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Search Results (330)

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14 pages, 2083 KiB  
Article
A Dynamic Game Model for Emergency Resource Managers and Compound Disasters Induced by Heavy Rainstorms
by Yi Wu, Xuezhi Tan, Haoyuan Mo, Xudong Li, Yin Zhang, Fang Yang, Lixiang Song, Yong He and Xiaohong Chen
Water 2024, 16(20), 2959; https://doi.org/10.3390/w16202959 - 17 Oct 2024
Viewed by 141
Abstract
Under the impact of global climate change and human activities, the occurrence of compound disasters such as cascading landslides and flash floods caused by heavy rainfall is increasing. In response to these compound disaster events, it is important to simultaneously transport emergency resources [...] Read more.
Under the impact of global climate change and human activities, the occurrence of compound disasters such as cascading landslides and flash floods caused by heavy rainfall is increasing. In response to these compound disaster events, it is important to simultaneously transport emergency resources from multiple emergency rescue points to the disaster sites to promptly control the cascading development of disasters and reduce the areas affected by the disasters and associated adverse impacts. This study proposes a dynamic game model for emergency resources dispatch to comprehensively consider the evolution of the compound disaster states and the timely dispatch of emergency resources from the rescue points to the disaster site. The dynamic game model is exemplarily applied to the emergency resource dispatch for a rainstorm-induced compound disaster that occurs in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Starting with the analysis of the characteristics of emergency resource management and the attributes of a cascading of heavy rainstorms, landslides, and flash floods, the game model simulates the dynamic game process between the “disaster state” and the “emergency resource manager” in the rescue operations. A two-stage dynamic game model can support decision-making with the objectives of minimal time cost and sufficient resource dispatch for the disaster sites. Game results show that the united emergency resource dispatch in the three GBA metropolitan areas can efficiently respond to compound disasters that occur within the GBA metropolitan area. The dynamic game model could be extended for compound disaster emergency responses with more complicated compound effects and resource constraints. Full article
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<p>Decision-making diagram of emergency resources dispatch for compound disaster events in the dynamic game framework. The dotted lines in the diagram are the “optimal schemes” evaluated by emergency resource managers in different disaster states.</p>
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<p>A diagram of the two-stage dynamic game process for compound disaster events.</p>
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<p>Overview of Guangdong–Hong Kong–Macao Greater Bay Area (GBA). (<b>a</b>), Regional overview map of China. (<b>b</b>), Regional overview map of Guangdong Province. (<b>c</b>), Three major metropolitan area of the GBA, with green representing “GFZ” metropolitan areas, blue representing “SDH” metropolitan areas and yellow representing “ZZJ” metropolitan areas.</p>
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<p>GBA metropolitan areas and resource transportation time cost for compound disasters in “GFZ” (green), “SDH” (blue), and “ZZJ” (yellow) metropolitan areas.</p>
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<p>The two-stage game processes and associated payments for emergency resource dispatch in a rainstorm-induced compound disaster.</p>
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12 pages, 838 KiB  
Review
Gut–Brain Axis and Psychopathology: Exploring the Impact of Diet with a Focus on the Low-FODMAP Approach
by Emanuela Ribichini, Giulia Scalese, Chiara Mocci and Carola Severi
Nutrients 2024, 16(20), 3515; https://doi.org/10.3390/nu16203515 - 17 Oct 2024
Viewed by 274
Abstract
Background: The gut–brain axis (GBA) is a bidirectional communication network connecting the central nervous system with the gastrointestinal (GI) tract, influencing both mental and physical health. Recent research has underscored the significant role of diet in modulating this axis, with attention to how [...] Read more.
Background: The gut–brain axis (GBA) is a bidirectional communication network connecting the central nervous system with the gastrointestinal (GI) tract, influencing both mental and physical health. Recent research has underscored the significant role of diet in modulating this axis, with attention to how specific dietary patterns can impact anxiety and depression, particularly when linked to disorders of gut–brain interaction (DGBIs), like intestinal bowel syndrome (IBS). Aims and Methods: This narrative review examines the effects of specific diet regimens on the GBA and its potential role in managing psychopathology, focusing on anxiety and depression, IBS, and the low-FODMAP diet. We conducted a search on PubMed and MEDLINE by combining the following key terms: “Gut–Brain Axis”, “Irritable Bowel Syndrome”, “Low FODMAP diet”, “Mediterranean Diet”, “Psychopathology”, “Anxiety and Depression”, and “Gut Microbiota”. We applied the following filters: “Clinical Trials”, “Randomized Controlled Trials”, “Reviews”, “Meta-Analyses”, and “Systematic Reviews”. In total, 59 papers were included. Results: Low-FODMAP diet, originally developed to alleviate GI symptoms in IBS, may also positively influence mental health by modulating the GBA and improving the gut microbiota (GM) composition. New insights suggest that combining the low-FODMAP diet with the Mediterranean diet could offer a synergistic effect, enhancing both GI and psychological therapeutic outcomes. Conclusions: Understanding the complex interactions between diet, the GM, and mental health opens new avenues for holistic approaches to managing psychopathology, particularly when linked to GI symptoms. Full article
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<p>Overview of dietary amino acid precursors and their corresponding neurotransmitters involved in mental health and neurobiology. Abbreviation: GABA, gamma-aminobutyric acid. * serve as neurotransmitter modulators.</p>
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<p>Impact of diet on the gut–brain axis: effects on gut health, mental well-being, and psychopathology. Abbreviations. PUFAs: Polyunsaturated fatty acids; GM: Gut microbiota; SCFAs: Short-chain fatty acids; GLP-1: Glucagon-like peptide-1; PYY: Peptide YY; FODMAP: Fermentable oligosaccharides, disaccharides, monosaccharides, and polyols. The arrows represent the bidirectional interaction within the gut-brain axis.</p>
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16 pages, 1575 KiB  
Article
Development Path of Macao Tourism Symbiosis Integration from the Configuration Perspective
by Xianke Li, Johnny Fat Iam Lam, Zhicong Lin and Chongyan Li
Sustainability 2024, 16(19), 8505; https://doi.org/10.3390/su16198505 - 29 Sep 2024
Viewed by 543
Abstract
The concept of symbiotic and integrated development represents the adaptive response of Macao tourism to the necessity of diversified development. It is the inevitable path for Macao tourism to achieve high-quality sustainable development. In accordance with the principles of the symbiosis theory, this [...] Read more.
The concept of symbiotic and integrated development represents the adaptive response of Macao tourism to the necessity of diversified development. It is the inevitable path for Macao tourism to achieve high-quality sustainable development. In accordance with the principles of the symbiosis theory, this paper presents an analytical framework and employs Qualitative Comparative Analysis (QCA) to examine the intricate causal processes that simultaneously influence the symbiosis integration development of Macao tourism. The results of the empirical test demonstrate that: (1) The development of Macao tourism symbiosis and integration is influenced by five factors: external policy (EP), regional integration (RI), new digital technology (DT), gaming industry (GI), and cultural element (CE); (2) There are three configuration paths for Macao’s tourism symbiosis, integration, and high-quality development, including an industrial synergy mode, innovation-leading mode, and value-sharing mode; (3) There are two configuration paths formed by the non-high-quality symbiotic integration of Macao tourism, namely, the government absence type and the market failure type; (4) RI and GI are the core conditions for the symbiotic and integrated development of Macao tourism, and there is a certain substitution relationship between EP, DT, and CE. This study advances the academic understanding of the asymmetric causal relationship between various factors and the symbiotic integration of tourism. It enhances the application of the symbiotic theory in the practise of tourism and reveals differences in the path of Macao tourism development under the combination of multiple factors. The findings provide a theoretical basis for the Macao government to optimise the tourism spatial layout and enhance tourism sustainability, build a multi-level “tourism+” symbiotic industrial structure, and establish a modern tourism governance system. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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<p>Symbiosis integration mechanism of Macao tourism from the configuration perspective.</p>
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<p>Distribution of the GBA urban agglomeration.</p>
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<p>The substitution relationship between the configuration paths of high-quality symbiosis integration in Macao tourism. Note: The solid line represents the variable in question. The two variables enclosed within the dotted line are subject to a substitution relationship, which implies that only one of the two variables is necessary. The same applies below in <a href="#sustainability-16-08505-f004" class="html-fig">Figure 4</a>.</p>
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<p>Substitution relationship between configuration paths of non-high-quality symbiosis integration in Macao tourism.</p>
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20 pages, 33767 KiB  
Article
Multi-Source Data-Driven Extraction of Urban Residential Space: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area Urban Agglomeration
by Xiaodie Yuan, Xiangjun Dai, Zeduo Zou, Xiong He, Yucong Sun and Chunshan Zhou
Remote Sens. 2024, 16(19), 3631; https://doi.org/10.3390/rs16193631 - 29 Sep 2024
Viewed by 731
Abstract
The accurate extraction of urban residential space (URS) is of great significance for recognizing the spatial structure of urban function, understanding the complex urban operating system, and scientific allocation and management of urban resources. The traditional URS identification process is generally conducted through [...] Read more.
The accurate extraction of urban residential space (URS) is of great significance for recognizing the spatial structure of urban function, understanding the complex urban operating system, and scientific allocation and management of urban resources. The traditional URS identification process is generally conducted through statistical analysis or a manual field survey. Currently, there are also superpixel segmentation and wavelet transform (WT) processes to extract urban spatial information, but these methods have shortcomings in extraction efficiency and accuracy. The superpixel wavelet fusion (SWF) method proposed in this paper is a convenient method to extract URS by integrating multi-source data such as Point of Interest (POI) data, Nighttime Light (NTL) data, LandScan (LDS) data, and High-resolution Image (HRI) data. This method fully considers the distribution law of image information in HRI and imparts the spatial information of URS into the WT so as to obtain the recognition results of URS based on multi-source data fusion under the perception of spatial structure. The steps of this study are as follows: Firstly, the SLIC algorithm is used to segment HRI in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration. Then, the discrete cosine wavelet transform (DCWT) is applied to POI–NTL, POI–LDS, and POI–NTL–LDS data sets, and the SWF is carried out based on different superpixel scale perspectives. Finally, the OSTU adaptive threshold algorithm is used to extract URS. The results show that the extraction accuracy of the NLT–POI data set is 81.52%, that of the LDS–POI data set is 77.70%, and that of the NLT–LDS–POI data set is 90.40%. The method proposed in this paper not only improves the accuracy of the extraction of URS, but also has good practical value for the optimal layout of residential space and regional planning of urban agglomerations. Full article
(This article belongs to the Special Issue Nighttime Light Remote Sensing Products for Urban Applications)
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<p>Residential space localization and non-residential space recognition based on superpixel segmentation. (Note: the blue circles represent the initial seed points, while the red, yellow, and green circles represent the sampling points of different feature types.)</p>
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<p>Research area of this work—the GBA urban agglomeration.</p>
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<p>Data presentation.</p>
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<p>Analysis frame diagram.</p>
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<p>Schematic diagram of wavelet decomposition.</p>
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<p>Fusion process of SWT.</p>
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<p>Three scales of superpixel segmentation.</p>
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<p>Image after the fusion of POI data, NTL data, and LDS data by SWT.</p>
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<p>Threshold extraction of POI–NTL–LDS data set.</p>
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<p>Residential area results extracted by the OSTU adaptive threshold calculation.</p>
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<p>Threshold extraction of POI–NTL and POI–LDS data set.</p>
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<p>Random verification points.</p>
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17 pages, 7405 KiB  
Article
Association between Land Use and Urban Vitality in the Guangdong–Hong Kong–Macao Greater Bay Area: A Multiscale Study
by Cefang Deng, Dailin Zhou, Yiming Wang, Jie Wu and Zhe Yin
Land 2024, 13(10), 1574; https://doi.org/10.3390/land13101574 - 27 Sep 2024
Viewed by 407
Abstract
Urban vitality, which indicates the development level of a city and the quality of life of its residents, is a complex subject in urban research due to its diverse assessment methods and intricate impact mechanisms. This study uses multisource data to evaluate the [...] Read more.
Urban vitality, which indicates the development level of a city and the quality of life of its residents, is a complex subject in urban research due to its diverse assessment methods and intricate impact mechanisms. This study uses multisource data to evaluate the urban vitality of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) across social, economic, cultural, and environmental dimensions. It analyzes the spatial distribution characteristics of urban vitality and examines the relationships between urban vitality and land use at both regional and city scales. The results indicate that the urban vitality in the GBA generally exhibits a spatial distribution pattern of a high central density and a low peripheral spread, where built-up areas and cropland emerge as key influencing factors. Cities with different developmental backgrounds have unique relationships between land use and urban vitality. In high-vitality cities, the role of the built-up area diminishes, and natural ecosystems, such as wetlands, enhance vitality. In contrast, in low-vitality cities, built-up areas boost urban vitality, and agriculture-related land types exert a lower negative or even positive effect. This research contributes to the understanding of the spatial structures of urban vitality related to land use at different scales and offers insights for urban planners, builders, and development managers in formulating targeted urban vitality enhancement strategies at the regional collaborative and city levels. Full article
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<p>Location of the study area.</p>
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<p>Spatial distribution of urban vitality. (<b>a</b>) social vitality; (<b>b</b>) economic vitality; (<b>c</b>) cultural vitality; (<b>d</b>) environmental vitality; (<b>e</b>) comprehensive urban vitality.</p>
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<p>LISA agglomeration of urban vitality in the GBA.</p>
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<p>Urban vitality cold- and hotspot distribution in the GBA based on hotspot analysis.</p>
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<p>Impact of land use on urban vitality based on the results of the GWR model.</p>
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23 pages, 2667 KiB  
Article
Functional Analysis of Human GBA1 Missense Mutations in Drosophila: Insights into Gaucher Disease Pathogenesis and Phenotypic Consequences
by Aparna Kuppuramalingam, Or Cabasso and Mia Horowitz
Cells 2024, 13(19), 1619; https://doi.org/10.3390/cells13191619 - 27 Sep 2024
Viewed by 588
Abstract
The human GBA1 gene encodes lysosomal acid β-glucocerebrosidase, whose activity is deficient in Gaucher disease (GD). In Drosophila, there are two GBA1 orthologs, Gba1a and Gba1b, and Gba1b is the bona fide GCase encoding gene. Several fly lines with different deletions [...] Read more.
The human GBA1 gene encodes lysosomal acid β-glucocerebrosidase, whose activity is deficient in Gaucher disease (GD). In Drosophila, there are two GBA1 orthologs, Gba1a and Gba1b, and Gba1b is the bona fide GCase encoding gene. Several fly lines with different deletions in the Gba1b were studied in the past. However, since most GD-associated GBA1 mutations are point mutations, we created missense mutations homologous to the two most common GD mutations: the mild N370S mutation (D415S in Drosophila) and the severe L444P mutation (L494P in Drosophila), using the CRISPR-Cas9 technology. Flies homozygous for the D415S mutation (dubbed D370S hereafter) presented low GCase activity and substrate accumulation, which led to lysosomal defects, activation of the Unfolded Protein Response (UPR), inflammation/neuroinflammation, and neurodegeneration along with earlier death compared to control flies. Surprisingly, the L494P (called L444P hereafter) flies presented higher GCase activity with fewer lysosomal defects and milder disease in comparison to that presented by the D370S homozygous flies. Treatment with ambroxol had a limited effect on all homozygous fly lines tested. Overall, our results underscore the differences between the fly and human GCase enzymes, as evidenced by the distinct phenotypic outcomes of mutations in flies compared to those observed in human GD patients. Full article
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<p>Design of <span class="html-italic">Drosophila Gba1b<sup>L444P</sup></span> and <span class="html-italic">Gba1b<sup>D370S</sup></span> genes. (<b>A</b>). Multiple sequence alignment of <span class="html-italic">GBA1</span> fragments from different organisms containing the two amino acids that were mutated in the present study. The N370 is highlighted in green, and the L444 is highlighted in yellow. (<b>B</b>). The original and the established nucleotide sequence of the mutated amino acids. Highlighted in red are the mutated nucleotides. (<b>C</b>). Shown in red is the exon localization of the mutated amino acids. (<b>D</b>). Comparison between <span class="html-italic">Gba1b</span> fragments containing either the mutant (M) or the normal (N) sequence based on non-lethal genotyping. Boxed in blue are the nucleotide changes introduced to obtain the D370S (D415S) mutation, and in red are the nucleotide changes introduced to obtain the L444P (L494P) mutation. (<b>E</b>). Schematic representation of the <span class="html-italic">Gba1b</span> region on chromosome 3 of the homozygous <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> line generated. (<b>F</b>). Schematic representation of the <span class="html-italic">Gba1b</span> region on chromosome 3 of the homozygous <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> line generated.</p>
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<p>Decreased GCase activity and substrate accumulation in the mutant fly lines. (<b>A</b>). GCase activity was measured in 50 µg protein lysates prepared from 2-day-old <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span>, <span class="html-italic">Gba1b<sup>D370/D370SS</sup></span> (homozygous—H) lines, and <span class="html-italic">Gba1b<sup>D370/+</sup></span>, <span class="html-italic">Gba1b<sup>L444P/+</sup></span> (heterozygous—T) flies, as well as from <span class="html-italic">Gba1b<sup>m/+</sup></span> (T), <span class="html-italic">Gba1b<sup>m/m</sup></span> (H), and w1118 lines, as detailed in the Methods section. The activity level of w1118 was considered 1. (<b>B</b>). The quantification of (<b>A</b>) is shown as the average ± standard error. (<b>C</b>). TLC analysis of GCase activity of the four selected homozygous lines (D370S-<span class="html-italic">Gba1b<sup>D370/D370SS</sup></span>; L444P-<span class="html-italic">Gba1b<sup>L444P/L444P</sup>)</span>. (<b>D</b>). The quantification of (<b>C</b>) is shown as the average ± standard error. One-way ANOVA was used to calculate the significance of the results. (<b>E</b>). TLC plate showing substrate accumulation in lipid extracts prepared from 22-day-old homozygous flies (D370S-<span class="html-italic">Gba1b<sup>D370/D370SS</sup></span>; L444P-<span class="html-italic">Gba1b<sup>L444P/L444P</sup></span>). (<b>F</b>). Quantification of results as shown in (<b>E</b>). The results are presented as average ± standard error. One-way ANOVA was used to calculate the significance of the results. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. SEM—standard error. Each dot denotes an independent experiment.</p>
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<p>Lysosomal abnormalities in the homozygous mutant flies. (<b>A</b>). Confocal images of the suboesophageal ganglion region in the brains of control w1118, <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> lines 1-1 and 3-2, and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1 flies, at 15 days post-eclosion. Red—LysoTracker, Blue—DAPI. (<b>B</b>). Graphical presentation of the <span class="html-italic">Drosophila</span> brain was created using BioRender. MB—mushroom body, AL—anntenal lobe, SOG—suboesophageal ganglion, A—anntena. The imaged region is circled in red. (<b>C</b>). Quantification of LysoTracker intensity in images like the one shown in (<b>A</b>). The results are presented as an average ± standard error for 25 different brains for each line. Significance was calculated using one-way ANOVA. (<b>D</b>). Confocal images of the gut region of w1118, <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> lines 1-1 and 3-2, and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1 flies at 15 days post-eclosion. Red—LysoTracker, Blue—DAPI. (<b>E</b>). Graphical presentation of the <span class="html-italic">Drosophila</span> gut. The image was taken from BioRender, and the imaged region is boxed in red. (<b>F</b>). Quantification of LysoTracker intensity in images like the one shown in (<b>D</b>). The results are presented as an average ± standard error for 7 different guts for each line. Significance was calculated using one-way ANOVA. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Each dot denotes an independent experiment.</p>
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<p>ERAD of the mutant <span class="html-italic">Gba1b</span> variants. (<b>A</b>). A total of 60 µg of protein lysates, prepared from 2-day-old flies expressing the WT-<span class="html-italic">Gba1b</span> (UAS-WT <span class="html-italic">Gba1b</span>), D370S (UAS-D370S), and L444P (UAS-L444P) mutants under the Da-GAL4 driver, were electrophoresed through SDS-PAGE and the corresponding blots were interacted with anti-myc antibody to visualize the GCase proteins and with anti-actin antibody, as a loading control. (<b>B</b>). Quantification of results as presented in (<b>A</b>). The results are presented as average ± standard error. One-way ANOVA was used to determine the statistical significance of the results. (<b>C</b>). Protein lysates (60 µg), prepared from 22-day-old mutant flies described in (<b>A</b>), were processed as specified in (<b>A</b>). (<b>D</b>). Quantification of results as presented in (<b>C</b>). The results are presented as average ± standard error. Analysis was performed as explained in (<b>B</b>). (<b>E</b>). Protein lysates (60 µg), prepared as in (<b>A</b>) and treated with endo-H were subjected to electrophoresis and blotting as in (<b>C</b>). The blots interacted with anti-myc antibody to visualize the GCase proteins and with anti-actin antibody as a loading control. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Each dot denotes an independent experiment.</p>
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<p>UPR activation in the mutant flies. (<b>A</b>). mRNA levels of UPR markers: HSc-70-3, Atf4, Atf6, and sXbp1 were tested in the bodies (<b>A</b>) and heads (<b>B</b>) of 22-day-old homozygous <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> fly lines 3-2 and 1-1 and homozygous <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> fly lines 6-1 and 11-1. The results are presented as average ± standard error. Each dot represents a triplicate of an independent experiment. One-way ANOVA was used to determine the statistical significance of the results. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001, ns—non-significant. Each dot denotes an independent experiment.</p>
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<p>Inflammation and neuroinflammation in the mutant flies. (<b>A</b>). The inflammatory pathways in <span class="html-italic">Drosophila</span> (created with BioRender). (<b>B</b>). mRNA levels of inflammatory markers: AttC, Cec, Drs, and Mtk were tested in the bodies (<b>B</b>) and heads (<b>C</b>) of 22-day-old <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> fly lines 3-2 and 1-1 and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1. The results are presented as average ± standard error. One-way ANOVA was used to determine the statistical significance of the results. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Each dot denotes an independent experiment.</p>
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<p>Neuropathology and survival of the mutant flies. (<b>A</b>). Thirty flies from <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> lines 3-2 and 1-1 and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1 were tested for their locomotion abilities at 2, 12, and 22 days post-eclosion. Results are presented as average ± standard error. Two-way ANOVA was used to determine the statistical significance of the results. (<b>B</b>) Kaplan–Meier curve presenting the survival of 100 control (w1118), homozygous <span class="html-italic">Gba1b<sup>L444P</sup></span> lines 3-2 and 1-1, and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1 flies. Below is a table showing the significance measured by Kaplan–Meier’s multiple comparisons. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Each dot denotes an independent experiment.</p>
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<p>Molecular dynamic simulation of <span class="html-italic">Gba1b</span>-encoded GCase with ambroxol. (<b>A</b>). X-ray structure of human WT GCase with ambroxol (depicted in cyan) (based on <a href="#cells-13-01619-f007" class="html-fig">Figure 7</a>B from JBC 2009 [<a href="#B21-cells-13-01619" class="html-bibr">21</a>]). The loops that are stabilized upon formation of ambroxol–GCase complex are pink (loop A), green (loop B), and blue (loop C). (<b>B</b>). The predicted <span class="html-italic">Gba1b</span> WT model with ambroxol (16 ns stimulation). Ambroxol is painted in dark pink. Loops A, B, and C are colored as in (<b>B</b>). (<b>C</b>). RMSD stimulation of <span class="html-italic">Gba1b</span> GCase with (16 nanoseconds) and without (10 nanoseconds) ambroxol. Each graph shows the RMSD status of a different loop in the <span class="html-italic">Gba1b</span>-encoded GCase. Loops A and C are stabilized upon ambroxol binding. (<b>D</b>). GCase activity of homozygous <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> flies (lines 1-1 and 3-2), grown for 22 days with and without ambroxol. GCase activity level of w1118 was considered 1. Results are presented as the average ± standard error. One-way ANOVA was used to calculate the statistical significance. (<b>E</b>). GCase activity of the homozygous <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> flies (lines 6-1 and 11-1), grown for 22 days with and without ambroxol. Activity levels of w1118 with ambroxol were considered 1. Results are represented as the average ± standard error. One-way ANOVA was used to calculate the statistical significance. *** <span class="html-italic">p</span> &lt; 0.005. Each dot denotes an independent experiment.</p>
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<p>Change in UPR parameters upon ambroxol treatment. (<b>A</b>). mRNA levels of UPR markers: HSc-70-3, Atf4, Atf6, and sXbp1 were tested in the bodies (<b>A</b>) and heads (<b>B</b>) of <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> lines 3-2 and 1-1 and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> lines 6-1 and 11-1 flies that were grown for 22 days with and without ambroxol. The results are presented as average ± standard error. Relative mRNA expression level was calculated using the 2<sup>−ΔΔCT</sup> method. Two-way ANOVA was used to calculate the statistical significance. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Each dot denotes an independent experiment.</p>
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<p>Effect of ambroxol on inflammation/neuroinflammation. (<b>A</b>). mRNA levels of inflammatory markers: AttC, Cec, Drs, and Mtk were tested in the bodies (<b>A</b>) and heads (<b>B</b>) of homozygous <span class="html-italic">Gba1b<sup>L444P/L444P</sup></span> lines 3-2 and 1-1 and <span class="html-italic">Gba1b<sup>D370S/D370S</sup></span> 6-1 and 11-1 flies that were grown for 22 days with and without ambroxol. The results are presented as average ± standard error. Relative mRNA expression level was calculated using the 2<sup>−ΔΔCT</sup> method. Two-way ANOVA was used to calculate the statistical significance. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Each dot denotes an independent experiment.</p>
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15 pages, 26612 KiB  
Article
Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)
by Estefania Ascencio-Medina, Shan He, Amirreza Daghighi, Kweeni Iduoku, Gerardo M. Casanola-Martin, Sonia Arrasate, Humberto González-Díaz and Bakhtiyor Rasulev
Polymers 2024, 16(19), 2731; https://doi.org/10.3390/polym16192731 - 26 Sep 2024
Viewed by 580
Abstract
This work is devoted to the investigation of dielectric permittivity which is influenced by electronic, ionic, and dipolar polarization mechanisms, contributing to the material’s capacity to store electrical energy. In this study, an extended dataset of 86 polymers was analyzed, and two quantitative [...] Read more.
This work is devoted to the investigation of dielectric permittivity which is influenced by electronic, ionic, and dipolar polarization mechanisms, contributing to the material’s capacity to store electrical energy. In this study, an extended dataset of 86 polymers was analyzed, and two quantitative structure–property relationship (QSPR) models were developed to predict dielectric permittivity. From an initial set of 1273 descriptors, the most relevant ones were selected using a genetic algorithm, and machine learning models were built using the Gradient Boosting Regressor (GBR). In contrast to Multiple Linear Regression (MLR)- and Partial Least Squares (PLS)-based models, the gradient boosting models excel in handling nonlinear relationships and multicollinearity, iteratively optimizing decision trees to improve accuracy without overfitting. The developed GBR models showed high R2 coefficients of 0.938 and 0.822, for the training and test sets, respectively. An Accumulated Local Effect (ALE) technique was applied to assess the relationship between the selected descriptors—eight for the GB_A model and six for the GB_B model, and their impact on target property. ALE analysis revealed that descriptors such as TDB09m had a strong positive effect on permittivity, while MLOGP2 showed a negative effect. These results highlight the effectiveness of the GBR approach in predicting the dielectric properties of polymers, offering improved accuracy and interpretability. Full article
(This article belongs to the Special Issue Computational Modeling and Simulations of Polymers)
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<p>(<b>A</b>) The original dataset includes dielectric permittivity values for 86 polymers. (<b>B</b>) After removing outliers, the dataset is reduced to 82 polymers. In both histograms, the <span class="html-italic">x</span>-axis represents dielectric permittivity values, while the <span class="html-italic">y</span>-axis indicates the frequency of their appearance. The blue lines, generated using Kernel Density Estimation (KDE), illustrate the data distribution and highlight central trends.</p>
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<p>Comparison of the predictive performance of various machine learning models in estimating the dielectric permittivity of polymers. The graph displays the coefficients of determination (<span class="html-italic">R<sup>2</sup></span>) for each model across both training and test sets.</p>
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<p>Plots of experimental vs. predicted values of the dielectric constant for (<b>A</b>) GBR_A and (<b>B</b>) GBR_B models.</p>
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<p>(<b>A</b>) Accumulated Local Effect (ALE) plots for the descriptors in the GB_A model, illustrating the influence of each descriptor on the prediction of dielectric permittivity. (<b>B</b>) Chemical compounds highlighting the positive or negative impact on the descriptors.</p>
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<p>(<b>A</b>) Accumulated Local Effect (ALE) plots for the descriptors in the GB_B model, illustrating the influence of each descriptor on the prediction of dielectric permittivity. (<b>B</b>) Chemical compounds highlighting the positive or negative impact on the descriptors.</p>
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24 pages, 1049 KiB  
Review
Investigating the Impact of Nutrition and Oxidative Stress on Attention Deficit Hyperactivity Disorder
by Malina Visternicu, Viorica Rarinca, Vasile Burlui, Gabriela Halitchi, Alin Ciobică, Ana-Maria Singeap, Romeo Dobrin, Ioannis Mavroudis and Anca Trifan
Nutrients 2024, 16(18), 3113; https://doi.org/10.3390/nu16183113 - 15 Sep 2024
Viewed by 2581
Abstract
Background/Objectives: Attention deficit hyperactivity disorder (ADHD) is the most common childhood-onset neurodevelopmental disorder, characterized by difficulty maintaining attention, impulsivity, and hyperactivity. While the cause of this disorder is still unclear, recent studies have stated that heredity is important in the development of ADHD. [...] Read more.
Background/Objectives: Attention deficit hyperactivity disorder (ADHD) is the most common childhood-onset neurodevelopmental disorder, characterized by difficulty maintaining attention, impulsivity, and hyperactivity. While the cause of this disorder is still unclear, recent studies have stated that heredity is important in the development of ADHD. This is linked to a few comorbidities, including depression, criminal behavior, and anxiety. Although genetic factors influence ADHD symptoms, there are also non-genetic factors, one of which is oxidative stress (OS), which plays a role in the pathogenesis and symptoms of ADHD. This review aims to explore the role of OS in ADHD and its connection to antioxidant enzyme levels, as well as the gut–brain axis (GBA), focusing on diet and its influence on ADHD symptoms, particularly in adults with comorbid conditions. Methods: The literature search included the main available databases (e.g., Science Direct, PubMed, and Google Scholar). Articles in the English language were taken into consideration and our screening was conducted based on several words such as “ADHD”, “oxidative stress”, “diet”, “gut–brain axis”, and “gut microbiota.” The review focused on studies examining the link between oxidative stress and ADHD, the role of the gut–brain axis, and the potential impact of dietary interventions. Results: Oxidative stress plays a critical role in the development and manifestation of ADHD symptoms. Studies have shown that individuals with ADHD exhibit reduced levels of key antioxidant enzymes, including glutathione peroxidase (GPx), catalase (CAT), and superoxide dismutase (SOD), as well as a diminished total antioxidant status (TOS) compared to healthy controls. Additionally, there is evidence of a close bidirectional interaction between the nervous system and gut microbiota, mediated by the gut–brain axis. This relationship suggests that dietary interventions targeting gut health may influence ADHD symptoms and related comorbidities. Conclusions: Oxidative stress and the gut–brain axis are key factors in the pathogenesis of ADHD, particularly in adults with comorbid conditions. A better understanding of these mechanisms could lead to more targeted treatments, including dietary interventions, to mitigate ADHD symptoms. Further research is required to explore the therapeutic potential of modulating oxidative stress and gut microbiota in the management of ADHD. Full article
(This article belongs to the Section Nutrition and Metabolism)
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<p>PRISMA flow chart illustrating the selection of studies and exclusion criteria.</p>
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<p>Treatment used for ADHD.</p>
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12 pages, 264 KiB  
Article
Breaking Siloed Policies: Applying a Gender-Based Analysis Plus (GBA+) to Homelessness during Pregnancy in Canada
by Barbara Chyzzy, Sepali Guruge, Kaitlin Schwan, Joon Lee and Stacia Stewart
Soc. Sci. 2024, 13(9), 486; https://doi.org/10.3390/socsci13090486 - 13 Sep 2024
Viewed by 684
Abstract
Amongst women and gender diverse (WGD) populations experiencing homelessness in Canada, one of the most vulnerable and understudied subgroups are those who are pregnant. A key barrier to accessing housing for this population are policies that lead to siloed sector work and complicated [...] Read more.
Amongst women and gender diverse (WGD) populations experiencing homelessness in Canada, one of the most vulnerable and understudied subgroups are those who are pregnant. A key barrier to accessing housing for this population are policies that lead to siloed sector work and complicated and inaccessible services. Frequent relocation and fragmented access to essential prenatal and postnatal support are the result. Experiences of homelessness for WGD people are distinct from that of cisgender men; the former tend to experience ‘hidden homelessness’ and are more likely to rely on relational, precarious, and sometimes dangerous housing options. The homelessness sector, its policies, and services tend to be cis-male-centric because of the greater visibility of homelessness in cis-men and fail to meet pregnant WGD people’s needs. This paper describes the findings from a one-day symposium that was held in Toronto, Canada, in June 2023 that aimed to address the siloed approach to housing provision for pregnant WGD people experiencing homelessness. A key focus was to understand how to incorporate a gendered and intersectional discourse into practice and policy. Adopting a gender-based analysis plus (GBA+) approach within policymaking can help illuminate and address why certain groups of WGD people are disproportionately affected by homelessness, including Indigenous Peoples, recent immigrants, racialized people, and those experiencing intimate partner violence, poverty, and substance use. Full article
18 pages, 3225 KiB  
Article
A Novel Rare PSEN2 Val226Ala in PSEN2 in a Korean Patient with Atypical Alzheimer’s Disease, and the Importance of PSEN2 5th Transmembrane Domain (TM5) in AD Pathogenesis
by YoungSoon Yang, Eva Bagyinszky and Seong Soo A. An
Int. J. Mol. Sci. 2024, 25(17), 9678; https://doi.org/10.3390/ijms25179678 - 6 Sep 2024
Viewed by 630
Abstract
In this manuscript, a novel presenilin-2 (PSEN2) mutation, Val226Ala, was found in a 59-year-old Korean patient who exhibited rapid progressive memory dysfunction and hallucinations six months prior to her first visit to the hospital. Her Magnetic Resonance Imaging (MRI) showed brain atrophy, and [...] Read more.
In this manuscript, a novel presenilin-2 (PSEN2) mutation, Val226Ala, was found in a 59-year-old Korean patient who exhibited rapid progressive memory dysfunction and hallucinations six months prior to her first visit to the hospital. Her Magnetic Resonance Imaging (MRI) showed brain atrophy, and both amyloid positron emission tomography (PET) and multimer detection system-oligomeric amyloid-beta (Aβ) results were positive. The patient was diagnosed with early onset Alzheimer’s disease. The whole-exome analysis revealed a new PSEN2 Val226Ala mutation with heterozygosity in the 5th transmembrane domain of the PSEN2 protein near the lumen region. Analyses of the structural prediction suggested structural changes in the helix, specifically a loss of a hydrogen bond between Val226 and Gln229, which may lead to elevated helix motion. Multiple PSEN2 mutations were reported in PSEN2 transmembrane-5 (TM5), such as Tyr231Cys, Ile235Phe, Ala237Val, Leu238Phe, Leu238Pro, and Met239Thr, highlighting the dynamic importance of the 5th transmembrane domain of PSEN2. Mutations in TM5 may alter the access tunnel of the Aβ substrate in the membrane to the gamma-secretase active site, indicating a possible influence on enzyme function that increases Aβ production. Interestingly, the current patient with the Val226Ala mutation presented with a combination of hallucinations and memory dysfunction. Although the causal mechanisms of hallucinations in AD remain unclear, it is possible that PSEN2 interacts with other disease risk factors, including Notch Receptor 3 (NOTCH3) or Glucosylceramidase Beta-1 (GBA) variants, enhancing the occurrence of hallucinations. In conclusion, the direct or indirect role of PSEN2 Val226Ala in AD onset cannot be ruled out. Full article
(This article belongs to the Special Issue Genetic Research in Neurological Diseases)
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<p>(<b>a</b>) Magnetic resonance imaging of the patient: observations of Axial FLAIR (A), (B), (C) sequences of the patient with mild diffuse brain atrophy. (<b>b</b>) Amyloid PET image of the patient: abnormal amyloid deposits observed in gray matter of whole brain, especially in the left temporal lobe. (A) Coronal plane. (B) Axial plane.</p>
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<p>Sanger sequencing data of patient with PSEN2 Val226Ala mutation.</p>
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<p>ExPASy predictions for PSEN2 Val226Ala, compared to normal PSEN2 and PSEN2 Val226Ala structure in terms of polarity, Kyte-Doolittle Hydropathy Plots and bulkiness index. The X axis present the residues in PSEN2 (between residue 215 and 227), while the Y axis presents the (<b>a</b>) polarity scores (<b>b</b>) the Kyte-Doolittle Hydropathy Plots (<b>c</b>) and the bulkiness index.</p>
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<p>(<b>a</b>) Aligned normal and mutant PSEN2 structures. (<b>b</b>) Intramolecular interactions in case of Val226. (<b>c</b>) Intramolecular interactions in case of Ala226. (<b>d</b>) 2D diagram of the intramolecular interaction of Val226 vs. Ala226. The residues which Val226 or Ala226 bind to as covalent bonds are labeled with purple, the hydrogen bonds are labeled with blue, and the Van der Waals bonds are labeled with green.</p>
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<p>Three-dimensional model of structure of mutations, located in TM5 of PSEN2. (<b>a</b>) Leu225Pro, (<b>b</b>) Glu228Leu, (<b>c</b>) Tyr231Cys, (<b>d</b>) Ile235Phe, (<b>e</b>) Met237Val, (<b>f</b>) Leu238Phe, (<b>g</b>) Leu238Pro, (<b>h</b>) Met239Val, (<b>i</b>) Met239Thr, and (<b>j</b>) Met239Ile.</p>
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<p>Mutations, located in the 5th transmembrane domain of PSEN2. Variants, which are highlighted in red, were verified to impact amyloid metabolism in cell lines, which are highlighted in red. The variants of which the pathogenic nature remained unclear are highlighted in orange. The location of Val226 is highlighted in yellow.</p>
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27 pages, 49596 KiB  
Article
An Inducible Luminescent System to Explore Parkinson’s Disease-Associated Genes
by Anelya Gandy, Gilles Maussion, Sara Al-Habyan, Michael Nicouleau, Zhipeng You, Carol X.-Q. Chen, Narges Abdian, Nathalia Aprahamian, Andrea I. Krahn, Louise Larocque, Thomas M. Durcan and Eric Deneault
Int. J. Mol. Sci. 2024, 25(17), 9493; https://doi.org/10.3390/ijms25179493 - 31 Aug 2024
Viewed by 993
Abstract
With emerging genetic association studies, new genes and pathways are revealed as causative factors in the development of Parkinson’s disease (PD). However, many of these PD genes are poorly characterized in terms of their function, subcellular localization, and interaction with other components in [...] Read more.
With emerging genetic association studies, new genes and pathways are revealed as causative factors in the development of Parkinson’s disease (PD). However, many of these PD genes are poorly characterized in terms of their function, subcellular localization, and interaction with other components in cellular pathways. This represents a major obstacle towards a better understanding of the molecular causes of PD, with deeper molecular studies often hindered by a lack of high-quality, validated antibodies for detecting the corresponding proteins of interest. In this study, we leveraged the nanoluciferase-derived LgBiT-HiBiT system by generating a cohort of tagged PD genes in both induced pluripotent stem cells (iPSCs) and iPSC-derived neuronal cells. To promote luminescence signals within cells, a master iPSC line was generated, in which LgBiT expression is under the control of a doxycycline-inducible promoter. LgBiT could bind to HiBiT when present either alone or when tagged onto different PD-associated proteins encoded by the genes GBA1, GPNMB, LRRK2, PINK1, PRKN, SNCA, VPS13C, and VPS35. Several HiBiT-tagged proteins could already generate luminescence in iPSCs in response to the doxycycline induction of LgBiT, with the enzyme glucosylceramidase beta 1 (GCase), encoded by GBA1, being one such example. Moreover, the GCase chaperone ambroxol elicited an increase in the luminescence signal in HiBiT-tagged GBA1 cells, correlating with an increase in the levels of GCase in dopaminergic cells. Taken together, we have developed and validated a Doxycycline-inducible luminescence system to serve as a sensitive assay for the quantification, localization, and activity of HiBiT-tagged PD-associated proteins with reliable sensitivity and efficiency. Full article
(This article belongs to the Special Issue Research in iPSC-Based Disease Models)
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<p>Generation of the master Dox-inducible LgBiT iPSC line. (<b>A</b>) Examples of challenges faced by current protein detection tools. (<b>B</b>) Overview of the LgBiT-HiBiT luminescent detection system. (<b>C</b>) Outline of the method used to generate the Dox-inducible LgBiT iPSCs. (<b>D</b>) Representative 2D ddPCR profile of an edited iPSC population composed of a ratio of 0.88 of CLYBL-iLgBiT alleles (blue) vs. SYT1 alleles (endogenous control; green). (<b>E</b>) Calculation table of the ratio iLgBiT:SYT1 alleles in different edited iPSC clones. (<b>F</b>) Top: graphical representation of the Dox-inducible expression cassette inserted into intron 2 (safe-harbor locus) of <span class="html-italic">CLYBL</span>, before and after treatment with Cre recombinase to remove the Neomycin selection cassette, as well as the <span class="html-italic">CLYBL</span> wt allele (without any insertion at the safe-harbor site); bottom: electrophoresis analysis of the corresponding PCR fragments. (<b>G</b>) Transcript levels of iLgBiT in different edited iPSC clones before (black) and after (red) Dox treatments. Values are presented as mean ± SD of (n) independent experiments, where n = 3 for M1G4 and M2E3 and n = 2 for M1C6 and M1D5, each including three technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used to calculate the p-values between each Dox-treated and non-treated sample. (<b>H</b>) Luminescence assay evaluating the expression of LgBiT upon Dox treatment in our different engineered iPSC lines, expected to reconstitute the nanoluciferase activity in the presence of different concentrations of HiBiT control protein added to the lysates. Values are presented as mean ± SD of three independent experiments, each including two technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used to calculate the <span class="html-italic">p</span>-values between each Dox-treated and non-treated sample. * <span class="html-italic">p</span> &lt; 0.03; LHA: left homology arm; RHA: right homology arm; Neo<sup>R</sup>: Neomycin resistance; Kan<sup>R</sup>: Kanamycin resistance; wt: wild-type.</p>
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<p>Characterization of M2E3 iPSCs and iPSC-derived dNPCs. (<b>A</b>) G-band analysis and (<b>B</b>) qPCR-based stability test revealed normal karyotype. (<b>C</b>) ICC detection of Nanog, Tra-160, SSEA-4, and OCT3/4 in M2E3 iPSCs. Scale bar 200 μm. (<b>D</b>) Transcript levels, evaluated by RT-qPCR, of Nanog, OCT3/4, Nestin, FOXA2, EN1, TH, and LMX1 in M2E3 iPSCs and dNPCs. Values are presented as mean ± SD of three experiments, each including three technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used to compare iPSC and dNPC samples; * <span class="html-italic">p</span> &lt; 0.002. (<b>E</b>) ICC detection of SOX1, FOXA2, and Nestin in M2E3 dNPCs. (<b>F</b>) ICC co-staining of iLgBiT with OCT3/4 in M2E3 iPSCs, and (<b>G</b>) iLgBiT with Nestin in M2E3 dNPCs, treated or not with Dox. Scale bar 200 μm. (<b>H</b>) Transcript levels, evaluated by RT-qPCR, of iLgBiT in M2E3 iPSCs and dNPCs, treated or not with Dox. Values are presented as mean ± SD of three experiments, each including three technical replicates. Two-way ANOVA followed by Bonferroni test was used to compare Dox and no Dox; * <span class="html-italic">p</span> &lt; 0.002. (<b>I</b>) Bar graph showing luminescence assay readout in M2E3 dNPCs, with 0 nM, 0.4 nM, or 40 nM HiBiT control protein, or LgBiT control protein 1/100, added to the lysates, after treatment with Dox or no. Relative light unit (RLU) values are presented as mean ± SD of 2 independent experiments, each including 2 technical replicates; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Generation of the HiBiT knock-in iPSC lines. (<b>A</b>) Outline of the method used to generate HiBiT-tagged genes in Dox-inducible LgBiT iPSCs, in order to produce luminescence. (<b>B</b>) Representative 2D ddPCR profile of a HiBiT knock-in iPSC population composed of a ratio ~1.0 of HiBiT alleles (blue) vs. SYT1 alleles (endogenous control; green). (<b>C</b>) Bar graph presenting the allele ratio HiBiT:SYT1, as measured by ddPCR, for each HiBiT knock-in iPSC clone isolated. Values are presented as mean ± SD of one experiment, including five technical replicates for GBA1-HiBiT, three for GPNMB-HiBiT, PINK1-HiBiT, PRKN-HiBiT, VPS13C-HiBiT, and one for the others. For each HiBiT-tagged line, between 24 and 32 separate clones were screened before finding at least one fully edited. (<b>D</b>) Sanger sequencing chromatograms depicting the insertion site of HiBiT (pink sequence), right before the stop codon (red frame), or right after the start codon (green frame), for each HiBiT knock-in iPSC clone isolated. Note that PINK1-HiBiT is the only one with an unclear sequence profile, probably composed of one HiBiT allele and one wt and/or indel allele. (<b>E</b>) Bar graph showing luminescence assay readout in master M2E3 iPSC line, as well as in the different HiBiT knock-in iPSC lines, treated (+) or not (−) with Dox. Raw relative light units (RLU) values are presented as mean ± SD of one experiment, including 3 technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used to calculate the <span class="html-italic">p</span>-values between each Dox-treated and non-treated samples; * <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Characterization of GBA1-HiBiT iPSCs and iPSC-derived dNPCs. (<b>A</b>) G-band analysis and (<b>B</b>) qPCR-based stability test revealed normal karyotype. (<b>C</b>) ICC detection of Nanog, Tra-160, SSEA-4, and OCT3/4 in GBA1-HiBiT iPSCs. Scale bar 200 µm. (<b>D</b>) Transcript levels, evaluated by RT-qPCR of Nanog, OCT3/4, Nestin, FOXA2, EN1, and TH in GBA1-HiBiT iPSCs and dNPCs. Values are presented as mean ± SD of three experiments, each including three technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used to compare iPSC and dNPC samples; * <span class="html-italic">p</span> &lt; 0.0001. (<b>E</b>) ICC detection of SOX1, FOXA2, and Nestin in GBA1-HiBiT dNPCs. (<b>F</b>) ICC co-staining of iLgBiT with OCT3/4 in GBA1-HiBiT iPSCs, and (<b>G</b>) iLgBiT with Nestin in GBA1-HiBiT dNPCs, treated or not with Dox; scale bar 200 µm. (<b>H</b>) Transcript levels evaluated by RT-qPCR of iLgBiT in GBA1-HiBiT iPSCs and dNPCs, treated or not with Dox. Values are presented as mean ± SD of three experiments, each including three technical replicates. Two-way ANOVA followed by Bonferroni test was used to compare Dox and no Dox; * <span class="html-italic">p</span> &lt; 0.0001. (<b>I</b>) Transcript levels, evaluated by RT-qPCR of GBA1-HiBiT in GBA1-HiBiT iPSCs and dNPCs, treated or not with Dox. Two-way ANOVA followed by Bonferroni test. Values are presented as mean ± SD of three experiments, each including three technical replicates. Two-way ANOVA followed by Bonferroni test was used to compare Dox and no Dox; * <span class="html-italic">p</span> &lt; 0.05. (<b>J</b>) ICC detection of GCase, HiBiT, iLgBiT, and GAPDH in GBA1-HiBiT iPSCs and dNPCs, treated or not with Dox.</p>
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<p>Functional validation of LgBiT-HiBiT system with a chaperone of GCase, Ambroxol, in M2E3 and GBA1-HiBiT, dNPCs, and DNs. (<b>A</b>) Luminescence measurement in M2E3 and GBA1-HiBiT dNPCs and (<b>B</b>) in 1-week DNs following a 6-day treatment with 70 μM Ambroxol. iLgBiT expression was induced by a 2-day Dox treatment in dNPCs and DNs and the addition of LgBiT recombinant protein in DNs. Relative light unit (RLU) values were normalized to DMSO conditions and presented as mean ± SD of four independent experiments, each including two technical replicates. Statistical comparisons were made using one-way ANOVA followed by Bonferroni test; * <span class="html-italic">p</span> &lt; 0.03. (<b>C</b>) 4-MUG kinetic assay for GCase enzyme activity in GBA1-HiBiT 1-week old DNs, treated or not with 70 μM Ambroxol for 6 days. Values are presented as mean ± SD of two independent experiments, each including two technical replicates. Two-tailed paired <span class="html-italic">t</span>-test was used for comparison; * <span class="html-italic">p</span> &lt; 0.03.</p>
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26 pages, 11651 KiB  
Article
The GBA1 K198E Variant Is Associated with Suppression of Glucocerebrosidase Activity, Autophagy Impairment, Oxidative Stress, Mitochondrial Damage, and Apoptosis in Skin Fibroblasts
by Laura Patricia Perez-Abshana, Miguel Mendivil-Perez, Marlene Jimenez-Del-Rio and Carlos Velez-Pardo
Int. J. Mol. Sci. 2024, 25(17), 9220; https://doi.org/10.3390/ijms25179220 - 25 Aug 2024
Viewed by 1031
Abstract
Parkinson’s disease (PD) is a multifactorial, chronic, and progressive neurodegenerative disorder inducing movement alterations as a result of the loss of dopaminergic (DAergic) neurons of the pars compacta in the substantia nigra and protein aggregates of alpha synuclein (α-Syn). Although its etiopathology agent [...] Read more.
Parkinson’s disease (PD) is a multifactorial, chronic, and progressive neurodegenerative disorder inducing movement alterations as a result of the loss of dopaminergic (DAergic) neurons of the pars compacta in the substantia nigra and protein aggregates of alpha synuclein (α-Syn). Although its etiopathology agent has not yet been clearly established, environmental and genetic factors have been suggested as the major contributors to the disease. Mutations in the glucosidase beta acid 1 (GBA1) gene, which encodes the lysosomal glucosylceramidase (GCase) enzyme, are one of the major genetic risks for PD. We found that the GBA1 K198E fibroblasts but not WT fibroblasts showed reduced catalytic activity of heterozygous mutant GCase by −70% but its expression levels increased by 3.68-fold; increased the acidification of autophagy vacuoles (e.g., autophagosomes, lysosomes, and autolysosomes) by +1600%; augmented the expression of autophagosome protein Beclin-1 (+133%) and LC3-II (+750%), and lysosomal–autophagosome fusion protein LAMP-2 (+107%); increased the accumulation of lysosomes (+400%); decreased the mitochondrial membrane potential (∆Ψm) by −19% but the expression of Parkin protein remained unperturbed; increased the oxidized DJ-1Cys106-SOH by +900%, as evidence of oxidative stress; increased phosphorylated LRRK2 at Ser935 (+1050%) along with phosphorylated α-synuclein (α-Syn) at pathological residue Ser129 (+1200%); increased the executer apoptotic protein caspase 3 (cleaved caspase 3) by +733%. Although exposure of WT fibroblasts to environmental neutoxin rotenone (ROT, 1 μM) exacerbated the autophagy–lysosomal system, oxidative stress, and apoptosis markers, ROT moderately increased those markers in GBA1 K198E fibroblasts. We concluded that the K198E mutation endogenously primes skin fibroblasts toward autophagy dysfunction, OS, and apoptosis. Our findings suggest that the GBA1 K198E fibroblasts are biochemically and molecularly equivalent to the response of WT GBA1 fibroblasts exposed to ROT. Full article
(This article belongs to the Special Issue Autophagy in Health, Aging and Disease, 4th Edition)
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<p>Enzyme activity and expression levels of glucocerebrosidase (GCase) in fibroblasts bearing the mutation GBA1 K198E with in silico molecular docking of glucosylsphingosine (GlcSph) and GCase. (<b>A</b>) Enzyme activity of GCase activity in WT GBA1 (blue bar) and GBA1 K198E fibroblasts (red bar). (<b>B</b>) Protein expression levels of glucocerebrosidase (GCase) in WT GBA1 (blue curve) and GBA1 K198E fibroblasts (red curve) assessed by flow cytometry. (<b>C</b>) Quantification of GCase expression levels. Numbers in histograms represent positive cellular population for the tested marker. (<b>D</b>) Representative CB-Dock2 3D images showing the molecular docking of WT GCase (created by Alphafold2) with GlcSph (PubChem CID: 5280570). (<b>E</b>) Representative enlarged image of (<b>D</b>) showing the molecular docking of WT GCase with GlcSph. (<b>F</b>) Two-dimensional diagram showing conventional hydrogen bond between GCaseGlcSph interaction. (<b>G</b>) Representative CB-Dock2 3D images showing the molecular docking of WT GCase with conduritol-B-epoxide (CBE, CID: 136345). (<b>H</b>) Representative enlarged image of (G) showing the molecular docking of WT GCase with CBE. The data are presented as mean ± SD of two independent experiments in triplicated (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>GBA1 K198E variant induces acute GCase deficiency in the autophagy–lysosome system reflected as acidification of autophagosomes, lysosomes, and autolysosomes in untreated or treated fibroblast with rapamycin (RAP) or bafilomycin A1 (BAF). (<b>A</b>) Representative flow cytometry histograms showing the autophagy–lysosome acidification in untreated WT (blue curve) and GBA1 K198E fibroblasts (red curve), (<b>B</b>) WT and GBA1 K198E fibroblasts treated with rapamycin (RAP, 10 nM) or (<b>C</b>) bafilomycin A1 (BAF, 10 nM). (<b>D</b>) Quantitative analysis of autophagy–lysosome (acidification)-positive cells. (<b>E</b>–<b>G</b>) Representative immunofluorescence images showing autophagy–lysosome acidification in (<b>E</b>) untreated WT fibroblasts, (<b>F</b>) treated with rapamycin (RAP, 10 nM) or (<b>G</b>) treated bafilomycin A1 (BAF, 10 nM). (<b>H</b>–<b>J</b>) Representative immunofluorescence images showing autophagy–lysosome acidification in (<b>H</b>) untreated GBA1 K198E fibroblasts, (<b>I</b>) treated with rapamycin (RAP, 10 nM) or (<b>J</b>) treated bafilomycin A1 (BAF, 10 nM). (<b>K</b>) Quantitative analysis of autophagy lysosome as mean fluorescence intensity (MFI). Numbers in histograms represent positive cellular population for the tested marker. The histograms and photomicrographs represent 1 out of 3 independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; ns = not significant. Image magnification: 200×.</p>
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<p>GBA1 K198E variant upregulates expression of autophagic Beclin-1, LC3-II, and LAMP-2 proteins in fibroblasts. (<b>A</b>) Representative flow cytometry histogram analysis showing Beclin-1 expression in WT-GBA1 (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Quantitative (%) analysis of Beclin-1 expression in WT (<b>blue bar</b>) and GBA1 K198E fibroblast (red bar); (<b>C</b>) representative immunofluorescence image showing Beclin-1 reactivity in WT GBA1 and (<b>D</b>) K198E GBA1 fibroblasts (red fluorescence). (<b>E</b>) Quantitative (MFI) analysis of Beclin-1. (<b>F</b>) Representative flow cytometry histogram analysis showing LC3-II expression in WT GBA1 (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>G</b>) Quantitative analysis of LC3-II in WT (blue bar) and GBA1 K198E fibroblasts (red bar). (<b>H</b>) Representative immunofluorescence images showing LCIII-2 reactivity in fibroblasts WT-GBA1 and (<b>I</b>) GBA1 K198E fibroblasts (red fluorescence). (<b>J</b>) Quantitative analysis of LC3-II. (<b>K</b>) Representative flow cytometry histogram analysis showing LAMP-2 expression in WT-GBA1 (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>L</b>) Quantitative analysis of LAMP-2 in WT (blue bar) and GBA1 K198E fibroblasts (red bar). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>M</b>) Representative immunofluorescence images showing LAMP-2 reactivity in fibroblasts WT GBA1 and (<b>N</b>) GBA1 K198E fibroblasts (red fluorescence). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>O</b>) Quantitative analysis of LAMP-2. Numbers in histograms represent positive cellular population for the tested marker. Histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Image magnification; 200×.</p>
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<p>GBA1 K198E variant increases the accumulation of lysosomes and decreases the mitochondrial membrane potential (∆Ψm) in mutant fibroblasts, while rotenone aggravates the damage. (<b>A</b>) Representative flow cytometry histogram showing WT (blue curve) or GBA1 K198E fibroblasts (red curve) stained with Lysotracker<sup>®</sup>. (<b>B</b>) Representative flow cytometry histogram showing WT (blue curve) or GBA1 K198E fibroblasts (red curve) exposed to rotenone (ROT, 1 μM) and stained with Lysotracker<sup>®</sup>. (<b>C</b>) Percentage of Lysotracker<sup>®</sup> stain-positive cells in untreated or treated WT (blue bar) and GBA1 K198E fibroblasts (red bar) with ROT. (<b>D</b>) Representative flow cytometry histogram showing WT (blue curve) or GBA1 K198E fibroblasts (red curve) stained with Mitotracker<sup>®</sup>. (<b>E</b>) Representative flow cytometry histogram showing WT (blue curve) or GBA1 K198E fibroblasts (red curve) exposed to rotenone (ROT, 1 μM) stained with Mitotracker<sup>®</sup>. (<b>F</b>) Percentage of Mitotracker<sup>®</sup> stain-positive cells in untreated or treated WT (blue bar) and GBA1 K198E fibroblasts (red bar) with ROT. (<b>G</b>) Representative fluorescence microscopy image showing untreated WT fibroblasts stained with Lysotracker<sup>®</sup> and Mitotracker<sup>®</sup> (red fluorescence), (<b>G’</b>) close-up of image G (white line square); (<b>H</b>) representative fluorescence microscopy image showing untreated GBA1 K198E fibroblasts stained with Lysotracker<sup>®</sup> (green fluorescence) and Mitotracker<sup>®</sup> (red fluorescence). (<b>H’</b>) Close-up of image H (white line square); (<b>I</b>) representative fluorescence microscopy photograph showing WT fibroblasts treated with ROT (1 μM) and stained with Lysotracker<sup>®</sup> (green fluorescence) and Mitotracker<sup>®</sup> (red fluorescence), (<b>I’</b>) close-up of image I (white line square); (<b>J</b>) representative fluorescence microscopy photograph showing GBA1 K198E fibroblasts treated with ROT (1 μM) and stained with Lysotracker<sup>®</sup> (green fluorescence) and Mitotracker<sup>®</sup>. (<b>J’</b>) Close-up of image J (white line square). (<b>K</b>) Quantification of the Lysotracker<sup>®</sup> mean fluorescence intensity (MFI) in untreated or treated WT (blue bar) and GBA1 K198E fibroblasts (red bar) with ROT. (<b>L</b>) Quantification of the MitoTracker<sup>®</sup> high mean fluorescence intensity (MFI) in untreated or treated WT (blue bar) and GBA1 K198E fibroblasts (red bar) with ROT. Nuclei were stained with Hoechst 33342 (blue fluorescence). Histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Image magnification, 200×. ns = not significant.</p>
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<p>GBA1 K198E fibroblasts show unchanged expression levels of Parkin and mitochondrial colocalization of Parkin and TOM20 proteins, but Parkin shows a tendency to increase and mitochondrial colocalization upon rotenone exposure. (<b>A</b>) Representative flow cytometry histogram analysis showing the expression of Parkin protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Representative flow cytometry histogram analysis showing the expression of Parkin protein in WT (blue) and GBA1 K198E fibroblasts (red) upon rotenone (ROT, 1 μM) exposure. (<b>C</b>) Quantitative analysis of parkin expression. (<b>D</b>–<b>G</b>) Representative fluorescence merge density images of colocalization of Parkin and the translocase of the outer membrane of mitochondria 20 (TOM20) proteins in (<b>D</b>) WT fibroblasts (white fluorescence), (<b>E</b>) GBA1 K198E fibroblasts, (<b>F</b>) WT fibroblasts treated with rotenone (ROT, 1 μM), and (<b>G</b>) GBA1 K198E fibroblasts exposed to ROT (1 μM). (<b>D’</b>–<b>G’</b>) Representative fluorescence merge images in layer colocalization of Parkin (<b>D’’</b>–<b>G’</b>’, green fluorescence) with TOM20 proteins (<b>D’’’</b>–<b>G”’</b>, red fluorescence). Nuclei were stained with Hoechst 33342 (blue, <b>F’’’’</b>–<b>G’”’</b>). (<b>H</b>) Quantification of the Parkin/mitochondria mean fluorescence intensity (MFI). Flow cytometry histograms represent one out of three conducted experiments. The results are reported as the mean ± standard deviation of 3 independent experiments (dots in bar). Fluorescence microphotographs represent one out of three experiments (n=3). A one-way ANOVA, followed by Tukey’s test, was conducted for statistical analysis. Statistically significant variations are indicated by * <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; ns = no significance.</p>
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<p>GBA1 K198E fibroblasts show an endogenously high percentage of oxidized DJ-1-Cys106-SOH into DJ-1 Cys106SO<sub>3</sub>. (<b>A</b>) Representative flow cytometry histogram analysis showing oxidized DJ-1 (Cys106-SO<sub>3</sub>) protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Representative flow cytometry histogram analysis showing oxidized DJ-1 (Cys106-SO<sub>3</sub>) protein in WT (blue color) and GBA1 K198E fibroblasts (red color) upon rotenone (ROT, 1 μM) exposure. Flow cytometry histograms represent one out of three conducted experiments. The results are reported as the mean ± standard deviation of 3 independent experiments. (<b>C</b>) Quantitative analysis of oxidized DJ-1 (Cys106-SO<sub>3</sub>) protein. (<b>D</b>) Representative immunofluorescence image showing oxidized DJ-1 protein (Cys106-SO<sub>3,</sub> green fluorescence) in WT GBA1 fibroblasts. (<b>E</b>) Representative immunofluorescence image showing oxidized DJ-1 protein (Cys106-SO<sub>3,</sub> green fluorescence) in GBA1 K198E fibroblasts. (<b>F</b>) Representative fluorescence microscopy image showing oxidized DJ-1 protein (Cys106-SO<sub>3,</sub> green fluorescence) in WT GBA1 fibroblast treated with ROT (1 μM). (<b>G</b>) Representative fluorescence microscopy image showing oxidized DJ-1 (Cys106-SO<sub>3,</sub> green fluorescence) protein in GBA1 K198E fibroblast treated with ROT (1 μM). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>H</b>) Quantitative analysis of oxidized DJ-1 protein (Cys106-SO<sub>3</sub>). Numbers in histograms represent positive cellular population for the tested marker. The histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; ns = not significance. Image magnification: 200×.</p>
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<p>GBA1 K198E fibroblasts show an endogenously high percentage of phosphorylated LRRK2 at Ser935. (<b>A</b>) Representative flow cytometry histogram analysis showing phosphorylated LRRK2 at Ser935 protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Representative flow cytometry histogram analysis showing pSer935 LRRK2 protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve) upon rotenone (ROT, 1 μM) exposure. (<b>C</b>) Quantitative analysis of pSer935 LRRK2 protein. (<b>D</b>) Representative immunofluorescence image showing pSer935 LRRK2 protein (green fluorescence) in WT GBA1 fibroblasts. (<b>E</b>) Representative immunofluorescence image showing pSer935 LRRK2 protein (green fluorescence) in GBA1 K198E fibroblasts. (<b>F</b>) Representative fluorescence microscopy image showing pSer935 LRRK2 protein (green fluorescence) in WT GBA1 fibroblast treated with ROT (1 μM). (<b>G</b>) Representative fluorescence microscopy image showing pSer935 LRRK2 protein (green fluorescence) protein in GBA1 K198E fibroblast treated with ROT (1 μM). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>H</b>) Quantitative analysis of pSer935 LRRK2 protein. Numbers in histograms represent positive cellular population for the tested marker. The histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: * <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Image magnification: 200×.</p>
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<p>GBA1 K198E fibroblasts show an endogenously high percentage of phosphorylated α-Syn at Ser129. (<b>A</b>) Representative flow cytometry histogram analysis showing phosphorylated α-Syn at Ser129 protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Representative flow cytometry histogram analysis showing pSer129 α-Syn protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve) upon rotenone (ROT, 1 μM) exposure. (<b>C</b>) Quantitative analysis of pSer129 α-Syn protein. (<b>D</b>) Representative immunofluorescence image showing pSer129 α-Syn protein (green fluorescence) in WT GBA1 fibroblasts. (<b>E</b>) Representative immunofluorescence image showing pSer129 α-Syn protein (green fluorescence) in GBA1 K198E fibroblasts. (<b>F</b>) Representative fluorescence microscopy image showing pSer129 α-Syn protein (green fluorescence) in WT GBA1 fibroblast treated with ROT (1 μM). (<b>G</b>) Representative fluorescence microscopy image showing pSer129 α-Syn protein (green fluorescence) in GBA1 K198E fibroblast treated with ROT (1 μM). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>H</b>) Quantitative analysis of pSer129 α-Syn protein. Numbers in histograms represent positive cellular population for the tested marker. The histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Image magnification: 200×.</p>
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<p>GBA1 K198E fibroblasts show endogenously high cleaved caspase 3 (CC3) compared to WT fibroblasts. (<b>A</b>) Representative flow cytometry histogram analysis showing cleaved caspase 3 (CC3) protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve). (<b>B</b>) Representative flow cytometry histogram analysis showing CC3 protein in WT (blue curve) and GBA1 K198E fibroblasts (red curve) upon rotenone (ROT, 1 μM) exposure. (<b>C</b>) Quantitative analysis of CC3 protein. (<b>D</b>) Representative immunofluorescence image showing CC3 protein (green fluorescence) in WT GBA1 fibroblasts. (<b>E</b>) Representative immunofluorescence image showing CC3 protein (green fluorescence) in GBA1 K198E fibroblasts. (<b>F</b>) Representative fluorescence microscopy image showing CC3 protein (green fluorescence) in WT GBA1 fibroblast treated with ROT (1 μM). (<b>G</b>) Representative fluorescence microscopy image showing CC3 protein (green fluorescence) protein in GBA1 K198E fibroblast treated with ROT (1 μM). Nuclei were stained with Hoechst 33342 (blue fluorescence). (<b>H</b>) Quantitative analysis of CC3 protein. Numbers in histograms represent positive cellular population for the tested marker. The histograms and photomicrographs represent one out of three independent experiments (n = 3). The data are presented as mean ± SD of three independent experiments (dots in bar). One-way ANOVA followed by Tukey’s test. Statistically significant differences: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. Image magnification: 200×.</p>
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<p>Schematic representation of the effect of K198E GCase on the autophagy–lysosomal pathway and apoptosis cell death in skin fibroblasts. (<b>A</b>) <span class="html-italic">Autophagy–lysosomal pathway and K198E GCase.</span> In WT GBA1 fibroblasts, the autophagy process begins with the ensemble of the ULK1 complex (unc-51-like kinase, ULK; autophagy-related protein 13, ATG13; RB1-inducible coiled-coil protein 1, FIP200; ATG101) (<b>1</b>), which then triggers nucleation of the phagophore (<b>2</b>) by phosphorylating components of the class III PI3K complex, involving Class IIIPI3K, vacuolar protein sorting 34 (VPS34) and Beclin 1 (Bc 1), among other proteins. These actions lead to the attachment of the microtubule-associated protein light chain 3 (LC3-II) to the phagophore (<b>3</b>), which further expand and form a sealed double-membrane, forming the autophagosome (<b>4</b>). This last vacuole, helped by lysosomal-associated membrane protein (LAMP-2, <b>5</b>), fused with the lysosome (<b>6</b>) to form the autolysosome (<b>7</b>), where unwanted cytosolic material (damaged mitochondria, protein aggregates, GlcCer (black dots)) is eliminated and recycled. On the other hand, enzymatic alteration of GCase mainly by genetic mutations (e.g., K198E) in at least one of the alleles of GBA1 almost leads to the undigested substrate GlcCer. As a result, lysosomes accumulate, thereby affecting the production line of autophagosomes, and autolysosomes. Indeed, heterozygous K198E GCase induces abnormal upregulation of protein Beclin 1, LC3-II and LAMP-2, and provokes an abnormally high accumulation of autophagosomes, lysosomes, and autolysosomes. Overall, K198E GCase provokes a highly deficient autophagy–lysosomal pathway in skin fibroblasts. (<b>B</b>) <span class="html-italic">Apoptosis pathway and K198E GCase.</span> In parallel, WT GCase interacts the mitochondrial respiratory component complex I (<b>8</b>, upper panel), thereby preserving energy metabolism (e.g., high ∆Ψm) and mitochondrial and nuclei integrity (<b>14</b>, upper panel). On the contrary, malfunction of mitochondrial Complex I due to improper interactions with K198E GCase (<b>8</b>, lower panel) allows electrons to leak, which are taken by molecular dioxygen (O2). Reduction of oxygen ends up in the formation of anion superoxide radicals (O2.-), which then dismutate into H2O2 (<b>9</b>). As a messenger molecule, H2O2 oxidized DJ-1Cys106-SOH (DJ-1red, <b>10</b>) into DJ-1Cys106-SO3 (-<span class="html-italic">sulfonic</span> group, DJ-1oxi, <b>11</b>) and induces the activation of the IKK complex (<b>10</b>), which phosphorylates LRRK2 at residue Ser935 (<b>11</b>). Phosphorylated LRRK2 kinase phosphorylates in turn the following three main targets: DLP-1 (dynamin-like protein), αSyn at residue Ser129, and PRDX3 (<b>12</b>). These three proteins might induce or contribute to mitochondria depolarization (e.g., low ∆Ψm), thereby inducing activation of caspase 3 (CASP3) into cleaved caspase 3 (CC3, <b>13</b>). Lastly, CC3 induces the fragmentation of nuclei (<b>14</b>). All these markers constitute typical signs of apoptosis (<b>8</b>–<b>14</b>).</p>
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15 pages, 3083 KiB  
Article
Carbon Accounting for Permeable Pavement Based on the Full Life Cycle Approach and Its Application
by Lu Wang, Zhiyuan Shao, Xurui Zhang and Yafei Wang
Sustainability 2024, 16(17), 7293; https://doi.org/10.3390/su16177293 - 24 Aug 2024
Viewed by 682
Abstract
Conventional pavement in aging communities requires renovation in alignment with global carbon reduction initiatives. This study, centered on upgrading facilities in Guangdong, Hong Kong, and the Macao Greater Bay Area (GBA), utilized the Energy Expert platform to assess the carbon footprint of permeable [...] Read more.
Conventional pavement in aging communities requires renovation in alignment with global carbon reduction initiatives. This study, centered on upgrading facilities in Guangdong, Hong Kong, and the Macao Greater Bay Area (GBA), utilized the Energy Expert platform to assess the carbon footprint of permeable pavement using life cycle assessment (LCA). The results revealed that the total carbon emission of the 64,065 m2 permeable pavement was 7066.21 tCO2eq. The carbon emission contribution, from highest to lowest, was the production phase, maintenance phase, end-of-life phase, and construction phase. Notably, transportation alone constituted a substantial portion, amounting to 30.15% of total carbon emissions. Compared to traditional pavements, permeable pavement showcased substantial potential for carbon reduction, primarily during the use phase, by enhancing groundwater recharge and mitigating the urban heat island effect, which is critical in reducing the carbon footprint. The estimated total carbon reduction was 853.10 tCO2eq. Sensitivity analysis highlighted diesel energy use in the maintenance phase (51.20%), transportation of cement raw materials in the production phase (45.80%), and transportation of graded gravel for disposal in the end-of-life phase (3.00%) as key factors. Our findings suggest that adopting specific carbon reduction measures, such as substituting gangue for cement binder, transitioning to manual sweeping, and recycling all discarded materials can achieve notable reductions in the respective phases. These findings contribute to a deeper understanding of the role of permeable pavement in reducing carbon emissions, providing insights for the renovation of aging communities. Full article
(This article belongs to the Special Issue Advances in Ecosystem Services and Urban Sustainability, 2nd Edition)
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<p>System boundary settings for the LCA of permeable pavement.</p>
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<p>The design of permeable pavement structure (self-drawn by the author).</p>
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<p>Permeable pavement LCA carbon emission inventory contribution. (<b>a</b>) Carbon emission contribution for each phase of permeable pavement; (<b>b</b>) Carbon emission contribution for various types of permeable pavement; (<b>c</b>) Carbon emission contribution of permeable pavement LCA list items in their phases.</p>
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<p>Carbon reduction benefits of permeable pavement.</p>
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<p>Comparison of carbon emissions before and after different carbon reduction measures. (<b>a</b>) Replace raw materials with fly ash and coal gangue, respectively, in the production phase; (<b>b</b>) Adopt the maintenance method of high-pressure washing combined with low-pressure suction in the maintenance phase; (<b>c</b>) Recycle materials in the end-of-life phase.</p>
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<p>Comparison of carbon reduction effects among manufacture, maintenance, and end-of-life phases. (<b>a</b>) Direct comparison of carbon reductions in each phase; (<b>b</b>) Comparison of carbon reduction percentages in each phase.</p>
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<p>Comparison of comprehensive optimization simulation and use-phase carbon reduction.</p>
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12 pages, 1729 KiB  
Article
Neurosteroid Levels in GBA Mutated and Non-Mutated Parkinson’s Disease: A Possible Factor Influencing Clinical Phenotype?
by Francesco Cavallieri, Chiara Lucchi, Sara Grisanti, Edoardo Monfrini, Valentina Fioravanti, Giulia Toschi, Giulia Di Rauso, Jessica Rossi, Alessio Di Fonzo, Giuseppe Biagini and Franco Valzania
Biomolecules 2024, 14(8), 1022; https://doi.org/10.3390/biom14081022 - 17 Aug 2024
Viewed by 620
Abstract
Neurosteroids are pleiotropic molecules involved in various neurodegenerative diseases with neuroinflammation. We assessed neurosteroids’ serum levels in a cohort of Parkinson’s Disease (PD) patients with heterozygous glucocerebrosidase (GBA) mutations (GBA-PD) compared with matched cohorts of consecutive non-mutated PD (NM-PD) patients and healthy subjects [...] Read more.
Neurosteroids are pleiotropic molecules involved in various neurodegenerative diseases with neuroinflammation. We assessed neurosteroids’ serum levels in a cohort of Parkinson’s Disease (PD) patients with heterozygous glucocerebrosidase (GBA) mutations (GBA-PD) compared with matched cohorts of consecutive non-mutated PD (NM-PD) patients and healthy subjects with (GBA-HC) and without (NM-HC) GBA mutations. A consecutive cohort of GBA-PD was paired for age, sex, disease duration, Hoehn and Yahr stage, and comorbidities with a cohort of consecutive NM-PD. Two cohorts of GBA-HC and HC were also considered. Clinical assessment included the Movement Disorder Society revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the Montreal Cognitive Assessment (MoCA). Serum samples were processed and analyzed by liquid chromatography coupled with the triple quadrupole mass spectrometry. Twenty-two GBA-PD (males: 11, age: 63.68), 22 NM-PD (males: 11, age: 63.05), 14 GBA-HC (males: 8; age: 49.36), and 15 HC (males: 4; age: 60.60) were studied. Compared to NM-PD, GBA-PD showed more hallucinations and psychosis (p < 0.05, Fisher’s exact test) and higher MDS-UPDRS part-II (p < 0.05). Most of the serum neurosteroids were reduced in both GBA-PD and NM-PD compared to the respective control cohorts, except for 5α-dihydroprogesterone. Allopregnanolone was the only neurosteroid significantly lower (p < 0.01, Dunn’s test) in NM-PD compared to GBA-PD patients. Only in GBA-PD, allopregnanolone, and pregnanolone levels correlated (Spearman) with a more severe MDS-UPDRS part-III. Allopregnanolone levels also negatively correlated with MoCA scores, and pregnanolone levels correlated with more pronounced bradykinesia. This pilot study provides the first observation of changes in neurosteroid peripheral levels in GBA-PD. The involvement of the observed changes in the development of neuropsychological and motor symptoms of GBA-PD deserves further attention. Full article
(This article belongs to the Special Issue Role of Neuroactive Steroids in Health and Disease: 2nd Edition)
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<p>Levels of different neurosteroids (NSs) were measured in the serum of GBA-HC, NM-HC, GBA-PD, and NM-PD patients. Data obtained for the investigated NSs were ordered according to their metabolic processing. All data are represented as mean ± standard error of the mean (SEM) and were compared using the Kruskal-Wallis one-way analysis of variance (ANOVA) on ranks, followed by Dunn’s test for multiple comparisons. The inserts show that NS act differently on the γ-aminobutyric acid A (GABA<sub>A</sub>) receptor. Pregnenolone and 5α–DHP did not affect the activity of GABA<sub>A</sub> receptors. Progesterone and its metabolites allopregnanolone and pregnanolone act in a rapid, non-genomic manner to enhance the function of GABA<sub>A</sub> receptors. Pregnenolone sulfate reduces the responses of GABA<sub>A</sub> receptors [<a href="#B13-biomolecules-14-01022" class="html-bibr">13</a>,<a href="#B14-biomolecules-14-01022" class="html-bibr">14</a>]. Significance: Pregnenolone, **** <span class="html-italic">p</span> &lt; 0.0001 GBA-HC vs. GBA-PD and NM-PD patients, **** <span class="html-italic">p</span> &lt; 0.0001 NM-HC vs. GBA-PD and NM-PD patients; Progesterone, **** <span class="html-italic">p</span> &lt; 0.0001 GBA-HC vs. GBA-PD and NM-PD patients, **** <span class="html-italic">p</span> &lt; 0.0001 NM-HC vs. GBA-PD and NM-PD patients; Pregnenolone sulfate, **** <span class="html-italic">p</span> &lt; 0.0001 GBA-HC vs. GBA-PD and NM-PD patients, **** <span class="html-italic">p</span> &lt; 0.0001 NM-HC vs. GBA-PD, ** <span class="html-italic">p</span> &lt; 0.001 NM-HC vs. NM-PD; 5α–DHP, ** <span class="html-italic">p</span> &lt; 0.001 GBA-HC vs. NM-PD; Pregnanolone, **** <span class="html-italic">p</span> &lt; 0.0001 GBA-HC vs. GBA-PD and NM-PD patients, **** <span class="html-italic">p</span> &lt; 0.0001 NM-HC vs. GBA-PD and NM-PD patients; Allopregnanolone, **** <span class="html-italic">p</span> &lt; 0.0001 GBA-HC vs. NM-PD patients, ** <span class="html-italic">p</span> &lt; 0.01 GBA-HC vs. GBA-PD patients, **** <span class="html-italic">p</span> &lt; 0.0001 NM-HC vs. NM-PD patients, ** <span class="html-italic">p</span> &lt; 0.01 GBA-PD vs. NM-PD.</p>
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<p>Comparison of PD clinical features between GBA-PD and NM-PD subgroups (<b>A</b>–<b>C</b>). The GBA-PD cohort showed a significant increment in hallucinations and psychosis symptoms. No differences emerged in depression and anxiety disorders. All data are represented as a percentage and were compared by using the Fisher’s exact test. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlations between neurosteroid serum levels and clinical features in GBA-PD patients. (<b>A</b>) In panel A, a significant positive correlation between allopregnanolone serum levels and the MDS-UPDRS III score was found. Also, pregnanolone (<b>B</b>) significantly correlates with the MDS-UPDRS III score. In panel (<b>C</b>), the negative correlation between allopregnanolone and MoCA proves that GBA-PD patients have a worse cognitive state when higher serum levels of allopregnanolone are present. Conversely, Panel (<b>D</b>) showed a significant positive correlation between pregnanolone levels and bradykinesia subscore. The correlations were performed by using the Spearman’s coefficient.</p>
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14 pages, 728 KiB  
Review
Role of Lipids in the Pathogenesis of Parkinson’s Disease
by Shumpei Kamano, Daisaku Ozawa, Kensuke Ikenaka and Yoshitaka Nagai
Int. J. Mol. Sci. 2024, 25(16), 8935; https://doi.org/10.3390/ijms25168935 - 16 Aug 2024
Viewed by 1070
Abstract
Aggregation of α-synuclein (αSyn) and its accumulation as Lewy bodies play a central role in the pathogenesis of Parkinson’s disease (PD). However, the mechanism by which αSyn aggregates in the brain remains unclear. Biochemical studies have demonstrated that αSyn interacts with lipids, and [...] Read more.
Aggregation of α-synuclein (αSyn) and its accumulation as Lewy bodies play a central role in the pathogenesis of Parkinson’s disease (PD). However, the mechanism by which αSyn aggregates in the brain remains unclear. Biochemical studies have demonstrated that αSyn interacts with lipids, and these interactions affect the aggregation process of αSyn. Furthermore, genetic studies have identified mutations in lipid metabolism-associated genes such as glucocerebrosidase 1 (GBA1) and synaptojanin 1 (SYNJ1) in sporadic and familial forms of PD, respectively. In this review, we focus on the role of lipids in triggering αSyn aggregation in the pathogenesis of PD and propose the possibility of modulating the interaction of lipids with αSyn as a potential therapy for PD. Full article
(This article belongs to the Special Issue The Structure and Function of Synuclein)
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Figure 1

Figure 1
<p>Schematic diagram of three regions of the αSyn protein. The N-terminal region binds to lipid membranes (blue). The non-amyloid-β component (NAC) region is the core of amyloid-like fibrils (red). The C-terminal region interacts with the N-terminal and NAC regions (green). The N-terminal region has tandem repeat motifs consisting of the KTKEGV sequence. Arrowheads indicate αSyn mutations responsible for fPD.</p>
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<p>Schematic model of the aggregation process of αSyn. Lipids interact with αSyn and possibly modulate its LLPS-induced liquid droplet formation, which may eventually trigger its aggregation.</p>
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