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Search Results (1,381)

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19 pages, 1822 KiB  
Article
Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques
by Bogdan Adrian Buhas, Lucia Ana-Maria Muntean, Guillaume Ploussard, Bogdan Ovidiu Feciche, Iulia Andras, Valentin Toma, Teodor Andrei Maghiar, Nicolae Crișan, Rareș-Ionuț Știufiuc and Constantin Mihai Lucaciu
Int. J. Mol. Sci. 2024, 25(18), 9830; https://doi.org/10.3390/ijms25189830 - 11 Sep 2024
Viewed by 365
Abstract
Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are found in urine samples from patients [...] Read more.
Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are found in urine samples from patients with RCC. In this study, we propose to investigate the use of Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR) on dried urine samples for distinguishing RCC. We analyzed dried urine samples from 49 patients with RCC, confirmed by histopathology, and 39 healthy donors using ATR-FTIR spectroscopy. The vibrational bands of the dried urine were identified by comparing them with spectra from dried artificial urine, individual urine components, and dried artificial urine spiked with urine components. Urea dominated all spectra, but smaller intensity peaks, corresponding to creatinine, phosphate, and uric acid, were also identified. Statistically significant differences between the FTIR spectra of the two groups were obtained only for creatinine, with lower intensities for RCC cases. The discrimination of RCC was performed through Principal Component Analysis combined with Linear Discriminant Analysis (PCA–LDA) and Support Vector Machine (SVM). Using PCA–LDA, we achieved a higher discrimination accuracy (82%) (using only six Principal Components to avoid overfitting), as compared to SVM (76%). Our results demonstrate the potential of urine ATR-FTIR combined with machine learning techniques for RCC discrimination. However, further studies, especially of other urological diseases, must validate this approach. Full article
(This article belongs to the Special Issue Machine Learning in Disease Diagnosis and Treatment)
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<p>ATR-FTIR spectrum of artificial urine (black) and the mean spectrum obtained from the urine of 39 control patients (red). The wavenumbers corresponding to the main peaks in the two sets of spectra are also indicated in cm<sup>−1</sup>.</p>
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<p>Comparison of the ATR-FTIR spectrum of artificial urine (black) with the spectra of the main organic urine components: urea (red), creatinine (blue), and uric acid (magenta). The vertical lines were traced to help identify the peaks of artificial urine with the peaks of the three components. The line and peak wavenumber colors indicate the compound for which we have the best match, and the black lines are traced for artificial urine peaks not matching the peaks of urea, creatinine, or uric acid.</p>
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<p>Matrix plot of the correlations between the ATR-FTIR absorption intensities measured for all the urine samples.</p>
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<p>The mean ATR-FTIR spectrum of urine from the RCC patients (red) and the healthy donors (CTRL) (blue) and the difference between the two mean spectra (black). Dashed areas represent the standard deviations. The difference spectrum was offset for better visualization.</p>
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<p>Loading plot for PC1 (black), PC2 (red), and PC4 (blue).</p>
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<p>Discrimination plot between the RCC and CTRL samples using a quadratic discrimination function and taking 15 PCs. For each sample, the software provides a score for the two groups CTRL and RCC. The sample is assigned to the group for which the score is highest. From a graphical point of view, the bi-dimensional space is split in two by the bisector of the first quadrant. The data points situated to the right from this bisector belong to the RCC group and the data points situated to the left from this bisector are assigned to the CTRL group. One can notice that three RCC cases (red circles) were assigned to the CTRL group (False Negative) and four CTRL samples (blue squares) were assigned to the RCC group (False Positive). The misassigned samples were marked with arrows. From 88 samples, 81 were assigned correctly, i.e., the accuracy was 92.05%.</p>
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<p>Accuracy of discrimination between the RCC and CTRL samples as a function of the number of PCs considered for the linear, quadratic, and Mahalanobis functions. The PCs were chosen in the order of their difference between the two groups (increasing the <span class="html-italic">p</span>, Pearson’s coefficient, from the Student’s <span class="html-italic">t</span>-Test, <a href="#ijms-25-09830-t003" class="html-table">Table 3</a>).</p>
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23 pages, 4038 KiB  
Article
Spectroscopic Relationship between XOD and TAOZHI Total Polyphenols Based on Chemometrics and Molecular Docking Techniques
by Mingyu Yang, Yitang Xu, Qihua Yu, Mengyu Li, Liyong Yang and Ye Yang
Molecules 2024, 29(18), 4288; https://doi.org/10.3390/molecules29184288 - 10 Sep 2024
Viewed by 268
Abstract
Xanthine oxidase (XOD) is a key enzyme that promotes the oxidation of xanthine/hypoxanthine to form uric acid, and the accumulation of uric acid leads to hyperuricaemia. The prevalence of gout caused by hyperuricaemia is increasing year by year. TAOZHI (TZ) can be used [...] Read more.
Xanthine oxidase (XOD) is a key enzyme that promotes the oxidation of xanthine/hypoxanthine to form uric acid, and the accumulation of uric acid leads to hyperuricaemia. The prevalence of gout caused by hyperuricaemia is increasing year by year. TAOZHI (TZ) can be used for the treatment of rheumatic arthralgia due to qi stagnation and blood stasis and contains a large number of polyphenolic components. The aim of this study was to investigate the relationship between chromatograms and XOD inhibition of 21 batches of TZ total polyphenol extract samples. Chemometric methods such as grey correlation analysis, bivariate correlation analysis, and partial least squares regression were used to identify the active ingredient groups in the total polyphenol extracts of TZ, which were validated using molecular docking techniques. The total polyphenol content contained in the 21 batches did not differ significantly, and all batches showed inhibitory effects on XOD. Spectroeffect correlation analysis showed that the inhibitory effect of TZ on XOD activity was the result of the synergistic effect of multiple components, and the active component groups screened to inhibit XOD were F2 (4-O-Caffeoylquinic acid), F4, and F10 (naringenin). The molecular docking results showed that the binding energies of all nine dockings were lower than −7.5 kcal/mol, and the binding modes included hydrogen bonding, hydrophobic forces, salt bridges, and π-staking, and the small molecules might exert their pharmacological effects by binding to XOD through the residue sites of the amino acids, such as threonine, arginine, and leucine. This study provides some theoretical basis for the development and utilisation of TZ total polyphenols. Full article
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<p>Histogram of total polyphenol yields of batches TZ–1-TZ–21 (<span class="html-italic">n</span> = 3).</p>
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<p>Screening of optimal reaction conditions for XOD (<span class="html-italic">n</span> = 3). (<b>A</b>) XOD concentration screening. (<b>B</b>) Xanthine substrate concentration screening. (<b>C</b>) Screening of PBS buffer pH. (<b>D</b>) Reaction temperature screening.</p>
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<p>IC<sub>50</sub> value of XOD activity inhibition by 21 batches with positive drug allopurinol.</p>
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<p>Fingerprint analysis of TZ batches. (<b>A</b>) Common patterns in the fingerprint profiles of 21 batches. The different colours in the figure represent the chromatograms of different batches of samples, where the red dots are the common peaks of the marker corrections. (<b>B</b>) A total of 16 common peaks were calibrated in the control spectrum obtained in the multi-point correction mode. (<b>C</b>) Fingerprint profiles of the five controls. (<b>D</b>) Fingerprint profile of the mixed control.</p>
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<p>Cluster analysis and principal component analysis of 21 batches of TZ fingerprint profiles. (<b>A</b>) Clustering heat map of 21 batches of TZ from different origins. (<b>B</b>) Plot of principal component scores for 21 TZ batches. The yellow orb in the figure indicates PCA classification I and the green orb indicates PCA classification II. (<b>C</b>) Plot of principal component scores for the 16 shared peaks in the TZ batch. (<b>D</b>) Plot of the fraction of batches and shared peaks mixed in PCA (triangles represent batches; pentagrams represent shared peaks). In the figure, S1–21 represents TZ1–21.</p>
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<p>BCA and OPLS–DA results. (<b>A</b>) Pearson correlation coefficient plot in BCA (the graph from yellow to green indicates high to low scores). (<b>B</b>) <span class="html-italic">p</span>-value plot of significance in BCA (the graph from blue to red indicates high to low scores). (<b>C</b>) The magnitude of VIP values of shared peaks in OPLS–DA. (<b>D</b>) Magnitude of standardised regression coefficients for OPLS–DA common peaks. (<b>E</b>) The S–plot in OPLS–DA indicates the degree of data discretization. (<b>F</b>) Orthogonal calibration model in OPLS–DA with the number of calibrations set to 200. * Significant at the 0.05 level (two–tailed). ** Significant correlation at the 0.01 level (two–tailed). *** Significant correlation at the 0.001 level (two–tailed).</p>
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<p>Visualisation of molecular docking results (The arrows in the figure indicate the experimental docking sequence). (<b>A</b>) Venn intersection plot for spectral effect correlation analysis. (<b>B</b>) 3D structure of two small molecules with XOD proteins. (<b>C</b>) Complex conformation of F2 with XOD protein. (<b>a</b>) is the overall composite view of F2 binding to the protein, (<b>b</b>) is the 3D site plan of F2 binding to amino acid residues of the protein (where the dark blue stick structures are amino acid residues), and (<b>c</b>) is the 2D plan view of F2 binding to amino acid residues in the conformation. (<b>D</b>) Complex conformation of F10 with XOD protein. (<b>a</b>) is the overall composite view of F10 binding to the protein, (<b>b</b>) is the 3D site plan of F10 binding to amino acid residues of the protein, and (<b>c</b>) is the 2D plan view of F2 binding to amino acid residues in the conformation.</p>
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18 pages, 5507 KiB  
Article
Microfibrous Carbon Paper Decorated with High-Density Manganese Dioxide Nanorods: An Electrochemical Nonenzymatic Platform of Glucose Sensing
by Khawtar Hasan Ahmed and Mohamed Mohamedi
Sensors 2024, 24(18), 5864; https://doi.org/10.3390/s24185864 - 10 Sep 2024
Viewed by 268
Abstract
Nanorod structures exhibit a high surface-to-volume ratio, enhancing the accessibility of electrolyte ions to the electrode surface and providing an abundance of active sites for improved electrochemical sensing performance. In this study, tetragonal α-MnO2 with a large K+-embedded tunnel structure, [...] Read more.
Nanorod structures exhibit a high surface-to-volume ratio, enhancing the accessibility of electrolyte ions to the electrode surface and providing an abundance of active sites for improved electrochemical sensing performance. In this study, tetragonal α-MnO2 with a large K+-embedded tunnel structure, directly grown on microfibrous carbon paper to form densely packed nanorod arrays, is investigated as an electrocatalytic material for non-enzymatic glucose sensing. The MnO2 nanorods electrode demonstrates outstanding catalytic activity for glucose oxidation, showcasing a high sensitivity of 143.82 µA cm−2 mM−1 within the linear range from 0.01 to 15 mM, with a limit of detection (LOD) of 0.282 mM specifically for glucose molecules. Importantly, the MnO2 nanorods electrode exhibits excellent selectivity towards glucose over ascorbic acid and uric acid, which is crucial for accurate glucose detection in complex samples. For comparison, a gold electrode shows a lower sensitivity of 52.48 µA cm−2 mM−1 within a linear range from 1 to 10 mM. These findings underscore the superior performance of the MnO2 nanorods electrode in both sensitivity and selectivity, offering significant potential for advancing electrochemical sensors and bioanalytical techniques for glucose monitoring in physiological and clinical settings. Full article
(This article belongs to the Special Issue Recent Innovations in Electrochemical Biosensors)
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<p>(<b>Panel A</b>) SEM images of (<b>a</b>) bare CP substrate, (<b>b</b>–<b>d</b>) of CP/MnO<sub>x</sub> at increasing magnifications. (<b>Panel B</b>) Element mapping and EDS spectrum.</p>
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<p>XRD patterns of (<b>a</b>) CP substrate and (<b>b</b>) CP/MnO<sub>x</sub>. Raman spectra of (<b>c</b>) CP substrate and (<b>d</b>) CP/MnO<sub>x</sub>.</p>
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<p>(<b>a</b>) Electrochemical windows of bare CP and CP/MnO<sub>2</sub> in 0.1 M NaOH solution. (<b>b</b>) and (<b>c</b>) capacitive behavior of CP and CP/MnO<sub>2</sub>, respectively. Numbers indicate the scan rate in mV/s. (<b>d</b>) Specific capacitance. (<b>e</b>) Anodic currents extracted from (<b>b</b>,<b>c</b>) vs. scan rate. (<b>f</b>) <span class="html-italic">ECSA</span> and <span class="html-italic">RF</span> parameters.</p>
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<p>An electrochemical window of an Au-wire electrode in 0.1 M NaOH solution recorded with a scan rate of 2 mV/s.</p>
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<p>Electrochemical oxidation of Glu (<b>a</b>,<b>b</b>), AA (<b>c</b>,<b>d</b>), and UA (<b>e</b>,<b>f</b>) on Au-wire electrode in 0.1 M NaOH solution recorded with a scan rate of 2 mV/s.</p>
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<p>Comparison of current peak densities with respect to the concentration of Glu, AA, and, UA. Overview of the potential ranges for the oxidation of Glu, AA, and UA <a href="#sensors-24-05864-f006" class="html-fig">Figure 6</a> (bottom right). Concentrations used: [Glu] = 7 mM, [AA] = 0.06 mM, [UA] = 0.2 mM. Scale: peak current density is normalized, with Glu as the reference (×1), and AA and UA are scaled by a factor of 80.</p>
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<p>Electrochemical oxidation of Glu (<b>a</b>–<b>c</b>) on CP electrode, and (<b>d</b>–<b>f</b>) CP/MnO<sub>2</sub> nanorods electrode in 0.1 M NaOH solution recorded with a scan rate of 2 mV s<sup>−1</sup>.</p>
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<p>(<b>a</b>) Peak potentials: P1 and P2 and Δ(P2 − P1) separation. (<b>b</b>) Current density of peak P1 and sensitivity. [Glu] = 6 mM.</p>
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<p>Electrochemical oxidation of (<b>a</b>) AA; (<b>b</b>) UA; (<b>c</b>,<b>d</b>) AA + UA; (<b>e</b>) Glu + AA and (<b>f</b>) Glu + UA on CP/MnO<sub>2</sub> nanorods electrode in 0.1 M NaOH solution recorded with a scan rate of 2 mV s<sup>−1</sup>.</p>
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<p>(<b>a</b>) Individual electrochemical oxidation of Glu, AA, and UA on CP/MnO<sub>2</sub> nanorods electrode, (<b>b</b>) Electrochemical oxidation of ternary Glu + AA + UA on CP/MnO<sub>2</sub> nanorods electrode in 0.1 M NaOH solution recorded with a scan rate of 2 mV/s.</p>
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15 pages, 6483 KiB  
Article
Lactiplantibacillus plantarum 06CC2 Enhanced the Expression of Intestinal Uric Acid Excretion Transporter in Mice
by Shunsuke Nei, Tatsuya Matsusaki, Hibiki Kawakubo, Kenjirou Ogawa, Kazuo Nishiyama, Chuluunbat Tsend-Ayush, Tomoki Nakano, Masahiko Takeshita, Takuo Shinyama and Masao Yamasaki
Nutrients 2024, 16(17), 3042; https://doi.org/10.3390/nu16173042 - 9 Sep 2024
Viewed by 547
Abstract
ATP-binding cassette transporter subfamily G member 2 (ABCG2) is responsible for the excretion of foreign substances, such as uric acid (UA) and indoxyl sulfate (IS), from the body. Given the importance of increased ABCG2 expression in UA excretion, we investigated the enhancement of [...] Read more.
ATP-binding cassette transporter subfamily G member 2 (ABCG2) is responsible for the excretion of foreign substances, such as uric acid (UA) and indoxyl sulfate (IS), from the body. Given the importance of increased ABCG2 expression in UA excretion, we investigated the enhancement of intestinal ABCG2 expression using Lactiplantibacillus plantarum 06CC2 (LP06CC2). Mice were reared on a potassium oxonate-induced high-purine model at doses of 0.02% or 0.1% LP06CC2 for three weeks. Results showed that LP06CC2 feeding resulted in increased ABCG2 expression in the small intestine. The expression level of large intestinal ABCG2 also showed a tendency to increase, suggesting upregulation of the intestinal excretion transporter ABCG2 by LP06CC2. Overall, LP06CC2 treatment increased fecal UA excretion and showed a trend towards increased fecal excretion of IS, suggesting that LP06CC2 treatment enhanced the expression of intestinal ABCG2, thereby promoting the excretion of UA and other substances from the intestinal tract. Full article
(This article belongs to the Special Issue Nutritional Management in Kidney Disease)
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<p>The effects of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on plasma (<b>a</b>), urine (<b>b</b>), and feces (<b>c</b>) uric acid levels Data are the means ± SE, n = 8, Significant difference * <span class="html-italic">p</span> &lt; 0.05 vs. Control for Tukey–Kramer. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Liver XOD activity. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on xanthine oxidase activity in the liver Data are the means ± SE, n = 8, Significant difference * <span class="html-italic">p</span> &lt; 0.05 vs. Control for Tukey–Kramer. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Intestinal uric acid excretion transporter expression level. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on uric acid excretion transporter expression levels in the intestine ABCG2 and PDZK1 transporter expression in the small intestine (<b>A</b>). ABCG2 and PDZK1 transporter expression in the large intestine (<b>B</b>). Data are the means ± SE, n = 8, * <span class="html-italic">p</span> &lt; 0.05 vs. PO for the Tukey–Kramer test. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Uric acid excretion transporter expression level in kidney. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on uric acid excretion transporter expression levels in the kidney Expression levels of ABCG2, URAT1 and OAT1 transporters in kidneys. Data are the means ± SE, n = 8. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Fecal excretion of protein-derived gut microbiota metabolites. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on the fecal excretion of protein-derived gut microbiota metabolites. Data are the means ± SE, n = 8, * <span class="html-italic">p</span> &lt; 0.05 vs. PO for the Tukey–Kramer test. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Short-chain fatty acids. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on short-chain fatty acids (SCFAs) in fecal excretion (<b>A</b>) and cecal content (<b>B</b>). Data are the means ± SE, n = 8, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05 vs. PO for the Tukey–Kramer test. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Short-chain fatty acids. Effect of <span class="html-italic">Lactiplantibacillus plantarum</span> 06CC2 on short-chain fatty acids (SCFAs) in fecal excretion (<b>A</b>) and cecal content (<b>B</b>). Data are the means ± SE, n = 8, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05 vs. PO for the Tukey–Kramer test. Con: control diet, PO: potassium oxonate diet, PO + LP: potassium oxonate, 0.1% LP06CC2 diet, PO + L-LP: potassium oxonate, and 0.02% (low) LP06CC2 diet, SE: standard error.</p>
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<p>Correlation between fecal uric acid levels and fecal indoxyl sulphate. Graph of the correlation coefficients between fecal uric acid and fecal indoxyl sulfate levels using Statcel 4. R<sup>2</sup>: coefficient of determination; R*<sup>2</sup>: degrees of freedom adjusted coefficient of determination; <span class="html-italic">p</span>: <span class="html-italic">p</span>-value, UA: uric acid, IS: indoxyl sulfate.</p>
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10 pages, 427 KiB  
Article
Effects of Different Photoperiods during Incubation on Post-Hatch Broiler Performance and Stress Response
by Yasir Arslan Noor, Muhammad Usman, Usman Elahi, Shahid Mehmood, Muhammad Faisal Riaz, Ehsaan Ullah Khan, Kinza Saleem and Sohail Ahmad
Vet. Sci. 2024, 11(9), 418; https://doi.org/10.3390/vetsci11090418 - 9 Sep 2024
Viewed by 397
Abstract
This study evaluated the subsequent effect of photoperiods during incubation on post-hatch growth and stress response of commercial broiler chickens. A total of 875 Ross 308 broiler breeder (48 weeks of age) eggs were hatched using different durations (0, 4, 8, 12, 16, [...] Read more.
This study evaluated the subsequent effect of photoperiods during incubation on post-hatch growth and stress response of commercial broiler chickens. A total of 875 Ross 308 broiler breeder (48 weeks of age) eggs were hatched using different durations (0, 4, 8, 12, 16, 20, and 24 h a day) of dichromatic light [green and red (495 to 750 nm); 2700 K; 250 lux; SUNJIE; China] throughout the whole period of incubation. A total of 50 0-day-old hatched straight run broiler chicks from each photoperiod during incubation were used to evaluate subsequent growth performance (feed intake, body weight, and feed conversion ratio); stress parameters (physical asymmetry, tonic immobility, and vocalization,); welfare traits (feather score and gait score); carcass traits (live weight, dressed weight, carcass yield, liver weight, gizzard weight, heart weight, abdominal fat weight, breast weight, and leg weight); and serum chemistry (globulin, total protein, cholesterol, glucose, and uric acid). There were no influences of photoperiod during incubation on post-hatch growth, stress parameters, welfare, and carcass traits. Heart yield was higher in birds incubated under 20 h light than in those from the 16 h light group. Incubation under different lighting durations also altered blood biochemical profile but did not influence serum globulin and cholesterol levels. It was concluded that under experimental conditions, incubation of broiler eggs under different lighting durations did not impact subsequent post-hatch performance (21–35 d). Full article
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<p>Physical asymmetry of commercial broiler among different treatment groups.</p>
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14 pages, 5675 KiB  
Article
A Novel Non-Enzymatic Efficient H2O2 Sensor Utilizing δ-FeOOH and Prussian Blue Anchoring on Carbon Felt Electrode
by Karoline S. Nantes, Ana L. H. K. Ferreira, Marcio C. Pereira, Francisco G. E. Nogueira and André S. Afonso
C 2024, 10(3), 82; https://doi.org/10.3390/c10030082 - 9 Sep 2024
Viewed by 332
Abstract
In this study, an efficient H2O2 sensor was developed based on electrochemical Prussian blue (PB) synthesized from the acid suspension of δ-FeOOH and K3[Fe(CN)6] using cyclic voltammetry (CV) and anchored on carbon felt (CF), yielding an [...] Read more.
In this study, an efficient H2O2 sensor was developed based on electrochemical Prussian blue (PB) synthesized from the acid suspension of δ-FeOOH and K3[Fe(CN)6] using cyclic voltammetry (CV) and anchored on carbon felt (CF), yielding an enhanced CF/PB-FeOOH electrode for sensing of H2O2 in pH-neutral solution. CF/PB-FeOOH electrode construction was proved by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD), and electrochemical properties were verified by impedance electrochemical and CV. The synergy of δ-FeOOH and PB coupled to CF increases electrocatalytic activity toward H2O2, with the sensor showing a linear range of 1.2 to 300 μM and a limit of detection of 0.36 μM. Notably, the CF/PB-FeOOH electrode exhibited excellent selectivity for H2O2 detection in the presence of dopamine (DA), uric acid (UA), and ascorbic acid (AA). The calculated H2O2 recovery rates varied between 93% and 101% in fetal bovine serum diluted in PBS. This work underscores the potential of CF/PB-FeOOH electrodes in progressing electrochemical sensing technologies for various biological and environmental applications. Full article
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<p>(<b>A</b>) Potentiodynamic growth of PB nanoparticles on CF electrode in N<sub>2</sub>-saturated 0.1 M KCl solution at pH 2.0 with 5 mM K<sub>3</sub>Fe(CN)<sub>6</sub> and 22 mg of δ-FeOOH. The potential window was set from −0.2 V to 0.7 V at a scan rate of 50 mV s<sup>−1</sup>, applying 30 scans. The arrows indicate scans increase. (<b>B</b>) CV of FC/PB-FeOOH electrode in N<sub>2</sub>-saturated 0.1 M KCl at pH 2.0 at a scan rate of 50 mV s<sup>−1</sup>. The CF was subjected to the following treatments: (a) i, (b) ii, and (c) iii.</p>
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<p>(<b>A</b>) Evaluation by the CV of PB synthesized in different pH levels of the precursor solution. (<b>B</b>) PB synthesized with (a) 44 mg, (b) 22 mg, or (c) 11 mg of δ-FeOOH. (<b>C</b>) Effect of the number of scans on the synthesis of PB: (a) background, (b) 15 scans, (c) 30 scans, (d) 50 scans, (e) 100 scans, and (f) 150 scans. N<sub>2</sub>-saturated 0.1 M KCl solution at pH 2.0 was the medium in which CVs were performed. The potential range was from −0.2 V to 0.7 V, and the scan rate was 50 mV s<sup>−1</sup>.</p>
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<p>The XRD pattern for the PB-FeOOH film was deposited on FTO.</p>
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<p>SEM micrographs of (<b>A</b>,<b>B</b>) CF electrode and (<b>C</b>,<b>D</b>) CF/PB-FeOOH electrode. (<b>E</b>) EDS spectrum of CF/PB-FeOOH electrode and (<b>F</b>) the weight % of EDS analysis.</p>
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<p>(<b>A</b>) CV curves at 100 mV·s<sup>−1</sup> and (<b>B</b>) EIS plots at open-circuit potential using N<sub>2</sub>-saturated 0.1 M KCl solution at pH 2.0 containing 1 mM K<sub>3</sub>Fe(CN)<sub>6</sub> and 1 mM K<sub>4</sub>Fe(CN)<sub>6</sub>, (a) CF, and (b) CF/PB-FeOOH.</p>
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<p>CV curves at a potential range from −0.2 V to 0.7 V at a scan rate of 100 mV·s<sup>−1</sup> in 0.1 M of PBS without or with 1.0 mM of H<sub>2</sub>O<sub>2</sub>. (<b>A</b>) CF/PB-FeOOH electrode and (<b>B</b>) CF/PB electrode.</p>
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<p>(<b>A</b>) Amperometric response of the CF/PB–δ-FeOOH electrode in 0.1 M PBS at −0.2 V versus Ag|AgCl with successive additions of H<sub>2</sub>O<sub>2</sub> under stirring. (<b>B</b>) Corresponding calibration curve. The error bars show the standard deviation for <span class="html-italic">n</span> = 3. The arrow indicates the increase in concentration of H<sub>2</sub>O<sub>2</sub>.</p>
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<p>Amperometric response of CF/PB-FeOOH electrode in 0.1 M PBS at −0.2 V using 80 μM of H<sub>2</sub>O<sub>2</sub> (initial and final additions), 400 µM of uric acid, 100 µM of ascorbic acid, and 40 µM of dopamine.</p>
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18 pages, 8379 KiB  
Article
Revealing Interactions of Gut Microbiota and Metabolite in Confined Environments Using High-Throughput Sequencing and Metabolomic Analysis
by Ziying Wang, Haodan Xu, Xin Song, Zheng Chen, Guangqiang Wang, Yijin Yang, Beiwei Zhu, Lianzhong Ai, Chenxi Liu, Yaxuan Zhang, Yong Yang, Chuan Wang and Yongjun Xia
Nutrients 2024, 16(17), 2998; https://doi.org/10.3390/nu16172998 - 5 Sep 2024
Viewed by 528
Abstract
A confined environment is a special kind of extreme working environment, and prolonged exposure to it tends to increase psychological stress and trigger rhythmic disorders, emotional abnormalities and other phenomena, thus seriously affecting work efficiency. However, the mechanisms through which confined environments affect [...] Read more.
A confined environment is a special kind of extreme working environment, and prolonged exposure to it tends to increase psychological stress and trigger rhythmic disorders, emotional abnormalities and other phenomena, thus seriously affecting work efficiency. However, the mechanisms through which confined environments affect human health remain unclear. Therefore, this study simulates a strictly controlled confined environment and employs integrative multi-omics techniques to analyze the alterations in gut microbiota and metabolites of workers under such conditions. The aim is to identify metabolic biomarkers and elucidate the relationship between gut microbiota and metabolites. High-throughput sequencing results showed that a confined environment significantly affects gut microbial composition and clusters subjects’ gut microbiota into two enterotypes (Bla and Bi). Differences in abundance of genera Bifidobacterium, Collinsella, Ruminococcus_gnavus_group, Faecalibacterium, Bacteroides, Prevotella and Succinivibronaceae UCG-002 were significant. Untarget metabolomics analyses showed that the confined environment resulted in significant alterations in intestinal metabolites and increased the activity of the body’s amino acid metabolism and bile acid metabolism pathways. Among the metabolites that differed after confined environment living, four metabolites such as uric acid and beta-PHENYL-gamma-aminobutyric acid may be potential biomarkers. Further correlation analysis demonstrated a strong association between the composition of the subjects’ gut microbiota and these four biomarkers. This study provides valuable reference data for improving the health status of workers in confined environments and facilitates the subsequent proposal of targeted prevention and treatment strategies. Full article
(This article belongs to the Section Prebiotics and Probiotics)
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<p>Analysis of enterotype clustering and α-diversity changes in closed environment. (<b>A</b>) Enterotype analysis of gut microbiota (A: before entering the cabin; D: in the cabin; E: out of the cabin). (<b>B</b>–<b>E</b>) Box plots plotted with the ACE, Shannon, Simpson and Chao indices, respectively. Kruskal-Wallis rank sum test was used to compare the group differences, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Alterations in intestinal microbial composition in closed environments. (<b>A</b>,<b>B</b>) Relative abundance barplot of intestinal microbiota based on phylum and genus levels; (<b>C</b>) bubble plot analysis of intestinal microbiota in different enterotype groups; (<b>D</b>) upset plots analysis of intestinal microbiota in different enterotype groups; (<b>E</b>) source tracker pieplot of intestinal microbiota in different enterotype groups.</p>
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<p>Significant differences analysis of intestinal microbiota in closed environments. (<b>A</b>,<b>B</b>) Analysis of interspecific difference analysis based on phylum (<b>A</b>) and genus (<b>B</b>) level; (<b>C</b>) NMDS analysis of gut microbiota; (<b>D</b>) significantly different species LDA score results (threshold value 2.5). Wilcoxon rank sum test was used to compare the group differences, * <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.</p>
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<p>Annotations on metabolites in confined environment. (<b>A</b>) Comparative analysis of subjects’ samples; (<b>B</b>) metabolite annotation pathway statistics; (<b>C</b>) statistics of important pathways and metabolites in the top 20; (<b>D</b>) annotations on metabolites in HWDB database.</p>
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<p>Analysis of significant difference of metabolites based on enterotypes. (<b>A</b>) Annotations on differential metabolites in HWDB database; (<b>B</b>) comparative analysis of different enterotype samples; (<b>C</b>) volcano map of different metabolites in two enterotype samples; (<b>D</b>) KEGG annotation analysis of differential metabolites; (<b>E</b>) KEGG enrichment analysis of differential metabolites; (<b>F</b>) analysis of VIP value of differential metabolites. * <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.</p>
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<p>Changes in relative abundance of uric acid in confined environment. (<b>A</b>) changes in relative abundance of uric acid in different enterotypes; (<b>B</b>,<b>C</b>) changes in relative abundance of uric acid in Bla and Bi enterotype at different stages, respectively. LSD multiple test was used to compare the group differences, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, ns represents no significance.</p>
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<p>Screening of potential biomarkers. (<b>A</b>) HWDB annotations on five metabolites; (<b>B</b>) the difference of relative abundance of five metabolites between two enterotypes; (<b>C</b>) ROC analysis. Unpaired student’s t-test was used to compare the group differences, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Linear regression analysis of four different biomarkers and gut microbiota characteristics. (<b>A</b>) Linear regression of gut microbiota with uric acid. (<b>B</b>) Linear regression of gut microbiota with (3S,5R,6R,6′S)-6,7-didehydro-5,6-dihydro-3,5,6′-trihydroxy-13,14,20-trinor-3′-oxo-beta, epsilon-caroten-19′,11′-olide 3-acetate. (<b>C</b>) Linear regression of gut microbiota with beta-PHENYL-gamma-aminobutyric acid. (<b>D</b>) Linear regression of gut microbiota with lyciumoside VIII.</p>
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<p>Correlation analysis between four different biomarkers and the composition of intestinal microbiota. (<b>A</b>) Correlation analysis between intestinal microbiota and biomarkers; (<b>B</b>–<b>E</b>) MaAslin analysis between intestinal microbiota and biomarkers. The asterisk in the heat map represents the significant <span class="html-italic">p</span> value, * <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.</p>
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14 pages, 1359 KiB  
Article
Effect of Moringa oleifera Leaf Powder Supplementation on Growth Performance, Digestive Enzyme Activity, Meat Quality, and Cecum Microbiota of Ningdu Yellow Chickens
by Qiongli Song, Zhiheng Zou, Xiaolian Chen, Gaoxiang Ai, Pingwen Xiong, Wenjing Song, Guohua Liu, Aijuan Zheng and Jiang Chen
Agriculture 2024, 14(9), 1523; https://doi.org/10.3390/agriculture14091523 - 4 Sep 2024
Viewed by 368
Abstract
This study aimed to investigate the impact of dietary supplementation with Moringa oleifera leaf powder (MOLP) on the growth performance, digestive enzyme activity, meat quality, and cecum microbiota of Ningdu yellow chickens. A total of 300 78-day-old Ningdu yellow chickens with similar initial [...] Read more.
This study aimed to investigate the impact of dietary supplementation with Moringa oleifera leaf powder (MOLP) on the growth performance, digestive enzyme activity, meat quality, and cecum microbiota of Ningdu yellow chickens. A total of 300 78-day-old Ningdu yellow chickens with similar initial body weights were randomly distributed into five treatments consisting of six replicates of 10 birds. The control group (M0) was fed a basal diet, and the experimental groups were fed diets supplemented with 0.5% (M0.5), 1% (M1), 2% (M2), and 4% (M4) of MOLP, respectively. Our results showed that dietary supplementation with 2% MOLP significantly (p < 0.05) decreased the feed to gain (F/G) and showed a quadratic (p < 0.05) decrease with the level of MOLP. Dietary supplementation with 1~4% MOLP resulted in a significant increase (p < 0.05) in serum total superoxide dismutase (T-SOD) activity and total antioxidant capacity (T-AOC). Furthermore, both serum T-SOD and T-AOC exhibited linear and quadratic increases (p < 0.01) in response to the supplementation with MOLP in the diets. Dietary supplementation with 1~4% MOLP significantly (p < 0.05) decreased serum uric acid (UA) level. Additionally, 4% MOLP significantly (p < 0.05) decreased triglycerides (TG), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels, and showed linear and quadratic effects. The activity of lipase in the duodenum showed a linear decreasing trend (p < 0.05) with the level of MOLP, while the activities of α-amylase (both in duodenum and jejunum) showed a linear and quadratic increasing trend (p < 0.05). In addition, there was a linear decrease response in abdominal fat (p < 0.05) to MOLP supplementation levels in the diets. In terms of meat quality, dietary supplementation with 4% MOLP significantly reduced (p < 0.05) the L*45 min and L*24 h values of the breast muscle, and drip loss had a linear decreasing trend (p < 0.05). In terms of cecum microbiota, dietary supplementation with 1~4% MOLP significantly increased the Bacteroidota abundance but decreased the Firmicutes abundance (p < 0.05). Overall, dietary supplementation with MOLP improved the growth performance and meat quality of Ningdu yellow chickens through improving the antioxidant function, intestinal digestive enzyme activity, and the cecal microbial structure. The optimum level of MOLP in the diet of Nindu yellow chicken is recommended to be 2.59%. Full article
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<p>Effects of <span class="html-italic">Moringa oleifera</span> leaf powder on cecal microbial alpha diversity of Ningdu yellow chickens. (<b>A</b>) Chao1 index; (<b>B</b>) Shannon index; (<b>C</b>) Simpson index; (<b>D</b>) Dominance index. Lowercase letters in the bar graphs indicate significant differences (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Phylum-level relative abundance of microbiota from the cecal digesta of Ningdu yellow chickens fed different diets. Lowercase letters in the bar graphs indicate significant differences (<span class="html-italic">p</span> ≤ 0.05). (<b>A</b>) Classification of cecum flora compositions with phylum level; (<b>B</b>) Comparison of Bacteroidota abundance among groups. (<b>C</b>) Comparison of Firmicutes abundance among groups.</p>
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<p>Genus-level relative abundance of microbiota from the cecal digesta of broilers fed different diets. Lowercase letters in the bar graphs indicate significant differences (<span class="html-italic">p</span> ≤ 0.05). (<b>A</b>) Classification of cecum flora compositions with genus level; (<b>B</b>) Comparison of Rikenellaceae_RC9 abundance among groups. (<b>C</b>) Comparison of CHKCI001 abundance among groups.</p>
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16 pages, 550 KiB  
Article
Influence of Dietary Heritage in a Restricted Geographic Area and Role of Food Additives on Risk of Recurrent Kidney Stone
by Piergiorgio Bolasco and Giorgio Reggiardo
Nutrients 2024, 16(17), 2984; https://doi.org/10.3390/nu16172984 - 4 Sep 2024
Viewed by 664
Abstract
Dietary factors may be implicated in the formation of kidney stones and should be closely monitored. To achieve this aim, patients are routinely assessed by means of generic dietary recall, a tool widely used by authors in a range of extensive patient populations [...] Read more.
Dietary factors may be implicated in the formation of kidney stones and should be closely monitored. To achieve this aim, patients are routinely assessed by means of generic dietary recall, a tool widely used by authors in a range of extensive patient populations to record food intake; the findings obtained, however, may be skewed due to dietary variations and underestimation of the effect of food additives. Fifty Frequent Kidney Stone Formers (FKSFs, mean age: 54.3 ± 13.9 years) with normal kidney function, absence of comorbidities, and reliable compliance were selected from a total of 68 patients’ resident in Sardinia, an Italian island where genetic admixtures have been relatively rare for generations. The study, conducted from 1 January 2020 to 31 December 2023, was aimed at assessing nutritional values based on the meticulous recording of food quantities, quality, and potential modifications related to food preparation. Patients were selected during an initial clinical check-up and all efforts made to ensure they were capable of reliably recording all food and drinks consumed. A seven-day food diary was provided in which food and drink intake and their impact on 24 h urine output was recorded. The following parameters were measured in both foods and urine output: citrates, oxalates, calcium, phosphorous, uric acid, proteins and nitrogen compounds, magnesium, sulfates, potassium, carbohydrates, free fatty acids. Study outcomes established the presence of hypocitraturia, hyperoxaluria, hypercalciuria, and moderately high levels of nitrogen compounds. Univariate analysis followed by multivariate analysis for further confirmation were performed and the following observations made. Citrate intake correlated with citraturia but did not promote oxaluria; calcium intake promoted onset of sulfaturia, azoturia, and ammoniuria, whilst magnesium correlated with magnesiuria but not with oxaluria, calciuria, phosphaturia, and azoturia; sulfate intake elicited onset of azoturia but not kaliuresis; potassium intake promoted oxaluria and protein intake resulted in onset of ammoniuria and azoturia. (A) The chemical composition of urine based on dietary intake is hard to predict without taking into account the presence of dietary and urinary interferents; (B) the geographic isolation of patients studied underlines the importance of epigenetics in maintaining a traditional dietary heritage. (C) Moreover, the widespread use of food additives should consistently be taken into account to ensure a correct diagnosis of FKSF and set up a valid treatment plan. Full article
(This article belongs to the Special Issue Nutrition Approach in Kidney Stone Diseases)
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<p>Correlation between protein intake from recall food records and calculated from urinary and non-urinary nitrogen compounds [<a href="#B27-nutrients-16-02984" class="html-bibr">27</a>].</p>
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16 pages, 9001 KiB  
Article
Consumption of Sylimarin, Pyrroloquinoline Quinone Sodium Salt and Myricetin: Effects on Alcohol Levels and Markers of Oxidative Stress—A Pilot Study
by Gerardo Bosco, Alessandra Vezzoli, Andrea Brizzolari, Matteo Paganini, Tommaso Antonio Giacon, Fabio Savini, Maristella Gussoni, Michela Montorsi, Cinzia Dellanoce and Simona Mrakic-Sposta
Nutrients 2024, 16(17), 2965; https://doi.org/10.3390/nu16172965 - 3 Sep 2024
Viewed by 905
Abstract
Background: Alcohol abuse is one of the most common causes of mortality worldwide. This study aimed to investigate the efficacy of a treatment in reducing circulating ethanol and oxidative stress biomarkers. Methods: Twenty wine-drinking subjects were investigated in a randomized controlled, single-blind trial [...] Read more.
Background: Alcohol abuse is one of the most common causes of mortality worldwide. This study aimed to investigate the efficacy of a treatment in reducing circulating ethanol and oxidative stress biomarkers. Methods: Twenty wine-drinking subjects were investigated in a randomized controlled, single-blind trial (ClinicalTrials.gov. Identifier: NCT06548503; Ethical Committee of the University of Padova (HEC-DSB/12-2023) to evaluate the effect of the intake of a product containing silymarin, pyrroloquinoline quinone sodium salt, and myricetin (referred to as Si.Pi.Mi. for this project) on blood alcohol, ethyl glucuronide (EtG: marker for alcohol consumption) and markers of oxidative stress levels (Reactive Oxygen Species—ROS, Total Antioxidant Capacity—TAC, CoQ10, thiols redox status, 8-isoprostane, NO metabolites, neopterin, and uric acid). The effects of the treatment versus placebo were evaluated acutely and after 1 week of supplementation in blood and/or saliva and urine samples. Results: Si.Pi.Mi intake reduced circulating ethanol after 120 min (−33%). Changes in oxidative stress biomarkers, particularly a TAC (range +9–12%) increase and an 8-isoprostane (marker of lipidic peroxidation) decrease (range −22–27%), were observed too. Conclusion: After the administration of Si.Pi.Mi, the data seemed to suggest a better alcohol metabolism and oxidative balance in response to wine intake. Further verification is requested. Full article
(This article belongs to the Special Issue Alcohol Consumption and Human Health)
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<p>Experiment design and timeline. BIA: Bioelectrical impedance analysis.</p>
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<p>(<b>A</b>) Alcohol level at 120 min after treatment (Si.Pi.Mi. in red) with respect to placebo intake (T1<sub>3</sub>; 1st day; in yellow); (<b>B</b>) ETG level 120 min after treatment or placebo intake (T1<sub>3</sub>; 1st day). Statistically significant differences are displayed as ****, <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>(<b>A</b>–<b>C</b>) ROS production, (<b>D</b>) TAC concentration assessed in plasma and (<b>E</b>) 8-iso-PGF2α biomarker of lipid peroxidation. Levels detected in urine, after treatment (in red) or placebo (in yellow) intake on the 1st and 7th day. Statistically significant intra (treaded: black lines; placebo: yellow line) and inter-group (purple lines) differences are displayed as follows: * <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.</p>
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<p>Time course (mean ± SD) of (<b>A</b>,<b>B</b>) Reactive Oxygen Species (ROS) production and (<b>C</b>,<b>D</b>) Total Antioxidant Capacity (TAC) detected on saliva in ten subjects (five treated-red/white + five placebo-yellow/white). Significant intra-group differences: * <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.</p>
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<p>Co Q10 plasma value after treatment (Si.Pi.Mi. in red) or placebo (yellow) intake on the 1st and 7th day.</p>
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<p>Total and reduced GSH (<b>A</b>,<b>B</b>) and cysteine (<b>C</b>,<b>D</b>) values after treatment (Si.Pi.Mi. in red) or placebo (yellow) intake on the 1st and 7th day. Statistically significant intra (treated: black line) and inter-group (purple lines) differences are displayed 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>(<b>A</b>) Neopterin and (<b>B</b>) uric acid levels after treatment (Si.Pi.Mi. in red) intake vs. placebo (yellow). Statistically significant intra differences (treated: black line; placebo: yellow lines) are displayed as * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Plots of the TAC concentration (mM) measured in plasma (in grey) versus ETG (ng·mL<sup>−1</sup>) measured in urine (in red). The linear regression fit (solid line) shows the correlation coefficient (r). A significant linear relationship (* &lt; 0.05) was estimated.</p>
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17 pages, 302 KiB  
Article
Sex and Age Differences in the Effects of Food Frequency on Metabolic Parameters in Japanese Adults
by Katsumi Iizuka, Kotone Yanagi, Kanako Deguchi, Chihiro Ushiroda, Risako Yamamoto-Wada, Kazuko Kobae, Yoshiko Yamada and Hiroyuki Naruse
Nutrients 2024, 16(17), 2931; https://doi.org/10.3390/nu16172931 - 2 Sep 2024
Viewed by 757
Abstract
Owing to differences in dietary preferences between men and women, the associations between dietary intake frequency and metabolic parameters may differ between the sexes. A retrospective observational study of the checkup findings of 3147 Japanese individuals (968 men, 2179 women) aged 20–59 years [...] Read more.
Owing to differences in dietary preferences between men and women, the associations between dietary intake frequency and metabolic parameters may differ between the sexes. A retrospective observational study of the checkup findings of 3147 Japanese individuals (968 men, 2179 women) aged 20–59 years was conducted to examine differences in dietary habits and associations between food frequency and blood parameters (eGFR, HbA1c, uric acid, and lipids) by sex and age. Males were more likely to consume meat, fish, soft drinks, and alcohol, whereas women were more likely to consume soybeans, dairy products, vegetables, fruits, and snacks. Multivariate linear regression models adjusted for age and BMI revealed that meat intake frequency was positively associated with HbA1c (β = 0.007, p = 0.03) and negatively associated with eGFR (β = −0.3, p = 0.01) only in males, whereas fish intake frequency was positively associated with eGFR (β = 0.4, p = 0.005) only in females. Egg and soy intake frequencies were positively and negatively associated with non-HDL-C (egg: β = 0.6, p = 0.02; soy: β = −0.3, p = 0.03) only in females. Alcohol consumption frequency was associated with uric acid (M: β = 0.06, p < 0.001; F: β = 0.06, p < 0.001) and HDL-C (M: β = 1.0, p < 0.001; F: β = 1.3, p < 0.001) in both sexes. Future research is needed to determine whether varying the emphasis of dietary guidance by sex and age group is effective, since the effects of dietary preferences on metabolic parameters vary by age and sex. Full article
(This article belongs to the Special Issue Dietary Habits and Metabolic Health)
18 pages, 3597 KiB  
Article
Adsorption Study of Uremic Toxins (Urea, Creatinine, and Uric Acid) Using Modified Clinoptilolite
by Shirley Carro, Christian J. Cabello-Alvarado, Marlene Andrade-Guel, Juan Carlos Aguilar-Márquez, Pedro R. García-Morán, Carlos A. Avila-Orta and Zoe V. Quiñones-Jurado
Coatings 2024, 14(9), 1099; https://doi.org/10.3390/coatings14091099 - 1 Sep 2024
Viewed by 442
Abstract
The development of materials for uremic toxin removal is under continuous research. In this work, a natural zeolite (clinoptilolite) was modified using tartaric acid through two different methods: conventional reflux heating and ultrasound energy. The resulting materials were used as an adsorbent material [...] Read more.
The development of materials for uremic toxin removal is under continuous research. In this work, a natural zeolite (clinoptilolite) was modified using tartaric acid through two different methods: conventional reflux heating and ultrasound energy. The resulting materials were used as an adsorbent material for the removal of uremic toxins such as urea, creatinine, and uric acid. In the uremic toxin removal study, it was observed that the material modified using ultrasound for 100 min had the highest removal values (74.49%, 40.31%, and 51.50% for urea, creatinine, and uric acid, respectively), while unmodified zeolite removed 30.57%, 18.07%, and 22.84% of the same toxins. The best results for conventional heating modification were 67.08%, 31.97%, and 32.39%, respectively. Therefore, acid group incorporation considerably improved the adsorption properties of the clinoptilolite. Regarding adsorption kinetics, it was found that the pseudo-second-order model better described the behavior of all the modified materials. Equilibrium adsorption data were adjusted to the Langmuir and Freundlich models. The Freundlich model (multilayer adsorption) described urea adsorption, while the Langmuir model (monolayer adsorption) described creatinine and uric acid. Full article
(This article belongs to the Special Issue Trends in Coatings and Surface Technology, 2nd Edition)
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<p>FT-IR spectra of unmodified clinoptilolite and modified clinoptilolite by conventional heating Clinop/ATarC1 and ClinopATarC2, respectively.</p>
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<p>FT-IR spectra of unmodified clinoptilolite and modified clinoptilolite by ultrasound, Clinop/Atar25US, Clinop/Atar50US, and Clinop/Atar100US, respectively.</p>
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<p>Thermogravimetric analyses for (<b>a</b>) unmodified clinoptilolite and modified by conventional heating, (<b>b</b>) Clinop/ATarC1, and (<b>c</b>) ClinopATarC2.</p>
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<p>Thermogravimetric analyses for (<b>a</b>) unmodified clinoptilolite and modified by ultrasound, (<b>b</b>) Clinop/ATar25US, (<b>c</b>) Clinop/ATar50US, and (<b>d</b>) Clinop/ATar100US.</p>
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<p>Removal results for (<b>a</b>) urea and (<b>b</b>) creatinine using unmodified and modified clinoptilolite as adsorbent.</p>
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<p>Removal results in uric acid using unmodified and modified clinoptilolite as an adsorbent.</p>
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<p>Experimental data fit the homogeneous solid diffusion model for urea adsorption in (<b>a</b>) Clinoptilolite, (<b>b</b>) Clinop/ATarC1, (<b>c</b>) Clinop/ATarC2, (<b>d</b>) Clinop/ATar25US, (<b>e</b>) Clinop/ATar50US, and (<b>f</b>) Clinop/ATar100US.</p>
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<p>Behavior of the adsorption capacities for (<b>a</b>) urea, (<b>b</b>) creatinine, and (<b>c</b>) uric acid.</p>
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<p>Diagram of the modification and absorption of toxins.</p>
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14 pages, 2677 KiB  
Article
Obesity-Associated Hyperuricemia in Female Mice: A Reevaluation
by Andrew P. Giromini, Sonia R. Salvatore, Brooke A. Maxwell, Sara E. Lewis, Michael R. Gunther, Marco Fazzari, Francisco J. Schopfer, Roberta Leonardi and Eric E. Kelley
Gout Urate Cryst. Depos. Dis. 2024, 2(3), 252-265; https://doi.org/10.3390/gucdd2030019 - 30 Aug 2024
Viewed by 470
Abstract
Many preclinical reports have coalesced to identify a strong association between obesity and increased levels of uric acid (UA) in tissues and, importantly, in the circulation (hyperuricemia). Unfortunately, nearly all these studies were conducted with male mice or, in one case, female mice [...] Read more.
Many preclinical reports have coalesced to identify a strong association between obesity and increased levels of uric acid (UA) in tissues and, importantly, in the circulation (hyperuricemia). Unfortunately, nearly all these studies were conducted with male mice or, in one case, female mice without a side-by-side male cohort. Therefore, the relationship between obesity and hyperuricemia in female mice remains undefined. This lack of clarity in the field has considerable impact as the downstream effects of obesity and allied hyperuricemia are extensive, resulting in many comorbidities including cardiovascular dysfunction, chronic kidney disease, and nonalcoholic fatty liver disease (NAFLD). Herein we begin to address this issue by revealing phenotypic and metabolic responses to diet-induced obesity (DIO) in a side-by-side male vs. female C57BL/6J study. Beginning at 6 weeks of age, mice were exposed to either an obesogenic diet (60% calories from fat) or control diet (10% calories from fat) for 19 weeks. Similar to numerous reported observations with the 60% diet, male mice experienced significant weight gain over time, elevated fasting blood glucose, impaired glucose tolerance and significantly elevated circulating uric acid levels (2.54 ± 0.33 mg/dL) compared to age-matched lean male controls (1.53 ± 0.19 mg/dL). As expected, the female mice experienced a slower rate of weight gain compared to the males; however, they also developed elevated fasting blood glucose and impaired glucose tolerance compared to age-matched lean controls. Countervailing our previous report whereby the control diet for the female-only study was vivarium standard chow (18% calories from fat), the obese female mice did demonstrate significantly elevated circulating UA levels (2.55 ± 0.15 mg/dL) compared to the proper control (1.68 ± 0.12 mg/dL). This affirms that the choice of control diet is crucial for reaching durable conclusions. In toto, these results, for the first time, reveal elevated circulating UA to be a similar long-term response to obesogenic feeding for both males and females and mirrors clinical observations demonstrating hyperuricemia in obesity for both sexes. Full article
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<p>Impact of diet on weight gain and caloric intake. (<b>A</b>) Male weight gain recorded weekly from the start of the diets. (<b>B</b>) Female weight gain recorded weekly from the start of the diets. (<b>C</b>,<b>D</b>) Amount of total food consumed by male (<b>C</b>) and female (<b>D</b>) mice during the diet, reported as kcals consumed per mouse per week. (<b>E</b>,<b>F</b>) Amount of total food consumed by male (<b>E</b>) and female (<b>F</b>) mice during the diet, reported as grams of food consumed per mouse per week. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.0001. Number in parenthesis indicates the number of mice in each group.</p>
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<p>Males demonstrate greater impairment of glucose tolerance at week 10. (<b>A</b>) GTT curves for male mice fed the HFD and control diet. (<b>B</b>) GTT curves for female mice fed the HFD and control diet. (<b>C</b>) Fasting blood glucose for male and female mice. (<b>D</b>) Area under the curve (AUC) for male and female mice, obtained after subtracting the initial fasting blood glucose value for each mouse. For statistically significant differences, <span class="html-italic">p</span> values are reported. HFD males <span class="html-italic">n</span> = 17, control males <span class="html-italic">n</span> = 17, HFD females <span class="html-italic">n</span> = 15, and control females <span class="html-italic">n</span> = 13.</p>
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<p>Male and female mice present with similar impairment in glucose tolerance at week 14. (<b>A</b>) GTT curves for male mice fed the HFD and control diet. (<b>B</b>) GTT curves for female mice fed the HFD and control diet. (<b>C</b>) Fasting blood glucose for male and female mice. (<b>D</b>) Area under the curve (AUC) for male and female mice, obtained after subtracting the initial fasting blood glucose value for each mouse. For statistically significant differences, <span class="html-italic">p</span> values are reported. HFD males <span class="html-italic">n</span> = 8, control males <span class="html-italic">n</span> = 6, HFD females <span class="html-italic">n</span> = 15, and control females <span class="html-italic">n</span> = 13.</p>
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<p>Body composition analysis (week 16) and terminal organ weights (week 19). (<b>A</b>,<b>B</b>) Total body weight of mice compared to lean mass and fat mass. (<b>A</b>) Male. (<b>B</b>) Female. (<b>C</b>,<b>D</b>) Terminal organ weights after 16 weeks on diets. (<b>C</b>) Male. (<b>D</b>) Female. In males, the fasting terminal body weights were 45.1 ± 1.2 g for mice fed the HFD and 26.0 ± 0.4 g for control mice. In females, the fasting terminal body weights were 39.4 ± 2.1 g for mice fed the HFD and 20.4 ± 0.4 g for control mice. Sk Mus–skeletal muscle. * <span class="html-italic">p</span> &lt; 0.05. For statistically significant differences, <span class="html-italic">p</span> values are reported. * <span class="html-italic">p</span> &lt; 0.05. HFD males <span class="html-italic">n</span> = 8, control males <span class="html-italic">n</span> = 8, HFD females <span class="html-italic">n</span> = 15, and control females <span class="html-italic">n</span> = 13.</p>
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<p>Plasma cholesterol, cholesteryl ester and triglyceride levels at week 19. (<b>A</b>) Plasma cholesterol content. (<b>B</b>) Plasma cholesteryl ester content. (<b>C</b>) Plasma triglyceride content. HFD males <span class="html-italic">n</span> = 8, control males <span class="html-italic">n</span> = 8, HFD females <span class="html-italic">n</span> = 15, and control females <span class="html-italic">n</span> = 13.</p>
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<p>XO activity and UA levels week 19. (<b>A</b>) Plasma XO activity. (<b>B</b>) Plasma UA levels. (<b>C</b>) Liver XOR activity. (<b>D</b>) Liver UA levels. For statistically significant differences, <span class="html-italic">p</span> values are reported. HFD males <span class="html-italic">n</span> = 8, control males <span class="html-italic">n</span> = 8, HFD females <span class="html-italic">n</span> = 15, and control females <span class="html-italic">n</span> = 13.</p>
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15 pages, 9936 KiB  
Article
Effect of Methylxanthines on Urate Crystallization: In Vitro Models of Gout and Renal Calculi
by Jaume Dietrich, Felix Grases and Antonia Costa-Bauza
Crystals 2024, 14(9), 768; https://doi.org/10.3390/cryst14090768 - 29 Aug 2024
Viewed by 349
Abstract
Background: Common forms of pathological crystals are uric acid or urates, which are responsible for gout, urolithiasis, and other conditions. Methods: We used a kinetic–turbidimetric crystallization assay to evaluate the effect of ten specific methylxanthines on the crystallization of monosodium urate, potassium urate, [...] Read more.
Background: Common forms of pathological crystals are uric acid or urates, which are responsible for gout, urolithiasis, and other conditions. Methods: We used a kinetic–turbidimetric crystallization assay to evaluate the effect of ten specific methylxanthines on the crystallization of monosodium urate, potassium urate, and ammonium urate in conditions that mimicked urine. We also studied the effect of different levels of 7-methylxanthine in the presence of other biological compounds (albumin and hyaluronic acid) on the solubility of monosodium urate in conditions that mimicked synovial fluid. Results: The results showed that 7-methylxanthine in the range of 16.61–49.84 mg/L inhibited the crystallization of each urate when the initial urate concentration was 3 × 10−3 M (500 mg/L) and the conditions mimicked urine, and that the greatest inhibitory effect was for monosodium urate. In addition, 7-methylxanthine at a concentration of 25 mg/L totally prevented the crystallization of monosodium urate at an initial urate concentration of 2.38 × 10−3 M (400 mg/L) in conditions that mimicked synovial fluid. Moreover, at a low concentration of 7-methylxanthine, albumin and hyaluronic acid increased this inhibitory effect. Conclusions: Our in vitro results demonstrate that 7-methylxanthine inhibits the crystallization of urates in conditions that mimic synovial fluid and urine. Full article
(This article belongs to the Special Issue Pathological Biomineralization: Recent Advances and Perspectives)
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<p>Chemical structure of uric acid, urate, 1,3-dimethyluric acid, and 9 methylxanthines tested as inhibitors of urate salts’ crystallization.</p>
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<p>Effect of different methylxanthines (0.3 mM) on the crystallization time, expressed as the mean of three replicates ± SD of ∆t<sub>i</sub> of ammonium urate (NH<sub>4</sub>U), monosodium urate (MSUM), and potassium urate (KU) in artificial urine at 37 °C and pH 7.45 relative to controls (no methylxanthines). <a href="#crystals-14-00768-t001" class="html-table">Table 1</a> shows the additional experimental conditions.</p>
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<p>Effect of 3-methylxanthine and 7-methylxanthine concentration on the increase in crystallization time (∆t<sub>i</sub>, expressed as the mean of three replicates ± SD) of ammonium urate, monosodium urate, and potassium urate in artificial urine at 37 °C and pH 7.45 relative to controls (no methylxanthines). <a href="#crystals-14-00768-t001" class="html-table">Table 1</a> shows the additional experimental conditions.</p>
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<p>Combined effect of 3-methylxanthine and 7-methylxanthine concentrations on the increase in crystallization time (∆t<sub>i</sub>, expressed as the mean of three replicates ± SD) of ammonium urate (<b>A</b>) and potassium urate (<b>B</b>) at 37 °C and pH 7.45 relative to controls (no methylxanthines). <a href="#crystals-14-00768-t001" class="html-table">Table 1</a> shows the additional experimental conditions.</p>
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<p>Effect of 7-methylxanthine concentration on crystallization of monosodium urate (initial uric acid concentration: 2.38 × 10<sup>−3</sup> M [400 mg/L]) in conditions that mimicked synovial fluid (31 °C, pH 7.4, initial sodium concentration: 0.4 × 10<sup>−1</sup> M, 96 h) expressed as mean ± SD (<b>A</b>) and image of a representative experiment at 96 h (<b>B</b>).</p>
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<p>Effect of initial uric acid concentration on the crystallization of monosodium urate without (1) and with 50 µM of 7-methylxanthine (2) in conditions that mimicked synovial fluid, expressed as the mean of three replicates ± SD. Initial sodium concentration: 0.4 × 10<sup>−1</sup> M, 31 °C, pH: 7.4, incubation time: 96 h.</p>
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<p>Effect of sodium and 7-methylxanthine concentrations on crystallization of monosodium urate in conditions that mimicked synovial fluid, expressed as the mean of three replicates ± SD. Initial uric acid concentration: 400 mg/L, 31 °C, pH 7.4, incubation time: 96 h.</p>
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<p>Effect of 7-methylxanthine concentration without (1) and with 96 mg/L calcium (2) on crystallization of monosodium urate in conditions that mimicked synovial fluid, expressed as the mean of three replicates ± SD. Initial uric acid concentration: 400 mg/L, 31 °C, pH 7.4, incubation time: 96 h.</p>
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<p>Effect of 7-methylxanthine concentration on crystallization of monosodium urate with no additions, addition of albumin (10 g/L), and addition of two different hyaluronic acid products (3 g/L each) in conditions that mimicked synovial fluid, expressed as the mean of three replicates ± SD. Initial uric acid concentration: 400 mg/L, 31 °C, pH 7.4, incubation time: 96 h.</p>
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<p>Effect of uric acid concentration on monosodium urate crystallization in human plasma without 7-methylxanthine (1), with 50 µM of 7-methylxanthine (2), and with 100 µM of 7-methylxanthine; (3) 31 °C, incubation time: 96 h.</p>
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<p>SEM images of ammonium urate crystals from the kinetic–turbidimetric assays in artificial urine without methylxanthines (<b>A</b>), with 0.3 × 10<sup>−3</sup> M 3-methylxanthine (<b>B</b>), and with 0.3 × 10<sup>−3</sup> M 7-methylxanthine (<b>C</b>). Initial uric acid concentration: 2.97 × 10<sup>−3</sup> M [500 mg/L], ammonium concentration: 2.64 × 10<sup>−1</sup> M, pH 7.45.</p>
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<p>SEM images of monosodium urate crystals from the kinetic–turbidimetric assays in artificial urine without methylxanthines (<b>A</b>), with 0.3 × 10<sup>−3</sup> M 3-methylxanthine (<b>B</b>), and with 0.3 × 10<sup>−3</sup> M 7-methylxanthine (<b>C</b>). Initial uric acid concentration: 2.97 × 10<sup>−3</sup> M [500 mg/L], sodium concentration: 6.18 × 10<sup>−1</sup> M, pH 7.45.</p>
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<p>SEM images of potassium urate crystals from the kinetic–turbidimetric assays in artificial urine without methylxanthines (<b>A</b>), with 0.3 × 10<sup>−3</sup> M 3-methylxanthine (<b>B</b>), and with 0.3 × 10<sup>−3</sup> M 7-methylxanthine (<b>C</b>). Initial uric acid concentration: 4.46 × 10<sup>−3</sup> M (750 mg/L), potassium concentration: 6 × 10<sup>−1</sup> M, pH 7.45.</p>
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14 pages, 652 KiB  
Article
Sex Differences in Biochemical Analyses, Cardiometabolic Risk Factors and Their Correlation with CRP in Healthy Mexican Individuals
by Aniel Jessica Leticia Brambila-Tapia, Alejandra Soledad González-Gómez, Laura Arely Carrillo-Delgadillo, Ana Míriam Saldaña-Cruz and Ingrid Patricia Dávalos-Rodríguez
J. Pers. Med. 2024, 14(9), 904; https://doi.org/10.3390/jpm14090904 - 26 Aug 2024
Viewed by 296
Abstract
Background: Few studies have been undertaken to detect the presence of cardiovascular risk factors (CRFs) in healthy populations (individuals auto-reported as healthy). These risk factors include high body mass index (BMI), high waist-to-hip ratio (WHR), high systolic and diastolic blood pressure (SBP, DBP), [...] Read more.
Background: Few studies have been undertaken to detect the presence of cardiovascular risk factors (CRFs) in healthy populations (individuals auto-reported as healthy). These risk factors include high body mass index (BMI), high waist-to-hip ratio (WHR), high systolic and diastolic blood pressure (SBP, DBP), high uric acid and high Castelli’s risk index (CRI); this last is the ratio of total cholesterol to HDL cholesterol (TC/HDL-c). In addition, the correlations between CRFs and the biomarker C-reactive protein (CRP) has not been explored in each sex. Aim: Therefore, this study aimed to determine sex differences in the abnormalities in blood and urine analyses, including CRFs and their correlation with CPR in a non-representative sample of healthy Mexican individuals. Results: A total of 238 subjects were included, 123 (51.7%) of whom were women. The main blood alterations detected were high serum lipids, including high total cholesterol, LDL-cholesterol, triglycerides, and the CRI, which were higher in men than in women. The men’s samples had a higher frequency of hypertensives and pre-hypertensives than the women’s sample. The CRP showed positive significant correlations with the CRFs: BMI, WHR, SBP, DBP, uric acid, and the CRI, with a higher correlation for BMI and WHR, and most of these correlations were higher in women than in men. Additionally, all these factors showed a positive correlation among them. Conclusion: In conclusion, the main alterations observed in blood are related to cardiovascular risk and were reported with a higher frequency in men when compared with women. This finding can be related to the higher values of WHR in this sex; additionally, the inflammatory marker CRP was more correlated with the cardiometabolic risk factors in women than in men, which suggests a different relationship between inflammation and cardiometabolic risk factors in each sex. Full article
(This article belongs to the Section Sex, Gender and Hormone Based Medicine)
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<p>Percentages in the main cardiovascular risk factors in each sex.</p>
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<p>Percentages in the main urinary abnormalities in each sex.</p>
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