Gene expression profiling of venous malformations identifies the role of SDC1 in venous endothelial cells.

Objective: To obtain insight into the molecular process implicated in venous malformations (VMs) and identify potential targets for treatment of VMs, this study profiled the gene expression pattern in VMs, investigated alterations of syndecan-1 (SDC1) expression in VMs, and tested the hypothesis that aberrant SDC1 expression triggers abnormal angiogenesis and VM development. Methods: Microarray analysis was performed to identify differentially expressed genes (DEGs) on a transcriptome-wide level in VMs and conjunctive normal. Gene Ontology molecular functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out to establish enhancement of biological signaling pathways involved in VMs. Among the DEGs, we focused on SDC1, which is involved in matrix remodeling, cell proliferation and invasion, and angiogenesis. SDC1 expression in VMs was verified by qRT-PCR, western blotting, and immunohistochemistry. Loss-of-function of SDC1 was achieved in human umbilical vein endothelial cells (HUVECs) by siRNA to investigate the roles of SDC1 in cell migration, invasion, and angiogenesis. Results: Compared with control tissue, the transcriptome study identified 274 upregulated DEGs and 3 downregulated DEGs. The transcript and protein levels of SDC1 were significantly decreased in VMs compared with normal tissue. Inhibition of SDC1 enhanced HUVEC migration, invasion, and angiogenesis. Conclusion: Our genome-wide microarray analysis suggests the involvement of numerous genes in VMs. Among them, SDC1 plays a substantial role in the process of angiogenesis and development of VMs. SDC1 may represent a potential target for a molecular therapy for VMs.

Identification of Differentially Expressed Genes and Protein-Protein Interaction in Patients With COVID-19 and Diabetes Peripheral Neuropathy: A Bioinformatics and System Biology Approach.

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact globally, resulting in a higher death toll and persistent health issues for survivors, particularly those with pre-existing medical conditions. Numerous studies have demonstrated a strong correlation between catastrophic COVID-19 results and diabetes. To gain deeper insights, we analysed the transcriptome dataset from COVID-19 and diabetic peripheral neuropathic patients. Using the R programming language, differentially expressed genes (DEGs) were identified and classified based on up and down regulations. The overlaps of DEGs were then explored between these groups. Functional annotation of those common DEGs was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Bio-Planet, Reactome, and Wiki pathways. A protein-protein interaction (PPI) network was created with bioinformatics tools to understand molecular interactions. Through topological analysis of the PPI network, we determined hub gene modules and explored gene regulatory networks (GRN). Furthermore, the study extended to suggesting potential drug molecules for the identified mutual DEG based on the comprehensive analysis. These approaches may contribute to understanding the molecular intricacies of COVID-19 in diabetic peripheral neuropathy patients through insights into potential therapeutic interventions.

Dissection of transcriptional events in graft incompatible reactions of "Bearss" lemon (Citrus limon) and "Valencia" sweet orange (C. sinensis) on a novel citrandarin (C. reticulata × Poncirus trifoliata) rootstock.

Citrus is commercially propagated via grafting, which ensures trees have consistent fruit traits combined with favorable traits from the rootstock such as soil adaptability, vigor, and resistance to soil pathogens. Graft incompatibility can occur when the scion and rootstock are not able to form a permanent, healthy union. Understanding and preventing graft incompatibility is of great importance in the breeding of new fruit cultivars and in the choice of scion and rootstock by growers. The rootstock US-1283, a citrandarin generated from a cross of "Ninkat" mandarin (Citrus reticulata) and "Gotha Road" #6 trifoliate orange (Poncirus trifoliata), was released after years of field evaluation because of its superior productivity and good fruit quality on "Hamlin" sweet orange (C. sinensis) under Florida's growing conditions. Subsequently, it was observed that trees of "Bearss" lemon (C. limon) and "Valencia" sweet orange (C. sinensis) grafted onto US-1283 exhibited unhealthy growth near the graft union. The incompatibility manifested as stem grooving and necrosis underneath the bark on the rootstock side of the graft. Another citrandarin rootstock, US-812 (C. reticulata "Sunki" × P. trifoliata "Benecke"), is fully graft compatible with the same scions. Transcriptome analysis was performed on the vascular tissues above and below the graft union of US-812 and US-1283 graft combinations with "Bearss" and "Valencia" to identify expression networks associated with incompatibility and help understand the processes and potential causes of incompatibility. Transcriptional reprogramming was stronger in the incompatible rootstock than in the grafted scions. Differentially expressed genes (DEGs) in US-1283, but not the scions, were associated with oxidative stress and plant defense, among others, similar to a pathogen-induced immune response localized to the rootstock; however, no pathogen infection was detected. Therefore, it is hypothesized that this response could have been triggered by signaling miscommunications between rootstock and scion either through (1) unknown molecules from the scion that were perceived as danger signals by the rootstock, (2) missing signals from the scion or missing receptors in the rootstock necessary for the formation of a healthy graft union, (3) the overall perception of the scion by the rootstock as non-self, or (4) a combination of the above.

Comparative transcriptome analysis reveals the potential mechanism of GA3-induced dormancy release in Suaeda glauca black seeds.

Suaeda glauca Bunge produces dimorphic seeds on the same plant, with brown seeds displaying non-dormant characteristics and black seeds exhibiting intermediate physiological dormancy traits. Previous studies have shown that black seeds have a very low germination rate under natural conditions, but exogenous GA3 effectively enhanced the germination rate of black seeds. However, the physiological and molecular mechanisms underlying the effects of GA3 on S. glauca black seeds are still unclear. In this study, transcriptomic profiles of seeds at different germination stages with and without GA3 treatment were analyzed and compared, and the TTF, H2O2, O2 -, starch, and soluble sugar contents of the corresponding seed samples were determined. The results indicated that exogenous GA3 treatment significantly increased seed vigor, H2O2, and O2 - contents but decreased starch and soluble sugar contents of S. glauca black seeds during seed dormancy release. RNA-seq results showed that a total of 1136 DEGs were identified in three comparison groups and were involved mainly in plant hormone signal transduction, diterpenoid biosynthesis, flavonoid biosynthesis, phenylpropanoid biosynthesis, and carbohydrate metabolism pathway. Among them, the DEGs related to diterpenoid biosynthesis (SgGA3ox1, SgKAO and SgGA2ox8) and ABA signal transduction (SgPP2Cs) could play important roles during seed dormancy release. Most genes involved in phenylpropanoid biosynthesis were activated under GA3 treatment conditions, especially many SgPER genes encoding peroxidase. In addition, exogenous GA3 treatment also significantly enhanced the expression of genes involved in flavonoid synthesis, which might be beneficial to seed dormancy release. In accordance with the decline in starch and soluble sugar contents, 15 genes involved in carbohydrate metabolism were significantly up-regulated during GA3-induced dormancy release, such as SgBAM, SgHXK2, and SgAGLU, etc. In a word, exogenous GA3 effectively increased the germination rate and seed vigor of S. glauca black seeds by mediating the metabolic process or signal transduction of plant hormones, phenylpropanoid and flavonoid biosynthesis, and carbohydrate metabolism processes. Our results provide novel insights into the transcriptional regulation mechanism of exogenous GA3 on the dormancy release of S. glauca black seeds. The candidate genes identified in this study may be further studied and used to enrich our knowledge of seed dormancy and germination.

Identification of the miRNA-mRNA regulatory network in a mouse model of early fracture.

Fracture healing is a complex process that involves multiple molecular events, and the regulation mechanism is not fully understood. We acquired miRNA and mRNA transcriptomes of mouse fractures from the Gene Expression Omnibus database (GSE76197 and GSE192542) and integrated the miRNAs and genes that were differentially expressed in the control and fracture groups to construct regulatory networks. There were 130 differentially expressed miRNAs and 4,819 differentially expressed genes, including 72 upregulated and 58 downregulated miRNAs, along with 2,855 upregulated and 1964 downregulated genes during early fracture healing. Gene ontology analysis revealed that most of the differentially expressed genes were enriched in the extracellular matrix (ECM) structure and the ECM organization. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment suggested cell cycle, DNA replication, and mismatch repair were involved in the progression of fracture healing. Furthermore, we constructed a molecular network of miRNAs and mRNAs with inverse expression patterns to elucidate the molecular basis of miRNA-mRNA regulation in fractures. The regulatory network highlighted the potential targets, which may help to provide a mechanistic basis for therapies to improve fracture patient outcomes.

Enhancing the revelation of key genes and interaction networks in non-small cell lung cancer with major depressive disorder: A bioinformatics analysis.

Background and Aims: Lung cancer is ranked as the second most prevalent form of cancer worldwide. Nonsmall cell lung cancer (NSCLC) represents the predominant histological subtype. Research suggests that one-third of lung cancer patients also experiencing depression. Antidepressants play an indispensable role in the management of NSCLC. Despite significant advancements in treatment, lung cancer patients still face a high mortality rate. Major depressive disorder (MDD) and related antidepressants involved in treatment efficacy and prognosis of NSCLC. However, there has been a lack of screening and analysis regarding genes and networks associated with both NSCLC and MDD. Methods: To investigate the correlation between MDD and NSCLC, our discovery and validation analysis included four datasets from the Gene Expression Omnibus database from NSCLC or MDD. Differential gene expression (DEGs) analysis, GO and KEGG Pathway, and protein-protein interaction network analyzes to identify hub genes, networks, and associated observations link between MDD and NSCLC. Results: The analysis of two datasets yielded a total of 84 downregulated and 52 upregulated DEGs. Pathway enrichment analyzes indicated that co-upregulated genes were enriched in the regulation of positive regulation of cellular development, collagen-containing extracellular matrix (ECM), cytokine binding, and axon guidance. We identified 20 key genes, which were further analyzed using the MCODE plugin to identify two core subnetworks. The integration of functionally similar genes provided valuable insights into the potential involvement of these hub genes in diverse biological processes including angiogenesis humoral immune response regulation inflammatory response organization ECM network. Conclusion: We have identified a total of 136 DEGs that participate in multiple biological signaling pathways. A total of 20 hub genes have demonstrated robust associations, potentially indicating novel diagnostic and therapeutic targets for both diseases.

Aging- and alcohol-associated spatial transcriptomic signature in mouse acute pancreatitis reveals heterogeneity of inflammation and potential pathogenic factors.

The rapidly aging population is consuming more alcohol, leading to increased alcohol-associated acute pancreatitis (AAP) with high mortality. However, the mechanisms remain undefined, and currently there are no effective therapies available. This study aims to elucidate aging- and alcohol-associated spatial transcriptomic signature by establishing an aging AAP mouse model and applying Visium spatial transcriptomics for understanding of the mechanisms in the context of the pancreatic tissue. Upon alcohol diet feeding and caerulein treatment, aging mice (18 months) developed significantly more severe AAP with 5.0-fold increase of injury score and 2.4-fold increase of amylase compared to young mice (3 months). Via Visium spatial transcriptomics, eight distinct tissue clusters were revealed from aggregated transcriptomes of aging and young AAP mice: five acinar, two stromal, and one islet, which were then merged into three clusters: acinar, stromal, and islet for the comparative analysis. Compared to young AAP mice, > 1300 differentially expressed genes (DEGs) and approximately 3000 differentially regulated pathways were identified in aging AAP mice. The top five DEGs upregulated in aging AAP mice include Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp with heterogeneous distributions among the clusters. Taken together, this study demonstrates spatial heterogeneity of inflammatory processes in aging AAP mice, offering novel insights into the mechanisms and potential drivers for AAP development. KEY MESSAGES: Mechanisms regarding high mortality of AAP in aging remain undefined. An aging AAP mouse model was developed recapturing clinical exhibition in humans. Spatial transcriptomics identified contrasted DEGs in aging vs. young AAP mice. Top five DEGs were Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp in aging vs. young AAP mice. Our findings shed insights for identification of molecular drivers in aging AAP.

Effect of static magnetic field on gene expression of human umbilical cord mesenchymal stem cells by transcriptome analysis.

PURPOSE: Static magnetic fields (SMFs) induce various biological reactions and have been applied in the biological therapy of diseases, especially in combination with mesenchymal stem cells (MSCs) and tissue engineering. However, the underlying influence of SMFs on MSCs gene expression remains largely unclear. In this study, we aim to investigate the effects of SMFs on gene expression of human MSCs. MATERIALS AND METHODS: We exposed human MSCs to two different intensities (0.35 â€‹T and 1.0 â€‹T) of SMFs and observed the effects of SMFs on cell morphology. Subsequently, RNA-sequencing was performed to explore the gene expression changes. RESULTS: Compared with control group cells, no significant differences in cell morphology were observed under a phase contrast inverted microscope, but the transcriptome of SMF-exposed MSCs were significantly changed in both 0.35 â€‹T and 1.0 â€‹T groups and the differential expressed genes are involved in multiple pathways, such as ubiquitin mediated proteolysis, TNF signaling pathway, NF-kappa B signaling pathway, TGF-beta signaling pathway, metabolic pathways, and apoptosis, which regulate the biological functions of MSCs. CONCLUSIONS: SMFs stimulation could affect the gene expression of human MSCs and the biological effects vary by the different intensities of SMFs. These data offer the molecular foundation for future application of SMFs in stem cell technology as well as tissue engineering medicine.

Root suberization in the response mechanism of melon to autotoxicity.

Continuous cropping obstacles poses significant challenges for melon cultivation, with autotoxicity being a primary inducer. Suberization of cells or tissues is a vital mechanism for plant stress response. Our study aimed to elucidate the potential mechanism of root suberization in melon's response to autotoxicity. Cinnamic acid was used to simulate autotoxicity. Results showed that autotoxicity worsened the root morphology and activity of seedlings. Significant reductions were observed in root length, diameter, surface area, volume and fork number compared to the control in the later stage of treatment, with a decrease ranging from 20% to 50%. The decrease in root activity ranged from 16.74% to 29.31%. Root suberization intensified, and peripheral suberin deposition became more prominent. Autotoxicity inhibited phenylalanineammonia-lyase activity, the decrease was 50% at 16 h. The effect of autotoxicity on cinnamylalcohol dehydrogenase and cinnamate 4-hydroxylase activity showed an initial increase followed by inhibition, resulting in reductions of 34.23% and 44.84% at 24 h, respectively. The peroxidase activity only significantly increased at 24 h, with an increase of 372%. Sixty-three differentially expressed genes (DEGs) associated with root suberization were identified, with KCS, HCT, and CYP family showing the highest gene abundance. GO annotated DEGs into nine categories, mainly related to binding and catalytic activity. DEGs were enriched in 27 KEGG pathways, particularly those involved in keratin, corkene, and wax biosynthesis. Seven proteins, including C4H, were centrally positioned within the protein interaction network. These findings provide insights for improving stress resistance in melons and breeding stress-tolerant varieties.

RNA Sequencing Analyses Reveal the Potential Anti-Inflammatory Mechanisms of Acacetin Against ODG/R Injuries in Microglia.

Background: Acacetin is a natural flavonoid known for its anti-tumor, antioxidant, and anti-inflammatory properties. Our previous studies have shown its protective effects against cerebral ischemia-reperfusion injury (IRI), but the underlying molecular mechanisms remain unclear. Purpose: The study delves into acacetin's mechanism in mitigating cerebral IRI, with a focus on transcriptomic insights. Methods: We established the oxygen-glucose deprivation/re-oxygenation (OGD/R) model in BV2 microglia, treating them with 10µM acacetin. Then we assessed cell proliferation using CCK-8 and measured Lactate Dehydrogenase (LDH) release. High-throughput RNA sequencing (RNA-seq) underpinned the analysis of differentially expressed genes (DEGs) and long non-coding RNAs (lncRNAs), functional enrichment, and alternative splicing events (ASEs), validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results: OGD/R injury significantly impaired cell proliferation and increased LDH release, effects mitigated by acacetin. RNA-seq identified 2148 upregulated and 2135 downregulated DEGs post-OGD/R. In contrast, the acacetin-treated group showed 248 upregulated and 240 downregulated DEGs compared to the OGD/R group. All DEGs were enriched in both Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapping analysis indicated that acacetin treatment reversed the expression of 203 genes affected by OGD/R, including inflammation-related genes such as Isg15, Fcgr1, Il1b, and Parp12. Moreover, the oxidative stress-related gene, Mt2, was downregulated post-OGD/R but upregulated following acacetin treatment. We further found that OGD/R and acacetin treatment could modulate gene splicing events, impacting cell apoptosis or inflammatory responses, such as the A3SS splicing event in the Trim47 gene. RNA-seq also highlighted differential expression of numerous lncRNAs, particularly the upregulation of lncRNA Rmrp and Terc post-OGD/R and their subsequent downregulation post-acacetin treatment. These lncRNAs might regulate cell proliferation through mediating target gene expressions. RT-qPCR validation confirmed these findings. Conclusion: Significant upregulation of genes and ASEs linked to oxidative stress and inflammatory response is observed in cerebral IRI. Acacetin intervention reverses these effects, highlighting its mechanism in alleviating the injury by modulating gene expression and splicing events.

AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

Physiological and transcriptomic analyses reveal the regulatory mechanisms of Anoectochilus roxburghii in response to high-temperature stress.

BACKGROUND: High temperatures significantly affect the growth, development, and yield of plants. Anoectochilus roxburghii prefers a cool and humid environment, intolerant of high temperatures. It is necessary to enhance the heat tolerance of A. roxburghii and breed heat-tolerant varieties. Therefore, we studied the physiological indexes and transcriptome of A. roxburghii under different times of high-temperature stress treatments. RESULTS: Under high-temperature stress, proline (Pro), H2O2 content increased, then decreased, then increased again, catalase (CAT) activity increased continuously, peroxidase (POD) activity decreased rapidly, then increased, then decreased again, superoxide dismutase (SOD) activity, malondialdehyde (MDA), and soluble sugars (SS) content all decreased, then increased, and chlorophyll and soluble proteins (SP) content increased, then decreased. Transcriptomic investigation indicated that a total of 2740 DEGs were identified and numerous DEGs were notably enriched for "Plant-pathogen interaction" and "Plant hormone signal transduction". We identified a total of 32 genes in these two pathways that may be the key genes for resistance to high-temperature stress in A. roxburghii. CONCLUSIONS: To sum up, the results of this study provide a reference for the molecular regulation of A. roxburghii's tolerance to high temperatures, which is useful for further cultivation of high-temperature-tolerant A. roxburghii varieties.

Identification of key genes as potential diagnostic biomarkers in sepsis by bioinformatics analysis.

Background: Sepsis, an infection-triggered inflammatory syndrome, poses a global clinical challenge with limited therapeutic options. Our study is designed to identify potential diagnostic biomarkers of sepsis onset in critically ill patients by bioinformatics analysis. Methods: Gene expression profiles of GSE28750 and GSE74224 were obtained from the Gene Expression Omnibus (GEO) database. These datasets were merged, normalized and de-batched. Weighted gene co-expression network analysis (WGCNA) was performed and the gene modules most associated with sepsis were identified as key modules. Functional enrichment analysis of the key module genes was then conducted. Moreover, differentially expressed gene (DEG) analysis was conducted by the "limma" R package. Protein-protein interaction (PPI) network was created using STRING and Cytoscape, and PPI hub genes were identified with the cytoHubba plugin. The PPI hub genes overlapping with the genes in key modules of WGCNA were determined to be the sepsis-related key genes. Subsequently, the key overlapping genes were validated in an external independent dataset and sepsis patients recruited in our hospital. In addition, CIBERSORT analysis evaluated immune cell infiltration and its correlation with key genes. Results: By WGCNA, the greenyellow module showed the highest positive correlation with sepsis (0.7, p = 2e - 19). 293 DEGs were identified in the merged datasets. The PPI network was created, and the CytoHubba was used to calculate the top 20 genes based on four algorithms (Degree, EPC, MCC, and MNC). Ultimately, LTF, LCN2, ELANE, MPO and CEACAM8 were identified as key overlapping genes as they appeared in the PPI hub genes and the key module genes of WGCNA. These sepsis-related key genes were validated in an independent external dataset (GSE131761) and sepsis patients recruited in our hospital. Additionally, the immune infiltration profiles differed significantly between sepsis and non-sepsis critical illness groups. Correlations between immune cells and these five key genes were assessed, revealing that plasma cells, macrophages M0, monocytes, T cells regulatory, eosinophils and NK cells resting were simultaneously and significantly associated with more than two key genes. Conclusion: This study suggests a critical role of LTF, LCN2, ELANE, MPO and CEACAM8 in sepsis and may provide potential diagnostic biomarkers and therapeutic targets for the treatment of sepsis.

Transcriptome-wide analysis of a superior xylan degrading isolate Penicillium oxalicum 5-18 revealed active lignocellulosic degrading genes.

Lignocellulose biomass raw materials have a high value in energy conversion. Recently, there has been growing interest in using microorganisms to secret a series of enzymes for converting low-cost biomass into high-value products such as biofuels. We previously isolated a strain of Penicillium oxalicun 5-18 with promising lignocellulose-degrading capability. However, the mechanisms of lignocellulosic degradation of this fungus on various substrates are still unclear. In this study, we performed transcriptome-wide profiling and comparative analysis of strain 5-18 cultivated in liquid media with glucose (Glu), xylan (Xyl) or wheat bran (WB) as sole carbon source. In comparison to Glu culture, the number of differentially expressed genes (DEGs) induced by WB and Xyl was 4134 and 1484, respectively, with 1176 and 868 genes upregulated. Identified DEGs were enriched in many of the same pathways in both comparison groups (WB vs. Glu and Xly vs. Glu). Specially, 118 and 82 CAZyme coding genes were highly upregulated in WB and Xyl cultures, respectively. Some specific pathways including (Hemi)cellulose metabolic processes were enriched in both comparison groups. The high upregulation of these genes also confirmed the ability of strain 5-18 to degrade lignocellulose. Co-expression and co-upregulated of genes encoding CE and AA CAZy families, as well as other (hemi)cellulase revealed a complex degradation strategy in this strain. Our findings provide new insights into critical genes, key pathways and enzyme arsenal involved in the biomass degradation of P. oxalicum 5-18.

Potential diagnostic biomarkers for immunogenic cell death in elderly female patients with ischemic stroke: identification and analysis.

Ischemic stroke (IS) is of increasing concern given the aging population and prevalence of unhealthy lifestyles, with older females exhibiting higher susceptibility. This study aimed to identify practical diagnostic markers, develop a diagnostic model for immunogenic cell death (ICD)-associated IS, and investigate alterations in the immune environment caused by hub genes. Differentially expressed genes associated with ICD in IS were identified based on weighted gene co-expression network analysis and the identification of significant modules. Subsequently, machine learning algorithms were employed to screened hub genes, which were further assessed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis. A nomogram mode lwas then constructed for IS diagnosis, and its diagnostic value was assessed using a receiver operating characteristic curve. Finally, alterations in immune cell infiltration were assessed within patients with IS, and the pan-cancer expression patterns of hub genes were evaluated. Three hub genes associated with ICD (PDK4, CCL20, and FBL) were identified. The corresponding nomogram model for IS diagnosis could effectively identify older female patients with IS (area under the curve (AUC) = 0.9555). Overall, the three hub genes exhibit good diagnostic value (AUC > 0.8). CCL20 and FBL are significantly associated with the extent of immune cells infiltration. Moreover, a strong link exists between hub gene expression and pan-cancer prognosis. Cumulatively, these results indicate that ICD-related hub genes critically influence IS progression in older females, presenting novel diagnostic and therapeutic targets for personalized treatment.

The role of interleukin-10 receptor alpha (IL10Rα) in Mycobacterium avium subsp. paratuberculosis infection of a mammary epithelial cell line.

BACKGROUND: Johne's disease is a chronic wasting disease caused by the bacterium Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease is highly contagious and MAP infection in dairy cattle can eventually lead to death. With no available treatment for Johne's disease, genetic selection and improvements in management practices could help reduce its prevalence. In a previous study, the gene coding interleukin-10 receptor subunit alpha (IL10Rα) was associated with Johne's disease in dairy cattle. Our objective was to determine how IL10Rα affects the pathogenesis of MAP by examining the effect of a live MAP challenge on a mammary epithelial cell line (MAC-T) that had IL10Rα knocked out using CRISPR/cas9. The wild type and the IL10Rα knockout MAC-T cell lines were exposed to live MAP bacteria for 72 h. Thereafter, mRNA was extracted from infected and uninfected cells. Differentially expressed genes were compared between the wild type and the IL10Rα knockout cell lines. Gene ontology was performed based on the differentially expressed genes to determine which biological pathways were involved. RESULTS: Immune system processes pathways were targeted to determine the effect of IL10Rα on the response to MAP infection. There was a difference in immune response between the wild type and IL10Rα knockout MAC-T cell lines, and less difference in immune response between infected and not infected IL10Rα knockout MAC-T cells, indicating IL10Rα plays an important role in the progression of MAP infection. Additionally, these comparisons allowed us to identify other genes involved in inflammation-mediated chemokine and cytokine signalling, interleukin signalling and toll-like receptor pathways. CONCLUSIONS: Identifying differentially expressed genes in wild type and ILR10α knockout MAC-T cells infected with live MAP bacteria provided further evidence that IL10Rα contributes to mounting an immune response to MAP infection and allowed us to identify additional potential candidate genes involved in this process. We found there was a complex immune response during MAP infection that is controlled by many genes.

Effects of prolonged application of peracetic acid-based disinfectant on recirculating aquaculture systems stocked with Atlantic salmon parr.

The use of recirculating aquaculture systems (RAS) for Atlantic salmon (Salmo salar) production has become increasingly common. RAS water disinfection plays a crucial role on its biosecurity. Peracetic acid (PAA) is a promising disinfectant due to its powerful oxidative properties, broad antimicrobial spectrum, and rapid degradation into no harmful compounds. This study focused on assessing the consequences of prolonged application of a PAA-based disinfectant in a RAS stocked with salmon parr. The experiment included three treatment groups in triplicate: 0 mg/L PAA (control), 0.1 mg/L PAA, and 1 mg/L PAA, using nine-replicated RAS with a total of 360 fish (14.8 ± 2.3 g; N = 40/RAS). The study spanned 28 days, with samples collected on days 0, 14, and 28. The analyzed parameters were water quality, and fish parameters, including external welfare indicators, gill histology, total antioxidant capacity (TAC), reactive oxygen species/reactive nitrogen species (ROC/RNC), oxidative stress biomarkers related to DNA and protein, cellular DNA damage, and global gene expression. While water quality remained relatively stable, there was an increase in bacterial populations in the groups exposed to PAA, particularly 1 mg/L PAA. Fish weight did not differ between the control and PAA-exposed groups. TAC, ROC/RNC, and oxidative stress biomarkers exhibited similar trends. The study identified >400 differentially expressed genes (DEGs) in the skin, gill, and olfactory organ, with many of these DEGs associated with immune responses. Comparing the transcriptomic profiles of the three tissue organs revealed that the olfactory organ was the most reactive to PAA treatment. This study shows that calculated PAA concentrations of 0.1 mg/L and 1 mg/L in the pump-sump, contributed to an increase of bacteria whereas no detectable differences in health and welfare of salmon parr were found. These findings are promising for the implementation of PAA-based disinfectants in RAS stoked with Atlantic salmon parr.

Observation of Agonistic Behavior in Pacific White Shrimp (Litopenaeus vannamei) and Transcriptome Analysis.

Agonistic behavior has been identified as a limiting factor in the development of intensive L. vannamei aquaculture. However, the characteristics and molecular mechanisms underlying agonistic behavior in L. vannamei remain unclear. In this study, we quantified agonistic behavior through a behavioral observation system and generated a comprehensive database of eyestalk and brain ganglion tissues obtained from both aggressive and nonaggressive L. vannamei employing transcriptome analysis. The results showed that there were nine behavior patterns in L. vannamei which were correlated, and the fighting followed a specific process. Transcriptome analysis revealed 5083 differentially expressed genes (DEGs) in eyestalk and 1239 DEGs in brain ganglion between aggressive and nonaggressive L. vannamei. Moreover, these DEGs were primarily enriched in the pathways related to the energy metabolism process and signal transduction. Specifically, the phototransduction (dme04745) signaling pathway emerges as a potential key pathway for the adjustment of the L. vannamei agonistic behavior. The G protein-coupled receptor kinase 1-like (LOC113809193) was screened out as a significant candidate gene within the phototransduction pathway. Therefore, these findings contribute to an enhanced comprehension of crustacean agonistic behavior and provide a theoretical basis for the selection and breeding of L. vannamei varieties suitable for high-density aquaculture environments.

Integrative bioinformatics approach for identifying key genes and potential therapeutic targets in the concurrent manifestation of hypertrophic cardiomyopathy and pulmonary hypertension.

Background: Hypertrophic cardiomyopathy (HCM), identified as a primary cause of sudden cardiac death (SCD), intertwines with pulmonary hypertension (PH) to amplify cardiovascular morbidity. This complex synergy poses significant therapeutic challenges due to the absence of drugs specifically targeting their concurrent manifestation. This study seeks to unravel the molecular intricacies linking HCM and PH, aiming to lay the groundwork for targeted therapeutic interventions. Methods: Through the analysis of gene expression profiles from datasets GSE36961 (HCM) and GSE113439 (PH) within the public data repository of Gene Expression Omnibus (GEO), this research systematically identified differentially expressed genes (DEGs), conducted extensive functional annotations, and constructed detailed protein-protein interaction (PPI) networks to uncover crucial hub genes. Further, co-expression analyses, alongside drug prediction and molecular docking simulations, were employed to pinpoint potential therapeutic agents that could ameliorate the combined pathology of HCM and PH. Results: Our comprehensive analysis unearthed 79 DEGs shared between HCM and PH, highlighting fourteen as pivotal hub genes. Validation across three additional datasets (GSE35229, GSE32453, and GSE53408) from GEO accentuated secreted phosphoprotein 1 (SPP1) as a key gene of interest. Remarkably, the study identified tacrolimus, ponatinib, bosutinib, dasatinib, doxorubicin, and zanubrutinib as promising drugs for addressing the dual challenge of HCM and PH. Conclusions: The findings of this investigation shed light on the genetic underpinnings of HCM and PH's simultaneous occurrence, emphasizing the central role of SPP1 in their pathogenesis. The identification of six candidate drugs offers a hopeful vista for future therapeutic strategies targeting this complex cardiovascular interplay, marking a significant stride towards mitigating the compounded morbidity of HCM and PH. Future mechanistic and clinical studies are warranted for the investigation of this potential target and therapeutics.

Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection.

This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care.