[go: up one dir, main page]

 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (29,347)

Search Parameters:
Keywords = rural

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 3990 KiB  
Article
Targeted Metabolites and Transcriptome Analysis Uncover the Putative Role of Auxin in Floral Sex Determination in Litchi chinensis Sonn.
by Zhe Chen, Tingting Yan, Farhat Abbas, Mingchao Yang, Xianghe Wang, Hao Deng, Hongna Zhang and Fuchu Hu
Plants 2024, 13(18), 2592; https://doi.org/10.3390/plants13182592 (registering DOI) - 16 Sep 2024
Abstract
Litchi exhibits a large number of flowers, many flowering batches, and an inconsistent ratio of male and female flowers, frequently leading to a low fruit-setting rate. Floral sexual differentiation is a crucial phase in perennial trees to ensure optimal fruit production. However, the [...] Read more.
Litchi exhibits a large number of flowers, many flowering batches, and an inconsistent ratio of male and female flowers, frequently leading to a low fruit-setting rate. Floral sexual differentiation is a crucial phase in perennial trees to ensure optimal fruit production. However, the mechanism behind floral differentiation remains unclear. The objective of the study was to identify the role of auxin in floral differentiation at the transcriptional level. The results showed that the ratio of female flowers treated with naphthalene acetic acid (NAA) was significantly lower than that of the control stage (M0/F0). The levels of endogenous auxin and auxin metabolites were measured in male and female flowers at different stages of development. It was found that the levels of IAA, IAA-Glu, IAA-Asp, and IAA-Ala were significantly higher in male flowers compared to female flowers. Next-generation sequencing and modeling were employed to perform an in-depth transcriptome analysis on all flower buds in litchi ‘Feizixiao’ cultivars (Litchi chinensis Sonn.). Plant hormones were found to exert a significant impact on the litchi flowering process and flower proliferation. Specifically, a majority of differentially expressed genes (DEGs) related to the auxin pathway were noticeably increased during male flower bud differentiation. The current findings will enhance our comprehension of the process and control mechanism of litchi floral sexual differentiation. It also offers a theoretical foundation for implementing strategies to regulate flowering and enhance fruit production in litchi cultivation. Full article
Show Figures

Figure 1

Figure 1
<p>Morphology of litchi flower development and effect of NAA on the ratio of flowers. (<b>A</b>) Pictorial observation of litchi floral bud development. Impact of exogenous NAA application on (<b>B</b>) total number of flowers and (<b>C</b>) ratio of female flowers. CK denotes control. Vertical bars denote standard error of mean of 3 biological replicates; differences at significance of <span class="html-italic">p</span> &lt; 0.01 are denoted by double asterisks (**).</p>
Full article ">Figure 2
<p>Expression analysis of auxin-related metabolites measured in litchi flowers during different developmental stages. (<b>A</b>) Heatmap and (<b>B</b>) K-mean cluster analysis of auxin-related metabolites detected during flower bud development. Data are denoted as the SEM of three biological replicates.</p>
Full article ">Figure 3
<p>Endogenous content of auxins during different phases of male and female flower development. The contents were measured by LC-MS/MS. The data are denoted by SEM of three biological replicates. IAA; Indole-3-acetic acid, IPA; 3-Indolepropionic acid, TRP; L-tryptophan, IAA-Glu; Indole-3-acetyl glutamic acid, IAA-Asp; Indole-3-acetyl-L-aspartic acid, IAA-Ala; N-(3-Indolylacetyl)-L-alanine.</p>
Full article ">Figure 4
<p>Auxin substantially influences the expression of genes during flower bud development. (<b>A</b>) Total number of DEGs. (<b>B</b>) UpSet R plot indicating the number of unique DEGs detected during different litchi flower development. Number of upregulated (<b>C</b>) and downregulated (<b>D</b>) DEGs denoted in Venn diagram.</p>
Full article ">Figure 5
<p>K-means Cluster analysis of DEGs obtained from the litchi floral bud development transcriptome dataset. The black line in the cluster represents the average expression pattern of DEGs.</p>
Full article ">Figure 6
<p>GO and KEGG analysis of DEGs during litchi floral bud development. GO classification among the (<b>A</b>) M0/F0 vs. F1, (<b>B</b>) M0/F0 vs. M1, and (<b>C</b>) F1 vs. M1 comparisons. MF, CC, and MF are denoted in red, green, and blue colors, respectively. BP; biological process, MF; molecular function, CC; cellular component. KEGG analysis of DEGs among the (<b>D</b>) M0/F0 vs. F1, (<b>E</b>) M0/F0 vs. M1, and (<b>F</b>) F1 vs. M1 comparisons.</p>
Full article ">Figure 7
<p>A depiction of DEGs found in the GO and KEGG databases, as well as DEGs related to auxin metabolism and signaling. (<b>A</b>) The DEGs found in GO and (<b>B</b>) KEGG pathways, including both upregulated and downregulated genes. (<b>C</b>) Heatmap showing the expression levels of auxin biosynthesis and (<b>D</b>) signaling-related genes identified in DEGs. The color scheme used in this study represents different levels of gene expression. Blue represents low expression, white indicates no specific pattern of expression, and red indicates high expression.</p>
Full article ">Figure 8
<p>The relative expression of YUC and IAA class genes throughout male and female flower development. Key DEGs associated with floral sexual differentiation. Actin was used as an endogenous control. Data are presented as the mean ± SEM (<span class="html-italic">n</span> = 3). The relative expression levels of target genes were calculated via the 2<sup>−ΔΔCt</sup> method.</p>
Full article ">Figure 9
<p>The relative expression of genes associated with androecium or gynoecium development. Actin was used as an endogenous control. Data are presented as the mean ± SEM (n = 3). The relative expression levels of target genes were calculated via the 2<sup>−ΔΔCt</sup> method.</p>
Full article ">
14 pages, 6303 KiB  
Article
The Integrated Analysis of miRNome and Degradome Sequencing Reveals the Regulatory Mechanisms of Seed Development and Oil Biosynthesis in Pecan (Carya illinoinensis)
by Kaikai Zhu, Lu Wei, Wenjuan Ma, Juan Zhao, Mengyun Chen, Guo Wei, Hui Liu, Pengpeng Tan and Fangren Peng
Foods 2024, 13(18), 2934; https://doi.org/10.3390/foods13182934 - 16 Sep 2024
Abstract
Pecan seed oil is a valuable source of essential fatty acids and various bioactive compounds; however, the functions of microRNAs and their targets in oil biosynthesis during seed development are still unknown. Here, we found that the oil content increased rapidly in the [...] Read more.
Pecan seed oil is a valuable source of essential fatty acids and various bioactive compounds; however, the functions of microRNAs and their targets in oil biosynthesis during seed development are still unknown. Here, we found that the oil content increased rapidly in the three early stages in three cultivars, and that oleic acid was the predominant fatty acid component in the mature pecan embryos. We identified, analyzed, and validated the expression levels of miRNAs related to seed development and oil biosynthesis, as well as their potential target genes, using small RNA sequencing data from three stages (120, 135, and 150 days after flowering). During the seed development process, 365 known and 321 novel miRNAs were discovered. In total, 91 known and 181 novel miRNAs were found to be differentially expressed, and 633 target genes were further investigated. The expression trend analysis revealed that the 91 known miRNAs were classified into eight groups, approximately two-thirds of which were up-regulated, whereas most novel miRNAs were down-regulated. The qRT–PCR and degradome sequencing data were used to identify five miRNA- target pairs. Overall, our study provides valuable insights into the molecular regulation of oil biosynthesis in pecan seeds. Full article
(This article belongs to the Section Foodomics)
Show Figures

Figure 1

Figure 1
<p>Oil content and fatty acid composition in developing pecan embryos. (<b>A</b>) Observation of morphological characteristics during five stages of pecan seed development. Bar = 1 cm. (<b>B</b>) Oil contents of seed samples at five stages from three pecan cultivars. (<b>C</b>) Changes in fatty acid composition at different stages in pecan embryos. c16:0, palmitic acid; c16:1, palmitoleic acid; c18:0, stearic acid; c18:1, oleic acid; c18:2, linoleic acid; c18:3n3, α-Linolenic acid; c18:3n6, γ-Linolenic acid; and c20:1, Eicosenoic acid.</p>
Full article ">Figure 2
<p>Length distribution of small RNA from the seeds of the ‘Pawnee’ cultivar of pecan at three developmental stages.</p>
Full article ">Figure 3
<p>Composition of the small RNA in nine libraries.</p>
Full article ">Figure 4
<p>Differentially expressed miRNAs in three developmental stages of pecan seeds. (<b>A</b>) The number of the known DEMs between the different groups. (<b>B</b>) The number of novel DEMs between the different groups. (<b>C</b>) Venn diagrams of the known DEMs. (<b>D</b>) Venn diagrams of the novel DEMs.</p>
Full article ">Figure 5
<p>Expression trends of known DEMs in three developmental stages of pecan seeds. The number of DEMs in each group is listed at the top of each group.</p>
Full article ">Figure 6
<p>qRT–PCR validation of miRNAs during three stages of seed development in pecan seeds. Values are means ± SE of three replicates, and bars with different letters were significantly different at <span class="html-italic">p</span> &lt; 0.05 using Duncan’s multiple range test.</p>
Full article ">Figure 7
<p>Validation of the target genes during three stages of seed development in pecan, showing the expression patterns of five candidate target genes and a prediction of the binding sites of miRNAs in targets using the psRNA Target. Values are means ± SE of three replicates, and bars with different letters were significantly different at <span class="html-italic">p</span> &lt; 0.05 using Duncan’s multiple range test.</p>
Full article ">
15 pages, 2896 KiB  
Article
Guard Band Protection Scheme to Facilitate Coexistence of 5G Base Stations and Radar Altimeters
by Jiaqi Li and Seung-Hoon Hwang
Electronics 2024, 13(18), 3681; https://doi.org/10.3390/electronics13183681 - 16 Sep 2024
Abstract
Reformation of the 3.7–4.0 GHz band to expand 5G communication deployment poses a risk of 5G signals disrupting radar altimeter operation, leading to data loss or inaccuracies. Thus, this paper proposes a guard band protection method to facilitate the coexistence of 5G base [...] Read more.
Reformation of the 3.7–4.0 GHz band to expand 5G communication deployment poses a risk of 5G signals disrupting radar altimeter operation, leading to data loss or inaccuracies. Thus, this paper proposes a guard band protection method to facilitate the coexistence of 5G base stations and radar altimeters operating in the 4.2–4.4 GHz band. To enhance the adjacent channel leakage ratio (ACLR), we implemented spectral regrowth on an oversampled waveform using a high-power amplifier model, filtering out-of-band spectral emissions. The results demonstrated that a 150 MHz guard band enables coexistence, except in the case of the 16-by-16 antenna array in rural environments. Notably, for the 4-by-4 antenna array in urban environments, coexistence can be achieved using a 50 MHz guard band. The proposed mitigation techniques may also be extended to promote coexistence between non-terrestrial networks and 5G communication systems, including satellites, unmanned aerial vehicles, and hot air balloons. Full article
(This article belongs to the Special Issue 5G/B5G/6G Wireless Communication and Its Applications)
Show Figures

Figure 1

Figure 1
<p>3GPP and mid-band spectrum with the radar altimeter band [<a href="#B4-electronics-13-03681" class="html-bibr">4</a>].</p>
Full article ">Figure 2
<p>5G emissions as a function of the radar altimeter band [<a href="#B5-electronics-13-03681" class="html-bibr">5</a>].</p>
Full article ">Figure 3
<p>Guard band protection.</p>
Full article ">Figure 4
<p>NR spectrum with 100 MHz channel bandwidth: (<b>a</b>) before filtering and (<b>b</b>) after filtering.</p>
Full article ">Figure 5
<p>Process flow of ACLR measurement with filter design.</p>
Full article ">Figure 6
<p>Adjacent channel selectivity of the radar altimeter.</p>
Full article ">Figure 7
<p>Adjacent channel interference ratio vs. guard band.</p>
Full article ">Figure 8
<p>CDF of interference-to-noise ratio in the rural environment with: (<b>a</b>) 4-by-4; (<b>b</b>) 8-by-8; and (<b>c</b>) 16-by-16 antenna arrays.</p>
Full article ">Figure 9
<p>CDF of interference-to-noise ratio in the suburban environment with: (<b>a</b>) 4-by-4; (<b>b</b>) 8-by-8; and (<b>c</b>) 16-by-16 antenna arrays.</p>
Full article ">Figure 10
<p>CDF of interference-to-noise ratio in the urban environment with: (<b>a</b>) 4-by-4; (<b>b</b>) 8-by-8; and (<b>c</b>) 16-by-16 antenna arrays.</p>
Full article ">
18 pages, 14147 KiB  
Article
Evolution Process and Land Use/Land Cover Response of Urban–Rural Space in Wuhan under Polycentric Structure
by Jisheng Yan and Jing Ye
Land 2024, 13(9), 1502; https://doi.org/10.3390/land13091502 - 16 Sep 2024
Abstract
Polycentric development facilitates urban–rural spatial reshaping and land use/land cover (LULC) protection. Previous studies have predominantly focused on urban areas, with spatial delineation methods biased towards the macro-level, lacking a holistic perspective that situates them within the urban–rural spatial framework. This study proposes [...] Read more.
Polycentric development facilitates urban–rural spatial reshaping and land use/land cover (LULC) protection. Previous studies have predominantly focused on urban areas, with spatial delineation methods biased towards the macro-level, lacking a holistic perspective that situates them within the urban–rural spatial framework. This study proposes a spatial delineation framework that is applicable to the polycentric structure, taking into account the social, economic, and natural characteristics of urbanization. It employs semivariance analysis and spatial continuous wavelet transform (SCWT) to analyze the effects of polycentric development on the urban–rural space of Wuhan from 2012 to 2021 and applies a land use transition matrix, landscape indices, and bivariate spatial autocorrelation to quantify the responses and differences of LULC within urban–rural space. The results indicate that 600m×600m is the best scale for exhibiting the multidimensional characterization of urbanization. The polycentric structure alleviates the compact development of the central city, and it drives rapid expansion at the urban–rural fringe, exacerbating the spatial heterogeneity in LULC change pattern, spatial configuration, and urbanization response within urban–rural spaces. The overall effects of urbanization on LULC are relatively weak along the urban–rural gradient, experiencing a transition from positive to negative and back to positive. This study employs a novel spatial delineation framework to depict the polycentric transformation of metropolitan areas and provides valuable insights for regional planning and ecological conservation in the urban–rural fringe. Full article
(This article belongs to the Special Issue Rural–Urban Gradients: Landscape and Nature Conservation II)
Show Figures

Figure 1

Figure 1
<p>Location of the study area.</p>
Full article ">Figure 2
<p>Workflow of the methods.</p>
Full article ">Figure 3
<p>Urbanization attributes at different sizes.</p>
Full article ">Figure 4
<p>Using mutation detection to divide urban–rural space. (<b>a</b>) Spatial distribution of the corrected mutation point groups. (<b>b</b>) Variance curve of SCWT coefficients at different scales.</p>
Full article ">Figure 5
<p>Urban–rural spatial distribution in Wuhan from 2012 to 2021.</p>
Full article ">Figure 6
<p>Polycentric expansion process in Wuhan from 2012 to 2021. (<b>a</b>) Spatial distribution of urban–rural fringe in different urban districts. (<b>b</b>) Directional expansion of urban area and urban–rural fringe.</p>
Full article ">Figure 7
<p>Spatiotemporal dynamics of LULC in urban–rural space. (<b>a</b>) Transform of LULC in urban–rural space. (<b>b</b>) Spatial configuration of LULC in urban–rural space. The unit of transfer area for LULC is km<sup>2</sup>.</p>
Full article ">Figure 8
<p>Effects and distributions of urbanization on the ecological risk of LULC.</p>
Full article ">Figure 9
<p>Comparison with other spatial division methods in polycentric structure. (<b>a</b>) Extraction results by the clustering method. (<b>b</b>) Extraction results by the threshold method. (<b>c</b>) The overlay comparison for the clustering model. Boxes 1 and 2 display enlarged areas from the remote sensing images. (<b>d</b>) The overlay comparison for the threshold model. Boxes 3 and 4 display enlarged areas from the remote sensing images. (<b>e</b>) Local remote sensing image. Subfigures (<b>e-1</b>–<b>e-4</b>) correspond to the remote sensing images associated with these boxes.</p>
Full article ">Figure 10
<p>Urban–rural spatial evolution in Wuhan from 2012 to 2021.</p>
Full article ">Figure 11
<p>Change and response curves of LULC along the urban–rural gradient. The curves indicate the change trends and magnitudes of LULC; the arrows indicate the temporal change of LULC. Yellow, blue, and green represent PLAND, PD, and AI, respectively; upward and downward arrows signify that the trend continues, with values increasing or decreasing.</p>
Full article ">
17 pages, 6206 KiB  
Article
Do Regional Integration Policies Promote Integrated Urban–Rural Development? Evidence from the Yangtze River Delta Region, China
by Jiaqing Zhang, Ziyan Chen, Biqiao Hu and Daolin Zhu
Land 2024, 13(9), 1501; https://doi.org/10.3390/land13091501 - 16 Sep 2024
Abstract
Regional integration policies play a crucial role in promoting coordinated regional development. However, it remains unclear whether the polices simultaneously take into account urban–rural integration to achieve a dynamic balance between efficiency and equity. Based on socioeconomic data from 250 cities in China [...] Read more.
Regional integration policies play a crucial role in promoting coordinated regional development. However, it remains unclear whether the polices simultaneously take into account urban–rural integration to achieve a dynamic balance between efficiency and equity. Based on socioeconomic data from 250 cities in China between 2003 and 2019, we used a staggered difference-in-difference method to investigate the impact of the strategy for the integrated development of the Yangtze River Delta (YD integrated development) on integrated urban–rural development. Our results indicate that the YD integrated development effectively promotes integrated urban–rural development and this conclusion holds after conducting various robustness tests and heterogeneity analyses. Additionally, the YD integrated development can facilitate integrated urban–rural development through the following three main pathways: promoting economic growth, improving road transport links, and advancing technological progress. This paper offers new insights for advancing integrated urban–rural development. The next step could involve the further exploration of the connections between external regional integration policies and internal rural reforms, which will contribute to expediting the establishment of an integrated urban–rural pattern. Full article
Show Figures

Figure 1

Figure 1
<p>Theoretical mechanism between regional integration policies and integrated urban–rural development.</p>
Full article ">Figure 2
<p>Study region and sample distribution.</p>
Full article ">Figure 3
<p>Parallel trend and dynamic effect test results.</p>
Full article ">Figure 4
<p>Placebo effect test.</p>
Full article ">
17 pages, 4553 KiB  
Article
Biological Decline of Alfalfa Is Accompanied by Negative Succession of Rhizosphere Soil Microbial Communities
by Yuanyuan Ma, Yan Shen, Xiaoping Zhou, Hongbin Ma, Jian Lan, Bingzhe Fu and Quanhong Xue
Plants 2024, 13(18), 2589; https://doi.org/10.3390/plants13182589 - 16 Sep 2024
Abstract
The growth and biological decline of alfalfa may be linked to the rhizosphere microbiome. However, plant–microbe interactions in the rhizosphere of alfalfa and associated microbial community variations with stand age remain elusive. This study explored the successional pattern of rhizosphere microbial communities across [...] Read more.
The growth and biological decline of alfalfa may be linked to the rhizosphere microbiome. However, plant–microbe interactions in the rhizosphere of alfalfa and associated microbial community variations with stand age remain elusive. This study explored the successional pattern of rhizosphere microbial communities across different aged alfalfa stands and its relationship with alfalfa decline. Rhizosphere soils were collected from 2- and 6-year-old alfalfa stands. Control soils were collected from interspaces between alfalfa plants in the same stands. Soil bacterial and fungal communities were characterized by 16S and ITS rRNA gene sequencing, respectively. Specific microbial taxa colonized the rhizosphere soils, but not the control soils. The rhizosphere-specific taxa mainly included potentially beneficial genera (e.g., Dechloromonas, Verrucomicrobium) in the young stand and harmful genera (e.g., Peziza, Campylocarpon) in the old stand. Alfalfa roots regulated soil microbial communities by selective promotion or inhibition of distinct taxa. The majority of time-enriched taxa were reported as harmful fungi, whose relative abundances were negatively correlated with plant traits. Time-depleted taxa were mostly known as beneficial bacteria, which had relative abundances positively correlated with plant traits. The relative abundances of functional bacterial genes associated with vancomycin biosynthesis, zeatin biosynthesis, and amino acid metabolism trended lower in rhizosphere soils from the old stand. An upward trend was observed for fungal pathogens and wood saprotrophs with increasing stand age. The results suggest that root activity drives the negative succession of rhizosphere microbial communities during alfalfa decline in old stands. Full article
(This article belongs to the Section Plant–Soil Interactions)
Show Figures

Figure 1

Figure 1
<p>Soil microbial community diversity in alfalfa stands of different ages: (<b>a</b>,<b>b</b>) Principal coordinates analysis of bacterial and fungal β-diversity based on Bray–Curtis distance. (<b>c</b>,<b>d</b>) α-Diversity indices of bacteria. (<b>e</b>,<b>f</b>) α-Diversity indices of fungi. 2R and 2C are rhizosphere soils from the 2-year-old alfalfa stand and corresponding control soils, respectively; 6R and 6C are rhizosphere soils from the 6-year-old alfalfa stand and corresponding control soils, respectively. Error bars represent the standard deviation of the means (n = 3). * indicates a significant difference in α-diversity between rhizosphere and control soils (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>Microbial taxa enriched in the rhizosphere soil of alfalfa: (<b>a</b>) Number of operational taxonomic units (right) and taxonomy of genera (left) in the rhizosphere-specific bacterial community. (<b>b</b>) Number of operational taxonomic units (left) and taxonomy of genera (right) in the rhizosphere-specific fungal community. The blue color indicates genera with a higher relative abundance in rhizosphere soils from the 2-year-old alfalfa stand (2R) than in the corresponding control soils (2C), and the red color indicates genera with a higher relative abundance in rhizosphere soils from the 6-year-old alfalfa stand (6R) than in the corresponding control soils (6C).</p>
Full article ">Figure 3
<p>The selection of rhizosphere soil bacteria by root activity of alfalfa. Log<sub>10</sub> fold changes in the relative abundance of the top 20 bacterial (<b>a</b>) phyla and (<b>b</b>) genera. 2R vs. 2C indicates the comparison group between rhizosphere soils from the 2-year-old alfalfa stand and corresponding control soils; 6R vs. 6C indicates the comparison group between rhizosphere soils from the 6-year-old alfalfa stand and corresponding control soils. * indicates a significant difference in taxa relative abundance between rhizosphere and control soils (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>The selection of rhizosphere soil fungi by root activity of alfalfa. Log<sub>10</sub> fold changes in the relative abundance of the nine fungal (<b>a</b>) phyla and (<b>b</b>) the top 19 most abundant genera. 2R vs. 2C indicates the comparison group between rhizosphere soils from the 2-year-old alfalfa stand and corresponding control soils; 6R vs. 6C indicates the comparison group between rhizosphere soils from the 6-year-old alfalfa stand and corresponding control soils. * indicates a significant difference in taxa relative abundance between rhizosphere and control soils (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>Relative abundances of time-enriched (<b>a</b>), time-depleted (<b>b</b>), pathogenic (<b>c</b>), and beneficial (<b>d</b>) microbial taxa in the rhizosphere soil of alfalfa. 2R and 2C represent rhizosphere soils from the 2-year-old alfalfa stand and corresponding control soils, respectively; 6R and 6C represent rhizosphere soils from the 6-year-old alfalfa stand and corresponding control soils, respectively. Error bars represent the standard deviation of the means (n = 3).</p>
Full article ">Figure 6
<p>Functional shifts of rhizosphere bacterial (<b>a</b>) and fungal (<b>b</b>) communities associated with alfalfa. 2R and 2C denote rhizosphere soils from the 2-year-old alfalfa stand and corresponding control soils, respectively; 6R and 6C represent rhizosphere soils from the 6-year-old alfalfa stand and corresponding control soils, respectively.</p>
Full article ">Figure 7
<p>Correlation heatmaps between rhizosphere microbial taxa and plant traits of alfalfa: (<b>a</b>) Rhizosphere-specific taxa; (<b>b</b>) Time-dependent taxa. 2R and 6R denote rhizosphere soils from the 2- and 6-year-old alfalfa stands, respectively. CP, crude protein; EE, ester extract; CF, crude fiber; NDF, neutral detergent fiber; ADF, acid detergent fiber; L/S, leaf-to-stem ratio. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">
15 pages, 12690 KiB  
Article
The Liver-Protective Effects of the Essential Oil from Amomum villosum in Tilapia (Oreochromis niloticus): Antioxidant, Transcriptomic, and Metabolomic Modulations
by Hongbiao Dong, Xiangbing Zeng, Xiaoting Zheng, Chenghui Li, Junchao Ming and Jiasong Zhang
Antioxidants 2024, 13(9), 1118; https://doi.org/10.3390/antiox13091118 - 16 Sep 2024
Viewed by 11
Abstract
This study investigates the effects of the essential oil from Amomum villosum (EOA) on liver-protective effects in Nile tilapia (Oreochromis niloticus), utilizing a multidisciplinary approach that integrates physiological assessments and transcriptomic and metabolomic analyses. Fish were fed diets containing 2 g/kg [...] Read more.
This study investigates the effects of the essential oil from Amomum villosum (EOA) on liver-protective effects in Nile tilapia (Oreochromis niloticus), utilizing a multidisciplinary approach that integrates physiological assessments and transcriptomic and metabolomic analyses. Fish were fed diets containing 2 g/kg of EOA over a 56-day trial, with a no-EOA diet serving as the control. The results demonstrate that EOA supplementation improves liver histology, enhances antioxidant capacities, and reduces inflammation in tilapia. The transcriptomic analysis revealed significant alterations in gene expression profiles related to RNA splicing, metabolism, and disease pathways. The identification of differential genes and disease databases identified key target genes associated with the primary component of EOA for its anti-hepatobiliary disease effects. Furthermore, a molecular docking analysis of EOA major components with core differentially expressed genes in the hepatobiliary syndrome indicated that α-pinene is a potential Hsp90 inhibitor, which may prevent inflammation. A metabolomic analysis further demonstrated that EOA supplementation leads to notable changes in liver phospholipids, fatty acids, and carbohydrate metabolism. These findings underscore the potential of EOA as a natural additive for improving liver health in tilapia, offering valuable insights to the aquaculture industry for enhancing fish health and welfare in intensive farming systems. Full article
(This article belongs to the Section Natural and Synthetic Antioxidants)
Show Figures

Figure 1

Figure 1
<p>Effects of dietary EOA on the liver histological structure (HE staining, ×200) and physiological indicators of tilapia. (<b>A</b>) Liver histological structure in CON, (<b>B</b>) liver histological structure in EOA, (<b>C</b>) antioxidant parameters, (<b>D</b>) inflammatory factors. * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 2
<p>Effects of dietary EOA on the transcriptomes in tilapia livers. (<b>A</b>) Volcano plot of DEGs. (<b>B</b>) GO functional analysis of DEGs. (<b>C</b>) KEGG enrichment analysis of DEGs. (<b>D</b>) Connectivity between KEGG pathways. (<b>E</b>) Interactive pathway analysis of DEGs in livers of tilapia after dietary EOA. Red lines indicate the enriched metabolic pathways.</p>
Full article ">Figure 3
<p>Analysis of the direct effects of EOA on hepatobiliary disease targets. (<b>A</b>) Venn plot of DEGs in transcriptome and hepatobiliary disease targets obtained from disease databases; HBSs, hepatobiliary disease targets; DEGs, differentially expressed genes. (<b>B</b>) Results of a PPI analysis using 113 EOA direct-effecting target proteins. (<b>C</b>) Degree node connectivity of the top 20 targets in the PPI network. Higher degrees indicate that these targets interact more strongly with other targets. (<b>D</b>) Gene expression heatmap of the top 20 degree node connectivity. (<b>E</b>) Results of a KEGG enrichment analysis of 113 EOA direct-effecting target genes. (<b>F</b>) Results of a GO functional analysis of 113 EOA direct-effecting target genes.</p>
Full article ">Figure 4
<p>Molecular docking scoring heatmap of EOA active ingredients and top 5 targets (binding energy/kJ·mol<sup>−1</sup>).</p>
Full article ">Figure 5
<p>The conformational interoperability mode for docking α-pinene with targets. (<b>A</b>) Sec61a. (<b>B</b>) Hsp90b1. (<b>C</b>) Gapdh. (<b>D</b>) Ccna2. (<b>E</b>) Top2a; from left to right is the overall 3D, partial 3D, and partial 2D constructure, respectively. In 2D interactions, dotted green lines denote a hydrophobic force.</p>
Full article ">Figure 6
<p>Metabolomic alterations by dietary EOA in the livers of <span class="html-italic">O. niloticus</span>. (<b>A</b>) PLS-DA score plot. (<b>B</b>) OPLS-DA score plot. (<b>C</b>) Volcano plot of DMs. (<b>D</b>) Heatmap of DMs. (<b>E</b>) KEGG pathway analysis of DMs.</p>
Full article ">Figure 7
<p>Visualization and interpretation of metabolisms of sugars and expressions of relevant genes.</p>
Full article ">
14 pages, 965 KiB  
Article
Evaluation of Agronomic Traits, Total Phenolic Content, and Antioxidant Properties of Sesame Seeds of Different Colors and Origin
by Collins Yeboah Osei, Sookyeong Lee, Gi-An Lee, Sae Hyun Lee, Eunae Yoo, Jae-Eun Lee, Eun-Gyeong Kim and Tae-Jin Yang
Foods 2024, 13(18), 2932; https://doi.org/10.3390/foods13182932 - 16 Sep 2024
Viewed by 60
Abstract
Rising health concerns regarding chronic diseases call for exploring natural sources of antioxidants and factors that influence their activity. This study evaluated the diversity of 112 sesame germplasms from Africa and Asia based on ten agronomic traits (seven quantitative and three qualitative), two [...] Read more.
Rising health concerns regarding chronic diseases call for exploring natural sources of antioxidants and factors that influence their activity. This study evaluated the diversity of 112 sesame germplasms from Africa and Asia based on ten agronomic traits (seven quantitative and three qualitative), two antioxidant activities (ABTS and DPPH radical scavenging activities), and the content of one metabolite (TPC). TPC, DPPH, and ABTS were in the ranges of 4.98–87.88 µg GAE/mg DE, 3.97–46.23 µg AAE/mg DE, and 3.42–176.01 µg TE/mg DE, respectively. Statistical analyses revealed significant variations in agronomic traits, TPC, and antioxidant activities among the sesame germplasms (p < 0.05). Furthermore, the individual and interaction effects of seed color and the continent of origin on the levels of the quantitative traits, TPC, ABTS, and DPPH were analyzed, and the correlation among the traits was further evaluated. Diversity in TPC, ABTS, and DPPH was significantly associated with seed color and most of the quantitative agronomic traits (p < 0.05) but not with continent of origin. Principal component analysis revealed TPC, ABTS, DPPH, and five quantitative traits as the most discriminant traits. In general, six sesame accessions with high TPC and antioxidant activities (IT194356, IT170094, IT29971, IT185998, IT104246, and IT169623) as well as important agronomic traits were identified and, hence, could be used for developing improved sesame varieties. Full article
(This article belongs to the Special Issue Advances on Functional Foods with Antioxidant Bioactivity)
Show Figures

Figure 1

Figure 1
<p>Heatmap of two-way hierarchical cluster analysis of sesame accessions based on continent, seed color, TPC, antioxidant activities, and quantitative agronomic traits. BLK: black, BRN: brown, LB: light brown, OLV: olive, WHT: white.</p>
Full article ">Figure 2
<p>Variable PCA biplot (<b>a</b>), score plot of sesame accessions according to continent (<b>b</b>) and seed colors (<b>c</b>), and hierarchical clustering principal component (HCPC) biplot based on quantitative traits, TPC, ABTS, and DPPH (<b>d</b>).</p>
Full article ">Figure 3
<p>Correlation matrix showing the relationship among quantitative agronomic traits, TPC, and antioxidant activities of sesame; ***, **, *: significant at 0.001, 0.01, and 0.05, respectively, ns: not significant.</p>
Full article ">
18 pages, 736 KiB  
Review
Hegemony and Colonialization in the Water Management Sector: Issues and Lessons for IWRM
by Neil Grigg
Water 2024, 16(18), 2624; https://doi.org/10.3390/w16182624 - 16 Sep 2024
Viewed by 90
Abstract
Water resources management and the broad concept of Integrated Water Resources Management (IWRM) attract varied perspectives about their effectiveness and equity as they address diverse needs across sectors and contextual situations. Managers in the water sector generally support their current governance models, while [...] Read more.
Water resources management and the broad concept of Integrated Water Resources Management (IWRM) attract varied perspectives about their effectiveness and equity as they address diverse needs across sectors and contextual situations. Managers in the water sector generally support their current governance models, while anti-poverty advocates seek more equity in the distribution of resources. Another group of stakeholders claims a lack of inclusivity in decision-making, leading to inequitable outcomes due to hegemony and colonialization of the water management domain by sector experts, officials, and other actors. IWRM focuses on reforms in water governance to achieve greater participation and sharing of power by all sectors of society in decision-making. It can facilitate the involvement of all groups of stakeholders, including those who may in some cases need to engage in social action to address water issues. This paper reviews the claims about the validity of IWRM and analyzes them according to management scenarios where water is a connector among sector issues. The scenarios show that participation in utility and local government decisions is the main pathway for urban water, wastewater, and stormwater management, while the same pathway is more difficult to organize in dispersed situations for domestic supply and irrigation in rural areas, some cases of aquifer management, and management of sprawling flood risk zones. The body of knowledge about participation in water resources management is robust, but organizational and financial capacities among existing entities pose barriers. Water resources management and IWRM do involve hegemony, and the field of practice has been colonialized, but the existential issues and complexity of the decisions and systems involved challenge society to manage successfully while assuring equity and participation through governance reform. The debates over hegemony and colonialization in water management provide an opportunity to continue improving the norms of practice and water resources education. Full article
Show Figures

Figure 1

Figure 1
<p>Varied settings of water resources management.</p>
Full article ">Figure 2
<p>Stakeholder group alignment by governance and priorities.</p>
Full article ">Figure 3
<p>Hierarchy of water needs with management scenarios.</p>
Full article ">
14 pages, 662 KiB  
Article
Effect of Dietary Standardized Ileal Digestible Arginine to Lysine Ratio on Reproductive Performance, Plasma Biochemical Index, and Immunity of Gestating Sows
by Xiaolu Wen, Zongyong Jiang, Xuefen Yang, Hao Xiao, Kaiguo Gao and Li Wang
Animals 2024, 14(18), 2688; https://doi.org/10.3390/ani14182688 - 15 Sep 2024
Viewed by 270
Abstract
The aim of this study was to determine the optimal SID Arg: Lys ratio for maximizing the reproductive performance, immunity and biochemical parameters of sows during gestation, the colostrum composition, and the performance of their offspring. A total of 174 multiparous sows were [...] Read more.
The aim of this study was to determine the optimal SID Arg: Lys ratio for maximizing the reproductive performance, immunity and biochemical parameters of sows during gestation, the colostrum composition, and the performance of their offspring. A total of 174 multiparous sows were randomly allocated to five treatment groups varying in dietary SID Arg: Lys ratios (0.91, 1.02, 1.14, 1.25 and 1.38) through modification of the levels of Arg or alanine supplementation (the total level of nitrogen was the same in all treatments). The results showed that increasing the dietary SID Arg: Lys ratio increased the number of piglets born alive (p < 0.05, linear and quadratic). The number of stillborn piglets, the birth weight variation of born alive piglets, the birth interval (p < 0.05, linear and quadratic) and the number of mummies (p < 0.05, quadratic) reduced with increasing the dietary SID Arg: Lys ratio. Broken-line regression analysis indicated that the optimal SID Arg: Lys ratio requirement for gestating sows to maximize the number of piglets born alive was 1.25. The content of non-fat solid, total solid, protein, and energy in colostrum increased linearly and quadratically (p < 0.05) with increasing dietary SID Arg: Lys ratio. Additionally, when increasing the dietary SID Arg: Lys ratio, the concentration of IgA (p < 0.05, quadratic) and IgM (p < 0.05, linear and quadratic) of plasma increased at day 90 of gestation; IgG (p < 0.05, linear and quadratic) concentration increased at day 110 of gestation of sows. The dietary SID Arg: Lys ratio had an increasing effect (p < 0.05, linear and quadratic) on plasma insulin levels at day 90 of gestation. Furthermore, there were increases in plasma concentrations of nitric oxide and ornithine at day 110 of gestation, Arg at day 90 and 110 of gestation (p < 0.05, linear and quadratic) and total protein at day 110 of gestation (p < 0.05, linear) with increasing dietary SID Arg: Lys ratio. The results of our study indicated that increases in the dietary SID Arg: Lys ratio during gestation resulted in an increase in the number of piglets born alive, a decrease in birth intervals, and an improvement in immunity and colostrum composition. The optimal SID Arg: Lys ratio for gestating sows to maximize the number of piglets born alive was 1.25. Full article
(This article belongs to the Section Animal Nutrition)
Show Figures

Figure 1

Figure 1
<p>Fitted straight broken-line and quadratic broken-line regression models on the number of born alive piglets as a function of increasing standardized ileal digestible (SID) Arg: Lys in gestating sows. The optimum SID Arg: Lys ratio determined by straight broken-line model was 1.25 [Y = 12.181 − 6.1628 (1.25-SID Arg: Lys ratio) (closed line); R<sup>2</sup> = 0.963, <span class="html-italic">p</span> &lt; 0.05]. Using the quadratic broken-line model, the optimum SID Arg: Lys ratio was 1.39 [Y = 12.2198 − 9.8062 × (1.39 − SID Arg: Lys)<sup>2</sup> (open line); R<sup>2</sup> = 0.895, <span class="html-italic">p</span> &lt; 0.05]. Data points (●) represent treatment means (n = 35, 34, 35, 36, 33).</p>
Full article ">Figure 2
<p>Fitted straight broken-line and quadratic broken-line regression models on the litter weight of born alive piglets as a function of increasing standardized ileal digestible (SID) Arg: Lys in gestating sows. The optimum SID Arg: Lys ratio determined by straight broken-line model was 1.25 [Y = 17.1289 − 9.1486 (1.25 − SID Arg: Lys ratio) (closed line); R<sup>2</sup> = 0.92687, <span class="html-italic">p</span> &lt; 0.05]. Using the quadratic broken-line model, the optimum SID Arg: Lys ratio was 1.44, [Y = 17.3295 − 12.0702 × (1.44 − SID Arg: Lys)<sup>2</sup> (open line); R<sup>2</sup> = 0.8593, <span class="html-italic">p</span> &lt; 0.05]. Data points (●) represent treatment means (n = 35, 34, 35, 36, 33).</p>
Full article ">
19 pages, 10340 KiB  
Article
Features of Temporal Variability of the Concentrations of Gaseous Trace Pollutants in the Air of the Urban and Rural Areas in the Southern Baikal Region (East Siberia, Russia)
by Maxim Y. Shikhovtsev, Yelena V. Molozhnikova, Vladimir A. Obolkin, Vladimir L. Potemkin, Evgeni S. Lutskin and Tamara V. Khodzher
Appl. Sci. 2024, 14(18), 8327; https://doi.org/10.3390/app14188327 (registering DOI) - 15 Sep 2024
Viewed by 349
Abstract
This article presents the results of the automatic monitoring of the concentrations of gaseous impurities of sulfur and nitrogen oxides in the ground-level atmosphere of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). The study was conducted from [...] Read more.
This article presents the results of the automatic monitoring of the concentrations of gaseous impurities of sulfur and nitrogen oxides in the ground-level atmosphere of the urban and rural areas in the Southern Baikal region (East Siberia, Russia). The study was conducted from 2020 to 2023 at the urban Irkutsk station and the rural Listvyanka station located at a distance of 70 km from each other. We calculated the main statistical characteristics of the variations in the concentrations of nitrogen oxides and sulfur dioxide in the ground-level atmosphere and determined a nature of variability in their concentrations on various time scales: annual, weekly, and daily. Annual variabilities of gaseous pollutants in the ground-level atmosphere above the Irkutsk city and the Listvyanka settlement were similar and showed the highest values in winter and the lowest in summer. The daily and weekly dynamics of the nitrogen oxide concentrations in the urban area clearly depended on the increase in the road traffic during rush hours (morning and evening). In the rural area, there was no such dependence. In this area, the daily and weekly variability in the concentrations of nitrogen oxides and sulfur dioxide mainly depended on natural meteorological processes. The work systematizes the meteorological parameters at which the largest amount of anthropogenic impurities enters the air basin of Lake Baikal. The maximum values of acid-forming gas concentrations were observed when the air masses were transferred from the northwest direction, which corresponds to the location of sources in the territory of the Irkutsk–Cheremkhovo industrial hub—the largest concentration of anthropogenic objects in the Irkutsk region. Full article
(This article belongs to the Special Issue Air Pollution and Its Impact on the Atmospheric Environment)
Show Figures

Figure 1

Figure 1
<p>Layout of the Irkutsk (IRK) and Listvyanka (LSTV) monitoring stations and the main sources of air pollution in the study region.</p>
Full article ">Figure 2
<p>An example of the accumulation of online monitoring data in the Grafana system on the LIN SB RAS server (Irkutsk).</p>
Full article ">Figure 3
<p>Frequency distribution graphs of 20-minute averaged concentrations of SO<sub>2</sub>, NO, and NO<sub>2</sub> at the Irkutsk and Listvyanka monitoring stations during the heating (blue) and non-heating (red) seasons. The ordinate axis shows the recurrence of the concentrations within a certain range. The abscissa axis shows the pollutant concentration ranges. The data are averaged for 2020–2023.</p>
Full article ">Figure 4
<p>Intra-annual variability of sulfur dioxide (SO<sub>2</sub>) concentrations at the Irkutsk and Listvyanka stations from 2020 to 2023, without atypical values (outliers). The ordinate axis shows the concentrations (µg/m<sup>3</sup>); the abscissa axis shows the month. The diagram shows the median (bold line), the first quartile (lower boundary of the box), and the third quartile (upper boundary of the box).</p>
Full article ">Figure 5
<p>Intra-annual variability of nitrogen dioxide (NO<sub>2</sub>) concentrations at the Irkutsk and Listvyanka stations from 2020 to 2023, without atypical values (outliers). The ordinate axis shows the concentrations (µg/m<sup>3</sup>); the abscissa axis shows the month. The diagram shows the median (bold line), the first quartile (lower boundary of the box), and the third quartile (upper boundary of the box).</p>
Full article ">Figure 6
<p>Intra-annual variability of nitrogen oxide (NO) concentrations at the Irkutsk and Listvyanka stations from 2020 to 2023, without atypical values (outliers). The ordinate axis shows the concentrations (µg/m<sup>3</sup>); the abscissa axis shows the month. The diagram shows the median (bold line), the first quartile (lower boundary of the box), and the third quartile (upper boundary of the box).</p>
Full article ">Figure 7
<p>Weekly and daily variations in the concentrations of nitrogen and sulfur oxides in the heating (October to April, blue) and non-heating (May to September, red) seasons. Shading shows the 95% confidence intervals of the mean value.</p>
Full article ">Figure 8
<p>NWR analysis for the 20-min concentrations of SO<sub>2</sub>, NO<sub>2</sub>, and NO at the Listvyanka station in the polar coordinate system from January 2020 to December 2023.</p>
Full article ">Figure 9
<p>Episode of severe air pollution at the Listvyanka station on 13 and 14 December 2023: (<b>a</b>) variability of the 20-min concentrations of gaseous pollutants (SO<sub>2</sub>, NO<sub>2</sub>, NO); (<b>b</b>,<b>c</b>) vertical profiles of the air temperature at the Listvyanka station; (<b>c</b>–<b>f</b>) temperature stratification at the Angarsk station based on radiosonde data (the dotted line reflects the altitude of the temperature inversion boundary).</p>
Full article ">Figure 10
<p>Air mass transport trajectories from large anthropogenic sources in Irkutsk, Angarsk, and Shelekhov calculated using the HYSPLIT model: (<b>a</b>) 13 December 2023 (6 a.m.) and (<b>b</b>) 14 December 2023 (10 p.m.).</p>
Full article ">
27 pages, 4776 KiB  
Systematic Review
A Megacities Review: Comparing Indicator-Based Evaluations of Sustainable Development and Urban Resilience
by Brian R. Mackay and Richard R. Shaker
Sustainability 2024, 16(18), 8076; https://doi.org/10.3390/su16188076 - 15 Sep 2024
Viewed by 280
Abstract
Urbanization is defining global change, and megacities are fast becoming a hallmark of the Anthropocene. Humanity’s pursuit toward sustainability is reliant on the successful management of these massive urban centers and their progression into sustainable and resilient settlements. Indicators and indices are applied [...] Read more.
Urbanization is defining global change, and megacities are fast becoming a hallmark of the Anthropocene. Humanity’s pursuit toward sustainability is reliant on the successful management of these massive urban centers and their progression into sustainable and resilient settlements. Indicators and indices are applied assessment and surveillance tools used to measure, monitor, and gauge the sustainable development and urban resilience of megacities. Unknown is how indicator-based evaluations of sustainable development and urban resilience of the world’s largest 43 cities compare. In response, this review paper used the PRISMA reporting protocol, governed by 33 established and 10 emerging megacities, to compare and contrast evaluations of sustainable development and urban resilience. Results reveal that applied assessments of sustainable development of megacities appeared earlier in time and were more abundant than those of urban resilience. Geographically, China dominated other nations in affiliations to scientific research for both sustainable development and urban resilience of megacities. Among the 100 most recurrent terms, three distinct key term clusters formed for sustainable development; seven budding key term clusters formed for urban resilience suggesting breadth in contrast to sustainable development depth. The most cited assessments of sustainable development emphasize topics of energy, methodological approaches, and statistical modeling. The most cited assessments of urban resilience emphasize topics of flooding, transit networks, and disaster risk resilience. Megacities research is dominated by few countries, suggesting a need for inclusion and international partnerships. Lastly, as the world’s people become increasingly urbanized, sustainable development and urban resilience of megacities will serve as a key barometer for humanity’s progress toward sustainability. Full article
21 pages, 3867 KiB  
Article
County-Level Cultivated Land Quality Evaluation Using Multi-Temporal Remote Sensing and Machine Learning Models: From the Perspective of National Standard
by Dingding Duan, Xinru Li, Yanghua Liu, Qingyan Meng, Chengming Li, Guotian Lin, Linlin Guo, Peng Guo, Tingting Tang, Huan Su, Weifeng Ma, Shikang Ming and Yadong Yang
Remote Sens. 2024, 16(18), 3427; https://doi.org/10.3390/rs16183427 - 15 Sep 2024
Viewed by 217
Abstract
Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization of cultivated land and achieving one of the Sustainable Development Goals (SDGs): Zero Hunger. However, the CLQ evaluation system proposed in previous studies was diversified, and the methods were inefficient. [...] Read more.
Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization of cultivated land and achieving one of the Sustainable Development Goals (SDGs): Zero Hunger. However, the CLQ evaluation system proposed in previous studies was diversified, and the methods were inefficient. In this study, based on China’s first national standard “Cultivated Land Quality Grade” (GB/T 33469-2016), we constructed a unified county-level CLQ evaluation system by selecting 15 indicators from five aspects—site condition, environmental condition, physicochemical property, nutrient status and field management—and used the Delphi method to calculate the membership degree of the indicators. Taking Jimo district of Shandong Province, China, as a case study, we compared the performance of three machine learning models, including random forest, AdaBoost, and support vector regression, to evaluate CLQ using multi-temporal remote sensing data. The comprehensive index method was used to reveal the spatial distribution of CLQ. The results showed that the CLQ evaluation based on multi-temporal remote sensing data and machine learning model was efficient and reliable, and the evaluation results had a significant positive correlation with crop yield (r was 0.44, p < 0.001). The proportions of cultivated land of high-, medium- and poor-quality were 27.43%, 59.37% and 13.20%, respectively. The CLQ in the western part of the study area was better, while it was worse in the eastern and central parts. The main limiting factors include irrigation capacity and texture configuration. Accordingly, a series of targeted measures and policies were suggested, such as strengthening the construction of farmland water conservancy facilities, deep tillage of soil and continuing to construct well-facilitated farmland. This study proposed a fast and reliable method for evaluating CLQ, and the results are helpful to promote the protection of cultivated land and ensure food security. Full article
Show Figures

Figure 1

Figure 1
<p>Summary map of the study area. (<b>a</b>) Geographical location of Shandong province in China, (<b>b</b>) geographical location of Jimo district in Shandong province, (<b>c</b>) terrain feature of Jimo district and (<b>d</b>) spatial distribution of cultivated land and soil sampling points.</p>
Full article ">Figure 2
<p>Technology roadmap.</p>
Full article ">Figure 3
<p>Optimal prediction results of CLQ evaluation indicators: (<b>a</b>) soil organic matter (SOM), (<b>b</b>) soil pH, (<b>c</b>) available phosphorus (AP), (<b>d</b>) available potassium (AK) and (<b>e</b>) soil bulk density (SBD).</p>
Full article ">Figure 4
<p>Relationship between crop yield, CLQ index (<b>a</b>) and CLQ grade (<b>b</b>).</p>
Full article ">Figure 5
<p>Spatial distribution of CLQ grade and level in Jimo district. DX: Daxin Street; LIS: Lingshan Street; LC: Lancun Street; TJ: Tongji Street; CH: Chaohai Street; TH: Tianheng town; JK: Jinkou town; BA: Beian Street; LOS: Longshan Street; HX: Huanxiu Street; YSD: Yifengdian town; ASW: Aoshanwei Street; DBL: Duanbolan town; LQ: Longquan Street; and WQ: Wenquan Street.</p>
Full article ">Figure 6
<p>Spatial distribution of CLQ factor obstacle degree.</p>
Full article ">Figure 7
<p>Average and maximum obstacle degrees of CLQ evaluation indicators.</p>
Full article ">
17 pages, 4188 KiB  
Article
Three in One with Dual-Functional Hydrogel of Lactoferrin/NZ2114/LMSH Promoting Staphylococcus aureus-Infected Wound Healing
by Kun Zhang, Xuanxuan Ma, Da Teng, Ruoyu Mao, Na Yang, Ya Hao and Jianhua Wang
Antibiotics 2024, 13(9), 889; https://doi.org/10.3390/antibiotics13090889 (registering DOI) - 15 Sep 2024
Viewed by 237
Abstract
Wound infections caused by Staphylococcus aureus often result in localized suppurative lesions that severely impede the healing process, so it is urgent to develop a dress with efficient antimicrobial and pro-healing functions. In this study, the bifunctional injectable hydrogel lactoferrin (Lf)/NZ2114/lithium magnesium silicate [...] Read more.
Wound infections caused by Staphylococcus aureus often result in localized suppurative lesions that severely impede the healing process, so it is urgent to develop a dress with efficient antimicrobial and pro-healing functions. In this study, the bifunctional injectable hydrogel lactoferrin (Lf)/NZ2114/lithium magnesium silicate hydrogel (LMSH) was first successfully prepared through the electrostatic interaction method. The physical, biological, and efficacy properties are systematically analyzed with good shear-thinning capacity and biocompatibility. More importantly, it inhibits infection and promotes wound healing in a mouse wound infection model after 14 d treatment, and the bactericidal rate and healing rate were over 99.92% and nearly 100%, respectively. Meanwhile, the massive reduction of inflammatory cells, restoration of tissue structure, and angiogenesis in mice showed the anti-inflammatory and pro-healing properties of the hydrogel. The healed wounds showed thickening with more hair follicles and glands, suggesting that the hydrogel Lf/NZ2114/LMSH (Three in One) could be a better dressing candidate for the treatment of S. aureus-induced wound infections. Full article
(This article belongs to the Special Issue Anti-microbial Coating Innovations to Prevent Infectious Diseases)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The photograph, antimicrobial activity and FT–IR spectrum of the injectable hydrogel Lf/NZ2114/LMSH. (<b>a</b>) The photograph of the synthetic injectable hydrogel; (<b>b</b>) Inhibition zone of NZ2114, Lf, 1% LMSH/Lf/NZ2114, 3% HACC/Lf/NZ2114, 3% SA, 1% LMSH; (<b>c</b>) The FT–IR spectra of 1% LMSH, 1% LMSH + Lf, 1% LMSH + NZ2114, 1% LMSH + Lf + NZ2114, 1.5% LMSH + Lf + NZ2114, 3% HACC, 3% HACC + Lf, 3% HACC + NZ2114, 3% HACC + Lf + NZ2114.</p>
Full article ">Figure 2
<p>The morphology of the synthetic injectable hydrogel. The SEM image of 0.5% LMSH + NZ2114, 1% LMSH + Lf + NZ2114, 1% LMSH + Lf + NZ2114, 3% HACC + Lf + NZ2114, 1% LMSH, 3% HACC, Lf + NZ2114.</p>
Full article ">Figure 3
<p>The viscosity, modulus, and bactericidal properties of different hydrogel samples. (<b>a</b>) The viscosity of 0.5% Lf/NZ2114/LMSH and 1% Lf/NZ2114/LMSH during sheer increase from 0.01 to 100 s<sup>−1</sup>; (<b>b</b>) The viscosity of 3% Lf/NZ2114/HACC during sheer increase from 0.01 to 100 s<sup>−1</sup>; (<b>c</b>) The storage modulus (G′) and loss modulus (G″) of 0.5% Lf/NZ2114/LMSH, 1% Lf/NZ2114/LMSH, and 3% Lf/NZ2114/HACC during strain increase from 0.1% to 1000% at the frequency of 1 Hz; (<b>d</b>,<b>e</b>) The bactericidal rate of 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, Lf + NZ2114, Lf, NZ2114, 1% LMSH, 3% HACC against <span class="html-italic">S. aureus</span> CVCC 546 (n = 3). These (−2, −3, −4, −5) are the number of dilutions. (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 4
<p>The biocompatibility of different hydrogel samples. (<b>a</b>,<b>b</b>) The images and hemolysis rate of Lf, Lf + NZ2114, 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC, 0.1% Trix-100; (<b>c</b>) Cytotoxicity of HACAT cells co-cultured with Lf, Lf + NZ2114, 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC. Samples at 1, 2, and 4 days, n = 3; (<b>d</b>) The images of calcein–AM/PI double staining of the HACAT cells that were incubated with 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC for 1, 2 and 4 days. (Scale bar = 100 μm). * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 5
<p>The body weight, skin load, and wound diagram of mice (n = 3). (<b>a</b>) The weight of mice untreated and treated with Lf + NZ2114, 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC for 0–14 days; (<b>b</b>) The bacteria of skin untreated and treated with Lf + NZ2114, 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC samples for 4 d; (<b>c</b>) The macroscopic images of wounds untreated and treated with 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC samples for 4, 8, 12 and 14 d; (<b>d</b>) The wound healing rate of mice untreated and treated with Lf + NZ2114, 1% Lf/NZ2114/LMSH, 3% Lf/NZ2114/HACC, 1% LMSH, 3% HACC samples for 4, 8, 12, and 14 d. * <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>
Full article ">Figure 6
<p>HE staining of the wounds without any treatment or treated with 1% Lf/NZ2114/LMSH and 3% Lf/NZ2114/HACC samples for 14 days.</p>
Full article ">Figure 7
<p>The cytokine secretion without any treatment or treated with 1% Lf/NZ2114/LMSH and 3% Lf/NZ2114/HACC samples for 14 days. (<b>a</b>–<b>c</b>) The expressions of IL-6, VEGF and EGFR were measured by ELISA kit. (<b>d</b>–<b>g</b>) The expressions of IL-6, VEGF, EGFR, and CD31 were measured at RNA level by qPCR.</p>
Full article ">Figure 8
<p>The immunohistochemistry of without any treatment or treated with 1% Lf/NZ2114/LMSH and 3% Lf/NZ2114/HACC samples for 14 days. CD31 staining of the wounds without any treatment or treated with different hydrogel samples for 14 days. IL-6 staining of the wounds for 14 days. (Red arrows are CD31 binding sites).</p>
Full article ">
20 pages, 5074 KiB  
Article
Chlorogenic Acid Enhances the Intestinal Health of Weaned Piglets by Inhibiting the TLR4/NF-κB Pathway and Activating the Nrf2 Pathway
by Beibei Zhang, Min Tian, Jing Wu, Yueqin Qiu, Xiaoming Xu, Chaoyang Tian, Jing Hou, Li Wang, Kaiguo Gao, Xuefen Yang and Zongyong Jiang
Int. J. Mol. Sci. 2024, 25(18), 9954; https://doi.org/10.3390/ijms25189954 (registering DOI) - 15 Sep 2024
Viewed by 205
Abstract
Chlorogenic acid (CGA) is a natural polyphenol with potent antioxidant and anti-inflammatory activities. However, the exact role of it in regulating intestinal health under oxidative stress is not fully understood. This study aims to investigate the effects of dietary CGA supplementation on the [...] Read more.
Chlorogenic acid (CGA) is a natural polyphenol with potent antioxidant and anti-inflammatory activities. However, the exact role of it in regulating intestinal health under oxidative stress is not fully understood. This study aims to investigate the effects of dietary CGA supplementation on the intestinal health of weaned piglets under oxidative stress, and to explore its regulatory mechanism. Twenty-four piglets were randomly divided into two groups and fed either a basal diet (CON) or a basal diet supplemented with 200 mg/kg CGA (CGA). CGA reduced the diarrhea rate, increased the villus height in the jejunum, and decreased the crypt depth in the duodenum, jejunum, and ileum of the weaned piglets (p < 0.05). Moreover, CGA increased the protein abundance of Claudin-1, Occludin, and zonula occludens (ZO)-1 in the jejunum and ileum (p < 0.05). In addition, CGA increased the mRNA expression of pBD2 in the jejunum, and pBD1 and pBD2 in the ileum (p < 0.05). The results of 16S rRNA sequencing showed that CGA altered the ileal microbiota composition and increased the relative abundance of Lactobacillus reuteri and Lactobacillus pontis (p < 0.05). Consistently, the findings suggested that the enhancement of the intestinal barrier in piglets was associated with increased concentrations of T-AOC, IL-22, and sIgA in the serum and T-AOC, T-SOD, and sIgA in the jejunum, as well as T-AOC and CAT in the ileum caused by CGA (p < 0.05). Meanwhile, CGA decreased the concentrations of MDA, IL-1β, IL-6, and TNF-α in the serum and jejunum and IL-1β and IL-6 in the ileum (p < 0.05). Importantly, this study found that CGA alleviated intestinal inflammation and oxidative stress in the piglets by inhibiting the TLR4/NF-κB signaling pathway and activating the Nrf2 signaling pathway. These findings showed that CGA enhances the intestinal health of weaned piglets by inhibiting the TLR4/NF-κB pathway and activating the Nrf2 pathway. Full article
(This article belongs to the Special Issue Antibacterial and Antioxidant Effects of Plant-Sourced Compounds)
Show Figures

Figure 1

Figure 1
<p>Effects of dietary supplementation with CGA on the villi height and crypt depth of the small intestine in piglets. (<b>A</b>) H&amp;E staining of the intestine (scale bar, 500 μm); (<b>B</b>–<b>D</b>) analysis of villi height and crypt depth in the intestine. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 2
<p>Effects of dietary CGA supplementation on the expression of tight junctions in the jejunum and ileum. (<b>A</b>,<b>B</b>) The immunoreactivity of tight junctions in the jejunum and ileum of piglets; (<b>C</b>–<b>F</b>) Western blot analysis of tight junctions in the jejunum and ileum of piglets. <span class="html-italic">n</span> = 6. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 3
<p>Effects of dietary CGA supplementation on the mRNA expression of mucins and porcine beta defensins in the jejunum (<b>A</b>) and ileum (<b>B</b>) mucosa of piglets. MUC, mucin; pBD, porcine beta defensins; PG1, Protegrin-1. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05.</p>
Full article ">Figure 4
<p>Effects of dietary CGA supplementation on the ileal microbiota of piglets. (<b>A</b>–<b>G</b>) Relative abundance of microbiota at the phylum, genus, and species levels. (<b>H</b>) Beta diversity; (<b>I</b>–<b>K</b>) alpha diversity. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 5
<p>Effects of dietary supplementation with CGA on antioxidant status and immune-inflammatory level in the serum of piglets. (<b>A</b>–<b>D</b>) The antioxidative and oxidative indicators in the serum. (<b>E</b>–<b>H</b>); the concentration of inflammatory factors in the serum; (<b>I</b>,<b>J</b>) the immunoglobulin concentration in the serum. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 6
<p>Effects of dietary supplementation with CGA on antioxidant status and immune-inflammatory level in the jejunum and ileum of piglets. (<b>A</b>–<b>D</b>) The antioxidative and oxidative indicators in the serum; (<b>E</b>–<b>H</b>) the concentration of inflammatory factors in the serum; (<b>I</b>) the immunoglobulin concentration in the serum. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 6). *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 7
<p>Effects of dietary CGA supplementation on the activation of the NF-κB and Nrf2 signaling pathways in the jejunum and ileum of piglets. (<b>A</b>–<b>D</b>) Jejunum; (<b>E</b>–<b>H</b>) ileum. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 8
<p>Correlation analysis between microorganisms, oxidative stress indicators, immunoglobulins, and inflammatory factors in the intestines of piglets. *, 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. **, <span class="html-italic">p</span> ≤ 0.01.</p>
Full article ">Figure 9
<p>Network pharmacological analysis between CGA, oxidative stress, and inflammation. (<b>A</b>,<b>B</b>) Intersection analysis between CGA targets and the disease targets of oxidative stress and inflammation, as well as screening of core targets; (<b>C</b>) the schematic diagram of the interaction between CGA and TLR4; (<b>D</b>) the top 20 KEGG pathways.</p>
Full article ">
Back to TopTop