n = 6). Values obtained by subtracting the IL-8 concentration in the absence of the peptide (Δpg/mL) are shown. Data are expressed as the mean ± standard deviation (SD) and were compared using a one-way analysis of variance and Tukey’s post hoc test. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to Day 0 or Day 14.</p>
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<p>(<b>A</b>) An overhead view of the HLA class II-peptide complex from the perspective of the TCR. Peptides rotate 130 degrees counterclockwise with each advancement of one residue. Yellow painted parts of the beta 1 domain indicate polymorphic residues. This is an original illustration. (<b>B</b>) A schematic diagram of the HLA class II-peptide complex viewed from the N-terminus of the binding peptide along the longitudinal axis (displaying only the first 4 residues). This is an original illustration. (<b>C</b>) TM45.2 cells were cultured in 96-well flat-bottom culture plates in the presence of irradiated autologous PBMCs and three types of peptides using R10H medium. “WT” represents the peptide p176-190. L176S refers to peptide p176-190 with a substitution of leucine at position 176 replaced by the neutral hydrophilic serine, while M177S indicates peptide p176-190 with a substitution of methionine at position 177 replaced by the neutral hydrophilic serine. Four days later, culture supernatant fluid was collected for an IFNγ ELISA (n = 6). Data are expressed as the mean ± SD and were compared by a one-way analysis of variance and Tukey’s post hoc test. ** <span class="html-italic">p</span> &lt; 0.01 compared to the culture without peptide.</p>
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18 pages, 2449 KiB  
Article
Decreased Circulating Gonadotropin-Releasing Hormone Associated with Keratoconus
by Paulina Escandon, Alexander J. Choi, Steve Mabry, Sarah E. Nicholas, Rebecca L. Cunningham, Liam Redden, David A. Murphy, Kamran M. Riaz, Tina B. McKay and Dimitrios Karamichos
Cells 2024, 13(20), 1704; https://doi.org/10.3390/cells13201704 (registering DOI) - 15 Oct 2024
Abstract
Keratoconus (KC) is a corneal thinning dystrophy that leads to visual impairment. While the cause of KC remains poorly understood, changes in sex hormone levels have been correlated with KC development. This study investigated circulating gonadotropin-releasing hormone (GnRH) in control and KC subjects [...] Read more.
Keratoconus (KC) is a corneal thinning dystrophy that leads to visual impairment. While the cause of KC remains poorly understood, changes in sex hormone levels have been correlated with KC development. This study investigated circulating gonadotropin-releasing hormone (GnRH) in control and KC subjects to determine if this master hormone regulator is linked to the KC pathology. Plasma and saliva were collected from KC subjects (n = 227 and n = 274, respectively) and non-KC controls (n = 58 and n = 101, respectively), in concert with patient demographics and clinical features. GnRH levels in both plasma and saliva were significantly lower in KC subjects compared to controls. This finding was retained in plasma when subjects were stratified based on age, sex, and KC severity. Control and KC corneal fibroblasts (HKCs) stimulated with recombinant GnRH protein in vitro revealed significantly increased luteinizing hormone receptor by HKCs and reduced expression of α-smooth muscle actin with treatment suggesting that GnRH may modulate hormonal and fibrotic responses in the KC corneal stroma. Further studies are needed to reveal the role of the hypothalamic–pituitary–gonadal axis in the onset and progression of KC and to explore this pathway as a novel therapeutic target. Full article
(This article belongs to the Special Issue Cell Therapeutics for Corneal Diseases)
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<p>Plasma gonadotropin-releasing hormone (GnRH) in control and KC patients. (<b>A</b>) GnRH concentration in plasma for all control and KC patients tested. Sub-analyses of GnRH concentrations based on (<b>B</b>) sex, (<b>C</b>) age, and (<b>D</b>) KC severity. Data are shown in box-and-whisker plots, with the box represent the 25% quartile, median, and 75% quartile, and the line extending to the minimum and maximum values. Statistical significance evaluated by a non-parametric Mann–Whitney test (<b>A</b>–<b>C</b>). Statistical significance evaluated by a non-parametric Kruskal–Wallis test with Dunn’s multiple comparisons test (<b>D</b>). Significance indicated as ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Saliva gonadotropin-releasing hormone (GnRH) in control and KC patients. (<b>A</b>) GnRH concentration in saliva for all control and KC patients tested. Sub-analyses of GnRH concentrations based on (<b>B</b>) sex, (<b>C</b>) age, and (<b>D</b>) KC severity. Data are shown in box-and-whisker plots, with the box representing the 25% quartile, median, and 75% quartile, and the line extending to the minimum and maximum values. Statistical significance evaluated by a non-parametric Mann–Whitney test (<b>A</b>–<b>C</b>). Statistical significance evaluated by a non-parametric Kruskal–Wallis test with Dunn’s multiple comparisons test (<b>D</b>). Significance indicated as * <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.</p>
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<p>Protein expression of gonadotropin-releasing hormone receptor (GnRHR) in 2D HCFs and HKCs after being stimulated with 1 ng/mL, 2 ng/mL, 4 ng/mL, 6 ng/mL, 8 ng/mL, and 10 ng/mL rGnRH for 48 h. Data shown as mean ± standard error of the mean. n = 3 per group. Statistical significance of dose with HCFs and HKCs based on a one-way ANOVA with Šídák’s multiple comparisons test. Post hoc significance indicated as * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01. Statistical significance between HCFs and HKCs within dose determined by unpaired <span class="html-italic">t</span>-test with Welch’s correction. Significance indicated as # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Immunofluorescence images and analysis for gonadotropin-releasing hormone receptor (GnRHR) expression in 2D GnRH stimulation of HCFs and HKCs. (<b>A</b>) The controls were not stimulated with GnRH; (<b>B</b>) 1 ng/mL; (<b>C</b>) 4 ng/mL; (<b>D</b>) 8 ng/mL; (<b>E</b>) immunofluorescence images’ signal intensity for GnRHR expression. Statistical significance between HCFs and HKCs within the dose determined by an unpaired <span class="html-italic">t</span>-test with Welch’s correction. Significance indicated as ## <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Protein expression of hormone receptors in 3D HCFs and HKCs following stimulation with 1 ng/mL, 4 ng/mL, and 8 ng/mL GnRH for 4 weeks. Protein expression of (<b>A</b>) GnRH receptor, (<b>B</b>) FSH receptor, and (<b>C</b>) LH receptor based on Western blot analysis. Statistical significance based on a one-way ANOVA with Šídák’s multiple comparisons test. Post hoc significance indicated as * <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; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001. Statistical significance between HCFs and HKCs within the dose determined by an unpaired <span class="html-italic">t</span>-test with Welch’s correction. Significance indicated as # <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.</p>
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<p>Protein expression of fibronectin and α-smooth muscle actin (SMA) in 3D HCFs and HKCs following stimulation with 1 ng/mL, 4 ng/mL, and 8 ng/mL GnRH for 4 weeks. (<b>A</b>) Results of EDA-Fn protein expression in HCFs and HKCs stimulated with GnRH. (<b>B</b>) Results of SMA protein expression in HCFs and HKCs stimulated with GnRH. Statistical significance based on a one-way ANOVA with Šídák’s multiple comparisons test. Post hoc significance indicated as * <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; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Statistical significance between HCFs and HKCs within the dose determined by the unpaired <span class="html-italic">t</span>-test with Welch’s correction. Significance indicated as # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Protein expression of matrix metalloproteinases (MMPs) in 3D HCFs and HKCs after being stimulated with 1 ng/mL, 4 ng/mL, and 8 ng/mL GnRH for 4 weeks. Protein expression of (<b>A</b>) MMP-1, (<b>B</b>) MMP-2, and (<b>C</b>) MMP-9 in HCFs and HKCs stimulated with GnRH. Statistical significance based on a one-way ANOVA with Šídák’s multiple comparisons test. Post hoc significance indicated as * <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; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001. Statistical significance between HCFs and HKCs within the dose determined by the unpaired <span class="html-italic">t</span>-test with Welch’s correction. Significance indicated as # <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.</p>
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21 pages, 12484 KiB  
Article
Assessment of Future Water Security under Climate Change: Practical Water Allocation Scenarios in a Drought-Prone Watershed in South Korea
by Wonjin Kim, Sijung Choi, Seongkyu Kang and Soyoung Woo
Water 2024, 16(20), 2933; https://doi.org/10.3390/w16202933 (registering DOI) - 15 Oct 2024
Abstract
Seomijn River Basin has numerous hydraulic structures designed to satisfy water demands and mitigate future droughts. However, the increasing water demand and export to neighboring areas cause water deficits and conflicts between water users. Therefore, practical strategies to mitigate the potential damage from [...] Read more.
Seomijn River Basin has numerous hydraulic structures designed to satisfy water demands and mitigate future droughts. However, the increasing water demand and export to neighboring areas cause water deficits and conflicts between water users. Therefore, practical strategies to mitigate the potential damage from climate change are essential. In this study, we aimed to propose practical strategies under climate change by examining the future water security of the Seomjin River Basin under five different water allocation scenarios referenced from the practical policies of various countries. Future climate models determined based on extreme precipitation indices of the ETCCDI were used to investigate their impact on water security, which was evaluated using unmet demand; demand coverage; reliability, resilience, and vulnerability; and aggregation index metrics. We found that prioritizing domestic and industrial water use is the optimal water security strategy, and unconditional allocation of instream flow can cause a significant water deficit for other water uses. However, prioritizing all water uses equally also proved effective under some conditions. Thus, our study highlights the importance of adaptive management and suggests that the optimal water allocation strategy lies in its flexibility in response to varying circumstances. Full article
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<p>Sequence of water use priority in different countries [<a href="#B18-water-16-02933" class="html-bibr">18</a>].</p>
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<p>Description of study area.</p>
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<p>SWAT input data: (<b>a</b>) land use map; (<b>b</b>) digital elevation map; (<b>c</b>) soil map.</p>
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<p>Schematic network of water supply: (<b>a</b>) domestic and industrial supply; (<b>b</b>) agricultural supply.</p>
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<p>Distribution of annual water demand: (<b>a</b>) domestic; (<b>b</b>) industrial; and (<b>c</b>) agricultural demands.</p>
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<p>Five water allocation scenarios employed in this study.</p>
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<p>Details of the 13 flow requirement points in the study area.</p>
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<p>Streamflow calibration results against six calibration points. The black graph represents the observed data and the red graph represents the simulated data.</p>
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<p>The 60 climate models ranked for dryness based on extreme precipitation indices.</p>
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<p>Demand coverage distribution for domestic water use.</p>
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<p>Demand coverage distribution for industrial water use.</p>
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<p>Demand coverage distribution for agricultural water use.</p>
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<p>AIs for different water allocation scenarios under dry and moderate climatic conditions.</p>
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12 pages, 4907 KiB  
Article
Multi-Wavelength Excitable Multicolor Upconversion and Ratiometric Luminescence Thermometry of Yb3+/Er3+ Co-Doped NaYGeO4 Microcrystals
by Hui Zeng, Yangbo Wang, Xiaoyi Zhang, Xiangbing Bu, Zongyi Liu and Huaiyong Li
Molecules 2024, 29(20), 4887; https://doi.org/10.3390/molecules29204887 (registering DOI) - 15 Oct 2024
Abstract
Excitation wavelength controllable lanthanide upconversion allows for real-time manipulation of luminescent color in a composition-fixed material, which has been proven to be conducive to a variety of applications, such as optical anti-counterfeiting and information security. However, current available materials highly rely on the [...] Read more.
Excitation wavelength controllable lanthanide upconversion allows for real-time manipulation of luminescent color in a composition-fixed material, which has been proven to be conducive to a variety of applications, such as optical anti-counterfeiting and information security. However, current available materials highly rely on the elaborate core–shell structure in order to ensure efficient excitation-dependent energy transfer routes. Herein, multicolor upconversion luminescence in response to both near-infrared I and near-infrared II (NIR-I and NIR-II) excitations is realized in a novel but simple NaYGeO4:Yb3+/Er3+ phosphor. The remarkably enhanced red emission ratio under 1532 nm excitation, compared with that under 980 nm excitation, could be attributed to the Yb3+-mediated cross-relaxation energy transfers. Moreover, multi-wavelength excitable temperature-dependent (295–823 K) upconversion luminescence realizes a ratiometric thermometry relying on the thermally coupled levels (TCLs) of Er3+. Detailed investigations demonstrate that changing excitation wavelength makes little difference for the performances of TCL-based ratiometric thermometry of NaYGeO4:Yb3+/Er3+. These findings gain more insights to manipulate cross-relaxations for excitation controllable upconversion in single activator doped materials and benefit the cognition of the effect of excitation wavelength on ratiometric luminescence thermometry. Full article
(This article belongs to the Special Issue Rare Earth Based Luminescent Materials)
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Graphical abstract

Graphical abstract
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<p>(<b>a</b>) Crystal structure of NaYGeO<sub>4</sub> and the coordination polyhedra of NaO<sub>6</sub>, YO<sub>6</sub>, and GeO<sub>4</sub>. (<b>b</b>) XRD patterns of NaYGeO<sub>4</sub>:xYb<sup>3+</sup>/2%Er<sup>3+</sup> microcrystals, x = 2–48%. The bar-like diffraction patterns at the bottom represent the standard data of orthorhombic NaYGeO<sub>4</sub> (PDF#88–1177). (<b>c</b>) Unit cell volume calculated from Rietveld refinement results as a function of Yb<sup>3+</sup> doping concentration. (<b>d</b>) XPS spectrum, (<b>e</b>) SEM image, and (<b>f</b>) EDS spectrum of NaYGeO<sub>4</sub>:18%Yb<sup>3+</sup>/2%Er<sup>3+</sup>. The inset in (<b>d</b>) is the high-resolution XPS spectrum in the range of 165–190 eV. (<b>g</b>) Elemental mappings corresponding to the SEM image in (<b>e</b>).</p>
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<p>(<b>a</b>) Upconversion emission spectra of NaYGeO<sub>4</sub>:18%Yb<sup>3+</sup>/2%Er<sup>3+</sup>, under 980 and 1532 nm laser excitation. The integral intensity evolutions of 515–570, 634–705, and 783–826 nm emissions for NaYGeO<sub>4</sub>: xYb<sup>3+</sup>/2%Er<sup>3+</sup> at increased Yb<sup>3+</sup> concentrations, under (<b>b</b>) 980 and (<b>c</b>) 1532 nm excitation. (<b>d</b>) The upconversion red/green ratios and (<b>e</b>) luminescence photographs of NaYGeO<sub>4</sub>:xYb<sup>3+</sup>/2%Er<sup>3+</sup> at increased Yb<sup>3+</sup> concentrations under 980 and 1532 nm excitation.</p>
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<p>Upconversion emission spectra of NaYGeO<sub>4</sub>:18%Yb<sup>3+</sup>/2%Er<sup>3+</sup> and NaYGeO<sub>4</sub>:2%Er<sup>3+</sup>, under (<b>a</b>) 980 and (<b>b</b>) 1532 nm excitation. Schematic upconversion luminescence mechanisms of NaYGeO<sub>4</sub>:Yb<sup>3+</sup>/Er<sup>3+</sup> with (<b>c</b>) 980 and (<b>d</b>) 1532 nm excitation. Decay curves of NaYGeO<sub>4</sub>: xYb<sup>3+</sup>/2%Er<sup>3+</sup> under 1532 nm excitation at (<b>e</b>) 558 and (<b>f</b>) 660 nm emissions; the insets show the calculated lifetimes as a function of Yb<sup>3+</sup> concentration.</p>
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<p>(<b>a</b>,<b>d</b>) Upconversion luminescence spectra, (<b>b</b>,<b>e</b>) normalized green upconversion spectra, and (<b>c</b>,<b>f</b>) calculated Ln LIR (<span class="html-italic">I</span><sub>532</sub>/<span class="html-italic">I</span><sub>558</sub>) of NaYGeO<sub>4</sub>:18%Yb<sup>3+</sup>/2%Er<sup>3+</sup> in the temperature range of 295–823 K, under (<b>a</b>–<b>c</b>) 980 and (<b>d</b>–<b>f</b>) 1532 nm excitation.</p>
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<p>(<b>a</b>,<b>d</b>) Absolute sensitivity, <span class="html-italic">S<sub>a</sub></span>, and relative sensitivity, <span class="html-italic">S<sub>r</sub></span>. (<b>b</b>,<b>e</b>) Temperature uncertainty <span class="html-italic">δT</span> relying on LIR (<span class="html-italic">I</span><sub>532</sub>/<span class="html-italic">I</span><sub>558</sub>) of NaYGeO<sub>4</sub>:18%Yb<sup>3+</sup>/2%Er<sup>3+</sup> at different temperatures. (<b>c</b>,<b>f</b>) LIR (<span class="html-italic">I</span><sub>532</sub>/<span class="html-italic">I</span><sub>558</sub>) at selected temperatures for two heating–cooling cycles between 323 and 823 K. Under (<b>a</b>–<b>c</b>) 980 and (<b>d</b>–<b>f</b>) 1532 nm excitation.</p>
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