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Search Results (3,095)

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17 pages, 2436 KiB  
Review
Treatment and Recycling of Tungsten Beneficiation Wastewater: A Review
by Wenxia Zhu, Jianhua Kang, Danxian Zhang, Wei Sun, Zhiyong Gao, Haisheng Han and Runqing Liu
Separations 2024, 11(10), 298; https://doi.org/10.3390/separations11100298 - 16 Oct 2024
Abstract
The large amount of wastewater containing various pollutants generated during the tungsten beneficiation process has become a bottleneck for the sustainable development of tungsten mining enterprises. Typical pollutants mainly include suspended solids (SSs), silicate ions, metal ions, and residual organic reagents. The direct [...] Read more.
The large amount of wastewater containing various pollutants generated during the tungsten beneficiation process has become a bottleneck for the sustainable development of tungsten mining enterprises. Typical pollutants mainly include suspended solids (SSs), silicate ions, metal ions, and residual organic reagents. The direct discharge of untreated tungsten beneficiation wastewater can cause serious harm to the ecological environment, while recycling can significantly affect flotation indicators. In this paper, the sources and characteristics of typical pollutants were analyzed, and various purification techniques were outlined, including coagulation, adsorption, chemical precipitation, oxidation, and biological treatment methods. Among these techniques, coagulation is particularly effective for the removal of SSs, while adsorption and chemical precipitation are recommended for the removal of soluble ions. For residual organic reagents, oxidation methods have demonstrated high treatment efficiencies. The mainstream methods for wastewater recycling were summarized, including centralized recycling, as well as internal recycling at certain stages. For tungsten beneficiation such a complex process, where the quality of wastewater varies greatly between different stages, it is suitable to recycle the wastewater after appropriate treatment at a specific stage. Furthermore, this study provided a perspective on the future directions of tungsten beneficiation wastewater treatment, serving as a reference for related research and industrial practices. Full article
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Graphical abstract

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<p>Common flow chart of tungsten beneficiation.</p>
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<p>Species distribution of silicate ions in solutions as a function of pH.</p>
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<p>Species distribution of lead (C<sub>Pb</sub> = 1 × 10<sup>−4</sup> mol/L) (<b>a</b>) and zinc (C<sub>Zn</sub> = 1 × 10<sup>−4</sup> mol/L) (<b>b</b>) in solution as a function of pH.</p>
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<p>Reaction mechanism for the Fenton process [<a href="#B84-separations-11-00298" class="html-bibr">84</a>].</p>
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<p>Schematic diagram of activated sludge process for wastewater treatment.</p>
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<p>Schematic diagram of centralized treatment and recycling of wastewater from molybdenite and scheelite enrichment.</p>
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<p>Principled process of wastewater recycling [<a href="#B104-separations-11-00298" class="html-bibr">104</a>].</p>
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18 pages, 4797 KiB  
Article
Structural and Physicochemical Characterization of Resistant Starch from Sixteen Banana Cultivars across Three Genome Groups
by Minhong Liang, Shiyun Tu, Jinfeng Fu, Juan Wang and Ou Sheng
Foods 2024, 13(20), 3277; https://doi.org/10.3390/foods13203277 (registering DOI) - 16 Oct 2024
Abstract
Banana fruits are rich in starch, and unripe banana flour is considered a beneficial ingredient in the food industry because it has high levels of resistant starch, which significantly aids in promoting gut health and regulating blood sugar and lipid levels. However, the [...] Read more.
Banana fruits are rich in starch, and unripe banana flour is considered a beneficial ingredient in the food industry because it has high levels of resistant starch, which significantly aids in promoting gut health and regulating blood sugar and lipid levels. However, the associations between banana cultivars with various genotypes cultivated globally and their resistant starch properties remain unclear. Herein, we investigated resistant starches from 16 banana cultivars covering three genome groups (ABB, AAB, and AAA) in order to reveal the differences and similarities among these cultivars. The results showed that there was a genotype-specific pattern in banana resistant starch (BRS) degradation. The AAA genome BRS exhibited a high degree of resistant starch degradation. The genotypes of the banana cultivars also impacted the granular morphology of the resistant starch. The ABB and AAB genome BRS were more conducive to forming resistant starch. The BRS samples from the three genome groups displayed either B-type or C-type structures. Even within the same genome group, the BRS samples exhibited differences in thermal and pasting properties. These findings reveal the impact of genotypes on BRS content and characteristics, providing a basis for future breeding and resistant starch utilization. Full article
(This article belongs to the Section Food Engineering and Technology)
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<p>Results of hierarchical cluster analysis of BRS from 16 banana cultivars at D1 and D7. The lines of the same color in the figure represent that these banana cultivars are classified into the same cluster.</p>
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<p>Optical microscopy images (×200) of BRS from 16 banana cultivars.</p>
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<p>Polarized light microscopy images (×200) of BRS from 16 banana cultivars.</p>
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<p>Scanning electron microscopy images (×500) of BRS from 16 banana cultivars.</p>
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<p>X-ray diffraction patterns and crystallinity indexes of BRS from 16 banana cultivars.</p>
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<p>Iodine absorption spectra from BRS of 16 BRS cultivars.</p>
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<p>Heat map with dendrogram of BRS from 16 banana cultivars. The lines of the same color in the figure represent that these banana cultivars are classified into the same cluster. 1-BRS, resistant starch content of D1 banana flour; 1-NRS, non-resistant starch content of D1 banana flour; 7-BRS, resistant starch content of D7 banana flour; 7-NRS, non-resistant starch content of D7 banana flour; pGI, predicted glycemic index of banana flour; CI, crystallinity of resistant banana starch; T<sub>o</sub>, onset temperature; T<sub>p</sub>, peak temperature; T<sub>c</sub>, conclusion temperature; ΔT, the gelatinization temperature range; A, initial gelatinization temperature; B, peak viscosity (BU); C, viscosity at 95 °C (BU); D, viscosity after 5 min at 95 °C (BU); E, viscosity at 50 °C (BU); F, viscosity after 5 min at 50 °C (BU); B-D: breakdown viscosity; E-D: retrogradation viscosity.</p>
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20 pages, 3681 KiB  
Article
The Effect of Lower Limb Combined Neuromuscular Electrical Stimulation on Skeletal Muscle Cross-Sectional Area and Inflammatory Signaling
by Amal Alharbi, Jia Li, Erika Womack, Matthew Farrow and Ceren Yarar-Fisher
Int. J. Mol. Sci. 2024, 25(20), 11095; https://doi.org/10.3390/ijms252011095 (registering DOI) - 16 Oct 2024
Viewed by 202
Abstract
In individuals with a spinal cord injury (SCI), rapid skeletal muscle atrophy and metabolic dysfunction pose profound rehabilitation challenges, often resulting in substantial loss of muscle mass and function. This study evaluates the effect of combined neuromuscular electrical stimulation (Comb-NMES) on skeletal muscle [...] Read more.
In individuals with a spinal cord injury (SCI), rapid skeletal muscle atrophy and metabolic dysfunction pose profound rehabilitation challenges, often resulting in substantial loss of muscle mass and function. This study evaluates the effect of combined neuromuscular electrical stimulation (Comb-NMES) on skeletal muscle cross-sectional area (CSA) and inflammatory signaling within the acute phase of SCI. We applied a novel Comb-NMES regimen, integrating both high-frequency resistance and low-frequency aerobic protocols on the vastus lateralis muscle, to participants early post-SCI. Muscle biopsies were analyzed for CSA and inflammatory markers pre- and post-intervention. The results suggest a potential preservation of muscle CSA in the Comb-NMES group compared to a control group. Inflammatory signaling proteins such as TLR4 and Atrogin-1 were downregulated, whereas markers associated with muscle repair and growth were modulated beneficially in the Comb-NMES group. The study’s findings suggest that early application of Comb-NMES post-SCI may attenuate inflammatory pathways linked to muscle atrophy and promote muscle repair. However, the small sample size and variability in injury characteristics emphasize the need for further research to corroborate these results across a more diverse and extensive SCI population. Full article
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<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
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<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
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<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
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<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
Full article ">Figure 1 Cont.
<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
Full article ">Figure 1 Cont.
<p>Normalized total protein levels for skeletal muscle inflammatory proteins in response to Comb-NMES vs. control. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05). Data are presented as means ± SD. Statistical significance was determined using a linear mixed model to assess group–time interactions, followed by pairwise post hoc comparisons using the Tukey–Kramer method. The model assumptions, including homogeneity of variance and normal distribution of residuals, were verified through diagnostic plots. Significance was set at <span class="html-italic">p</span> &lt; 0.05; toll-like receptor 4, TLR4; Janus kinase 1, JAK1; nuclear factor kappa-light-chain-enhancer of activated B cells, NF-kB; ribosomal protein S6 kinase, RS6K; myogenic differentiation 1, MyoD1; tumor necrosis factor alpha receptor 1, TNF-R1; tumor necrosis factor alpha, TNF-α; Interleukin 6 receptor, IL-6R; Interleukin 1 beta, IL-1β; Interleukin 1 receptor antagonist, IL-1RA; tumor necrosis factor receptor (TNFR)-associated factor 6, TRAF6; signal transducer and activator of transcription 3, STAT3; Interleukin 6, IL-6.</p>
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<p>Myofiber cross-sectional area (CSA) in response to the Comb-NMES and control groups. Data are means ± SD. Group × time interactions were evaluated using a linear mixed-effects model. Post hoc Tukey–Kramer tests were performed to determine specific differences between and within groups. Residuals were checked to ensure normal distribution and variance homogeneity. Statistical significance was defined as <span class="html-italic">p</span> &lt; 0.05. * Statistically significant changes within the group (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>A training program for a person with a complete motor SCI. (<b>A</b>) As a component of Dudley’s training (Comb-NMES), every session comprised four sets of ten actions. Initially, during the first two sessions, the individual completed four sets of 10 repetitions without introducing any additional weight. Once the person achieved 40 repetitions of full knee extension within a training session, the weights were gradually increased by 1 lb. Eventually, after completing 12 rounds, the individual was able to lift 5 pounds. (<b>B</b>) In the twitch training regimen, the exercise program commenced with 10 min of twitch activation at a frequency of 2 Hz. Over the course of the first week, this duration was gradually extended until each session lasted 30 min, with the frequency increased to 6 Hz [<a href="#B16-ijms-25-11095" class="html-bibr">16</a>].</p>
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16 pages, 1873 KiB  
Article
The Effects of Acid-Modified Biochar and Biomass Power Plant Ash on the Physiochemical Properties and Bacterial Community Structure of Sandy Alkaline Soils in the Ancient Region of the Yellow River
by Chuanzhe Li, Wenqi Shao, Qingjun Dong, Li Ji, Qing Li, Ankang Zhang, Chuan Chen and Wenjing Yao
Sustainability 2024, 16(20), 8909; https://doi.org/10.3390/su16208909 - 14 Oct 2024
Viewed by 323
Abstract
The application of biochar can effectively enhance soil organic matter (SOM) and improve soil structure. Biomass power plant ash (BPPA) is also rich in essential nutrients for plants, with similar carbon content. Considering production cost and agricultural waste recycling, it is beneficial to [...] Read more.
The application of biochar can effectively enhance soil organic matter (SOM) and improve soil structure. Biomass power plant ash (BPPA) is also rich in essential nutrients for plants, with similar carbon content. Considering production cost and agricultural waste recycling, it is beneficial to apply BPPA to improve soil fertility and quality. However, it remains unclear whether its ameliorative effects surpass those of biochar in alkaline soils. In the study, we set up seven pot experiments of faba beans in sandy alkaline soils from the ancient region of the Yellow River, including the controls (CK), different amounts of acid-modified BPPA (A1, A2, A3), and the same amounts of acid-modified biochar (B1, B2, B3), to compare their effects on soil physiochemical properties and bacterial community structure. The results indicate that the application of both biochar and BPPA can improve soil physiochemical properties. At the same dosage, the biochar application outperformed BPPA treatment in terms of soil physical properties such as bulk density (BD), maximum water-holding capacity (FC), and soil capillary porosity (SP2). Conversely, BPPA treatment displayed advantages in chemical properties such as readily oxidizable organic carbon (ROOC), total nitrogen (TN), alkaline nitrogen (AN), available phosphorus (AP), available potassium (AK), and electrical conductivity (EC). All the treatments enhanced the richness and diversity of bacterial communities, increasing the relative abundance of eutrophic groups such as Bacteroidota and Firmicutes while decreasing that of oligotrophic groups like Actinobacteriota. BPPA also increased the relative abundance of Proteobacteria, while the opposite was observed for biochar. Correlation analysis showed that the environmental factors such as soil pH, EC, TN, AK, SOM, and SP2 emerged as primary factors influencing the bacterial community structure of alkaline soils, significantly affecting their diversity and abundance. Among them, SP2 and SOM were the dominant physical and chemical factors, respectively. Overall, the application of both acid-modified BPPA and biochar can enhance the physiochemical properties of sandy alkaline soils, while the application of BPPA is superior for improving soil nutrient content and enhancing bacterial community structure. The study explores the potential mechanisms through which the application of acid-modified BPPA affects soil characteristics and microbial features, providing new insight into developing optimizing fertilization strategies for enhancing soil quality in the ancient region of the Yellow River. Full article
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<p>Soil bacterial community composition at the phylum level under different treatments.</p>
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<p>Alpha diversity index of soil bacterial communities under different treatments. Notes: Different lowercase letters in the same column indicate significant difference among the treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Principal component analysis (PCA) of the composition of soil bacterial community under different treatments. (<b>a</b>) PCA at the phylum level; (<b>b</b>) PCA at the genus level.</p>
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<p>Redundancy analysis between soil bacterial community composition and physiochemical properties.</p>
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<p>Heatmap analysis between the relative abundances of soil bacterial communities and soil physiochemical properties. Notes: * means <span class="html-italic">p</span> &lt; 0.05, ** means <span class="html-italic">p</span> &lt; 0.01. The red stands for positive correlation and the blue stands for negative correlation.</p>
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35 pages, 820 KiB  
Review
Setting the Social Media Stage, a Narrative Review: The Role of Theory and Research in Understanding Adolescent Online Sexual Health Information-Seeking
by Yvonne Allsop
Sexes 2024, 5(4), 544-578; https://doi.org/10.3390/sexes5040037 (registering DOI) - 12 Oct 2024
Viewed by 759
Abstract
This narrative review offers a deep dive into the theoretical and empirical literature on adolescent online health information-seeking behavior, specifically in relation to sexual health. It presents ways in which motivational influences impact adolescent social media use to seek sexual health information and [...] Read more.
This narrative review offers a deep dive into the theoretical and empirical literature on adolescent online health information-seeking behavior, specifically in relation to sexual health. It presents ways in which motivational influences impact adolescent social media use to seek sexual health information and offers insight into how Longo’s comprehensive and integrated model for understanding health information, communication, and information-seeking and self-determination theory may be used as frameworks for improved understanding in adolescent use of social media for seeking information related to sexual health. The main objectives of this article are, first, to examine the existing literature pertaining to social media, namely its main characteristics and uses by adolescents, its use as an educational tool, and its relation to health information; second, to explore information-seeking and learning through online platforms, particularly social media; and third, to provide a framework utilizing self-determination theory to better understand adolescent motivation in health-seeking behavior. This manuscript advances current knowledge and practices in supporting adolescent skill-development surrounding information-seeking and evaluation behaviors. Such practices will only become more beneficial as young people seek information in various settings (e.g., online, social media platforms, and artificial intelligence systems), particularly sensitive information such as that related to sexual health. Full article
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<p>Information-seeking based in Longo’s model [<a href="#B97-sexes-05-00037" class="html-bibr">97</a>].</p>
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18 pages, 5772 KiB  
Article
Indole-3-Acetic Acid Esterified with Waxy, Normal, and High-Amylose Maize Starches: Comparative Study on Colon-Targeted Delivery and Intestinal Health Impact
by Qian Gong, Xinyan Qu, Yisheng Zhao, Xingjing Zhang, Shuhua Cao, Xiao Wang, Yingying Song, Charles R. Mackay and Quanbo Wang
Nutrients 2024, 16(20), 3446; https://doi.org/10.3390/nu16203446 - 11 Oct 2024
Viewed by 495
Abstract
Abstract: Background: Accumulating research suggests that metabolites produced by gut microbiota are essential for maintaining a balanced gut and immune system. Indole-3-acetic acid (IAA), one of tryptophan metabolites from gut microbiota, is critical for gut health through mechanisms such as activating aryl hydrocarbon [...] Read more.
Abstract: Background: Accumulating research suggests that metabolites produced by gut microbiota are essential for maintaining a balanced gut and immune system. Indole-3-acetic acid (IAA), one of tryptophan metabolites from gut microbiota, is critical for gut health through mechanisms such as activating aryl hydrocarbon receptor. Delivery of IAA to colon is beneficial for treatment of gastrointestinal diseases, and one promising strategy is IAA esterified starch, which is digested by gut microbes in colon and releases loaded IAA. Amylose content is a key structural characteristic that controls the physicochemical properties and digestibility of starch. Methods: In the current study, IAA was esterified with three typical starches with distinct amylose content to obtain indolyl acetylated waxy maize starch (WMSIAA), indolyl acetylated normal maize starch (NMSIAA), and indolyl acetylated high-amylose maize starch (HAMSIAA). The study comparatively analyzed their respective physicochemical properties, how they behave under in vitro digestion conditions, their ability to deliver IAA directly to the colon, and their effects on the properties of the gut microbiota. Results: The new characteristic peak of 1H NMR at 10.83 ppm, as well as the new characteristic peak of FTIR spectra at 1729 cm−1, represented the successful esterification of IAA on starch backbone. The following in vitro digestion study further revealed that treatment with indolyl acetylation significantly elevated the resistant starch content in the starch samples. In vivo experimental results demonstrated that WMSIAA exhibited the most significant increase in IAA levels in the stomach, whereas HAMSIAA and NMSIAA demonstrated the most remarkable increases in IAA levels in the small intestine and colon, respectively. The elevated IAA levels in the colon are conducive to promoting the growth of beneficial intestinal bacteria and significantly alleviating DSS-induced colitis. Conclusions: This research presents innovative insights and options for the advancement of colon-specific drug delivery systems aimed at preventing and curing gastrointestinal disorders. Full article
(This article belongs to the Special Issue Dietary Nutrients and Additives on Gut Microbiota and Immunity)
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<p><sup>1</sup>H NMR spectra of starch. Note: HAMS: high-amylose maize starch; NMS: normal maize starch; WMS: waxy maize starch; HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>FTIR spectra of starch. Note: HAMS: high-amylose maize starch; NMS: normal maize starch; WMS: waxy maize starch; HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>XRD patterns of starch. Note: HAMS: high-amylose maize starch; NMS: normal maize starch; WMS: waxy maize starch; HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>SEM of starch. Note: HAMS: high-amylose maize starch; NMS: normal maize starch; WMS: waxy maize starch; HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>Colon-targeted IAA delivery in vivo. (<b>A</b>) IAA concentrations in stomach contents; (<b>B</b>) IAA concentrations in small intestine contents; (<b>C</b>) IAA concentrations in colon contents; (<b>D</b>) IAA concentrations in portal venous blood. Results are mean ± SEM (n = 6), * <span class="html-italic">p</span> &lt; 0.05. Note: HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>Phylum (<b>A</b>), genus (<b>B</b>) changes, Venn diagram, (<b>C</b>) and heatmap (<b>D</b>) in mice fecal microbiota composition of control, HAMSIAA, NMSIAA and WMSIAA group. Note: HAMSIAA: indole acetylated high-amylose maize starch; NMSIAA: indole acetylated normal maize starch; WMSIAA: indole acetylated waxy maize starch.</p>
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<p>NMSIAA ameliorated DSS-induced murine colitis. The schematic diagram of animal study design (<b>A</b>). Weight change (<b>B</b>), DAI (<b>C</b>), colon length (<b>D</b>,<b>E</b>), histopathological changes in colonic tissues (<b>F</b>) and histopathology score (<b>G</b>). Results are mean ± SEM (n = 6), * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Note: NMSIAA: indole acetylated normal maize starch.</p>
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18 pages, 2018 KiB  
Article
Trichoderma Rhizosphere Soil Improvement: Regulation of Nitrogen Fertilizer in Saline–Alkali Soil in Semi-Arid Region and Its Effect on the Microbial Community Structure of Maize Roots
by Yicong Li, Jianming Cui, Jiarui Kang, Wei Zhao, Kejun Yang and Jian Fu
Agronomy 2024, 14(10), 2340; https://doi.org/10.3390/agronomy14102340 - 11 Oct 2024
Viewed by 411
Abstract
In order to reduce the actual impact of a saline–alkali environment on maize production in semi-arid areas, it is particularly important to use the combined fertilization strategy of Trichoderma microbial fertilizer and nitrogen fertilizer. The purpose of this study was to investigate the [...] Read more.
In order to reduce the actual impact of a saline–alkali environment on maize production in semi-arid areas, it is particularly important to use the combined fertilization strategy of Trichoderma microbial fertilizer and nitrogen fertilizer. The purpose of this study was to investigate the effects of different concentrations of nitrogen fertilizer combined with Trichoderma on improving the structural characteristics and ecological functions of maize rhizosphere microbial community in semi-arid saline–alkali soil. Through the microbiome analysis of maize rhizosphere soil samples with 60 kg N·ha−1 (N1) and 300 kg N·ha−1 (N2) nitrogen fertilizer combined with Trichoderma (T1) and without Trichoderma (T0), we found that the combination of Trichoderma and different concentrations of nitrogen fertilizer significantly affected the structure of bacterial and fungal communities. The results of this study showed that the combination of Trichoderma and low-concentration nitrogen fertilizer (N1T1) could improve soil nutritional status and enhance its productivity potential, revealing the relationship between beneficial and harmful fungal genera, microbial diversity and abundance, and crop biomass, which is of great significance for improving agricultural production efficiency and sustainable development. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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<p>Cluster tree structure and relative abundance of microorganisms in maize rhizosphere soil under different treatments ((<b>a</b>): phylum level of bacteria, (<b>b</b>): genus level of bacteria, (<b>c</b>): phylum level of fungi, (<b>d</b>): genus level of fungi). The relative abundance of beneficial and harmful fungi at the genus level ((<b>c</b>): beneficial fungi, (<b>d</b>): harmful fungi) was compared by functional screening, (<b>e</b>): The relative abundance of beneficial fungi at the genus level was compared by functional screening, (<b>f</b>): The relative abundance of harmful fungi at the genus level was compared by functional screening. Con (control), N1T0 (nitrogen 60), N1T1 (nitrogen 60 + <span class="html-italic">Trichoderma</span>), N2T0 (nitrogen 300), N2T1 (nitrogen 300 + <span class="html-italic">Trichoderma</span>).</p>
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<p>Rhizosphere soil bacterial community function (soil carbon cycle and nitrogen cycle-related dominant tube energy group) and fungal community function prediction (pathotrophic, symbiotic, and saprophytic) under different treatments ((<b>a</b>): bacteria, (<b>b</b>): fungi). Con (control), N1T0 (nitrogen 60), N1T1 (nitrogen 60 + <span class="html-italic">Trichoderma</span>), N2T0 (nitrogen 300), N2T1 (nitrogen 300 + <span class="html-italic">Trichoderma</span>).</p>
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<p>Structural equation model (SEM) shows the direct effects of bacteria, fungal richness and diversity, and beneficial and harmful fungi on plant leaves, plant stems, and grains. Green and brown represent positive and negative effects. CMIN/DF: chi-square degree of freedom ratio, which is used to evaluate the goodness of fit between the model and the data. GFI: goodness-of-fit index, mainly using the determination coefficient and regression standard deviation to test the fitting degree of the model to the sample observations. CFI: comparing the fitting index, the size of the sample capacity is basically unaffected by it, which can better reflect the situation of the model and is an ideal relative fitting index. ** means <span class="html-italic">p</span> &lt; 0.01 level difference, *** means <span class="html-italic">p</span> &lt; 0.001 level difference.</p>
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34 pages, 3580 KiB  
Review
Biosurfactants: Chemical Properties, Ecofriendly Environmental Applications, and Uses in the Industrial Energy Sector
by Yslla Emanuelly da Silva Faccioli, Kaio Wêdann de Oliveira, Jenyffer Medeiros Campos-Guerra, Attilio Converti, Rita de Cássia F. Soares da Silva and Leonie A. Sarubbo
Energies 2024, 17(20), 5042; https://doi.org/10.3390/en17205042 - 10 Oct 2024
Viewed by 642
Abstract
The exploitation of nature and the increase in manufacturing production are the cause of major environmental concerns, and considerable efforts are needed to resolve such issues. Oil and petroleum derivatives constitute the primary energy sources used in industries. However, the transportation and use [...] Read more.
The exploitation of nature and the increase in manufacturing production are the cause of major environmental concerns, and considerable efforts are needed to resolve such issues. Oil and petroleum derivatives constitute the primary energy sources used in industries. However, the transportation and use of these products have huge environmental impacts. A significant issue with oil-related pollution is that hydrocarbons are highly toxic and have low biodegradability, posing a risk to ecosystems and biodiversity. Thus, there has been growing interest in the use of renewable compounds from natural sources. Biosurfactants are amphipathic microbial biomolecules emerging as sustainable alternatives with beneficial characteristics, including biodegradability and low toxicity. Biosurfactants and biosurfactant-producing microorganisms serve as an ecologically correct bioremediation strategy for ecosystems polluted by hydrocarbons. Moreover, synthetic surfactants can constitute additional recalcitrant contaminants introduced into the environment, leading to undesirable outcomes. The replacement of synthetic surfactants with biosurfactants can help solve such problems. Thus, there has been growing interest in the use of biosurfactants in a broad gamut of industrial sectors. The purpose of this review was to furnish a comprehensive view of biosurfactants, classifications, properties, and applications in the environmental and energy fields. In particular, practical applications of biosurfactants in environmental remediation are discussed, with special focus on bioremediation, removal of heavy metals, phytoremediation, microbial enhanced oil recovery, metal corrosion inhibition, and improvements in agriculture. The review also describes innovating decontamination methods, including nanobioremediation, use of genetically modified microorganisms, enzymatic bioremediation, modeling and prototyping, biotechnology, and process engineering. Research patents and market prospects are also discussed to illustrate trends in environmental and industrial applications of biosurfactants. Full article
(This article belongs to the Section B: Energy and Environment)
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<p>Surfactant concentration increases until critical micelle concentration (CMC) is reached.</p>
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<p>Representation of micellar structure.</p>
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<p>Chemical structure of biosurfactants. (<b>a</b>) Rhamnolipid; (<b>b</b>) Sophorolipids; (<b>c</b>) Surfactin; (<b>d</b>) Emulsan.</p>
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<p>Environmental applications of biosurfactants [<a href="#B25-energies-17-05042" class="html-bibr">25</a>].</p>
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<p>Comparison between bioaugmentation and biostimulation techniques.</p>
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<p>Mechanism of heavy metal removal by biosurfactants.</p>
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<p>Mechanism of biosurfactant-assisted phytoremediation.</p>
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<p>Schematic of mechanisms involved in biosurfactant-mediated microbial enhanced oil recovery (adapted from Santos et al. [<a href="#B23-energies-17-05042" class="html-bibr">23</a>]).</p>
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30 pages, 2414 KiB  
Review
Promising Phytogenic Feed Additives Used as Anti-Mycotoxin Solutions in Animal Nutrition
by Sergio Quesada-Vázquez, Raquel Codina Moreno, Antonella Della Badia, Oscar Castro and Insaf Riahi
Toxins 2024, 16(10), 434; https://doi.org/10.3390/toxins16100434 - 10 Oct 2024
Viewed by 855
Abstract
Mycotoxins are a major threat to animal and human health, as well as to the global feed supply chain. Among them, aflatoxins, fumonisins, zearalenone, T-2 toxins, deoxynivalenol, and Alternaria toxins are the most common mycotoxins found in animal feed, with genotoxic, cytotoxic, carcinogenic, [...] Read more.
Mycotoxins are a major threat to animal and human health, as well as to the global feed supply chain. Among them, aflatoxins, fumonisins, zearalenone, T-2 toxins, deoxynivalenol, and Alternaria toxins are the most common mycotoxins found in animal feed, with genotoxic, cytotoxic, carcinogenic, and mutagenic effects that concern the animal industry. The chronic negative effects of mycotoxins on animal health and production and the negative economic impact on the livestock industry make it crucial to develop and implement solutions to mitigate mycotoxins. In this review, we summarize the current knowledge of the mycotoxicosis effect in livestock animals as a result of their contaminated diet. In addition, we discuss the potential of five promising phytogenics (curcumin, silymarin, grape pomace, olive pomace, and orange peel extracts) with demonstrated positive effects on animal performance and health, to present them as potential anti-mycotoxin solutions. We describe the composition and the main promising characteristics of these bioactive compounds that can exert beneficial effects on animal health and performance, and how these phytogenic feed additives can help to alleviate mycotoxins’ deleterious effects. Full article
(This article belongs to the Special Issue Mitigation and Detoxification Strategies of Mycotoxins)
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<p>Synthesis of curcumin by the general method proposed by Pabon [<a href="#B79-toxins-16-00434" class="html-bibr">79</a>] (image adapted from Zerazion et al., 2016) [<a href="#B86-toxins-16-00434" class="html-bibr">86</a>]. <b>1.</b> A suspension of B<sub>2</sub>O<sub>3</sub> (3 mmol) and acetylacetone (2 mmol) in 1.5 mL of DMF was stirred for 30 min at 80 °C. <b>2.</b> To this was added 4-hydroxy-3-methoxybenzaldehyde (5.4 mmol), followed by the slow addition of n-butylamine solution, and this was stirred at 80 °C for 4 h. <b>3.</b> The solution was acidified with 0.5 M HCl at 80 °C for 1 h. <b>4.</b> Curcumin was dried and recrystallized.</p>
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<p>Chemical structure of main flavonolignans contained in silymarin complex.</p>
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<p>Composition and principal bioactive components of grape pomace extract.</p>
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<p>Composition and principal bioactive components of olive pomace extract.</p>
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<p>Composition and principal bioactive components of orange peel extract.</p>
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43 pages, 770 KiB  
Review
Towards Sustainable Biomass Conversion Technologies: A Review of Mathematical Modeling Approaches
by Sylwia Polesek-Karczewska, Paulina Hercel, Behrouz Adibimanesh and Izabela Wardach-Świȩcicka
Sustainability 2024, 16(19), 8719; https://doi.org/10.3390/su16198719 - 9 Oct 2024
Viewed by 529
Abstract
The sustainable utilization of biomass, particularly troublesome waste biomass, has become one of the pathways to meet the urgent demand for providing energy safety and environmental protection. The variety of biomass hinders the design of energy devices and systems, which must be highly [...] Read more.
The sustainable utilization of biomass, particularly troublesome waste biomass, has become one of the pathways to meet the urgent demand for providing energy safety and environmental protection. The variety of biomass hinders the design of energy devices and systems, which must be highly efficient and reliable. Along with the technological developments in this field, broad works have been carried out on the mathematical modeling of the processes to support design and optimization for decreasing the environmental impact of energy systems. This paper aims to provide an extensive review of the various approaches proposed in the field of the mathematical modeling of the thermochemical conversion of biomass. The general focus is on pyrolysis and gasification, which are considered among the most beneficial methods for waste biomass utilization. The thermal and flow issues accompanying fuel conversion, with the basic governing equations and closing relationships, are presented with regard to the micro- (single particle) and macro-scale (multi-particle) problems, including different approaches (Eulerian, Lagrangian, and mixed). The data-driven techniques utilizing artificial neural networks and machine learning, gaining increasing interest as complementary to the traditional models, are also presented. The impact of the complexity of the physicochemical processes and the upscaling problem on the variations in the modeling approaches are discussed. The advantages and limitations of the proposed models are indicated. Potential options for further development in this area are outlined. The study shows that efforts towards obtaining reliable predictions of process characteristics while preserving reasonable computational efficiency result in a variety of modeling methods. These contribute to advancing environmentally conscious energy solutions in line with the global sustainability goals. Full article
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<p>Logical structure of the analysis.</p>
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<p>Logical structure of the analyzed models.</p>
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<p>The multistage mechanism model of biomass pyrolysis.</p>
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<p>Global one-stage mechanism model of wood pyrolysis involving reactions between pyrolysis products.</p>
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16 pages, 8633 KiB  
Article
Stress-Strain Behavior and Strength Development of High-Amount Phosphogypsum-Based Sustainable Cementitious Materials
by Ying Shi, Yue Li, Hongwei Wang, Yixuan Ma and Xinyue Lu
Materials 2024, 17(19), 4927; https://doi.org/10.3390/ma17194927 - 9 Oct 2024
Viewed by 488
Abstract
Phosphogypsum is a common industrial solid waste that faces the challenges of high stockpiling and low utilization rates. This study focuses on the mechanical properties and internal characteristics of cementitious materials with a high phosphogypsum content. Specifically, we examined the effects of varying [...] Read more.
Phosphogypsum is a common industrial solid waste that faces the challenges of high stockpiling and low utilization rates. This study focuses on the mechanical properties and internal characteristics of cementitious materials with a high phosphogypsum content. Specifically, we examined the effects of varying amounts of ground granulated blast furnace slag (5–28%), fly ash (5–20%), and hydrated lime (0.5–2%) on the stress–strain curve, unconfined uniaxial compressive strength, and elastic modulus (E50) of these materials. The test results indicate that increasing the ground granulated blast furnace slag content can significantly enhance the mechanical properties of phosphogypsum-based cementitious materials. Additionally, increasing the fly ash content can have a similar beneficial effect with an appropriate amount of hydrated lime. Furthermore, microscopic analysis of the cementitious materials using a scanning electron microscope revealed that the high sulfate content in phosphogypsum leads to the formation of calcium aluminate as the main product. Concurrently, a continuous reaction of the raw materials contributes to the strength development of the cementitious materials over time. The results could provide a novel method for improving the reusing phosphogypsum amount in civil engineering materials. Full article
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<p>Particle size analysis of raw materials.</p>
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<p>XRF analysis of raw materials: (<b>a</b>) PG; (<b>b</b>) GGBS; (<b>c</b>) FA.</p>
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<p>Specimen preparation process and test.</p>
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<p>(<b>a</b>) Stress–strain relationship for different GGBS content levels; (<b>b</b>) is an enlargement of the typical curves in (<b>a</b>).</p>
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<p>(<b>a</b>) Stress–strain relationship for different FA content levels; (<b>b</b>) is an enlargement of the typical curves in (<b>a</b>).</p>
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<p>(<b>a</b>) Stress–strain relationship for different HL content levels; (<b>b</b>) is an enlargement of the typical curves in (<b>a</b>).</p>
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<p>Effect of GGBS content on (<b>a</b>) UCS and (<b>b</b>) growth rate.</p>
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<p>Effect of FA content on (<b>a</b>) UCS and (<b>b</b>) growth rate.</p>
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<p>Effect of HL content on (<b>a</b>) UCS and (<b>b</b>) growth rate.</p>
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<p>Comparison of experimental and predicted UCS.</p>
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<p>E<sub>50</sub> for different GGBS content groups.</p>
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<p>E<sub>50</sub> for different FA content groups.</p>
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<p>E<sub>50</sub> for different HL content groups.</p>
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<p>Relationship between E<sub>50</sub> and UCS.</p>
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<p>SEM images of typical specimens. (<b>a</b>) specimen (×100); (<b>b</b>) is a local enlargement of (<b>a</b>) (×1000); (<b>c</b>) is a local enlargement of (<b>b</b>) (×3000); (<b>d</b>) is a local enlargement of (<b>c</b>) (×5000).</p>
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14 pages, 1302 KiB  
Review
Research Progress on Bioactive Substances of Beets and Their Functions
by Chun Bian, Lanyang Ji, Wei Xu, Shirong Dong and Nan Pan
Molecules 2024, 29(19), 4756; https://doi.org/10.3390/molecules29194756 - 8 Oct 2024
Viewed by 569
Abstract
As a globally cultivated and economic crop, beets are particularly important in the cane sugar and feed industries. Beet pigments are among the most important natural pigments, while various chemical components in beets display beneficial biological functions. Phenolic substances and betalains, as the [...] Read more.
As a globally cultivated and economic crop, beets are particularly important in the cane sugar and feed industries. Beet pigments are among the most important natural pigments, while various chemical components in beets display beneficial biological functions. Phenolic substances and betalains, as the main bioactive compounds, determine the functional characteristics of beets. This review categorizes the basic types of beets by the chemical composition of bioactive substances in their leaves, stems, and roots and emphatically summarizes the research progress made on the functions of two major substances in different types of beets: phenolic compounds and betalain pigments. This study provides useful insights for the comprehensive and effective application of beets in the health food and pharmaceutical industries. Full article
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<p>Leaf feet. (<b>a</b>) Field growth showing high diversity. (<b>b</b>) The effect of pigments on the petiole’s color. (1) A beet lacking a pigment; (2) dominant betaxanthin content; (3) high betaxanthin + low betacyanin contents; (4) low betaxanthin + high betacyanin contents; (5) dominant betacyanin content.</p>
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<p>Table beet.</p>
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<p>Fodder beet (<b>a</b>) and sugar beet (<b>b</b>).</p>
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<p>Resonance structures of betalamic acid, betaxanthins, and betalains [<a href="#B33-molecules-29-04756" class="html-bibr">33</a>].</p>
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<p>Resonance structures of several betacyanins [<a href="#B12-molecules-29-04756" class="html-bibr">12</a>,<a href="#B34-molecules-29-04756" class="html-bibr">34</a>]: (<b>a</b>) betanin, (<b>b</b>) isobetanin, and (<b>c</b>) betanidin.</p>
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24 pages, 10093 KiB  
Article
Enhancing a You Only Look Once-Plated Detector via Auxiliary Textual Coding for Multi-Scale Rotating Remote Sensing Objects in Transportation Monitoring Applications
by Sarentuya Bao, Mingwang Zhang, Rui Xie, Dabhvrbayar Huang and Jianlei Kong
Appl. Sci. 2024, 14(19), 9074; https://doi.org/10.3390/app14199074 - 8 Oct 2024
Viewed by 538
Abstract
With the rapid development of intelligent information technologies, remote sensing object detection has played an important role in different field applications. Particularly in recent years, it has attracted widespread attention in assisting with food safety supervision, which still faces troubling issues between oversized [...] Read more.
With the rapid development of intelligent information technologies, remote sensing object detection has played an important role in different field applications. Particularly in recent years, it has attracted widespread attention in assisting with food safety supervision, which still faces troubling issues between oversized parameters and low performance that are challenging to solve. Hence, this article proposes a novel remote sensing detection framework for multi-scale objects with a rotating status and mutual occlusion, defined as EYMR-Net. This proposed approach is established on the YOLO-v7 architecture with a Swin Transformer backbone, which offers multi-scale receptive fields to mine massive features. Then, an enhanced attention module is added to exploit the spatial and dimensional interrelationships among different local characteristics. Subsequently, the effective rotating frame regression mechanism via circular smoothing labels is introduced to the EYMR-Net structure, addressing the problem of horizontal YOLO (You Only Look Once) frames ignoring direction changes. Extensive experiments on DOTA datasets demonstrated the outstanding performance of EYMR-Net, which achieved an impressive mAP0.5 of up to 74.3%. Further ablation experiments verified that our proposed approach obtains a balance between performance and efficiency, which is beneficial for practical remote sensing applications in transportation monitoring and supply chain management. Full article
(This article belongs to the Special Issue Deep Learning in Satellite Remote Sensing Applications)
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<p>Proposed EYMR-Net framework.</p>
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<p>Swin Transformer backbone framework.</p>
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<p>CBAM network architecture.</p>
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<p>Rotating box regression via circular smoothing labels.</p>
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<p>DOTA dataset description.</p>
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<p>Performance comparison of different models.</p>
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<p>Remote sensing detection results of comparative models.</p>
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<p>Detection error distribution of different object types.</p>
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<p>Results of curve analysis.</p>
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<p>Remote sensing detection results of EYMR-Net vs. YOLOv7 series.</p>
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<p>Detection and thermal diagrams of EYMR-Net vs. YOLOv7 series.</p>
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<p>Confusion matrix of EYMR-Net detector.</p>
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14 pages, 242 KiB  
Article
Impact of Hypoalbuminemia on Outcomes Following Hepatic Resection: A NSQIP Retrospective Cohort Analysis of 26,394 Patients
by Dunavan Morris-Janzen, Sukhdeep Jatana, Kevin Verhoeff, A. M. James Shapiro, David L. Bigam, Khaled Dajani and Blaire Anderson
Livers 2024, 4(4), 507-520; https://doi.org/10.3390/livers4040036 - 7 Oct 2024
Viewed by 259
Abstract
Background/Objectives: Efforts to preoperatively risk stratify and optimize patients before liver resection allow for improvements in postoperative outcomes, with hypoalbuminemia being increasingly researched as a surrogate for nutrition, overall health and functional status. Given the paucity of studies examining the relationship between hypoalbuminemia [...] Read more.
Background/Objectives: Efforts to preoperatively risk stratify and optimize patients before liver resection allow for improvements in postoperative outcomes, with hypoalbuminemia being increasingly researched as a surrogate for nutrition, overall health and functional status. Given the paucity of studies examining the relationship between hypoalbuminemia and liver resection, this study aims to determine the impact of hypoalbuminemia on outcomes following liver resections using a large multicenter database. Methods: The American College of Surgeons–National Surgical Quality Improvement Program (2017–2021) database was used to extract the data of patients who underwent a hepatic resection. Two cohorts were defined; those with hypoalbuminemia (HA; <3.0 g/L) and those with normal albumin levels (≥3.0 g/L). Both baseline characteristics and 30-day postoperative complication rates were compared between the two cohorts. Multivariable logistic regression models were used to assess the independent effect of HA on various outcomes. Area under curve–receiver operating characteristic (AUC-ROC) curves were used to identify optimal albumin thresholds for both serious complications and mortality. Results: We evaluated 26,394 patients who underwent liver resections, with 1347 (5.1%) having preoperative HA. The HA patients were older (62.3 vs. 59.8; p < 0.001) and more likely to be of an ASA class ≥ 4 (13.0% vs. 6.5%; p < 0.001). The patients with HA had significantly more complications such as an increased length of stay, readmission, reoperation, sepsis, surgical site infection, bile leak, and need for transfusion. After controlling for demographics and comorbidities, HA remained a significant independent predictor associated with both 30-day serious complication rates (aOR 2.93 [CI 95% 2.36–3.65, p < 0.001]) and mortality (aOR 2.15 [CI 95% 1.38–3.36, p = 0.001]). The optimal cut-off for albumin with respect to predicting serious complications was 4.0 g/dL (sensitivity 59.1%, specificity 56.8%, AUC-ROC 0.61) and 3.8 g/dL (sensitivity 56.6%, specificity 68.3%, AUC-ROC 0.67) for mortality. Conclusions: In this large, retrospective database analysis, preoperative HA was significantly associated with 30-day morbidity and mortality rates following hepatic resection. Preoperative albumin may serve as a useful marker for risk stratification in conjunction with pre-existing calculators. Future studies evaluating the risk mitigation impact of nutrition and exercise prehabilitation in these patients and its capacity to modify hypoalbuminemia would be beneficial. Full article
22 pages, 22401 KiB  
Article
Residual Effect of Microbial-Inoculated Biochar with Nitrogen on Rice Growth and Salinity Reduction in Paddy Soil
by Hafiz Muhammad Mazhar Abbas, Ummah Rais, Haider Sultan, Ashar Tahir, Saraj Bahadur, Asad Shah, Asim Iqbal, Yusheng Li, Mohammad Nauman Khan and Lixiao Nie
Plants 2024, 13(19), 2804; https://doi.org/10.3390/plants13192804 - 6 Oct 2024
Viewed by 1141
Abstract
Increasing soil and water salinity threatens global agriculture, particularly affecting rice. This study investigated the residual effects of microbial biochar and nitrogen fertilizer in mitigating salt stress in paddy soil and regulating the biochemical characteristics of rice plants. Two rice varieties, Shuang Liang [...] Read more.
Increasing soil and water salinity threatens global agriculture, particularly affecting rice. This study investigated the residual effects of microbial biochar and nitrogen fertilizer in mitigating salt stress in paddy soil and regulating the biochemical characteristics of rice plants. Two rice varieties, Shuang Liang You 138 (SLY138), a salt-tolerant, and Jing Liang You 534 (JLY534), a salt-sensitive, were grown under 0.4 ds/m EC (S0) and 6.84 ds/m EC (S1) in a glass house under controlled conditions. Three types of biochar—rice straw biochar (BC), fungal biochar (BF), and bacterial biochar (BB)—were applied alongside two nitrogen (N) fertilizer rates (60 kg ha−1 and 120 kg ha−1) in a previous study. The required salinity levels were maintained in respective pots through the application of saline irrigation water. Results showed that residual effects of microbial biochars (BF and BB) had higher salt mitigation efficiency than sole BC. The combination of BB and N fertilizer (BB + N120) significantly decreased soil pH by 23.45% and Na+ levels by 46.85%, creating a more conducive environment for rice growth by enhancing beneficial microbial abundance and decreasing pathogenic fungi in saline soil. Microbial biochars (BF and BB) positively improved soil properties (physicochemical) and biochemical and physiological properties of plants, ultimately rice growth. SLY138 significantly had a less severe response to salt stress compared to JLY534. The mitigation effects of BB + N120 kg ha−1 were particularly favorable for SLY138. In summary, the combined residual effect of BF and BB with N120 kg ha−1, especially bacterial biochar (BB), played a positive role in alleviating salt stress on rice growth, suggesting its potential utility for enhancing rice yield in paddy fields. Full article
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<p>The residual effect of biochar, microbial-inoculated biochar, and N on soil physicochemical properties for growing conditions of both varieties (<b>A</b>) soil pH, (<b>B</b>) soil organic matter, (<b>C</b>) exchangeable Na<sup>+</sup>, (<b>D</b>) Exchangeable K<sup>+</sup>, (<b>E</b>) NH<sub>4</sub><sup>+</sup>-N accumulation, and (<b>F</b>) NO<sub>3</sub><sup>−</sup>-N accumulation. BC (simple biochar); BF (fungal biochar); BB (bacterial biochar); BF + N (fungal biochar and nitrogen); BB + N (bacterial biochar and nitrogen). The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The residual effect of different biochars and N on Na<sup>+</sup>, K<sup>+</sup>, and K<sup>+</sup>/Na<sup>+</sup> in rice leaves of both varieties; (<b>A</b>) Na<sup>+</sup> content; (<b>B</b>) K<sup>+</sup> content; (<b>C</b>) K<sup>+</sup>/Na<sup>+</sup>. BC (simple biochar); BF (fungal biochar); BB (bacterial biochar); BF + N (fungal biochar and nitrogen); BB + N (bacterial biochar and nitrogen). The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The residual effect of biochars and N on MDA, SOD, POD, and CAT in rice leaves of both varieties: (<b>A</b>) MDA activities, (<b>B</b>) SOD activities, (<b>C</b>) POD activities, and (<b>D</b>) CAT activities. BC (simple biochar); BF (fungal biochar); BB (bacterial biochar); BF + N (fungal biochar and nitrogen); BB + N (bacterial biochar and nitrogen). The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The residual effect of biochars and N on RWC and MSI in rice plants of both varieties, (<b>A</b>) RWC and (<b>B</b>) MSI. BC (simple biochar); BF (fungal biochar); BB (bacterial biochar); BF + N (fungal biochar and nitrogen); BB + N (bacterial biochar and nitrogen). The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The residual effect of Biochars and N on (ΦPSII), (Fv/Fm), (NPQ), and (qP) in rice leaves of both varieties, (<b>A</b>) ΦPSII, (<b>B</b>) Fv/Fm, (<b>C</b>) NPQ, and (<b>D</b>) qP. BC (simple biochar); BF (fungal biochar); BB (bacterial biochar); BF + N (fungal biochar and nitrogen); BB + N (bacterial biochar and nitrogen). The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The residual effect of Biochars and N on CP, VC, xylem width, and total area of root cross-section in rice roots of both varieties, (<b>A</b>) CP (<b>B</b>) VC (<b>C</b>) Xylem width (<b>D</b>) Total area of root cross-section: SLY138 (V1); JLY534 (V2): CP (Cortical parenchyma); VC (Vascular cylinder); BC (simple biochar); BB + N (bacterial biochar and nitrogen); BCS0—rice straw biochar applied into the soil with no salt; BCS1—rice straw biochar applied into the soil irrigated with saline water; BBNS0—bacterial biochar and N applied into the soil with no salt; BBNS1—bacterial biochar and N applied into the soil irrigated with saline water; N-nitrogen applied at the rate of 120 kg ha<sup>−1</sup>. The means that have the same letter do not differ substantially at <span class="html-italic">p</span> &gt; 0.05 for a parameter, significant * (<span class="html-italic">p</span> ≤ 0.05), non-significant (ns; <span class="html-italic">p</span> &gt; 0.05). T (Treatment), S (Salt), V (Variety).</p>
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<p>The ultrastructure of leaf cells in rice seedlings for SLY138 (V1) and JLY534 (V2) (B). S0—0% NaCl; S1—0.4% NaCl; BC—rice straw biochar applied into the soil; BF—Fungal biochar produced applied into the soil; BB—biochar produced applied into the soil; N—nitrogen applied at the rate of 120 kgha<sup>−1</sup>. CW—cell wall; Ch—chloroplast.</p>
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