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15 pages, 5035 KiB  
Article
Development and Optimization of a Redox Enzyme-Based Fluorescence Biosensor for the Identification of MsrB1 Inhibitors
by Hyun Bo Shim, Hyunjeong Lee, Hwa Yeon Cho, Young Ho Jo, Lionel Tarrago, Hyunggee Kim, Vadim N. Gladyshev and Byung Cheon Lee
Antioxidants 2024, 13(11), 1348; https://doi.org/10.3390/antiox13111348 - 2 Nov 2024
Viewed by 1182
Abstract
MsrB1 is a thiol-dependent enzyme that reduces protein methionine-R-sulfoxide and regulates inflammatory response in macrophages. Therefore, MsrB1 could be a promising therapeutic target for the control of inflammation. To identify MsrB1 inhibitors, we construct a redox protein-based fluorescence biosensor composed of [...] Read more.
MsrB1 is a thiol-dependent enzyme that reduces protein methionine-R-sulfoxide and regulates inflammatory response in macrophages. Therefore, MsrB1 could be a promising therapeutic target for the control of inflammation. To identify MsrB1 inhibitors, we construct a redox protein-based fluorescence biosensor composed of MsrB1, a circularly permutated fluorescent protein, and the thioredoxin1 in a single polypeptide chain. This protein-based biosensor, named RIYsense, efficiently measures protein methionine sulfoxide reduction by ratiometric fluorescence increase. We used it for high-throughput screening of potential MsrB1 inhibitors among 6868 compounds. A total of 192 compounds were selected based on their ability to reduce relative fluorescence intensity by more than 50% compared to the control. Then, we used molecular docking simulations of the compound on MsrB1, affinity assays, and MsrB1 activity measurement to identify compounds with reliable and strong inhibitory effects. Two compounds were selected as MsrB1 inhibitors: 4-[5-(4-ethylphenyl)-3-(4-hydroxyphenyl)-3,4-dihydropyrazol-2-yl]benzenesulfonamide and 6-chloro-10-(4-ethylphenyl)pyrimido[4,5-b]quinoline-2,4-dione. They are heterocyclic, polyaromatic compounds with a substituted phenyl moiety interacting with the MsrB1 active site, as revealed by docking simulation. These compounds were found to decrease the expression of anti-inflammatory cytokines such as IL-10 and IL-1rn, leading to auricular skin swelling and increased thickness in an ear edema model, effectively mimicking the effects observed in MsrB1 knockout mice. In summary, using a novel redox protein-based fluorescence biosensor, we identified potential MsrB1 inhibitors that can regulate the inflammatory response, particularly by influencing the expression of anti-inflammatory cytokines. These compounds are promising tools for understanding MsrB1’s role during inflammation and eventually controlling inflammation in therapeutic approaches. Full article
(This article belongs to the Special Issue Advances in Redox Biosensor)
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20 pages, 5032 KiB  
Article
Enhanced Learning Enriched Features Mechanism Using Deep Convolutional Neural Network for Image Denoising and Super-Resolution
by Iqra Waseem, Muhammad Habib, Eid Rehman, Ruqia Bibi, Rehan Mehmood Yousaf, Muhammad Aslam, Syeda Fizzah Jilani and Muhammad Waqar Younis
Appl. Sci. 2024, 14(14), 6281; https://doi.org/10.3390/app14146281 - 18 Jul 2024
Viewed by 1719
Abstract
Image denoising and super-resolution play vital roles in imaging systems, greatly reducing the preprocessing cost of many AI techniques for object detection, segmentation, and tracking. Various advancements have been accomplished in this field, but progress is still needed. In this paper, we have [...] Read more.
Image denoising and super-resolution play vital roles in imaging systems, greatly reducing the preprocessing cost of many AI techniques for object detection, segmentation, and tracking. Various advancements have been accomplished in this field, but progress is still needed. In this paper, we have proposed a novel technique named the Enhanced Learning Enriched Features (ELEF) mechanism using a deep convolutional neural network, which makes significant improvements to existing techniques. ELEF consists of two major processes: (1) Denoising, which removes the noise from images; and (2) Super-resolution, which improves the clarity and details of images. Features are learned through deep CNN and not through traditional algorithms so that we can better refine and enhance images. To effectively capture features, the network architecture adopted Dual Attention Units (DUs), which align with the Multi-Scale Residual Block (MSRB) for robust feature extraction, working sidewise with the feature-matching Selective Kernel Extraction (SKF). In addition, resolution mismatching cases are processed in detail to produce high-quality images. The effectiveness of the ELEF model is highlighted by the performance metrics, achieving a Peak Signal-to-Noise Ratio (PSNR) of 42.99 and a Structural Similarity Index (SSIM) of 0.9889, which indicates the ability to carry out the desired high-quality image restoration and enhancement. Full article
(This article belongs to the Special Issue Advances in Image Enhancement and Restoration Technology)
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29 pages, 1770 KiB  
Article
A Bayesian Network Model of Megaproject Social Responsibility Behavior and Project Performance: From the Perspective of Resource-Based Theory
by Yuhua Wu, Zhao Zhou, Linlin Xie, Bo Xia and Mian Huang
Buildings 2024, 14(4), 1143; https://doi.org/10.3390/buildings14041143 - 18 Apr 2024
Viewed by 1264
Abstract
Megaproject Social Responsibility (MSR) is widely acknowledged as contributing to project performance. However, the effect of Megaproject Social Responsibility Behavior (MSRB) implemented by organizations participating in construction on project performance remains a subject of considerable debate, and the intrinsic mechanism of MSRB’s effect [...] Read more.
Megaproject Social Responsibility (MSR) is widely acknowledged as contributing to project performance. However, the effect of Megaproject Social Responsibility Behavior (MSRB) implemented by organizations participating in construction on project performance remains a subject of considerable debate, and the intrinsic mechanism of MSRB’s effect on the performance of megaprojects has not been elucidated. Therefore, this study employs resource-based theory to investigate the mechanism underlying MSRB’s effect on project performance, taking into account both internal and external social capital as well as resource integration capacity as pivotal influences. Drawing on sample data from 206 experienced project managers across the various parties involved, this study develops a Bayesian network model to elucidate the MSRB effect mechanism. Through inference and sensitivity analysis, this study discovers variations in the enhancement effects across the four dimensions of MSRB on project performance. Notably, a combination strategy yields superior enhancement effects. Furthermore, when project performance is suboptimal, resource integration capacity emerges as a significant mediator between MSRB and project performance. Conversely, at high levels of project performance, MSRB directly contributes to enhancing project outcomes. The findings of this study offer valuable insights for the governance of MSR and the enhancement of project performance in megaprojects. Full article
(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings)
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18 pages, 4586 KiB  
Article
Whole-Genome Scanning for Selection Signatures Reveals Candidate Genes Associated with Growth and Tail Length in Sheep
by Taotao Li, Meilin Jin, Huihua Wang, Wentao Zhang, Zehu Yuan and Caihong Wei
Animals 2024, 14(5), 687; https://doi.org/10.3390/ani14050687 - 22 Feb 2024
Cited by 5 | Viewed by 2408
Abstract
Compared to Chinese indigenous sheep, Western sheep have rapid growth rate, larger physique, and higher meat yield. These excellent Western sheep were introduced into China for crossbreeding to expedite the enhancement of production performance and mutton quality in local breeds. Here, we investigated [...] Read more.
Compared to Chinese indigenous sheep, Western sheep have rapid growth rate, larger physique, and higher meat yield. These excellent Western sheep were introduced into China for crossbreeding to expedite the enhancement of production performance and mutton quality in local breeds. Here, we investigated population genetic structure and genome-wide selection signatures among the Chinese indigenous sheep and the introduced sheep based on whole-genome resequencing data. The PCA, N-J tree and ADMIXTURE results showed significant genetic difference between Chinese indigenous sheep and introduced sheep. The nucleotide diversity (π) and linkage disequilibrium (LD) decay results indicated that the genomic diversity of introduced breeds were lower. Then, Fst & π ratio, XP-EHH, and de-correlated composite of multiple signals (DCMS) methods were used to detect the selection signals. The results showed that we identified important candidate genes related to growth rate and body size in the introduced breeds. Selected genes with stronger selection signatures are associated with growth rate (CRADD), embryonic development (BVES, LIN28B, and WNT11), body size (HMGA2, MSRB3, and PTCH1), muscle development and fat metabolism (MSTN, PDE3A, LGALS12, GGPS1, and SAR1B), wool color (ASIP), and hair development (KRT71, KRT74, and IRF2BP2). Thus, these genes have the potential to serve as candidate genes for enhancing the growth traits of Chinese indigenous sheep. We also identified tail-length trait-related candidate genes (HOXB13, LIN28A, PAX3, and VEGFA) in Chinese long-tailed breeds. Among these genes, HOXB13 is the main candidate gene for sheep tail length phenotype. LIN28A, PAX3, and VEGFA are related to embryonic development and angiogenesis, so these genes may be candidate genes for sheep tail type traits. This study will serve as a foundation for further genetic improvement of Chinese indigenous sheep and as a reference for studies related to growth and development of sheep. Full article
(This article belongs to the Special Issue Adaptive Evolution and Trait Formation of Animals)
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14 pages, 3570 KiB  
Article
A Multi-Stage Progressive Network with Feature Transmission and Fusion for Marine Snow Removal
by Lixin Liu, Yuyang Liao and Bo He
Sensors 2024, 24(2), 356; https://doi.org/10.3390/s24020356 - 7 Jan 2024
Cited by 1 | Viewed by 1331
Abstract
Improving underwater image quality is crucial for marine detection applications. However, in the marine environment, captured images are often affected by various degradation factors due to the complexity of underwater conditions. In addition to common color distortions, marine snow noise in underwater images [...] Read more.
Improving underwater image quality is crucial for marine detection applications. However, in the marine environment, captured images are often affected by various degradation factors due to the complexity of underwater conditions. In addition to common color distortions, marine snow noise in underwater images is also a significant issue. The backscatter of artificial light on marine snow generates specks in images, thereby affecting image quality, scene perception, and subsequently impacting downstream tasks such as target detection and segmentation. Addressing the issues caused by marine snow noise, we have designed a new network structure. In this work, a novel skip-connection structure called a dual channel multi-scale feature transmitter (DCMFT) is implemented to reduce information loss during downsampling in the feature encoding and decoding section. Additionally, in the feature transfer process for each stage, iterative attentional feature fusion (iAFF) modules are inserted to fully utilize marine snow features extracted at different stages. Finally, to further optimize the network’s performance, we incorporate the multi-scale structural similarity index (MS-SSIM) into the loss function to ensure more effective convergence during training. Through experiments conducted on the Marine Snow Removal Benchmark (MSRB) dataset with an augmented sample size, our method has achieved significant results. The experimental results demonstrate that our approach excels in removing marine snow noise, with a peak signal-to-noise ratio reaching 38.9251 dB, significantly outperforming existing methods. Full article
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16 pages, 1539 KiB  
Review
Role of Oxidative Stress, Methionine Oxidation and Methionine Sulfoxide Reductases (MSR) in Alzheimer’s Disease
by Sanjana Chandran and David Binninger
Antioxidants 2024, 13(1), 21; https://doi.org/10.3390/antiox13010021 - 21 Dec 2023
Cited by 15 | Viewed by 2827
Abstract
A major contributor to dementia seen in aging is Alzheimer’s disease (AD). Amyloid beta (Aβ), a main component of senile plaques (SPs) in AD, induces neuronal death through damage to cellular organelles and structures, caused by oxidation of important molecules such as proteins [...] Read more.
A major contributor to dementia seen in aging is Alzheimer’s disease (AD). Amyloid beta (Aβ), a main component of senile plaques (SPs) in AD, induces neuronal death through damage to cellular organelles and structures, caused by oxidation of important molecules such as proteins by reactive oxygen species (ROS). Hyperphosphorylation and accumulation of the protein tau in the microtubules within the brain also promote ROS production. Methionine, a residue of proteins, is particularly sensitive to oxidation by ROS. One of the enzyme systems that reverses the oxidative damage in mammalian cells is the enzyme system known as Methionine Sulfoxide Reductases (MSRs). The components of the MSR system, namely MSRA and MSRB, reduce oxidized forms of methionine (Met-(o)) in proteins back to methionine (Met). Furthermore, the MSRs scavenge ROS by allowing methionine residues in proteins to utilize their antioxidant properties. This review aims to improve the understanding of the role of the MSR system of enzymes in reducing cellular oxidative damage and AD pathogenesis, which may contribute to effective therapeutic approaches for AD by targeting the MSR system. Full article
(This article belongs to the Section Health Outcomes of Antioxidants and Oxidative Stress)
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22 pages, 1754 KiB  
Article
Kinetics of Phosphate Ions and Phytase Activity Production for Lactic Acid-Producing Bacteria Utilizing Milling and Whitening Stages Rice Bran as Biopolymer Substrates
by Rojarej Nunta, Julaluk Khemacheewakul, Charin Techapun, Sumeth Sommanee, Juan Feng, Su Lwin Htike, Chatchadaporn Mahakuntha, Kritsadaporn Porninta, Yuthana Phimolsiripol, Kittisak Jantanasakulwong, Churairat Moukamnerd, Masanori Watanabe, Anbarasu Kumar and Noppol Leksawasdi
Biomolecules 2023, 13(12), 1770; https://doi.org/10.3390/biom13121770 - 10 Dec 2023
Cited by 1 | Viewed by 1623
Abstract
A study evaluated nine kinetic data and four kinetic parameters related to growth, production of various phytase activities (PEact), and released phosphate ion concentration ([Pi]) from five lactic acid bacteria (LAB) strains cultivated in three types of media: phytate (IP6), milling [...] Read more.
A study evaluated nine kinetic data and four kinetic parameters related to growth, production of various phytase activities (PEact), and released phosphate ion concentration ([Pi]) from five lactic acid bacteria (LAB) strains cultivated in three types of media: phytate (IP6), milling stage rice bran (MsRB), and whitening stage rice bran (WsRB). Score ranking techniques were used, combining these kinetic data and parameters to select the most suitable LAB strain for each medium across three cultivation time periods (24, 48, and 72 h). In the IP6 medium, Lacticaseibacillus casei TISTR 1500 exhibited statistically significant highest (p ≤ 0.05) normalized summation scores using a 2:1 weighting between kinetic and parameter data sets. This strain also had the statistically highest levels (p ≤ 0.05) of produced phosphate ion concentration ([Pi]) (0.55 g/L) at 72 h and produced extracellular specific phytase activity (ExSp-PEact) (0.278 U/mgprotein) at 48 h. For the MsRB and WsRB media, Lactiplantibacillus plantarum TISTR 877 performed exceptionally well after 72 h of cultivation. It produced ([Pi], ExSp-PEact) pairs of (0.53 g/L, 0.0790 U/mgprotein) in MsRB and (0.85 g/L, 0.0593 U/mgprotein) in WsRB, respectively. Overall, these findings indicate the most promising LAB strains for each medium and cultivation time based on their ability to produce phosphate ions and extracellular specific phytase activity. The selection process utilized a combination of kinetic data and parameter analysis. Full article
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14 pages, 13414 KiB  
Article
Genomic Dissection through Whole-Genome Resequencing of Five Local Pig Breeds from Shanghai, China
by Jun Gao, Lingwei Sun, Hongmei Pan, Shushan Zhang, Jiehuan Xu, Mengqian He, Keqing Zhang, Jinyong Zhou, Defu Zhang, Caifeng Wu and Jianjun Dai
Animals 2023, 13(23), 3727; https://doi.org/10.3390/ani13233727 - 1 Dec 2023
Cited by 5 | Viewed by 2479
Abstract
China has rich genetic resources of local pig breeds. In this study, whole-genome resequencing was performed on five Shanghai local pig breeds, aiming to analyze their population genetic structure and unique genomic characteristics. Tens of millions of single nucleotide variants were obtained through [...] Read more.
China has rich genetic resources of local pig breeds. In this study, whole-genome resequencing was performed on five Shanghai local pig breeds, aiming to analyze their population genetic structure and unique genomic characteristics. Tens of millions of single nucleotide variants were obtained through the resequencing of a total of 150 individual pigs from five local pig breeds (Meishan, Fengjing, Shawutou, Pudong White, and Shanghai White) after mapping them with the pig reference genome of Sus scrofa 11.1. The results of admixture structure analysis also clearly demonstrated the genetic differences between the Shanghai local pig breeds and the three commercial pig breeds (Duroc, Landrace, and Yorkshire). The genetic infiltration of Landrace and Yorkshire pig breeds in the SHW breed was detected, which is consistent with the early history of crossbreeding in this breed. Selective sweep analysis between four indigenous Shanghai pig breed populations and three commercial pig breed populations identified 270 and 224 genes with selective signatures in the commercial and indigenous Shanghai pig populations, respectively. Six genes (TGS1, PLAG1, CHCHD7, LCORL, TMEM68, and TMEM8B) were found to be associated with animal growth in the commercial pig population through gene enrichment and protein–protein interaction analysis. In contrast, the MSRB3 gene in the indigenous Shanghai pig population was significantly under selection, which correlated with the long pendulous ear phenotype of the indigenous Shanghai pig population. In conclusion, this study is the first genomic profiling of five representative local pig breeds in Shanghai, which provides molecular genetic data and foundations for better conservation and utilization of local pig breed resources in Shanghai, China. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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17 pages, 12307 KiB  
Article
Forest Single-Frame Remote Sensing Image Super-Resolution Using GANs
by Yafeng Zhao, Shuai Zhang and Junfeng Hu
Forests 2023, 14(11), 2188; https://doi.org/10.3390/f14112188 - 3 Nov 2023
Cited by 2 | Viewed by 1658
Abstract
Generative Adversarial Networks (GANs) possess remarkable fitting capabilities and play a crucial role in the field of computer vision. Super-resolution restoration is the process of converting low-resolution images into high-resolution ones, providing more detail and information. This is of paramount importance for monitoring [...] Read more.
Generative Adversarial Networks (GANs) possess remarkable fitting capabilities and play a crucial role in the field of computer vision. Super-resolution restoration is the process of converting low-resolution images into high-resolution ones, providing more detail and information. This is of paramount importance for monitoring and managing forest resources, enabling the surveillance of vegetation, wildlife, and potential disruptive factors in forest ecosystems. In this study, we propose an image super-resolution model based on Generative Adversarial Networks. We incorporate Multi-Scale Residual Blocks (MSRB) as the core feature extraction component to obtain image features at different scales, enhancing feature extraction capabilities. We introduce a novel attention mechanism, GAM Attention, which is added to the VGG network to capture more accurate feature dependencies in both spatial and channel domains. We also employ the adaptive activation function Meta ACONC and Ghost convolution to optimize training efficiency and reduce network parameters. Our model is trained on the DIV2K and LOVEDA datasets, and experimental results indicate improvements in evaluation metrics compared to SRGAN, with a PSNR increase of 0.709/2.213 dB, SSIM increase of 0.032/0.142, and LPIPS reduction of 0.03/0.013. The model performs on par with Real-ESRGAN but offers significantly improved speed. Our model efficiently restores single-frame remote sensing images of forests while achieving results comparable to state-of-the-art methods. It overcomes issues related to image distortion and texture details, producing forest remote sensing images that closely resemble high-resolution real images and align more closely with human perception. This research has significant implications on a global scale for ecological conservation, resource management, climate change research, risk management, and decision-making processes. Full article
(This article belongs to the Special Issue Machine Learning Techniques in Forest Mapping and Vegetation Analysis)
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19 pages, 2036 KiB  
Article
Dietary Supplementation with Pomegranate and Onion Affects Lipid and Protein Oxidation in the Breast Meat, Thigh, and Liver, Cellular Stress Protein Responses, and Gene Expression of Liver Enzymes Involved in Protein Synthesis in Broilers
by Soumela Savvidou, Nikolas Panteli, Vassilios Dotas, George Symeon, Dimitrios Galamatis, Ioannis Panitsidis, Eirini Voutsinou, Christina Tatidou, Prafulla Kumar, Efthimia Antonopoulou, Georgios Michailidis and Ilias Giannenas
Foods 2023, 12(20), 3870; https://doi.org/10.3390/foods12203870 - 22 Oct 2023
Viewed by 2342
Abstract
The present study examined the effects of dietary supplementation with extracts of pomegranate (Punica granatum) and onion (Allium cepa), either encapsulated in cyclodextrin (POMALCD group) or in an aqueous (POMALAQ group) form, on breast meat, thigh meat, and liver [...] Read more.
The present study examined the effects of dietary supplementation with extracts of pomegranate (Punica granatum) and onion (Allium cepa), either encapsulated in cyclodextrin (POMALCD group) or in an aqueous (POMALAQ group) form, on breast meat, thigh meat, and liver composition, oxidative stability, cellular signaling pathways, and the gene expression of certain hepatic genes. The results showed that breast and thigh meat contained significantly (p < 0.05) higher moisture content in the group with the aqueous extract, compared to the control and POMALCD groups. Moreover, the protein content was significantly (p < 0.05) higher in the thigh and liver samples of the treated groups in comparison to the control. The iron-induced challenge deteriorated (p < 0.001) the lipid and protein oxidative status of the control group, whereas both supplemented groups showed considerable tolerance in all tissues. The supplementation of pomegranate and onion extracts mitigated or maintained heat shock protein (HSP) levels and elevated (p < 0.05) the Bcl-2/Bad ratio in thigh and breast meat, whereas mitogen-activated protein kinase (MAPK) activation was modulated at a lower rate. After normalization to β-actin expression, quantitative real-time PCR analysis revealed a significant (p < 0.05) induction in the expression of MTR and MSRB1 genes in the liver of the supplemented groups. No differences were observed for the TAT, SMS, and BHMT genes. In conclusion, dietary mixtures of herbal extracts with pomegranate and onion improved protein and lipid oxidative stability in meat, enhanced the hepatic energy status, and exerted ameliorative effects on stress-related proteins. The encapsulated extract of pomegranate and onion, using cyclodextrin as a carrier, appeared to reduce lipid oxidation to a greater extent than the aqueous extract. In contrast, the aqueous extract exhibited higher total antioxidant capacity (TAC) values and provided better protection against protein carbonyl formation. Full article
(This article belongs to the Section Meat)
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19 pages, 2459 KiB  
Article
Genome-Wide Association and Pathway Analysis of Carcass and Meat Quality Traits in Karachai Young Goats
by Marina Selionova, Magomet Aibazov, Alexander Sermyagin, Anna Belous, Tatiana Deniskova, Tatiana Mamontova, Ekaterina Zharkova and Natalia Zinovieva
Animals 2023, 13(20), 3237; https://doi.org/10.3390/ani13203237 - 17 Oct 2023
Cited by 3 | Viewed by 1867
Abstract
Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. The work aimed to search for candidate [...] Read more.
Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. The work aimed to search for candidate genes related to body measurements and body weight of Karachai goats and develop an experimental PCR-RV test system for genotyping significant SNPs. Comparison of GWAS results for ages 4 and 8 months revealed 58 common SNPs for significant genotypes. 11 common SNPs were identified for body weight, 4 SNPs—for group of traits withers height, rump height, body length, 2 SNPs—for withers height and rump height, 1 SNP—for body length and chest depth. Structural annotation of genomic regions covering a window of ±0.20 Mb showed the presence of 288 genes; 52 of them had the described functions in accordance with gene ontology. The main molecular functions of proteins encoded by these genes are the regulation of transcription, cell proliferation, angiogenesis, body growth, fatty acid and lipid metabolism, nervous system development, and spermatogenesis. SNPs common to body weight and localized within a window of ±200 kb from the structural genes CRADD, HMGA2, MSRB3, FUT8, MAX, and RAB15 were selected to create a test system. The study of meat productivity after slaughter and chemical analysis of muscle tissue in Karachai goats at the age of 8 months of different genotypes according to the identified SNPs revealed that rs268269710 is the most promising for further research and use in breeding. The GG genotype is associated with a larger live weight of animals, a larger carcass yield, the content of the boneless part in it, and the ratio of protein and adipose tissue in meat preferred for dietary nutrition. These results will contribute to the genetic improvement of Karachai goats. Full article
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16 pages, 3242 KiB  
Article
Multi-Scale Feature Fusion and Structure-Preserving Network for Face Super-Resolution
by Dingkang Yang, Yehua Wei, Chunwei Hu, Xin Yu, Cheng Sun, Sheng Wu and Jin Zhang
Appl. Sci. 2023, 13(15), 8928; https://doi.org/10.3390/app13158928 - 3 Aug 2023
Cited by 4 | Viewed by 2320
Abstract
Deep convolutional neural networks have demonstrated significant performance improvements in face super-resolution tasks. However, many deep learning-based approaches tend to overlook the inherent structural information and feature correlation across different scales in face images, making the accurate recovery of face structure in low-resolution [...] Read more.
Deep convolutional neural networks have demonstrated significant performance improvements in face super-resolution tasks. However, many deep learning-based approaches tend to overlook the inherent structural information and feature correlation across different scales in face images, making the accurate recovery of face structure in low-resolution cases challenging. To address this, this paper proposes a method that fuses multi-scale features while preserving the facial structure. It introduces a novel multi-scale residual block (MSRB) to reconstruct key facial parts and structures from spatial and channel dimensions, and utilizes pyramid attention (PA) to exploit non-local self-similarity, improving the details of the reconstructed face. Feature Enhancement Modules (FEM) are employed in the upscale stage to refine and enhance current features using multi-scale features from previous stages. The experimental results on CelebA, Helen and LFW datasets provide evidence that our method achieves superior quantitative metrics compared to the baseline, the Peak Signal-to-Noise Ratio (PSNR) outperforms the baseline by 0.282 dB, 0.343 dB, and 0.336 dB. Furthermore, our method demonstrates improved visual performance on two additional no-reference datasets, Widerface and Webface. Full article
(This article belongs to the Special Issue Advances in Image and Video Processing: Techniques and Applications)
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18 pages, 11121 KiB  
Article
Multi-Scale Feature Residual Feedback Network for Super-Resolution Reconstruction of the Vertical Structure of the Radar Echo
by Xiangyu Fu, Qiangyu Zeng, Ming Zhu, Tao Zhang, Hao Wang, Qingqing Chen, Qiu Yu and Linlin Xie
Remote Sens. 2023, 15(14), 3676; https://doi.org/10.3390/rs15143676 - 23 Jul 2023
Viewed by 1386
Abstract
The vertical structure of radar echo is crucial for understanding complex microphysical processes of clouds and precipitation, and for providing essential data support for the study of low-level wind shear and turbulence formation, evolution, and dissipation. Therefore, finding methods to improve the vertical [...] Read more.
The vertical structure of radar echo is crucial for understanding complex microphysical processes of clouds and precipitation, and for providing essential data support for the study of low-level wind shear and turbulence formation, evolution, and dissipation. Therefore, finding methods to improve the vertical data resolution of the existing radar network is crucial. Existing algorithms for improving image resolution usually focus on increasing the width and height of images. However, improving the vertical data resolution of weather radar requires a focus on improving the elevation angle resolution while maintaining distance resolution. To address this challenge, we propose a network for super-resolution reconstruction of weather radar echo vertical structures. The network is based on a multi-scale residual feedback network (MR-FBN) and uses new multi-scale feature residual blocks (MSRB) to effectively extract and utilize data features at different scales. The feedback network gradually generates the final high-resolution vertical structure data. In addition, we propose an elevation upsampling layer (EUL) specifically for this task, replacing the traditional image subpixel convolution layer. Experimental results show that the proposed method can effectively improve the elevation angle resolution of weather radar echo vertical structure data, providing valuable help for atmospheric detection. Full article
(This article belongs to the Special Issue Doppler Radar: Signal, Data and Applications)
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12 pages, 7663 KiB  
Article
The Influence of MSR-B Mg Alloy Surface Preparation on Bonding Properties
by Katarzyna Łyczkowska, Damian Miara, Beata Rams, Janusz Adamiec and Katarzyna Baluch
Materials 2023, 16(10), 3887; https://doi.org/10.3390/ma16103887 - 22 May 2023
Cited by 3 | Viewed by 1724
Abstract
Nowadays, industrial adhesives are replacing conventional bonding methods in many industries, including the automotive, aviation, and power industries, among others. The continuous development of joining technology has promoted adhesive bonding as one of the basic methods of joining metal materials. This article presents [...] Read more.
Nowadays, industrial adhesives are replacing conventional bonding methods in many industries, including the automotive, aviation, and power industries, among others. The continuous development of joining technology has promoted adhesive bonding as one of the basic methods of joining metal materials. This article presents the influence of surface preparation of magnesium alloys on the strength properties of a single-lap adhesive joint using a one-component epoxy adhesive. The samples were subjected to shear strength tests and metallographic observations. The lowest properties of the adhesive joint were obtained on samples degreased with isopropyl alcohol. The lack of surface treatment before joining led to destruction by adhesive and mixed mechanisms. Higher properties were obtained for samples ground with sandpaper. The depressions created as a result of grinding increased the contact area of the adhesive with the magnesium alloys. The highest properties were noticed for samples after sandblasting. This proved that the development of the surface layer and the formation of larger grooves increased both the shear strength and the resistance of the adhesive bonding to fracture toughness. It was found that the method of surface preparation had a significant influence on the resulting failure mechanism, and the adhesive bonding of the casting of magnesium alloy QE22 can be used successfully. Full article
(This article belongs to the Special Issue Welding, Joining, and Additive Manufacturing of Metals and Alloys)
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16 pages, 2431 KiB  
Article
Different Effects and Mechanisms of Selenium Compounds in Improving Pathology in Alzheimer’s Disease
by Zhong-Hao Zhang, Jia-Ying Peng, Yu-Bin Chen, Chao Wang, Chen Chen and Guo-Li Song
Antioxidants 2023, 12(3), 702; https://doi.org/10.3390/antiox12030702 - 12 Mar 2023
Cited by 10 | Viewed by 2808
Abstract
Owing to the strong antioxidant capacity of selenium (Se) in vivo, a variety of Se compounds have been shown to have great potential for improving the main pathologies and cognitive impairment in Alzheimer’s disease (AD) models. However, the differences in the anti-AD effects [...] Read more.
Owing to the strong antioxidant capacity of selenium (Se) in vivo, a variety of Se compounds have been shown to have great potential for improving the main pathologies and cognitive impairment in Alzheimer’s disease (AD) models. However, the differences in the anti-AD effects and mechanisms of different Se compounds are still unclear. Theoretically, the absorption and metabolism of different forms of Se in the body vary, which directly determines the diversification of downstream regulatory pathways. In this study, low doses of Se-methylselenocysteine (SMC), selenomethionine (SeM), or sodium selenate (SeNa) were administered to triple transgenic AD (3× Tg-AD) mice for short time periods. AD pathology, activities of selenoenzymes, and metabolic profiles in the brain were studied to explore the similarities and differences in the anti-AD effects and mechanisms of the three Se compounds. We found that all of these Se compounds significantly increased Se levels and antioxidant capacity, regulated amino acid metabolism, and ameliorated synaptic deficits, thus improving the cognitive capacity of AD mice. Importantly, SMC preferentially increased the expression and activity of thioredoxin reductase and reduced tau phosphorylation by inhibiting glycogen synthase kinase-3 beta (GSK-3β) activity. Glutathione peroxidase 1 (GPx1), the selenoenzyme most affected by SeM, decreased amyloid beta production and improved mitochondrial function. SeNa improved methionine sulfoxide reductase B1 (MsrB1) expression, reflected in AD pathology as promoting the expression of synaptic proteins and restoring synaptic deficits. Herein, we reveal the differences and mechanisms by which different Se compounds improve multiple pathologies of AD and provide novel insights into the targeted administration of Se-containing drugs in the treatment of AD. Full article
(This article belongs to the Special Issue The Role of Selenium/Selenoproteins in Metabolism and Diseases)
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