Search Results (49)

Background: Ischemic stroke (IS) is a major cause of disability and mortality worldwide, with mitochondrial dysfunction playing a critical role in its pathogenesis. This study aimed to identify immune-related mitochondrial biomarkers associated with IS and evaluate their diagnostic potential. Methods: IS-related gene expression datasets were obtained from the GEO database. Differentially expressed genes (DEGs) were identified from the GSE58294 dataset, followed by functional enrichment analysis, immune infiltration assessment, and weighted gene co-expression network analysis (WGCNA). Immune-related mitochondrial genes were screened using the MITOCARTA 3.0 database. Four machine learning algorithms—random forest (RF), support vector machine (SVM), generalized linear model (GLM), and extreme gradient boosting (XGB)—were applied to identify hub genes. External validation was performed using the GSE16561 dataset, and RT-qPCR confirmed key gene expression. Functional enrichment and single-cell RNA sequencing analyses explored biological pathways and cellular localization. Results: Five key genes (ECHDC3, EPHX2, SPTLC2, MSRB2, and TK2) were identified, among which ECHDC3, EPHX2, and SPTLC2 showed strong diagnostic potential (AUC > 0.7). These genes were significantly enriched in apoptosis, JAK-STAT, MAPK, and VEGF signaling pathways and were closely associated with neutrophil infiltration. Single-cell analysis revealed increased immune cell populations and distinct expression patterns of key genes in the ischemic mouse brain. Conclusions: This study identifies novel immune-related mitochondrial biomarkers for IS, providing insights into its pathogenesis and offering potential targets for early diagnosis and therapeutic intervention. Full article

Background/Objectives: Selenoproteins play indispensable roles in embryonic development, with their dysregulation linked to various metabolic and neurological disorders. This study aims to systematically quantify the mRNA expression levels of all 24 selenoprotein genes in murine heart, brain, liver, and kidney tissues across embryonic (E8.5, E12.5, E18.5) and postnatal (P7, P30, P90) developmental stages, in order to elucidate the regulatory landscape of selenium metabolism during development. Methods: We collected tissues from mice at six developmental stages and performed RNA extraction followed by quantitative real-time PCR (qPCR) to measure the expression of all 24 selenoprotein genes. Data were normalized using the geometric mean of ActB and Gapdh, and statistical analyses were conducted using one-way ANOVA with Duncan’s post hoc test. Results: Our analysis reveals three principal findings: (1) Distinct expression patterns emerge among selenoprotein families—deiodinases (Dio1-3) and thioredoxin reductases (Txnrd1-3) exhibit limited embryonic expression (<20-fold changes), while glutathione peroxidases (Gpx1, Gpx3, Gpx4) and biosynthesis-related genes (Selenop, Msrb1) show substantial postnatal upregulation (up to 600-fold increases); (2) Selenoproteins essential for embryonic survival (Gpx4, Txnrd1, Txnrd2, Selenoi, Selenot) display expression profiles concordant with their essential developmental functions; (3) Selenop and Msrb1, involved in selenium transport and redox regulation, demonstrate early embryonic upregulation with further increases during postnatal development. Conclusions: These spatiotemporal expression patterns elucidate the regulatory landscape of selenium metabolism during development and provide mechanistic insights into the phenotypes associated with selenium deficiency. The findings offer valuable implications for human nutritional interventions and developmental health. Full article

Here we report that the Salmonella Typhimurium NatB (SeNatB) protein N-terminal acetyltransferase acetylated the N-terminal methionine of the nucleoid-associated HU proteins. Our findings were supported by an in vitro analysis of acetylation of the HUα and HUβ proteins and lysine-null (K-null) variants, and by an in vivo analysis of the effect of acetylation on HU-mediated transcriptional regulation of a known target of HU, the hilA promoter. SeNatB did not acetylate the initiating methionines of HU proteins that were oxidized to methionine sulfoxide, but the reduction of these methionine sulfoxide residues restored the acetylation of HU proteins by SeNatB. These results demonstrate that the SeHU proteins are bona fide substrates for the methionine sulfoxide reductases MsrA and MsrB. Finally, we showed that the Bacillus subtilis acetyltransferase, YfmK, is a functional homolog of SeNatB, and that BsYfmK acetylates the N^α amino group of the initiating methionine of the B. subtilis HU protein (HBsu). Full article

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

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

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

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, F_st & 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

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

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

A study evaluated nine kinetic data and four kinetic parameters related to growth, production of various phytase activities (PE_act), 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-PE_act) (0.278 U/mg_protein) 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-PE_act) pairs of (0.53 g/L, 0.0790 U/mg_protein) in MsRB and (0.85 g/L, 0.0593 U/mg_protein) 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

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

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

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

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

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