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15 pages, 5563 KiB  
Article
Design, Synthesis and Crystal Structure of a Novel Fluorescence Probe for Zn2+ Based on Pyrano[3,2-c] Carbazole
by Ziyin Xie, Qingwen Fang, Shuzhen Xiao, Jie Wang, Ping Lin, Chunmei Guo, Huihua Cao, Zhongping Yin, Lihong Dong and Dayong Peng
Molecules 2024, 29(22), 5454; https://doi.org/10.3390/molecules29225454 - 19 Nov 2024
Viewed by 635
Abstract
Zinc is a trace element, which plays an important role in many biological processes. The deficiency of zinc will lead to many diseases. Thus, it is of great significance to develop fast and efficient quantitative detection technology for zinc ions. In this study, [...] Read more.
Zinc is a trace element, which plays an important role in many biological processes. The deficiency of zinc will lead to many diseases. Thus, it is of great significance to develop fast and efficient quantitative detection technology for zinc ions. In this study, a novel fluorescence probe FP2 was designed for Zn2+ quantification based on pyrano[3,2-c] carbazole. The structure of FP2 was characterized by 1HNMR, 13CNMR, HRMS, and X-ray diffraction. In the HEPES buffer solution, FP2 is responsive to Zn2+ and greatly enhanced. The pH value and reaction time were investigated, and the optimum reaction conditions were determined as follows: the pH was 7~9 and the reaction time was longer than 24 min. Under the optimized conditions, the concentration of FP2 and Zn2+ showed a good linear relationship in the range of 0~10 μM, and the LOD was 0.0065 μmol/L. In addition, through the 1H NMR titration experiment, density functional theory calculation, and the job plot of FP2 with Zn2+ in the HEPES buffer solution, the binding mode of FP2 and Zn2+ was explained. Finally, the method of flame atomic absorption spectrometry (FAAS) and FP2 were used to detect the content of Zn2+ in the water extract of tea. The results showed that the FP2 method is more accurate than the FAAS method, which shows that the method described in this work could be used to detect the content of Zn2+ in practical samples and verify the practicability of this method. Full article
Show Figures

Figure 1

Figure 1
<p>Crystal structure of compound <b>FP2</b> with 30% thermal ellipsoids.</p>
Full article ">Figure 2
<p>Fluorescence spectra of <b>FP2</b>.</p>
Full article ">Figure 3
<p>The effect of pH value of fluorescence intensity for <b>FP2</b> (10 μM) in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>) in the absence and presence of Zn<sup>2+</sup> (10 equivalent). (λ<sub>ex</sub> = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Figure 4
<p>Time-dependent fluorescence intensity changes for <b>FP2</b> (10 μM) at 468nm in the presence of Zn<sup>2+</sup> (10 μM/10 equiv.) in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH = 7.0). (λ<sub>ex</sub> = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Figure 5
<p>Fluorescence response of <b>FP2</b> (10 μM) to various meta ions and Specific recognition in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH 7.0). (λ<sub>ex</sub> = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Figure 6
<p>The photos of <b>FP2</b> (10 μM) to various metal ions in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH 7.0).</p>
Full article ">Figure 7
<p>Fluorescence spectra of <b>FP2</b> (10 μM) in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH 7.0) in the presence of different concentrations of Zn<sup>2+</sup> (0~10 μM) equation of linear regression. (λ<sub>ex</sub> = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Figure 8
<p>(<b>a</b>) <sup>1</sup>H NMR spectra of <b>FP2</b> (1 mM) in the absence and presence of Zn<sup>2+</sup> (1 equiv) in DMSO-<span class="html-italic">d</span><sub>6</sub>; (<b>b</b>) the HOMOs and LUMOs of <b>FP2</b> and FP2 + Zn<sup>2+</sup> (The isosurface values are set to 0.04 a.u.); (<b>c</b>) the job plot of <b>FP2</b> with Zn<sup>2+</sup> in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH 7.0) (λex = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Figure 8 Cont.
<p>(<b>a</b>) <sup>1</sup>H NMR spectra of <b>FP2</b> (1 mM) in the absence and presence of Zn<sup>2+</sup> (1 equiv) in DMSO-<span class="html-italic">d</span><sub>6</sub>; (<b>b</b>) the HOMOs and LUMOs of <b>FP2</b> and FP2 + Zn<sup>2+</sup> (The isosurface values are set to 0.04 a.u.); (<b>c</b>) the job plot of <b>FP2</b> with Zn<sup>2+</sup> in HEPES buffer solution (25 mM, C<sub>2</sub>H<sub>5</sub>OH/H<sub>2</sub>O = 1:1, <span class="html-italic">v</span>/<span class="html-italic">v</span>, pH 7.0) (λex = 367 nm, Slit: 5 nm/10 nm).</p>
Full article ">Scheme 1
<p>The synthetic route for preparation of compounds <b>FP2</b>.</p>
Full article ">
16 pages, 1773 KiB  
Article
Synthesis and Evaluation of Phenyltriazole-Deoxynojirimycin Hybrids as Potent α-Glucosidase Inhibitors
by Lin Wang, Wei Luo, Yonghong Zhao, Xinling Guo, Xiangru Bai, Leilei Guo and Nailiang Zhu
Molecules 2024, 29(21), 5062; https://doi.org/10.3390/molecules29215062 - 26 Oct 2024
Viewed by 728
Abstract
1-deoxynojirimycin (DNJ) is a well-known α-glucosidase inhibitor. A series of phenyltriazole-deoxynojirimycin hybrids containing C4 and C6 (4 and 6 methylenes, respectively) linkers were synthesized. These novel compounds were assessed for preliminary glucosidase inhibition and cytotoxicity tests in vitro. Among them, compounds [...] Read more.
1-deoxynojirimycin (DNJ) is a well-known α-glucosidase inhibitor. A series of phenyltriazole-deoxynojirimycin hybrids containing C4 and C6 (4 and 6 methylenes, respectively) linkers were synthesized. These novel compounds were assessed for preliminary glucosidase inhibition and cytotoxicity tests in vitro. Among them, compounds 1214 and 1620 (IC50: 105 ± 9–11 ± 1 μM) were more active than deoxynojirimycin (DNJ, IC50 = 155 ± 15 μM). The kinetics of enzyme inhibition measured by using Lineweaver–Burk plots indicated that compounds 18 and 19 were competitive inhibitors. In addition, a molecular docking study of α-glucosidase revealed that the interaction modes and the orientations of compound 18 and DNJ were clearly different. Furthermore, in tissue culture, HL60 cell compounds showed no cytotoxicity at low concentrations. When the concentration reached 50 µM, only compound 20 exhibited cytotoxicity. The structure–activity relationships exhibit that the length of the linker and the nature of 4-position substituents on the phenyl have a significant effect on the inhibitory potency of glucosidases and cytotoxicity. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) Known potent glycosidase inhibitors derived from DNJ and (<b>b</b>) general structure of the library of phenyltriazole-deoxynojirimycin hybrids in this work.</p>
Full article ">Figure 2
<p>Double-reciprocal plots of the inhibition kinetics of yeast α-glucosidase by compounds <b>18</b> (<b>a</b>), <b>19</b> (<b>b</b>). Substrate concentration: 0.0625, 0.125, 0.25, 0.5, 1 mM; inhibitor concentration: 0 µM (control, ●), 3.125 µM (<span style="color:red">■</span>), 12.5 µM (<span style="color:blue">▲</span>).</p>
Full article ">Figure 3
<p>Molecular docking simulation of MAL12 and DNJ. (<b>A</b>) The 2D binding mode of MAL12 and DNJ. (<b>B</b>) The binding model of DNJ on the molecular surface of MAL12. DNJ is colored in cyan, and the molecular surface of MAL12 is colored in pale yellow. (<b>C</b>) The 3D binding mode of MAL12 and DNJ. DNJ is colored in cyan, the surrounding residues in the binding pockets are colored in yellow, and the backbone of the receptor is depicted as white cartoons with transparency.</p>
Full article ">Figure 4
<p>Molecular docking simulation of MAL12 and compound <b>18</b>: (<b>A</b>) The 2D binding mode of MAL12 and compound <b>18</b>. (<b>B</b>) The binding model of compound <b>18</b> on the molecular surface of MAL12. Compound <b>18</b> is colored in cyan, and the molecular surface of MAL12 is colored in pale yellow. (<b>C</b>) The 3D binding mode of MAL12 and compound <b>18</b>. Compound <b>18</b> is colored in cyan, the surrounding residues in the binding pockets are colored in yellow, and the backbone of the receptor is depicted as white cartoons with transparency.</p>
Full article ">Figure 5
<p>Effect of DNJ analogues on HL60 cell growth.</p>
Full article ">Scheme 1
<p>Synthesis of the target 1,4-disubstituted cycloadducts <b>10–20</b>. Reaction conditions: (a) K<sub>2</sub>CO<sub>3</sub>, DMF, 80 °C, 4 h; (b) Ac<sub>2</sub>O, Py, r.t., 12 h (over two steps, 86% (<b>22a</b>), 83% (<b>22b</b>); (c) CuSO<sub>4</sub>·5H<sub>2</sub>O, Na ascorbate, DMF/H<sub>2</sub>O (2:1), r.t., 6 h, 81–92% (<b>23–33</b>); (d) MeOH, NaOMe, r.t., 91–96% (<b>10–20</b>).</p>
Full article ">
17 pages, 3440 KiB  
Article
Caution for Multidrug Therapy: Significant Baroreflex Afferent Neuroexcitation Coordinated by Multi-Channels/Pumps Under the Threshold Concentration of Yoda1 and Dobutamine Combination
by Yin-zhi Xu, Zhao-yuan Xu, Hui-xiao Fu, Mao Yue, Jia-qun Li, Chang-peng Cui, Di Wu and Bai-yan Li
Biomolecules 2024, 14(10), 1311; https://doi.org/10.3390/biom14101311 - 16 Oct 2024
Viewed by 796
Abstract
Multi-drug therapies are common in cardiovascular disease intervention; however, io channel/pump coordination has not been tested electrophysiologically. Apparently, inward currents were not elicited by Yoda1/10 nM or Dobutamine/100 nM alone in Ah-type baroreceptor neurons, but were by their combination. To verify this, electroneurography [...] Read more.
Multi-drug therapies are common in cardiovascular disease intervention; however, io channel/pump coordination has not been tested electrophysiologically. Apparently, inward currents were not elicited by Yoda1/10 nM or Dobutamine/100 nM alone in Ah-type baroreceptor neurons, but were by their combination. To verify this, electroneurography and the whole-cell patch-clamp technique were performed. The results showed that Ah- and C-volley were dramatically increased by the combination at 0.5 V and 5 V, in contrast to A-volley, as consistent with repetitive discharge elicited by step and ramp with markedly reduced current injection/stimulus intensity. Notably, a frequency-dependent action potential (AP) duration was increased with Iberiotoxin-sensitive K+ component. Furthermore, an increased peak in AP measured in phase plots suggested enhanced Na+ influx, cytoplasmic Ca2+ accumulation through reverse mode of Na+/Ca2+ exchanger, and, consequently, functional KCa1.1 up-regulation. Strikingly, the Yoda1- or Dbtm-mediated small/transient Na+/K+-pump currents were robustly increased by their combination, implying a quick ion equilibration that may also be synchronized by hyperpolarization-induced voltage-sag, enabling faster repetitive firing. These novel findings demonstrate multi-channel/pump collaboration together to integrate neurotransmission at the cellular level for baroreflex, providing an afferent explanation in sexual dimorphic blood pressure regulation, and raising the caution regarding the individual drug concentration in multi-drug therapies to optimize efficacy and minimize toxicity. Full article
(This article belongs to the Section Molecular Medicine)
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Figure 1

Figure 1
<p>Inward currents recorded in the identified Ah-type baroreceptor neurons using gap-free protocol under voltage-clamp mode before and after Yoda1 (10, 30, 100 nM), Dobutamine (Dbtm, 100, 300, 1000 nM), and the combination. The recording was held at −60 mV for 120 s. (<b>A</b>,<b>D</b>,<b>G</b>): Concentration-dependent effects of Yoda1 on inward currents. (<b>B</b>,<b>E</b>,<b>H</b>): Concentration-dependent effects of Dbtm on inward currents. (<b>C</b>,<b>F</b>,<b>I</b>): Concentration-dependent effect of Yoda1/Dbtm combination on inward currents. The black dot dash line: time to application; red dot dash line: the peak time of Yoda1; green dot dash line: peak time of the combination.</p>
Full article ">Figure 2
<p>Changes in compound action potential (AP) recorded from aortic depressor nerve (ADN) in intact adult female SD rats in the presence of Yoda1 or Yoda1 alone with Dobutamine (Dbtm). Compound AP was elicited by bi-polar electrode using a series of voltage ranged from 0.1 to 20 V and averaged root mean square (RMS, μV) was calculated. A-volley, Ah-volley, and C-volley represented the composition of all A-, Ah-, and C-type baroreceptor afferents, respectively, and were identified according to the afferent fiber conduction velocity (time from stimulation to the waveform/length of ADN, m/s). (<b>A</b>): Representative recording with 2.0 V stimulation. (<b>B</b>–<b>D</b>): Representative A-volley (&gt;10 m/s), Ah-volley (2–10 m/s), and C-volley (&lt;2 m/s) between each paired vertical dash dot line; downward arrowhead shown in (<b>B</b>) means the stimulus artifact. (<b>E</b>–<b>G</b>): Averaged (Avg.) RMS for (<b>B</b>–<b>D</b>). Unpaired <span class="html-italic">t</span>-test was used between groups, data were presented as mean ± SD, and <span class="html-italic">n</span> = 4 and 6 for Yoda1 (10 nM) and Yoda1 + Dbtm (100 nM); * <span class="html-italic">p</span> &lt; 0.05 and <sup>#</sup> <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1 at the same time point.</p>
Full article ">Figure 3
<p>Changes in discharge capability of action potential (AP) recorded from identified Ah-type baroreceptor neurons (BRNs) isolated from adult female SD rats in the presence of Yoda1 or Yoda1 + Dobutamine (Dbtm). AP was elicited by stepped current injection under voltage-clamp mode of whole-cell patch configuration. (<b>A1</b>,<b>A2</b>): Representative recordings were obtained from two different Ah-type BRNs (Cell #1 @ the top two rows and Cell #2 @ the bottom two rows with three steps for each treatment) in the presence of Yoda1 10 nM (as control) or Yoda1 + Dbtm 100 nM. (<b>B</b>): Summarized data of the number of AP elicited within each step before (black/step #1, blue/step #2, and yellow/step #3) and after treatment (red/step #1, light blue/step #2, and green/step #3). (<b>C</b>): Summarized data of the step current applied for step. Repetitive discharges were collected before and after Dbtm and paired <span class="html-italic">t</span>-test was applied. Averaged data were expressed as mean ± SD, <span class="html-italic">n</span> = 7. ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1. Scaled bars also applied for other step recordings of the same cell.</p>
Full article ">Figure 4
<p>Changes in the ramp current applied for evoking similar AP discharge in identified Ah-type BRNs in the presence of Yoda1 or Yoda1 + Dbtm. To determine the excitability under similar AP discharge by ramp protocol, the ramp current was quantified in identified Ah-type BRNs. (<b>A</b>): Representative recordings in the presence of Yoda1 (10 nM, black) and Yoda1 + Dbtm (100 nM, red). (<b>B</b>): Summarized data for the resting membrane potential (RMP). (<b>C</b>): Summarized ramp current applied. (<b>D</b>) Summarized APFT. Unpaired <span class="html-italic">t</span>-test was selected between groups and averaged data were expressed as mean ± SD, <span class="html-italic">n</span> = 20 for Yoda1, and <span class="html-italic">n</span> = 24 for Yoda1 + Dbtm. ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1.</p>
Full article ">Figure 5
<p>Alternative changes in action potential duration (APD<sub>50</sub>) of identified Ah-type BRNs in the presence of Yoda1 or Yoda1 + Dbtm. The first (1st) and the last APs in the spike trains of repetitive discharges in the presence of Yoda1 and Yoda1 + Dbtm shown were superimposed; resting membrane potential (RMP), APD<sub>50</sub>, and the peak of AP were measured accordingly: (<b>A</b>): the 1st APs, (<b>B</b>): the last APs. Averaged data were expressed as mean ± SD, <span class="html-italic">n</span> = 6 complete recordings. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1. The horizontal bar in the (<b>B</b>) was also applied for (<b>A</b>).</p>
Full article ">Figure 6
<p>Iberiotoxin/KCa1.1 inactivation abolishes AP widening induced by Yoda1 + Dbtm in identified Ah-type BRNs. Repetitive discharge of AP was elicited by step depolarization in the presence of Yoda1 and Yoda1 + Dbtm without/with Iberiotoxin, and complete recordings in one cell were included for further analysis. (<b>A</b>): The last APs in the spike trains were superimposed. (<b>B</b>): Phase plots: the total membrane current plotted as a function of membrane voltage from each AP shown in (<b>A</b>), and α, β, χ, δ, and ε were represented for the AP firing threshold, the maximal up-stroke velocity of total inward current/depolarization phase (negative portion), the peak of AP, the maximal down-stroke velocity of total outward current/repolarization phase (positive portion), and the peak of hyperpolarization, respectively; blue arrowhead means the location of the repolarization humps: <span class="html-italic">Inset/left and inset/right</span>: changes in total inward and outward. Averaged data were presented as mean ± SD, <span class="html-italic">n</span> = 6 complete recordings from at least four preparations, ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1 + Dbtm.</p>
Full article ">Figure 7
<p>Effects of Iberiotoxin (IbTx) on total K<sup>+</sup> currents in the presence of Yoda1 + Dbtm recorded from identified Ah-BRNs. After AP was recorded for afferent fiber type identification, the extracellular solution was changed with bath perfusion to the one for potassium current recording; the cell was clamped at a holding potential of −80 mV and stepped from −70 mV up to +40 mV with 5 mV increment with an interval of 1 s between sweeps. Potassium currents were recorded in the presence of Yoda1/10 nM, Dbtm/100 nM, and Yoda1 + Dbtm, respectively. IbTx 100 nM was micropurfused to the tested cell to avoid contaminating other cells in the chamber after successfully recording the total K<sup>+</sup> currents, and IbTx-sensitive components were obtained by subtraction. Total current was divided by its whole-cell capacitance and current density was presented as pA/pF. (<b>A</b>): Representative recording of Ah-type BRN identified by waveform characters, the vertical dash dot line means the presence of repolarization hump. (<b>B</b>,<b>C</b>): Representative tracings of total and IbTx-sensitive K<sup>+</sup> currents. Scale bars also applied for (<b>B</b>). (<b>D</b>): Summarized data for comparisons of total and IbTx-sensitive components. Averaged results were presented as mean ± SD, <span class="html-italic">n</span> = 19 recordings from at least nine preparations; ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1.</p>
Full article ">Figure 8
<p>Changes in Na<sup>+</sup>-K<sup>+</sup>-ATPase currents recorded in identified Ah-type BRNs in the presence of Yoda1 or Yoda1 + Dbtm. Na<sup>+</sup>-K<sup>+</sup>-ATPase currents were recorded under physiological condition with intracellular concentration of 8.9 mM and extracellular concentration of 145 mM. The order of the recording was Yoda1 (10 nM, black, <span class="html-italic">n</span> = 6), Dbtm (100 nM, red, <span class="html-italic">n</span> = 6), Yoda1 + 30 nM Dbtm (green, <span class="html-italic">n</span> = 7), and Yoda1 + 100 nM Dbtm (blue, <span class="html-italic">n</span> = 7). Inset showing the summarized analysis. Unpaired <span class="html-italic">t</span>-test was applied between groups, and one-way ANOVA was also tested among groups with post-hoc Tukey test. Averaged data were expressed as mean ± SD; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. Yoda1; <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. Dbtm.</p>
Full article ">Figure 9
<p>Schematic outline of up-regulated baroreflex afferent neuroexcitation through coordination of multi-ion channel and pump activation over the course of action potential by the combination use of Yoda1 and Dobutamine under threshold concentration.</p>
Full article ">
16 pages, 5685 KiB  
Article
A Dy(III) Coordination Polymer Material as a Dual-Functional Fluorescent Sensor for the Selective Detection of Inorganic Pollutants
by Ying Wang, Baigang An, Si Li, Lijiang Chen, Lin Tao, Timing Fang and Lei Guan
Molecules 2024, 29(18), 4495; https://doi.org/10.3390/molecules29184495 - 22 Sep 2024
Viewed by 827
Abstract
A Dy(III) coordination polymer (CP), [Dy(spasds)(H2O)2]n (1) (Na2Hspasds = 5-(4-sulfophenylazo)salicylic disodium salt), has been synthesized using a hydrothermal method and characterized. 1 features a 2D layered structure, where the spasda3− anions act as [...] Read more.
A Dy(III) coordination polymer (CP), [Dy(spasds)(H2O)2]n (1) (Na2Hspasds = 5-(4-sulfophenylazo)salicylic disodium salt), has been synthesized using a hydrothermal method and characterized. 1 features a 2D layered structure, where the spasda3− anions act as pentadentate ligands, adopting carboxylate, sulfonate and phenolate groups to bridge with four Dy centers in η3-μ1: μ2, η2-μ1: μ1, and monodentate coordination modes, respectively. It possesses a unique (4,4)-connected net with a Schläfli symbol of {44·62}{4}2. The luminescence study revealed that 1 exhibited a broad fluorescent emission band at 392 nm. Moreover, the visual blue color has been confirmed by the CIE plot. 1 can serve as a dual-functional luminescent sensor toward Fe3+ and MnO4 through the luminescence quenching effect, with limits of detection (LODs) of 9.30 × 10−7 and 1.19 × 10−6 M, respectively. The LODs are relatively low in comparison with those of the reported CP-based sensors for Fe3+ and MnO4. In addition, 1 also has high selectivity and remarkable anti-interference ability, as well as good recyclability for at least five cycles. Furthermore, the potential application of the sensor for the detection of Fe3+ and MnO4 was studied through simulated wastewater samples with different concentrations. The possible sensing mechanisms were investigated using Ultraviolet-Visible (UV-Vis) absorption spectroscopy and density functional theory (DFT) calculations. The results revealed that the luminescence turn-off effects toward Fe3+ and MnO4 were caused by competitive absorption and photoinduced electron transfer (PET), and competitive absorption and inner filter effect (IFE), respectively. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>a</b>) The coordination environment of Dy<sup>3+</sup> (symmetry codes #1: 2−<span class="html-italic">x</span>, −<span class="html-italic">y</span>, 4−<span class="html-italic">z</span>; #2: 1+<span class="html-italic">x</span>, 1−<span class="html-italic">y</span>, 2+<span class="html-italic">z</span>; #3: 2.5−<span class="html-italic">x</span>, 0.5−<span class="html-italic">y</span>, 5−<span class="html-italic">z</span>); (<b>b</b>) double-capped triangular prism coordination geometry of Dy<sup>3+</sup>; (<b>c</b>) coordination mode of spasds<sup>3−</sup> anion; (<b>d</b>) 2D layered structure constructed by spasds<sup>3−</sup> anions and Dy<sup>3+</sup> cations; (<b>e</b>) (4,4)-connected topological structure.</p>
Full article ">Figure 2
<p>Fluorescence excitation and emission spectra of (<b>a</b>) free Na<sub>2</sub>Hspasda ligand and <b>1</b>; (<b>b</b>) CIE plot of <b>1</b> (<b>1</b> refers to the title CP. The circle indicates the color).</p>
Full article ">Figure 3
<p>Fluorescence responses of <b>1</b> toward different solvents (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm).</p>
Full article ">Figure 4
<p>(<b>a</b>) Fluorescence responses; and (<b>b</b>) fluorescence intensities of <b>1</b> toward different metal cations at 0.01 M in aqueous solution (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm).</p>
Full article ">Figure 5
<p>Competitive experiments of the suspensions of <b>1</b> with (<b>a</b>) one interfering metal ion, and (<b>b</b>) several interfering metal ions (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm).</p>
Full article ">Figure 6
<p>(<b>a</b>) Fluorescence responses of <b>1</b> with the dropwise addition of the aqueous solution of Fe<sup>3+</sup>; (<b>b</b>) Stern–Volmer plot for the quenching effect of Fe<sup>3+</sup> on <b>1</b> (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm). (The different color lines and square shapes represent different concentrations).</p>
Full article ">Figure 7
<p>Quenching and regeneration experiments of <b>1</b> for the detection of Fe<sup>3+</sup>.</p>
Full article ">Figure 8
<p>(<b>a</b>) Fluorescence responses; and (<b>b</b>) fluorescence intensities of <b>1</b> toward different inorganic anions at 0.01 M in aqueous solution (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm).</p>
Full article ">Figure 9
<p>Competitive experiments of the suspensions of <b>1</b> with (<b>a</b>) one interfering anion; and (<b>b</b>) several interfering anions (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm).</p>
Full article ">Figure 10
<p>(<b>a</b>) Fluorescence responses of <b>1</b> with the dropwise addition of the aqueous solution of MnO<sub>4</sub><sup>−</sup>; (<b>b</b>) Stern–Volmer plot for the quenching effect of MnO<sub>4</sub><sup>−</sup> on <b>1</b> (<span class="html-italic">λ</span><sub>ex</sub> = 370 nm). (The different color lines and square shapes represent different concentrations).</p>
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<p>Quenching and regeneration experiments of <b>1</b> for the detection of MnO<sub>4</sub><sup>−</sup>.</p>
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<p>(<b>a</b>,<b>b</b>) Comparison of luminescence changes before and after the addition of the simulated samples.</p>
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<p>(<b>a</b>) Measured PXRD pattern of the sample of <b>1</b> after soaking in Fe<sup>3+</sup> for 24 h and simulated one based on single crystal data of <b>1</b>; (<b>b</b>) UV-Vis absorption spectrum of Fe<sup>3+</sup> and fluorescence excitation spectrum of <b>1</b>.</p>
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<p>(<b>a</b>) Measured PXRD pattern of the sample of <b>1</b> after soaking in MnO<sub>4</sub><sup>−</sup> for 24 h and simulated one based on single crystal data of <b>1</b>; (<b>b</b>) UV-Vis absorption spectrum of MnO<sub>4</sub><sup>−</sup> and fluorescence excitation spectrum of <b>1</b>.</p>
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<p>Structure optimization and the frontier molecular orbital energy levels of the ligand, Fe<sup>3+</sup> and MnO<sub>4</sub><sup>−</sup>.</p>
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17 pages, 5449 KiB  
Article
Croton gratissimus Burch Herbal Tea Exhibits Anti-Hyperglycemic and Anti-Lipidemic Properties via Inhibition of Glycation and Digestive Enzyme Activities
by Veronica F. Salau, Kolawole A. Olofinsan, Abhay P. Mishra, Olufemi A. Odewole, Corinne R. Ngnameko and Motlalepula G. Matsabisa
Plants 2024, 13(14), 1952; https://doi.org/10.3390/plants13141952 - 17 Jul 2024
Viewed by 1037
Abstract
Over the years, the world has continued to be plagued by type 2 diabetes (T2D). As a lifestyle disease, obese individuals are at higher risk of developing the disease. Medicinal plants have increasingly been utilized as remedial agents for managing metabolic syndrome. The [...] Read more.
Over the years, the world has continued to be plagued by type 2 diabetes (T2D). As a lifestyle disease, obese individuals are at higher risk of developing the disease. Medicinal plants have increasingly been utilized as remedial agents for managing metabolic syndrome. The aim of the present study was to investigate the in vitro anti-hyperglycemic and anti-lipidemic potential of Croton gratissimus herbal tea infusion. The inhibitory activities of C. gratissimus on carbohydrate (α-glucosidase and α-amylase) and lipid (pancreatic lipase) hydrolyzing enzymes were determined, and the mode of inhibition of the carbohydrate digestive enzymes was analyzed and calculated via Lineweaver–Burk plots and Michaelis Menten’s equation. Its effect on Advanced Glycation End Product (AGE) formation, glucose adsorption, and yeast glucose utilization were also determined. High-performance liquid chromatography (HPLC) was used to quantify the possible phenolic compounds present in the herbal tea infusion, and the compounds were docked with the digestive enzymes. C. gratissimus significantly (p < 0.05) inhibited α-glucosidase (IC50 = 60.56 ± 2.78 μg/mL), α-amylase (IC50 = 35.67 ± 0.07 μg/mL), as well as pancreatic lipase (IC50 = 50.27 ± 1.51 μg/mL) in a dose-dependent (15–240 µg/mL) trend. The infusion also inhibited the non-enzymatic glycation process, adsorbed glucose effectively, and enhanced glucose uptake in yeast cell solutions at increasing concentrations. Molecular docking analysis showed strong binding affinity between HPLC-quantified compounds (quercetin, caffeic acid, gallic acid, and catechin) of C. gratissimus herbal tea and the studied digestive enzymes. Moreover, the herbal tea product did not present cytotoxicity on 3T3-L1 cell lines. Results from this study suggest that C. gratissimus herbal tea could improve glucose homeostasis and support its local usage as a potential anti-hyperglycemic and anti-obesogenic agent. Further in vivo and molecular studies are required to bolster the results from this study. Full article
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<p>(<b>A</b>) α-Glucosidase inhibitory activities of <span class="html-italic">C. gratissimus</span> tea and (<b>B</b>) Lineweaver–Burk plot for <span class="html-italic">C. gratissimus</span> tea mode of <span class="html-italic">α</span>-glucosidase inhibition. Data = mean ± SD; n = 3. <sup>ab</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p>(<b>A</b>) α-Amylase inhibitory activities of <span class="html-italic">C. gratissimus</span> tea and (<b>B</b>) Lineweaver–Burk plot for <span class="html-italic">C. gratissimus</span> tea mode of α-amylase inhibition. Data = mean ± SD; n = 3. <sup>ab</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p>Glucose binding capacity of <span class="html-italic">C. gratissimus</span> tea at different concentrations of glucose. Data = mean ± SD; n = 3. <sup>abcd</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p>Effect of <span class="html-italic">C. gratissimus</span> tea on glucose uptake by yeast cells. Data = mean ± SD; n = 3. <sup>ab</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p><span class="html-italic">C. gratissimus</span> tea inhibition of glycation as compared to a standard antiglycation drug. Data = mean ± SD; n = 3. <sup>abcde</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p>Pancreatic lipase inhibitory activities of <span class="html-italic">C. gratissimus</span> tea. Data = mean ± SD; n = 3. <sup>ab</sup> Values with different letters above the bars for a given concentration are significantly (<span class="html-italic">p</span> &lt; 0.05) different from each other.</p>
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<p>The 3D and 2D images of the molecular interactions of quercetin with the active site amino residues of (<b>A</b>) lipase, (<b>B</b>) amylase, and (<b>C</b>) glucosidase.</p>
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<p>Cytotoxic effect of <span class="html-italic">C. gratissimus</span> on the 3T3 fibroblast cell line. Value = mean ± SD; n = 3. <sup>a</sup> Statistically significant compared to the doxorubicin group; <sup>b</sup> statistically significant compared to the normal control cell (<span class="html-italic">p</span> &lt; 0.05, Tukey’s HSD-multiple range post hoc test).</p>
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12 pages, 2359 KiB  
Article
Determination of Luteolin and Apigenin in Herbal Teas by Online In-Tube Solid-Phase Microextraction Coupled with LC–MS/MS
by Atsushi Ishizaki, Akiko Miura and Hiroyuki Kataoka
Foods 2024, 13(11), 1687; https://doi.org/10.3390/foods13111687 - 28 May 2024
Cited by 2 | Viewed by 1647
Abstract
Herbal teas have attracted attention as functional beverages containing luteolin and apigenin, which exhibit antioxidant and anti-inflammatory effects. The objective of this study was to develop a sensitive online automated method to determine these flavones’ contents in herbal teas using in-tube solid-phase microextraction [...] Read more.
Herbal teas have attracted attention as functional beverages containing luteolin and apigenin, which exhibit antioxidant and anti-inflammatory effects. The objective of this study was to develop a sensitive online automated method to determine these flavones’ contents in herbal teas using in-tube solid-phase microextraction (IT-SPME) coupled with liquid chromatography–tandem mass spectrometry (LC–MS/MS). These compounds were extracted and concentrated by IT-SPME using a Supel Q PLOT capillary column and then separated and detected within 6 min using a CAPCELL PAK C18 MG III analytical column and a negative electrospray ionization-mode multiple-reaction monitoring system by LC–MS/MS. The detection limits (S/N = 3) for luteolin and apigenin were 0.4 and 0.8 pg mL−1, respectively, and the calibration curves were linear in the range of 2–2000 pg mL−1 with correlation coefficients above 0.9995, and intra-day and inter-day precisions with relative standard deviations below 2.9 and 3.6% (n = 6), respectively. The luteolin and apigenin in herbal tea were quantified using IT-SPME/LC-MS/MS following the acid hydrolysis of their glycosides. Among the 10 herbal teas tested, luteolin was detected in peppermint and sage at concentrations of 375 and 99 µg mL−1, respectively, while apigenin was detected in German chamomile at 110 µg mL−1, which were higher than in the other herbal teas. The method is expected to be a useful method for evaluating the efficacy of luteolin and apigenin in herbal teas as functional beverages. Full article
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<p>Structures of luteolin, apigenin, and apigenin-d<sub>5</sub>.</p>
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<p>Schematic diagram of the improved IT-SPME LC-MS/MS system used in this study. (<b>A</b>) Adsorption of compound on stationary phase in capillary column, (<b>B</b>) desorption of compound by mobile phase solvent.</p>
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<p>Effects of capillary coatings on IT-SPME of luteolin and apigenin. For each capillary column, 40 µL of a 100 pg mL<sup>−1</sup> standard solution was repeatedly injected 5 times.</p>
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<p>Effects of pH of sample solution on IT-SPME of luteolin and apigenin. For each pH, 40 µL of a 100 pg mL<sup>−1</sup> standard solution was repeatedly injected 5 times.</p>
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<p>Effects of number of sample injections on IT-SPME of luteolin and apigenin. For each injection number, 40 µL of a 100 pg mL<sup>−1</sup> standard solution was repeatedly injected.</p>
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<p>MRM chromatograms obtained from standard solution by IT-SPME LC-MS/MS in the negative ion mode. IT-SPME LC-MS/MS conditions are described in the Experimental Section.</p>
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<p>MRM chromatograms obtained from herbal tea by IT- SPME LC-MS/MS in the negative ion mode. IT-SPME LC-MS/MS conditions are described in the Experimental Section. MRM transitions are the same as in <a href="#foods-13-01687-f006" class="html-fig">Figure 6</a>.</p>
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17 pages, 3181 KiB  
Article
Development of Noninvasive Method for the Automated Analysis of Nine Steroid Hormones in Human Saliva by Online Coupling of In-Tube Solid-Phase Microextraction with Liquid Chromatography–Tandem Mass Spectrometry
by Takashi Hitomi and Hiroyuki Kataoka
Analytica 2024, 5(2), 233-249; https://doi.org/10.3390/analytica5020015 - 9 May 2024
Cited by 3 | Viewed by 1526
Abstract
Accurate measurement of steroid hormones is crucial to elucidate new mechanisms of action and diagnose steroid metabolism-related diseases. This study presents a simple, sensitive, and automated analytical method for nine representative steroid hormones. The method involves on-line coupling of in-tube solid-phase microextraction (IT-SPME) [...] Read more.
Accurate measurement of steroid hormones is crucial to elucidate new mechanisms of action and diagnose steroid metabolism-related diseases. This study presents a simple, sensitive, and automated analytical method for nine representative steroid hormones. The method involves on-line coupling of in-tube solid-phase microextraction (IT-SPME) with liquid chromatography–tandem mass spectrometry (LC–MS/MS). The steroid hormones were extracted and enriched on a Supel-Q PLOT capillary column using IT-SPME. Subsequently, they were separated and detected within 6 min using a Discovery HS F5-3 column and positive ion mode multiple reaction monitoring system via LC–MS/MS. Calibration curves of these compounds using each stable isotope-labeled internal standard (IS) showed linearity with correlation coefficients greater than 0.9990 in the range of 0.01–40 ng/mL, with limits of detection (S/N = 3) of 0.7–21 pg/mL. Moreover, intra- and inter-day variations were lower than 8.1 and 15% (n = 6), respectively. The recoveries of these compounds from saliva samples were in the range of 82–114%. The developed IT-SPME/LC–MS/MS method of steroid hormones is a highly sensitive, specific, and non-invasive analytical method that allows extraction and enrichment with no organic solvents, and enables direct automated online analysis by simply ultrafiltrating a small sample of saliva. Full article
(This article belongs to the Section Sample Pretreatment and Extraction)
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<p>Structures of steroid hormones and their stable isotope-labeled internal standards.</p>
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<p>Schematic diagram of the on-line IT-SPME LC–MS/MS system. Analytes in the sample solution are extracted into the capillary column in the Load position (<b>A</b>), and after switching the six-port valve in the Injection position (<b>B</b>), the mobile phase flows into the capillary to desorb the analytes and inject them directly into the HPLC. The red two-way arrows indicate repeated draw/eject of sample solution, and the blue arrows indicate mobile phase flow.</p>
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<p>MRM chromatograms obtained from standard solution by IT-SPME LC–MS/MS in the positive ion mode. IT-SPME LC–MS/MS conditions are described in the Experiment section.</p>
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<p>Effects of capillary coatings on IT-SPME of steroid hormones. The three compounds were extracted by 25 draw/eject cycles of 40 μL of standard solution.</p>
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<p>Effects of draw/eject cycles on IT-SPME of steroid hormones. These compounds were extracted with Supel-Q PLOT capillary by draw/eject cycles of 40 μL of standard solution.</p>
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<p>MRM chromatograms obtained from 0.05 mL of saliva sample via IT-SPME LC–MS/MS in positive ion mode. IT-SPME LC–MS/MS conditions are described in the Experiment section.</p>
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20 pages, 13103 KiB  
Article
Response Surface Methodology Optimization of Resistance Welding Process for Unidirectional Carbon Fiber/PPS Composites
by Da-Wei Yu, Xiao-Ting Qing, Hong-Yu Lin, Jie Yang, Jia-Cao Yang and Xiao-Jun Wang
Materials 2024, 17(10), 2176; https://doi.org/10.3390/ma17102176 - 7 May 2024
Cited by 4 | Viewed by 1244
Abstract
The use of thermoplastic composites (TPCs) as one of the lightweight solutions will inevitably encounter problems in connection. Resistance welding has the characteristics of high strength, simplicity, and high reliability, and is considered a very potential hot-melt connection technology. The resistance welding technology [...] Read more.
The use of thermoplastic composites (TPCs) as one of the lightweight solutions will inevitably encounter problems in connection. Resistance welding has the characteristics of high strength, simplicity, and high reliability, and is considered a very potential hot-melt connection technology. The resistance welding technology of unidirectional carbon fiber-reinforced polyphenylene sulfide composites (UCF/PPS) was systematically studied. The experimental results show that the 100-mesh brass mesh has the best resin wetting effect and heating efficiency, and the PPS/oxidized 100-mesh brass mesh composite resistance element (Ox-RE/PPS) has the highest welding strength. The welding failure mode changes from interface failure and RE failure to interlayer structure damage and fiber fracture. The single-factor experimental results show that the maximum welding strength is reached at 310 °C, 1.15 MPa, and 120 kW/m2. According to the conclusion of the single-factor experiment, the Box–Behnken method was further used to design a three-factor, three-level experiment, and a quadratic regression model was established according to the test results. The results of variance analysis, fitting curve analysis, and perturbation plot analysis proved that the model had high fitting and prediction abilities. From the 3D surface diagram analysis, the influence of power density is the largest, and the interaction between welding temperature and power density is the most significant. Combined with the analysis of Design Expert 13 software, the optimal range of process parameters was obtained as follows: welding temperature 313–314 °C, welding pressure 1.04–1.2 MPa, and power density 124–128 kW/m2. The average strength of resistance welding joints prepared in the optimal range of process parameters was 13.58 MPa. Full article
(This article belongs to the Special Issue Advanced Manufacturing Technologies of Thermoplastic Composites)
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<p>(<b>a</b>) Schematic diagram of UCF/PPS laminate and (<b>b</b>) schematic diagram of UCF/PPS specimen.</p>
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<p>Resistance elements: (<b>a</b>) UT-RE, (<b>b</b>) Ox-RE, and (<b>c</b>) Ox-RE/PPS.</p>
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<p>(<b>a</b>) Single-lap resistance welding experimental device and (<b>b</b>) schematic diagram of PPS/UCF single-lap resistance welding.</p>
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<p>LSS of joints at different mesh sizes.</p>
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<p>Heating curve: (<b>a</b>) brass mesh 40 mesh, (<b>b</b>) brass mesh 100 mesh, and (<b>c</b>) brass mesh 200 mesh.</p>
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<p>Macroscopic morphology of the failure surface: (<b>a</b>) brass mesh 40 mesh, (<b>b</b>) brass mesh 100 mesh, and (<b>c</b>) brass mesh 200 mesh.</p>
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<p>LSS of joints at different RE process methods.</p>
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<p>Macroscopic morphology of the failure surface: (<b>a</b>) UT-RE, (<b>b</b>) Ox-RE, and (<b>c</b>) Ox-RE/PPS.</p>
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<p>Microscopic morphology of the failure surface: (<b>a</b>) UT-RE, (<b>b</b>) Ox-RE, and (<b>c</b>) Ox-RE/PPS.</p>
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<p>Microscopic morphology of the section: (<b>a</b>) Ox-RE and (<b>b</b>) Ox-RE/PPS.</p>
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<p>LSS of joints at different pressure holding times.</p>
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<p>LSS of joints at different welding temperatures.</p>
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<p>LSS of joints at different welding pressures.</p>
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<p>LSS of joints at different power densities.</p>
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<p>(<b>a</b>) Experimental and predicted values of welding strength and (<b>b</b>) perturbation plot of welding strength. The color square in <a href="#materials-17-02176-f015" class="html-fig">Figure 15</a>a correspond to the LSS experiment results in <a href="#materials-17-02176-t002" class="html-table">Table 2</a>.</p>
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<p>3D surface diagram of interaction: (<b>a</b>) T and F, (<b>b</b>) T and P, and (<b>c</b>) F and P. The welding strength from low to high corresponds to the color in figure form blur to red.</p>
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<p>Strength of the hot pressing connection method.</p>
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<p>Macroscopic morphology of the failure surface: (<b>a</b>) 1 MPa, (<b>b</b>) 3 MPa, and (<b>c</b>) 5 MPa.</p>
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<p>Microscopic morphology of the failure surface: (<b>a</b>) 1 MPa, (<b>b</b>) 3 MPa, and (<b>c</b>) 5 MPa.</p>
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16 pages, 4679 KiB  
Article
Study on the Neuroprotective Effects of Eight Iridoid Components Using Cell Metabolomics
by Bingxian Zhang, Ning Zhou, Zhenkai Zhang, Ruifeng Wang, Long Chen, Xiaoke Zheng and Weisheng Feng
Molecules 2024, 29(7), 1497; https://doi.org/10.3390/molecules29071497 - 27 Mar 2024
Viewed by 1456
Abstract
Iridoid components have been reported to have significant neuroprotective effects. However, it is not yet clear whether the efficacy and mechanisms of iridoid components with similar structures are also similar. This study aimed to compare the neuroprotective effects and mechanisms of eight iridoid [...] Read more.
Iridoid components have been reported to have significant neuroprotective effects. However, it is not yet clear whether the efficacy and mechanisms of iridoid components with similar structures are also similar. This study aimed to compare the neuroprotective effects and mechanisms of eight iridoid components (catalpol (CAT), genipin (GE), geniposide (GEN), geniposidic acid (GPA), aucubin (AU), ajugol (AJU), rehmannioside C (RC), and rehmannioside D (RD)) based on corticosterone (CORT)-induced injury in PC12 cells. PC12 cells were randomly divided into a normal control group (NC), model group (M), positive drug group (FLX), and eight iridoid administration groups. Firstly, PC12 cells were induced with CORT to simulate neuronal injury. Then, the MTT method and flow cytometry were applied to evaluate the protective effects of eight iridoid components on PC12 cell damage. Thirdly, a cell metabolomics study based on ultra-performance liquid chromatography–quadrupole–time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was performed to explore changes in relevant biomarkers and metabolic pathways following the intervention of administration. The MTT assay and flow cytometry analysis showed that the eight iridoid components can improve cell viability, inhibit cell apoptosis, reduce intracellular ROS levels, and elevate MMP levels. In the PCA score plots, the sample points of the treatment groups showed a trend towards approaching the NC group. Among them, AU, AJU, and RC had a weaker effect. There were 38 metabolites (19 metabolites each in positive and negative ion modes, respectively) identified as potential biomarkers during the experiment, among which 23 metabolites were common biomarkers of the eight iridoid groups. Pathway enrichment analysis revealed that the eight iridoid components regulated the metabolism mainly in relation to D-glutamine and D-glutamate metabolism, arginine biosynthesis, the TCA cycle, purine metabolism, and glutathione metabolism. In conclusion, the eight iridoid components could reverse an imbalanced metabolic state by regulating amino acid neurotransmitters, interfering with amino acid metabolism and energy metabolism, and harmonizing the level of oxidized substances to exhibit neuroprotective effects. Full article
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<p>Structures of eight active iridoid components.</p>
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<p>Interventional effects of eight iridoid components on CORT-induced PC12 cells. (<b>A</b>) Effect of eleven iridoid components on cell viability in CORT-induced PC12 cells (mean ± SD, <span class="html-italic">n</span> = 6 per group). (<b>B</b>–<b>D</b>) Effects of eight iridoid components on cell apoptosis, intracellular ROS levels, and MMP levels in CORT-induced PC12 cells (mean ± SD, <span class="html-italic">n</span> = 3 per group). In (<b>B</b>), pseudocolour shows the density of cells by shades of colour. In (<b>D</b>), blue fluorescence represents JC-1 monomer and red fluorescence represents JC-1 in polymer form. <span class="html-italic">** p</span> &lt; 0.01, compared with NC group; <span class="html-italic"><sup>#</sup> p</span> &lt; 0.05, <span class="html-italic"><sup>##</sup> p</span> &lt; 0.01, compared with M group.</p>
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<p>The PCA score plots obtained from NC, M, and eight treatment groups. (<b>A</b>) NC, M, FLX, GE, CAT, GPA and GEN groups in the first stage. (<b>B</b>) NC, M, FLX, AU, AJU, RC and RD groups in the second stage.</p>
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<p>UpSet plots of differential biomarkers in the eight iridoid groups. The horizontal bar graph on the left side indicates the number of markers in each group, the connecting lines among points in the middle array indicate specific intersections in different groups, and the vertical bar graph indicates the number of markers corresponding to intersections.</p>
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<p>Cluster analysis of potential biomarkers in the groups (Pearson correlation was used for clustering, average linkage clustering was used for the clustering method, and double gradient was used for gradient style). (<b>A</b>) NC, M, FLX, GE, CAT, GPA and GEN groups in the first stage. (<b>B</b>) NC, M, FLX, AU, AJU, RC and RD groups in the second stage. Each row represents a metabolite, and each column represents an experimental group (N/M/CAT/GE/GEN/GPA/AU/AJU/RC/RD). The color from red to blue represents the average content from high to low.</p>
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<p>Metabolic pathway enrichment in GE/CAT/GPA/GEN/AU/AJU/RC/RD groups. (<span class="html-italic">p</span> &lt; 0.05; the size of dots represents the impact factor of the metabolic pathway).</p>
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<p>Metabolic network associated with neuroprotective effects of iridoids. Mini bar chart from left to right represents the average content of biomarkers in NC, M, GE, CAT, GPA, and GEN groups in the first stage and NC, M, AU, AJU, RC, and RD groups in the second stage. Metabolites labeled in red were from cell samples.</p>
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12 pages, 2663 KiB  
Article
Ignition Delay and Reaction Time Measurements of Hydrogen–Air Mixtures at High Temperatures
by Yauhen Baranyshyn, Vyacheslav Kuzmitski, Oleg Penyazkov and Kirill Sevrouk
Fire 2024, 7(2), 43; https://doi.org/10.3390/fire7020043 - 30 Jan 2024
Cited by 1 | Viewed by 2381
Abstract
Induction and reaction times of hydrogen–air mixtures (ϕ = 0.5–2) have been measured behind reflected shock waves at temperatures of 1000–1600 K, pressures of 0.1, 0.3, 0.6 MPa in the domain of the extended second explosion limit. The measurements were performed in the [...] Read more.
Induction and reaction times of hydrogen–air mixtures (ϕ = 0.5–2) have been measured behind reflected shock waves at temperatures of 1000–1600 K, pressures of 0.1, 0.3, 0.6 MPa in the domain of the extended second explosion limit. The measurements were performed in the shock tube with a completely transparent test section of 0.5 m long, which provides pressure, ion current, OH and high-speed chemiluminescence observations. The experimental induction time plots demonstrate a clear increasing of the global activation energy from high- to low temperature post-shock conditions. This trend is strongly pronounced at higher post-shock pressures. For a high-temperature range of T > 1200 K, induction time measurements show an activation energy for the global reaction rate of hydrogen oxidation of 64–83 kJ/mole. Detected reaction times exhibit a big scatter and a weak temperature dependence. The minimum reaction time value was nearly 2 µs. Obtained induction time data were compared with calculations carried out in accordance with the known kinetic mechanisms. For current and former shock-tube experiments within a pressure range of 0.1–2 MPa, critical temperatures required for strong (1000–1100 K), transient and weak auto-ignition modes behind reflected shock waves were identified by means of the pressure and ion-probe measurements in stoichiometric hydrogen-air mixture. The transfer from the strong volumetric self-ignition near the reflecting wall to the hot spot ignition (transient) was established and visualized below <1200 K with a post-shock temperature decreasing. Full article
(This article belongs to the Special Issue State-of-the-Art on Hydrogen Combustion)
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<p>Schematic of the test section in the shock tube: 1—high-frequency pressure sensors, 2—ion current sensors, 3—photomultiplier with diaphragm and double narrowband filter, 4—high-speed video camera.</p>
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<p>Comparisons of the experimental end wall ion current record with OH yield (<b>a</b>) and gas temperature (<b>b</b>) temporary profiles deduced from detailed GRI Mech 3.0 reaction mechanism at auto-ignition of the lean stoichiometric hydrogen–air mixture at similar post-shock conditions.</p>
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<p>Criterion for definition of the critical temperature for strong ignition mode in stoichiometric hydrogen–air mixture at 0.29 ± 0.036 MPa using a temperature dependence of the velocity of reflected shock wave.</p>
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<p>Comparison of the measured induction times in stoichiometric hydrogen–air mixture at post-shock pressures 0.31 (<b>a</b>), and 0.57 (<b>b</b>) MPa with existing literature data at similar conditions [<a href="#B3-fire-07-00043" class="html-bibr">3</a>,<a href="#B5-fire-07-00043" class="html-bibr">5</a>,<a href="#B7-fire-07-00043" class="html-bibr">7</a>,<a href="#B18-fire-07-00043" class="html-bibr">18</a>,<a href="#B23-fire-07-00043" class="html-bibr">23</a>].</p>
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<p>Induction and reaction times vs. reciprocal temperature in stoichiometric (ϕ = 1) (<b>a</b>), lean (ϕ = 0.5) with 15% N<sub>2</sub> dilution (<b>b</b>) and rich (ϕ = 2) (<b>c</b>) hydrogen–air mixtures at mean post-shock pressures of 0.31–0.34 and 0.57–0.62 MPa.</p>
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<p>Collections of ignition delay data points in stoichiometric (ϕ = 1), lean (ϕ = 0.5) and rich (ϕ = 2) hydrogen-air mixture at mean post-shock pressures of 0.31–0.34 MPa (<b>a</b>) and 0.57–0.62 MPa (<b>b</b>).</p>
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<p>High-speed video observation of self-ignition in stoichiometric hydrogen–air mixture: (<b>a</b>) volumetric self-ignition near the reflecting wall at 1230 K and 0.53 MPa; (<b>b</b>) self-ignition with hot spot formation at 1100 K and 0.31 MPa.</p>
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<p>Autoignition domain in stoichiometric hydrogen-air mixture in a P-T plane: I—strong ignition; II—transient ignition; III—weak ignition; IV—no ignition and lines of the constant induction times.</p>
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13 pages, 2902 KiB  
Article
Determination of Electrical and Mechanical Properties of Liquids Using a Resonator with a Longitudinal Electric Field
by Alexander Semyonov, Boris Zaitsev, Andrey Teplykh and Irina Borodina
Sensors 2024, 24(3), 793; https://doi.org/10.3390/s24030793 - 25 Jan 2024
Viewed by 894
Abstract
The possibility of determining the elastic modules, viscosity coefficients, dielectric constant and electrical conductivity of a viscous conducting liquid using a piezoelectric resonator with a longitudinal electric field is shown. For the research, we chose a piezoelectric resonator made on an AT-cut quartz [...] Read more.
The possibility of determining the elastic modules, viscosity coefficients, dielectric constant and electrical conductivity of a viscous conducting liquid using a piezoelectric resonator with a longitudinal electric field is shown. For the research, we chose a piezoelectric resonator made on an AT-cut quartz plate with round electrodes, operating with a shear acoustic mode at a frequency of about 4.4 MHz. The resonator was fixed to the bottom of a 30 mL liquid container. The samples of a mixture of glycerol and water with different viscosity and conductivity were used as test liquids. First, the frequency dependences of the real and imaginary parts of the electrical impedance of a free resonator were measured and, using the Mason electromechanical circuit, the elastic module, viscosity coefficient, piezoelectric constant and dielectric constant of the resonator material (quartz) were determined. Then, the container was filled with the test sample of a liquid mixture so that the resonator was completely covered with liquid, and the measurement of the frequency dependences of the real and imaginary parts of the electrical impedance of the loaded resonator was repeated. The dependences of the frequency of parallel and series resonances, as well as the maximum values of the electrical impedance and admittance on the conductivity of liquids for various viscosity values, were plotted. It was shown that these dependences can be used to unambiguously determine the viscosity and conductivity of the test liquid. Next, by fitting the theoretical frequency dependences of the real and imaginary parts of the electrical impedance of the resonator loaded with the liquid under study to the experimental dependences, the elastic module of the liquid and its dielectric constant were determined. Full article
(This article belongs to the Special Issue Piezoelectric Resonator-Based Sensors)
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<p>Set-up for determining the dielectric constant of liquids.</p>
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<p>The liquid container with the quartz resonator.</p>
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<p>Dependences of the resonant frequency of parallel (<b>a</b>) and series (<b>b</b>) resonances, as well as the maximum values of the real parts of the electrical impedance (<b>c</b>) and admittance (<b>d</b>) of a quartz resonator on the conductivity of the liquid. (1—aqueous solution of sodium chloride (<span class="html-italic">β</span> = 0), 2—mixture “water-glycerol” <span class="html-italic">β</span> = 44%, 3—mixture “water-glycerol” <span class="html-italic">β</span> = 65%, 4—mixture “water-glycerol” <span class="html-italic">β</span> = 75%).</p>
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<p>Dependences of the resonant frequency of parallel (<b>a</b>) and series (<b>b</b>) resonances, as well as the maximum values of the real parts of the electrical admittance (<b>c</b>) of a quartz resonator on the viscosity of the liquid. Liquid conductivity: 1—1.4 μS/cm, 2—27 μS/cm, 3—55 μS/cm, 4—82 μS/cm, 5—123 μS/cm.</p>
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<p>The frequency dependences of the real (<b>a</b>) and imaginary (<b>b</b>) parts of the electrical impedance of the AT-quartz resonator without load (pink—experiment, blue—the result of fitting).</p>
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<p>Equivalent circuit of a resonator with electrodes immersed in a liquid, taking into account additional capacitance (<span class="html-italic">C<sub>a</sub></span>) and resistance (<span class="html-italic">R<sub>a</sub></span>).</p>
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<p>Frequency dependences of the real (<b>a</b>,<b>c</b>) and imaginary (<b>b</b>,<b>d</b>) parts of the electrical impedance of a quartz resonator for an aqueous solution of NaCl with a conductivity of 1.4 μS/cm (<b>a</b>,<b>b</b>), and for a “water–glycerol” mixture <span class="html-italic">β</span> = 75%, <span class="html-italic">σ<sup>l</sup></span> = 55 μS/cm (<b>c</b>,<b>d</b>). Blue color—theory, green color—experiment.</p>
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<p>Frequency dependences of the real (<b>a</b>,<b>c</b>) and imaginary (<b>b</b>,<b>d</b>) parts of the electrical impedance of a quartz resonator for an aqueous solution of NaCl with a conductivity of 1.4 μS/cm (<b>a</b>,<b>b</b>), and for a “water–glycerol” mixture <span class="html-italic">β</span> = 75%, <span class="html-italic">σ<sup>l</sup></span> = 55 μS/cm (<b>c</b>,<b>d</b>). Blue color—theory, green color—experiment.</p>
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<p>(<b>a</b>)—dependence of the additional capacity <span class="html-italic">C<sub>a</sub></span> on the conductivity of the liquid with different percentages of glycerol: 1—water, 2—mixture “water–glycerol” <span class="html-italic">β</span> = 44%, 3—mixture “water–glycerol” <span class="html-italic">β</span> = 65%, 4—mixture “water–glycerol” <span class="html-italic">β</span> = 75%. (<b>b</b>)—dependence of the average value of the additional capacity &lt;<span class="html-italic">Ca</span>&gt; on the measured value of <span class="html-italic">ε<sup>l</sup></span>.</p>
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<p>Dependence of the additional resistance <span class="html-italic">R<sub>a</sub></span> on the conductivity of a liquid with different percentages of glycerol: 1—water, 2—water–glycerol mixture <span class="html-italic">β</span> = 44%, 3—water–glycerol mixture <span class="html-italic">β</span> = 65%, 4—water–glycerol mixture <span class="html-italic">β</span> = 75%.</p>
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23 pages, 3823 KiB  
Article
Effects of Dietary Protein Levels on Sheep Gut Metabolite Profiles during the Lactating Stage
by Sikandar Ali, Xiaojun Ni, Muhammad Khan, Xiaoqi Zhao, Hongyuan Yang, Baiji Danzeng, Imtiaz Hussain Raja and Guobo Quan
Animals 2024, 14(1), 121; https://doi.org/10.3390/ani14010121 - 29 Dec 2023
Cited by 2 | Viewed by 1806
Abstract
Diet-associated characteristics such as dietary protein levels can modulate the gut’s primary or secondary metabolites, leading to effects on the productive performance and overall health of animals. Whereas fecal metabolite changes are closely associated with gut metabolome, this study aimed to see changes [...] Read more.
Diet-associated characteristics such as dietary protein levels can modulate the gut’s primary or secondary metabolites, leading to effects on the productive performance and overall health of animals. Whereas fecal metabolite changes are closely associated with gut metabolome, this study aimed to see changes in the rumen metabolite profile of lactating ewes fed different dietary protein levels. For this, eighteen lactating ewes (approximately 2 years old, averaging 38.52 ± 1.57 kg in their initial body weight) were divided into three groups (n = 6 ewes/group) by following the complete randomized design, and each group was assigned to one of three low-protein (D_I), medium-protein (D_m), and high-protein (D_h) diets containing 8.58%, 10.34%, and 13.93% crude protein contents on a dry basis, respectively. The fecal samples were subjected to untargeted metabolomics using ultra-performance liquid chromatography (UPLC). The metabolomes of the sheep fed to the high-protein-diet group were distinguished as per principal-component analysis from the medium- and low-protein diets. Fecal metabolite concentrations as well as their patterns were changed by feeding different dietary protein levels. The discriminating metabolites between groups of nursing sheep fed different protein levels were identified using partial least-squares discriminant analysis. The pathway enrichment revealed that dietary protein levels mainly influenced the metabolism-associated pathways (n = 63 and 39 in positive as well as negative ionic modes, respectively) followed by protein (n = 15 and 8 in positive as well as negative ionic modes, respectively) and amino-acid (n = 14 and 7 in positive as well as negative ionic modes, respectively) synthesis. Multivariate and univariate analyses showed comparative changes in the fecal concentrations of metabolites in both positive and negative ionic modes. Major changes were observed in protein metabolism, organic-acid biosynthesis, and fatty-acid oxidation. Pairwise analysis and PCA reveal a higher degree of aggregation within the D-h group than all other pairs. In both the PCA and PLS-DA plots, the comparative separation among the D_h/D_m, D_h/D_I, and D_m/D_I groups was superior in positive as well as negative ionic modes, which indicated that sheep fed higher protein levels had alterations in the levels of the metabolites. These metabolic findings provide insights into potentiated biomarker changes in the metabolism influenced by dietary protein levels. The target identification may further increase our knowledge of sheep gut metabolome, particularly regarding how dietary protein levels influence the molecular mechanisms of nutritional metabolism, growth performance, and milk synthesis of sheep. Full article
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<p>PCA analysis of positive (A+) and negative (A−) ionic modes detected fecal metabolites of the lactating ewes fed different dietary protein levels (D_h = high, D_m = medium, and D_I = low dietary protein levels).</p>
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<p>Enriched chemical class KEGG pathways of positive (A+) and negative (A−) ionic mode detected fecal metabolites of the lactating ewes fed different dietary protein levels (D_h = high, D_m = medium, and D_I = low dietary protein levels).</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_I = low dietary protein levels; (<b>b</b>) comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_I = low dietary protein levels.</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_I = low dietary protein levels; (<b>b</b>) comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_I = low dietary protein levels.</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_m = medium dietary protein levels. (<b>b</b>) Comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_m = medium dietary protein levels.</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_m = medium dietary protein levels. (<b>b</b>) Comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_h = high and D_m = medium dietary protein levels.</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_m = medium and D_I = low dietary protein levels. (<b>b</b>) Comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_m = medium and D_I = low dietary protein levels.</p>
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<p>(<b>a</b>) Comparative PCA and PLS-DA analysis of positive (A+ and B+) and negative (A− and B−) ionic mode detected fecal metabolites of the lactating ewes fed D_m = medium and D_I = low dietary protein levels. (<b>b</b>) Comparative volcano plots of positive (E+ and F+) and negative (E− and F−) ionic mode detected fecal metabolites of the lactating ewes fed D_m = medium and D_I = low dietary protein levels.</p>
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986 KiB  
Proceeding Paper
Mechanistic Insights into the Metabolic Pathways Using High-Resolution Mass Spectrometry and Predictive Models in Pancreatic β-Cell Lines (β-TC-6)
by Ghada A. Soliman, Ye He and Rinat Abzalimov
Biol. Life Sci. Forum 2023, 29(1), 16; https://doi.org/10.3390/IECN2023-15878 - 7 Nov 2023
Viewed by 745
Abstract
Objectives: We have previously shown that inhibition of the mTORC1 nutrient-sensing complex by rapamycin and mTORC1/mTORC2 inhibition by either Torin-2 or RapaLink-1 have differential effects on the global untargeted metabolomics in in vivo and in vitro cell culture models. Methods: In this study, [...] Read more.
Objectives: We have previously shown that inhibition of the mTORC1 nutrient-sensing complex by rapamycin and mTORC1/mTORC2 inhibition by either Torin-2 or RapaLink-1 have differential effects on the global untargeted metabolomics in in vivo and in vitro cell culture models. Methods: In this study, we leveraged the mummichog Python algorithm to analyze the high-dimension untargeted metabolomics data to model the biochemical pathways and metabolic networks and predict their functional activity. We used pancreatic beta-cell culture (Beta TC6) and incubated the cells with either Rapalink-1, Rapamycin or the vehicle control for 24 h. Cells were harvested and flush-frozen in liquid nitrogen. Cells were extracted in ethanol, and the supernatant was collected. The untargeted metabolomics was performed using the high-resolution mass spectrometry LC-MS/MS HILIC peak detection of ESI-positive and -negative polarity modes. The data were collected using Bruker’s maXis-II ESI-Q-q-TOF coupled to Dionex Ultimate-3000 U(H)PLC system using Sequant ZIC-HILIC 150 × 2.1 mm column (Bruker, Hamburg, Germany). We compared the high-resolution untargeted precision metabolomics (LC-MS/MS) between groups using positive and negative polarity modes to capture both hydrophilic and hydrophobic metabolites. We employed the XCMS plus bioinformatics platform to link mTOR-regulated metabolites to the predicted biological pathways. Statistical significance (p < 0.001) was assessed by ANOVA and Ranked order data by Whitney-Cox followed by ad hoc unpaired t-test. Results: The cluster heatmap deconvolution and cloud plot analysis show the differential pattern of metabolites between Rapamycin and Rapalink-treated pancreatic beta cell lines. Mapping the downstream metabolites data onto predictive metabolic pathways and activity networks revealed that the top pathways affected included the pentose phosphate pathway, dopamine and ubiquinol degradation pathways in the ESI-positive polarity mode, and creatine synthesis/glycine degradation and nicotine degradation pathways in the ESI negative polarity mode. Conclusions: The high-resolution untargeted metabolomics can be leveraged as a proxy of the internal exposome yielding high-dimensional data that provide mechanistic insights into metabolic and signaling pathways, and the underlying biology. This approach will have beneficial applications of the internal exposome in determining the optimal precision nutrition pathways for personalized medicine. Full article
(This article belongs to the Proceedings of The 3rd International Electronic Conference on Nutrients)
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<p>Principal component analysis (PCA) and heatmap visualization tools to compare the treatment groups. Pancreatic beta cell lines (β-TC-6) were incubated with either RapaLink, Rapamycin, or control for 24 h. Cells were harvested, flush-frozen, extracted and analyzed using an ESI-LC-MS/MS spectrometry-based approach. The data were collected and analyzed using the XCMS-Plus bioinformatics platform. (<b>A</b>) Principal component analysis (PCA) clusters of the treatment groups. (<b>B</b>). Heatmap visualization of the comparison of the untargeted metabolomics data.</p>
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<p>Visualization of data by cloud plot, PCA cluster, and heatmap of the differences of the untargeted metabolomics between the effects of mTORC1 inhibitor (Rapamycin) and mTORC1/mTORC2 inhibitor (RapaLink-1) on pancreatic cell lines (β-TC-6) in the ESI-positive and negative modes. Cells were incubated with either Rapalink, Rapamycin or control cells were harvested and analyzed by ESI-LC-MS/MS, followed by bioinformatics analysis using the XCMS-Plus platform. (<b>A</b>) Cloud plot of the comparison between RapaLink and Rapa incubation, showing (<b>A</b>) 55 features in the ESI-positive mode, (<b>B</b>) 344 features with a <span class="html-italic">p</span>-value ≤ 0.001, and fold change ≥ 1.5. (<b>C</b>) Principal component analysis (PCA) between RapaLink and Rapamycin in ESI-positive mode and (<b>D</b>) ESI-negative mode, respectively. (<b>E</b>) Heatmap of all the features in the global untargeted metabolomics dataset comparison between RapaLink-versus Rapamycin-treated pancreatic beta cells (β-TC-6).</p>
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15 pages, 1925 KiB  
Article
The Responses of Stem and Leaf Functional Traits of Medicago sativa and Bromus inermis to Different Mixed Planting Patterns
by Fuhong Miao, Xiaoxu Yu, Xinkai Tang, Xindi Liu, Wei Tang, Yanhua Zhao, Chao Yang, Yufang Xu, Guofeng Yang and Juan Sun
Agronomy 2023, 13(11), 2733; https://doi.org/10.3390/agronomy13112733 - 30 Oct 2023
Viewed by 1373
Abstract
This study investigated the differences in stem and leaf growth characteristics of Medicago sativa and Bromus inermis in the Jiaozhou region of China during 2019–2020 under three different planting modes of the two forages: monoculture, mixed species sowing in the same rows, and [...] Read more.
This study investigated the differences in stem and leaf growth characteristics of Medicago sativa and Bromus inermis in the Jiaozhou region of China during 2019–2020 under three different planting modes of the two forages: monoculture, mixed species sowing in the same rows, and mixed species sowing in alternating rows. No special management of the experimental plots was carried out in this study to simulate as much as possible the growth of forages in their natural state. The stem and leaf characteristics influencing the dry matter weight were calculated using grey correlation. These characteristics included leaf length, leaf width, leaf thickness, leaf area, leaf fresh weight, stem length, stem diameter, stem fresh weight, stem–leaf ratio, fresh matter yield, dry matter yield, and protein yield of M. sativa and B. inermis under different sowing methods in different years. The results showed that the weight pattern of the characteristics affecting the yield of M. sativa and B. inermis production was leaf area > stem diameter > leaf length > stem length > leaf width > leaf thickness, leaf area > leaf length > stem length > leaf width > leaf thickness > stem diameter. Considering all the growth factors, the production capacity was ranked as mixed sowing in alternating rows > mixed sowing in same rows > monoculture. Thus, the suitable mode for M. sativaB. inermis sowing was mixed sowing in alternating rows. Full article
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<p>Annual average temperature of test field in Jiaozhou area. Data from China Meteorological Data Service Centre (<a href="http://data.cma.cn" target="_blank">http://data.cma.cn</a> 8 February 2020).</p>
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<p>Correlation of <span class="html-italic">Medicago sativa</span> stem and leaf indicators under different sowing methods. LL is leaf length. LW is leaf width. LT is leaf thickness. LA is leaf area. SL is stem length. SD is stem diameter. Peer mix (P), heterocomplex (H), monoculture (M). Significance levels are as follows: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlation of <span class="html-italic">Bromus inermis</span> stem and leaf indicators under different sowing methods. LL is leaf length. LW is leaf width. LT is leaf thickness. LA is leaf area. SL is stem length. SD is stem diameter. Peer mix (P), heterocomplex (H), monoculture (M). Significance levels are as follows: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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14 pages, 3392 KiB  
Article
Multivariable Analysis of Nonlinear Optical Loop Mirror Operating Parameters Using Jones Matrices and Three-Dimensional Renderings
by Jose D. Filoteo-Razo, Juan C. Hernandez-Garcia, Julian M. Estudillo-Ayala, Olivier Pottiez, Jose R. Martinez-Angulo, Jose H. Barron-Zambrano, Juan C. Elizondo-Leal, Vicente P. Saldivar-Alonso, Jesus P. Lauterio-Cruz and Roberto Rojas-Laguna
Photonics 2023, 10(10), 1071; https://doi.org/10.3390/photonics10101071 - 23 Sep 2023
Viewed by 1463
Abstract
Nonlinear optical loop mirrors (NOLMs) are used in modern fiber optic devices and optical communications. In this study, we present numerical analyses of the multiple variables involved in the operation of an NOLM in low- and high-power transmissions. The Jones matrix formalism was [...] Read more.
Nonlinear optical loop mirrors (NOLMs) are used in modern fiber optic devices and optical communications. In this study, we present numerical analyses of the multiple variables involved in the operation of an NOLM in low- and high-power transmissions. The Jones matrix formalism was used to model linear and circular polarization inputs. We used three-dimensional (3D) plots to identify the characteristics required in the experimental operation of the NOLM. These characteristics, including the critical power, low- and high-power transmission, and dynamic range, depend on parameters such as the fiber loop length, input power, angle of retarder plate, and input polarization. A standard single-mode fiber (SMF-28) with high twist loop lengths of 100, 300, and 500 m and input powers of 0–100 W was simulated. Three-dimensional surface graphics provided a comprehensive view of the NOLM transmission and considerably enhanced the optimal transmission by manipulating adjustable device components including the power and polarization control plates. Optimal transmission facilitates its use in integrating ultrafast pulse generation, optical signal processing, optical communication systems, and photonic integrated circuit applications. Full article
(This article belongs to the Special Issue Recent Advances in Mode-Locked Fiber Laser)
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<p>Configuration of the NOLM investigated in this study.</p>
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<p>Three-dimensional surface plots of NOLM transmission for circular input polarization as a function of QWR angle (<span class="html-italic">α</span>) and input power (<span class="html-italic">P<sub>in</sub></span>) for (<b>a</b>) loop length <span class="html-italic">L</span> = 100 m, (<b>d</b>) <span class="html-italic">L</span> = 300 m, and (<b>g</b>) <span class="html-italic">L</span> = 500 m. (<b>b</b>,<b>e</b>,<b>h</b>) Contour maps showing the same data as in (<b>a</b>,<b>d</b>,<b>g</b>), respectively. (<b>c</b>,<b>f</b>,<b>i</b>) Switching power (<span class="html-italic">P<sub>π</sub></span>) as a function of the fiber loop length (<span class="html-italic">L</span>) corresponding to the data shown in (<b>a</b>,<b>b</b>), (<b>d</b>,<b>e</b>), and (<b>g</b>,<b>h</b>), respectively.</p>
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<p>Three-dimensional surface plots of NOLM transmission with linear input polarization as a function of input polarization angle (<span class="html-italic">ϕ</span>) and input power (<span class="html-italic">P<sub>in</sub></span>) for (<b>a</b>) loop length <span class="html-italic">L</span> = 100 m, (<b>d</b>) <span class="html-italic">L</span> = 300 m, and (<b>g</b>) <span class="html-italic">L</span> = 500 m. (<b>b</b>,<b>e</b>,<b>h</b>) Contour maps corresponding to the data shown in (<b>a</b>,<b>d</b>,<b>g</b>), respectively. (<b>c</b>,<b>f</b>,<b>i</b>) Switching power as a function of <span class="html-italic">ϕ</span> corresponding to the data shown in (<b>a</b>,<b>b</b>), (<b>d</b>,<b>e</b>), and (<b>g</b>,<b>h</b>), respectively.</p>
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<p>Three-dimensional surface plots showing switching power (<span class="html-italic">P<sub>π</sub></span>) for NOLM transmission versus loop length (<span class="html-italic">L</span>) and (<b>a</b>) polarization angle (<span class="html-italic">ϕ</span>) (for linear input polarization) or (<b>b</b>) QWR angle (<span class="html-italic">α</span>) (for circular input polarization).</p>
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<p>NOLM operation in an F8L with a loop length of 250 m. Three-dimensional surfaces for (<b>a</b>) circular input polarization with low power, (<b>c</b>) circular input polarization with high power, and (<b>e</b>) linear input polarization with high power. Five specific cases of QWR rotation (α) (A–E) over a range of <span class="html-italic">P<sub>in</sub></span> values: (<b>b</b>,<b>d</b>) 2D analysis of NOLM transmission vs. <span class="html-italic">P<sub>in</sub></span> at high and low power, respectively. (<b>f</b>) Input polarization in 2D analysis of NOLM transmission vs. <span class="html-italic">P<sub>in</sub></span> at high power.</p>
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