Search Results (14)

This study identifies and classifies resistance gene analogues (RGAs) in the genomes of Brassica nigra, Sinapis arvensis and Sinapis alba using the RGAugury pipeline. RGAs were categorised into four main classes: receptor-like kinases (RLKs), receptor-like proteins (RLPs), nucleotide-binding leucine-rich repeat (NLR) proteins and transmembrane-coiled-coil (TM-CC) genes. A total of 4499 candidate RGAs were detected, with species-specific proportions. RLKs were the most abundant across all genomes, followed by TM-CCs and RLPs. The sub-classification of RLKs and RLPs identified LRR-RLKs, LRR-RLPs, LysM-RLKs, and LysM-RLPs. Atypical NLRs were more frequent than typical ones in all species. Atypical NLRs were more frequent than typical ones in all species. We explored the relationship between chromosome size and RGA count using regression analysis. In B. nigra and S. arvensis, larger chromosomes generally harboured more RGAs, while S. alba displayed the opposite trend. Exceptions were observed in all species, where some larger chromosomes contained fewer RGAs in B. nigra and S. arvensis, or more RGAs in S. alba. The distribution and density of RGAs across chromosomes were examined. RGA distribution was skewed towards chromosomal ends, with patterns differing across RGA types. Sequence hierarchical pairwise similarity analysis revealed distinct gene clusters, suggesting evolutionary relationships. The study also identified homologous genes among RGAs and non-RGAs in each species, providing insights into disease resistance mechanisms. Finally, RLKs and RLPs were co-localised with reported disease resistance loci in Brassica, indicating significant associations. Phylogenetic analysis of cloned RGAs and QTL-mapped RLKs and RLPs identified distinct clusters, enhancing our understanding of their evolutionary trajectories. These findings provide a comprehensive view of RGA diversity and genomics in these Brassicaceae species, providing valuable insights for future research in plant disease resistance and crop improvement. Full article

The laser cladding (LC) of titanium matrix composite coatings (TMCCs) on titanium components not only effectively enhances the wear resistance, fatigue resistance, corrosion resistance, and biocompatibility of titanium and its alloys, but also circumvents the incompatibility and low bonding strength issues associated with other metallic composite coatings. While the incorporation of ceramic particles is a critical strategy for improving the coating performance, the limited interfacial bonding strength between ceramic particles and the matrix has historically constrained its advancement. To further elevate its performance and meet the demands of components operating in harsh environments, researchers worldwide have employed LC to synthesize in situ hard ceramic reinforcements such as TiC, TiB, TiN, and others within TMCCs on titanium substrates. This approach successfully addresses the aforementioned challenges, achieving coatings that combine a high interfacial bonding strength with superior mechanical properties. This paper provides a comprehensive review of the processing techniques, phase composition, microstructure, and mechanical properties of in situ-synthesized ceramic-reinforced TMCCs via LC on titanium components, with a focused summary of their strengthening mechanisms. Furthermore, it critically discusses the challenges and future prospects for advancing this technology. Full article

Background: Bladder cancer (BC) is a common malignancy in the urinary system, with an increasing incidence rate. Immune cell infiltration within the tumor microenvironment (TME) plays a crucial role in BC progression and treatment response. However, the immune cell composition of the TME presents a significant challenge to the effectiveness of current therapeutic strategies. Methods: We performed bidirectional Mendelian randomization (MR) analysis to investigate the impact of immune cells on BC risk. Single nucleotide polymorphisms (SNPs) related to immune cells were annotated, and candidate genes associated with BC risk were identified. Differential expression analysis identified immune-related differentially expressed genes (iDEGs), and a protein–protein interaction (PPI) network along with functional enrichment analysis were conducted to explore their roles in tumor development. Machine learning-based feature selection was applied to identify potential biomarkers and therapeutic targets. Results: MR analysis revealed eight immune cell subtypes significantly associated with BC. Using SNPs linked to these immune cells, 129 candidate genes were identified through the SNPense tool and cross-referenced with differentially expressed genes in BC, resulting in identification of 28 iDEGs. Machine learning identified five potential diagnostic biomarkers (COLEC12, TMCC1, CEP55, KLK3, COL4A1) with an AUC of 0.903, which are implicated in immune modulation and cancer progression. Conclusions: This study provides new insights into immune mechanisms in BC and identifies promising biomarkers for early diagnosis and therapeutic intervention. Full article

Sepsis is a life-threatening condition driven by dysregulated immune responses, resulting in organ dysfunction and high mortality rates. Identifying key genes and pathways involved in sepsis progression is crucial for improving diagnostic and therapeutic strategies. This study analyzed transcriptomic data from 49 samples (37 septic patients across days 0, 1, and 8, and 12 healthy controls) using weighted gene co-expression network analysis (WGCNA) and multi-algorithm feature selection approaches. Differential expression analysis, pathway enrichment, and network analyses were employed to uncover potential biomarkers and molecular mechanisms. WGCNA identified modules such as MEbrown4 and MEblack, which strongly correlated with sepsis progression (r > 0.7, p < 0.01). Differential expression analysis highlighted up-regulated genes like CD177 and down-regulated genes like LOC440311. KEGG analysis revealed significant pathways including neuroactive ligand–receptor interaction, PI3K-Akt signaling, and MAPK signaling. Gene ontology analysis showed involvement in immune-related processes such as complement activation and antigen binding. Protein–protein interaction network analysis identified hub genes such as TNFSF10, IGLL5, BCL2L1, and SNCA. Feature selection methods (random forest, LASSO regression, SVM-RFE) consistently identified top predictors like TMCC2, TNFSF10, and PLVAP. Receiver operating characteristic (ROC) analysis demonstrated high predictive accuracy for sepsis progression, with AUC values of 0.973 (TMCC2), 0.969 (TNFSF10), and 0.897 (PLVAP). Correlation analysis linked key genes such as TNFSF10, GUCD1, and PLVAP to pathways involved in immune response, cell death, and inflammation. This integrative transcriptomic analysis identifies critical gene modules, pathways, and biomarkers associated with sepsis progression. Key genes like TNFSF10, TMCC2, and PLVAP genes show strong diagnostic potential, providing novel insights into sepsis pathogenesis and offering promising targets for future therapeutic interventions. Among these, TNFSF10 and PLVAP are known to encode secreted proteins, suggesting their potential as circulating biomarkers. This enhances their translational relevance in clinical diagnostics. Full article

Cuproptosis and N6-methyladenosine (m6A) have potential as prognostic predictors in cancer patients, but their roles in hepatocellular carcinoma (HCC) are unclear. This study aimed to screen a total of 375 HCC samples were retrieved from the TCGA database, and lncRNAs related to cuproptosis and m6A were obtained through correlation analysis. To construct a risk assessment model, univariate Cox regression analysis and LASSO Cox regression were employed. Analyze the regulatory effect of relevant risk assessment models on tumor mutation load (TMB) and immune microenvironment. A total of five lncRNAs (AC007405.3, AL031985.3, TMCC1-AS1, MIR210HG, TMEM220-AS1) with independent overall survival-related risk models were obtained by LASSO survival regression. TP53 and CTNNB1 were the three genes found to have the most mutations in high-risk group patients. The high-risk group with low TMB had the worst survival, whereas the low-risk group with high TMB had the best survival. KEGG pathway analysis revealed that the high-risk group was enriched with cell cycle, oocyte meiosis, cell senescence, and glycolysis/glucose production pathways. We constructed a reliable cuproptosis- and m6A-related lncRNA model for the prognosis of HCC. The model may provide new insights into managing HCC patients, but further research is needed to validate it. Full article

The purpose of the current study was to examine transcriptomic-based profiling of differentially expressed innate immune genes between indigenous and commercial chickens. In order to compare the transcriptome profiles of the different chicken breeds, we extracted RNA from blood samples of the Isfahan indigenous chicken (as indigenous) and Ross broiler chicken (as commercial) breeds. RNA-Seq yielded totals of 36,763,939 and 31,545,002 reads for the indigenous and commercial breeds, respectively, with clean reads then aligned to the chicken reference genome (Galgal5). Overall, 1327 genes were significantly differentially expressed, of which 1013 genes were upregulated in the commercial versus the indigenous breed, while 314 were more highly expressed in the indigenous birds. Furthermore, our results demonstrated that the SPARC, ATP6V0D2, IL4I1, SMPDL3A, ADAM7, TMCC3, ULK2, MYO6, THG1L and IRG1 genes were the most significantly expressed genes in the commercial birds and the PAPPA, DUSP1, PSMD12, LHX8, IL8, TRPM2, GDAP1L1, FAM161A, ABCC2 and ASAH2 genes were the most significant in the indigenous chickens. Of notable finding in this study was that the high-level gene expressions of heat-shock proteins (HSPs) in the indigenous breeds could serve as a guideline for future genetic improvement. This study identified genes with breed-specific expression, and comparative transcriptome analysis helped understanding of the differences in underlying genetic mechanisms between commercial and local breeds. Therefore, the current results can be used to identify candidate genes for further breed improvement. Full article

Host genetic variability plays a pivotal role in modulating COVID-19 clinical outcomes. Despite the functional relevance of protein-coding regions, rare variants located here are less likely to completely explain the considerable numbers of acutely affected COVID-19 patients worldwide. Using an exome-wide association approach, with individuals of European descent, we sought to identify common coding variants linked with variation in COVID-19 severity. Herein, cohort 1 compared non-hospitalized (controls) and hospitalized (cases) individuals, and in cohort 2, hospitalized subjects requiring respiratory support (cases) were compared to those not requiring it (controls). 229 and 111 variants differed significantly between cases and controls in cohorts 1 and 2, respectively. This included FBXO34, CNTN2, and TMCC2 previously linked with COVID-19 severity using association studies. Overall, we report SNPs in 26 known and 12 novel candidate genes with strong molecular evidence implicating them in the pathophysiology of life-threatening COVID-19 and post-recovery sequelae. Of these few notable known genes include, HLA-DQB1, AHSG, ALOX5AP, MUC5AC, SMPD1, SPG7, SPEG,GAS6, and SERPINA12. These results enhance our understanding of the pathomechanisms underlying the COVID-19 clinical spectrum and may be exploited to prioritize biomarkers for predicting disease severity, as well as to improve treatment strategies in individuals of European ancestry. Full article

(1) Background: Transcriptomic and proteomic studies provide a wealth of new genes potentially involved in red blood cell (RBC) maturation or implicated in the pathogenesis of anemias, necessitating validation of candidate genes in vivo; (2) Methods: We inactivated one such candidate, transmembrane and coiled-coil domain 2 (Tmcc2) in mice, and analyzed the erythropoietic phenotype by light microscopy, transmission electron microscopy (TEM), and flow cytometry of erythrocytes and erythroid precursors; (3) Results: Tmcc2^−/− pups presented pallor and reduced body weight due to the profound neonatal macrocytic anemia with numerous nucleated RBCs (nRBCs) and occasional multinucleated RBCs. Tmcc2^−/− nRBCs had cytoplasmic intrusions into the nucleus and double membranes. Significantly fewer erythroid cells were enucleated. Adult knockouts were normocytic, mildly polycythemic, with active extramedullary erythropoiesis in the spleen. Altered relative content of different stage CD71⁺TER119⁺ erythroid precursors in the bone marrow indicated a severe defect of erythroid maturation at the polychromatic to orthochromatic transition stage; (4) Conclusions: Tmcc2 is required for normal erythropoiesis in mice. While several phenotypic features resemble congenital dyserythropoietic anemias (CDA) types II, III, and IV, the involvement of TMCC2 in the pathogenesis of CDA in humans remains to be determined. Full article

Powdery mildew (PM), caused by the fungus Oidium lini in flax, can cause defoliation and reduce seed yield and quality. To date, one major dominant gene (Pm1) and three quantitative trait loci (QTL) on chromosomes 1, 7 and 9 have been reported for PM resistance. To fully dissect the genetic architecture of PM resistance and identify QTL, a diverse flax core collection of 372 accessions augmented with an additional 75 breeding lines were sequenced, and PM resistance was evaluated in the field for eight years (2010–2017) in Morden, Manitoba, Canada. Genome-wide association studies (GWAS) were performed using two single-locus and seven multi-locus statistical models with 247,160 single nucleotide polymorphisms (SNPs) and the phenotypes of the 447 individuals for each year separately as well as the means over years. A total of 349 quantitative trait nucleotides (QTNs) were identified, of which 44 large-effect QTNs (R² = 10–30%) were highly stable over years. The total number of favourable alleles per accession was significantly correlated with PM resistance (r = 0.74), and genomic selection (GS) models using all identified QTNs generated significantly higher predictive ability (r = 0.93) than those constructed using the 247,160 genome-wide random SNP (r = 0.69), validating the overall reliability of the QTNs and showing the additivity of PM resistance in flax. The QTNs were clustered on the distal ends of all 15 chromosomes, especially on chromosome 5 (0.4–5.6 Mb and 9.4–16.9 Mb) and 13 (4.7–5.2 Mb). To identify candidate genes, a dataset of 3230 SNPs located in resistance gene analogues (RGAs) was used as input for GWAS, from which an additional 39 RGA-specific QTNs were identified. Overall, 269 QTN loci harboured 445 RGAs within the 200 Kb regions spanning the QTNs, including 45 QTNs located within the RGAs. These RGAs supported by significant QTN/SNP allele effects were mostly nucleotide binding site and leucine-rich repeat receptors (NLRs) belonging to either coiled-coil (CC) NLR (CNL) or toll interleukin-1 (TIR) NLR (TNL), receptor-like kinase (RLK), receptor-like protein kinase (RLP), transmembrane-coiled-coil (TM-CC), WRKY, and mildew locus O (MLO) genes. These results constitute an important genomic tool for resistance breeding and gene cloning for PM in flax. Full article

Due to the increasing use of renewable energy sources, and to counter the effects of fossil fuels, renewable dispatchable hydro power can be used for balancing load and generation from intermittent sources (solar and wind). During higher percentage change in load acceptance or rejection in the intermittent grid, the operations of surge tanks are crucial in terms of water mass oscillation and water hammer pressure, and to avoid wear and tear in actuators and other equipment, such as hydro turbines. Surge tanks are broadly classified as open types, with access to open air, and closed types, with a closed volume of pressurized air. Closed surge tanks are considered to have a more flexible operation in terms of suppressing water mass oscillation and water hammer pressure. In this paper, a mechanistic model of an air cushion surge tank (ACST) for hydro power plants is developed based on the ordinary differential equations (ODEs) for mass and momentum balances. The developed mechanistic model of the ACST is a feature extension to an existing open-source hydro power library—OpenHPL. The developed model is validated with experimental data from the Torpa hydro power plant (HPP) in Norway. Results show that the air friction inside the ACST is negligible as compared to the water friction. The results also indicate that a hydro power plant with an ACST is a potential candidate as a flexible hydro power in an interconnected power system grid supplied with intermittent energy sources. Conclusions are drawn based on the simulation results from hydraulic performance of the ACST. Full article

Background: Prostate cancer (PCa) is the second most common tumour diagnosed in men. Tumoral heterogeneity in PCa creates a significant challenge to develop robust prognostic markers and novel targets for therapy. An analysis of gene regulatory networks (GRNs) in PCa may provide insight into progressive PCa. Herein, we exploited a graph-based enrichment score to integrate data from GRNs identified in preclinical prostate orthografts and differentially expressed genes in clinical resected PCa. We identified active regulons (transcriptional regulators and their targeted genes) associated with PCa recurrence following radical prostatectomy. Methods: The expression of known transcription factors and co-factors was analysed in a panel of prostate orthografts (n = 18). We searched for genes (as part of individual GRNs) predicted to be regulated by the highest number of transcriptional factors. Using differentially expressed gene analysis (on a per sample basis) coupled with gene graph enrichment analysis, we identified candidate genes and associated GRNs in PCa within the UTA cohort, with the most enriched regulon being JMJD6, which was further validated in two additional cohorts, namely EMC and ICGC cohorts. Cox regression analysis was performed to evaluate the association of the JMJD6 regulon activity with disease-free survival time in the three clinical cohorts as well as compared to three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). Results: 1308 regulons were correlated to transcriptomic data from the three clinical prostatectomy cohorts. The JMJD6 regulon was identified as the top enriched regulon in the UTA cohort and again validated in the EMC cohort as the top-ranking regulon. In both UTA and EMC cohorts, the JMJD6 regulon was significantly associated with cancer recurrence. Active JMJD6 regulon also correlated with disease recurrence in the ICGC cohort. Furthermore, Kaplan–Meier analysis confirmed shorter time to recurrence in patients with active JMJD6 regulon for all three clinical cohorts (UTA, EMC and ICGC), which was not the case for three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). In multivariate analysis, the JMJD6 regulon status significantly predicted disease recurrence in the UTA and EMC, but not ICGC datasets, while none of the three published signatures significantly prognosticate for cancer recurrence. Conclusions: We have characterised gene regulatory networks from preclinical prostate orthografts and applied transcriptomic data from three clinical cohorts to evaluate the prognostic potential of the JMJD6 regulon. Full article

In a microgrid connected with both intermittent and dispatchable sources, intermittency caused by sources such as solar and wind power plants can be balanced by dispatching hydro power into the grid. Both intermittent generation and consumption are stochastic in nature, not known perfectly, and require future prediction. The stochastic generation and consumption will cause the grid frequency to drift away from a required range. To improve performance, operation should be optimized over some horizon, with the added problem that intermittent power varies randomly into the future. Optimal management of dynamic system over a future horizon with disturbances is often posed as a Model Predictive Control (MPC) problem. In this paper, we have employed an MPC scheme for generating a hydro-turbine valve signal for dispatching necessary hydro power to the intermittent grid and maintaining grid frequency. Parameter sensitivity analysis shows that grid frequency is mostly sensitive to the turbine valve signal. We have found that controller discretization time, grid frequency, and power injection into the grid are interrelated, and play an important role in maintaining the grid frequency within the thresholds. Results also indicate that the fluctuations in grid frequency are insignificant on the turbine valve position during power injection into the grid. Full article

In the integrated services digital broadcasting-terrestrial (ISDB-T) system, the combination of digital terrestrial transmission and MPEG-4 advanced video coding (MPEG-4 AVC) has offered ways to provide a variety of digital high-definition television (HDTV) programs. Using band segmented transmission orthogonal frequency division multiplexing (BST-OFDM), the delivery of innovative video-on-demand and HDTV services is supported. To take full advantage of the attractive benefits of BST-OFDM, it is important to estimate integer frequency offset (IFO) without a priori knowledge on the segment type that is transmitted over transmission and the multiplexing configuration control (TMCC) signal. To address this issue, an efficient IFO detection method is proposed for the ISDB-T system employing BST-OFDM. To enable IFO detection independent of the segment type, information-bearing TMCC signals that are asymmetrically distributed in the frequency domain are used as pilot symbols. Numerical analysis is performed to present the relationship between error probability and design parameter. We show via the numerical results that the multiple transmitted TMCC information is efficiently used for blind estimation of the IFO, achieving robust estimation in the presence of the fractional frequency offset. Full article

The integrated services digital broadcasting-terrestrial (ISDB-T) system is designed in order to accommodate high-quality video/audio and multimedia services, using band segmented transmission orthogonal frequency division multiplexing (BST-OFDM) scheme. In the ISDB-T system, the pilot configuration varies depending on whether a segment uses a coherent or differential modulation. Therefore, it is necessary to perform a joint estimation of carrier frequency offset (CFO) and sampling frequency offset (SFO) independent of the segment format in the ISDB-T system. The goal is to complete those synchronization tasks while considering an information-carrying transmission and multiplexing configuration control (TMCC) signal as pilot symbols. It is demonstrated through numerical simulations that the differential BPSK-modulated TMCC information can be efficiently used for a least-squares estimation of CFO and SFO, offering an acceptable performance. Full article