Severe Type 2 Inflammation Leads to High Platelet-Activating-Factor-Associated Pathology in Chronic Rhinosinusitis with Nasal Polyps-A Hierarchical Cluster Analysis Using Bulk RNA Barcoding and Sequencing.

Platelet-activating factor (PAF) is a phospholipid-derived inflammatory mediator that triggers various inflammatory conditions, including eosinophil activation and recruitment. This study aimed to evaluate the expressions of PAF-metabolism-associated genes, namely genes coding the enzymes involved in PAF synthesis (LPCAT1, LPCAT2, LPCAT3, and LPCAT4), PAF degradation (PAFAH1B2, PAFAH1B3, and PAFAH2), and the gene for the PAF receptor (PTAFR) in subtypes of CRSwNP classified by clinical- or hierarchal-analysis-based classifications. Transcriptomic analysis using bulk RNA barcoding and sequencing (BRB-seq) was performed with CRSwNP, including eosinophilic CRS (ECRS) (n = 9), nonECRS (n = 8), ECRS with aspirin-exacerbated respiratory disease (Asp) (n = 3), and controls with a normal uncinate process mucosa (n = 6). PTAFR was only upregulated in ECRS and nonECRS. In the hierarchical cluster analysis with clusters 1 and 2 reflecting patients with low-to-moderate and high levels of type 2 inflammation, respectively, cluster 1 exhibited a significant downregulation of LPCAT2 and an upregulation of PTAFR expression, while cluster 2 showed an upregulation of LPCAT1, PAFAH1B2, and PTAFR and downregulation of PAFAH2 expression. Understanding this strong PAF-associated pathophysiology in the severe type 2 inflammation group could provide valuable insights into the treatment and management of CRSwNP.

Integrative analyses of genes related to liver ischemia reperfusion injury.

BACKGROUND: Liver ischemia reperfusion injury (LIRI) is not only a common injury during liver transplantation and major hepatic surgery, but also one of the primary factors that affect the outcome of postoperative diseases. However, there are still no reliable ways to tackle the problem. Our study aimed to find some characteristic genes associated with immune infiltration that affect LIRI, which can provide some insights for future research in the future. Therefore, it is essential for the treatment of LIRI, the elucidation of the mechanisms of LIRI, and exploring the potential biomarkers. Efficient microarray and bioinformatics analyses can promote the understanding of the molecular mechanisms of disease occurrence and development. METHOD: Data from GSE151648 were downloaded from GEO data sets, and we performed a comprehensive analysis of the differential expression, biological functions and interactions of LIRI-associated genes. Then we performed Gene ontology (GO) analysis and Kyotoencydlopedia of genes and genomes (KEGG) enrichment analysis of DEGs. At last, we performed a protein-protein interaction network to screen out hub genes. RESULTS: A total of 161 differentially expressed genes (DEGs) were identified. GO analysis results revealed that the changes in the modules were mostly enriched in the neutrophil degranulation, neutrophil activation involved in immune response, and neutrophil mediated immunity. KEGG enrichment analysis of DEGs demonstrated that LIRI mainly involved the cytokine-cytokine receptor interaction. Our data indicated that macrophages and neutrophils are closely related to LIRI. 9 hub genes were screened out in the protein-protein interaction network. CONCLUSIONS: In summary, our data indicated that neutrophil degranulation, neutrophil activation involved in immune response, neutrophil mediated immunity and cytokine-cytokine receptor interaction may play a key role in LIRI, HRH1, LRP2, P2RY6, PKD1L1, SLC8A3 and TNFRSF8, which were identified as potential biomarkers in the occurrence and development of LIRI. However, further studies are needed to validate these findings and explore the molecular mechanism of these biomarkers in LIRI.

IRF1 as a potential biomarker in Mycobacterium tuberculosis infection.

Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456, GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell-cell adhesion and regulation of T-cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine-cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein-protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up-regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834. Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up-regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.

Gene Expression of Prox-1 and Hif-1a in Primo Vessels Inside Lymph Vessels of the Rabbit.

The gene expression of Prox-1 and Hif-1a for the isolated primo vessels (PVs) and composite lymphatic vessels (LVs) containing PVs (LVs + PVs) was investigated by RNA-sequencing (Seq) and quantitative polymerase chain reaction (qRT-PCR) analysis. RNA-Seq on the passed 10 samples on RNA-QC for two experimental groups with PVs and PVs + LVs proceeded to the library construction stage automatically and analyzed differentially expressed genes (DEGs). From the real-time qRT-PCR analysis data, we found the marker genes of Prox-1 and Hif-1a were enriched and decreased in an isolated PVs compared to LVs, respectively. Based on mRNA transcriptional data, Prox-1 and Hif-1a were increased and decreased in PVs compared to LVs + PVs under lipopolysaccharide (LPS) treatment and relieved by acupuncture electric stimulation (AES), respectively. This finding indicates that high and low levels of Prox-1 and Hif-1a may be involved in the function of PVs and that pathophysiological and physiological condition could progress into inflamed lymphatic endothelial cells expanding the PV within the LV.

Transcriptomic variation of the flower-fruit transition in Physalis and Solanum.

MAIN CONCLUSION: Gene expression variations in response to fertilization between Physalis and Solanum might play essential roles in species divergence and fruit evolution. Fertilization triggers variation in fruit development and morphology. The Chinese lantern, a morphological novelty derived from the calyx, is formed upon fertilization in Physalis but is not observed in Solanum. The underlying genetic variations are largely unknown. Here, we documented the developmental and morphological differences in the flower and fruit between Physalis floridana and Solanum pimpinellifolium and then evaluated both the transcript sequence variation and gene expression at the transcriptomic level at fertilization between the two species. In Physalis transcriptomic analysis, 468 unigenes were identified as differentially expressed genes (DEGs) that were strongly regulated by fertilization across 3 years. In comparison with tomato, 14,536 strict single-copy orthologous gene pairs were identified between P. floridana and S. pimpinellifolium in the flower-fruit transcriptome. Nine types of gene variations with specific GO-enriched patterns were identified, covering 58.82% orthologous gene pairs that were DEGs in either trend or dosage at the flower-fruit transition between the two species, which could adequately distinguish Solanum and Physalis, implying that differential gene expression at fertilization might play essential roles during the divergence and fruit evolution of Solanum-Physalis. Virus-induced gene silencing analyses revealed the developmental roles of some transcription factor genes in fertility, Chinese lantern development, and fruit weight control in Physalis. This study presents the first floral transcriptomic resource of Physalis, and reveals some candidate genetic variations accounting for the early fruit developmental evolution in Physalis in comparison to Solanum.

Analysis and Differential Expression of Primo Genes Using RNA-Seq and qRT-PCR Experiments.

Although the existence of the primo vasculature system has been shown in many species, including mice, rats, rabbits and humans, the biological role of this system, including expression of genes and proteins, has not yet been investigated. Especially the transcriptional action by mRNA, which is required for biological action, needs to be studied in primo vasculature biology. Differentially expressed genes in both isolated primo vessels and lymphatic vessels of rabbits were analyzed by RNA sequencing experiments. Primer efficiency and RNA purity of the primo vessels under lipopolysaccharides were confirmed prior to performing real-time qRT-PCR analysis following RNA extraction. We demonstrated that FLT4 was enriched in primo vessels and that several genes, including HSPH1 and EPHB2, were highly expressed in primo vessels compared with lymphatic vessels. Our data show that almost all genes, except HSPA4, were increased or sustained in isolated primo vessels compared with lymphatic vessels (FLT4 2.58 fold, HSPH1 1.83 fold, EPHB2 1.52 fold; whereas HSPA4 decreased 0.50 fold), suggesting primo vessels as a central regulator in diverse physiology. This implies that FLT4, HSPH1, and EPHB2 in high amounts may be involved in the functional activity of primo vessels. Our experimental data show that several genes are highly enriched in primo vessels in the lymphatic vessels of the rabbit.

Integrative analyses of genes associated with idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF), characterized by irreversible scarring and progressive destruction of the lung tissue, is one of the most common types of idiopathic interstitial pneumonia worldwide. However, there are no reliable candidates for curative therapies. Hence, elucidation of the mechanisms of IPF genesis and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis and treatment of IPF. Recently, efficient microarray and bioinformatics analyses have promoted an understanding of the molecular mechanisms of disease occurrence and development, which is necessary to explore genetic alternations and identify potential diagnostic biomarkers. However, high false-positive rates results have been observed based on single microarray datasets. In the current study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of IPF-related genes. Three publicly available microarray datasets including 54 IPF samples and 34 normal samples were integrated by performing gene set enrichment analysis and analyzing differentially expressed genes (DEGs). Our results identified 350 DEGs genetically associated with IPF. Gene ontology analyses revealed that the changes in the modules were mostly enriched in the positive regulation of smooth muscle cell proliferation, positive regulation of inflammatory responses, and the extracellular space. Kyoto encyclopedia of genes and genomes enrichment analysis of DEGs revealed that IPF involves the TNF signaling pathway, NOD-like receptor signaling pathway, and PPAR signaling pathway. To identify key genes related to IPF in the protein-protein interaction network, 20 hub genes were screened out with highest scores. Our results provided a framework for developing new pathological molecular networks related to specific diseases in silico.

Genome-wide characterization of differentially expressed genes provides insights into regulatory network of heat stress response in radish (Raphanus sativus L.).

Heat stress (HS) causes detrimental effects on plant morphology, physiology, and biochemistry that lead to drastic reduction in plant biomass production and economic yield worldwide. To date, little is known about HS-responsive genes involved in thermotolerance mechanism in radish. In this study, a total of 6600 differentially expressed genes (DEGs) from the control and Heat24 cDNA libraries of radish were isolated by high-throughput sequencing. With Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, some genes including MAPK, DREB, ERF, AP2, GST, Hsf, and Hsp were predominantly assigned in signal transductions, metabolic pathways, and biosynthesis and abiotic stress-responsive pathways. These pathways played significant roles in reducing stress-induced damages and enhancing heat tolerance in radish. Expression patterns of 24 candidate genes were validated by reverse-transcription quantitative PCR (RT-qPCR). Based mainly on the analysis of DEGs combining with the previous miRNAs analysis, the schematic model of HS-responsive regulatory network was proposed. To counter the effects of HS, a rapid response of the plasma membrane leads to the opening of specific calcium channels and cytoskeletal reorganization, after which HS-responsive genes are activated to repair damaged proteins and ultimately facilitate further enhancement of thermotolerance in radish. These results could provide fundamental insight into the regulatory network underlying heat tolerance in radish and facilitate further genetic manipulation of thermotolerance in root vegetable crops.

Transcriptome profiling of litchi leaves in response to low temperature reveals candidate regulatory genes and key metabolic events during floral induction.

BACKGROUND: Litchi (Litchi chinensis Sonn.) is an economically important evergreen fruit tree widely cultivated in subtropical areas. Low temperature is absolutely required for floral induction of litchi, but its molecular mechanism is not fully understood. Leaves of litchi played a key role during floral induction and could be the site of low temperature perception. Therefore, leaves were treated under different temperature (15 °C/25 °C), and high-throughput RNA sequencing (RNA-Seq) performed with leaf samples for the de novo assembly and digital gene expression (DGE) profiling analyses to investigate low temperature-induced gene expression changes. RESULTS: 83,107 RNA-Seq unigenes were de novo assembled with a mean length of 1221 bp and approximately 61% of these unigenes (50,345) were annotated against public protein databases. Differentially-expressed genes (DEGs) under low temperature treatment in comparison with the control group were the main focus of our study. Hierarchical clustering analysis arranged 2755 DEGs into eight groups with three significant expression clusters (p-value ≤ 0.05) during floral induction. With the increasing contents of sugars and starch, the expression of genes involved in metabolism of sugars increased dramatically after low temperature induction. One FT gene (Unigene0025396, LcFT1) which produces a protein called 'florigen' was also detected among DEGs of litchi. LcFT1 exhibited an apparent specific tissue and its expression was highly increased after low temperature induction, GUS staining results also showed GUS activity driven by LcFT1 gene promoter can be induced by low temperature, which indicated LcFT1 probably played a pivotal role in the floral induction of litchi under low temperature. CONCLUSIONS: Our study provides a global survey of transcriptomes to better understand the molecular mechanisms underlying changes of leaves in response to low temperature induction in litchi. The analyses of transcriptome profiles and physiological indicators will help us study the complicated metabolism of floral induction in the subtropic evergreen plants.

Transcriptomic characterization of differential gene expression in oral squamous cell carcinoma: a meta-analysis of publicly available microarray data sets.

Oral squamous cell carcinoma (OSCC) is a highly prevalent cancer worldwide, and OSCC often goes undiagnosed until advanced disease is present, which contributes to a low survival rate for OSCC patients. The identification of biomarkers for the early detection OSCC and novel therapeutic targets for OSCC treatment is an important research objective. We performed bioinformatics analyses of the gene expression profile of OSCC using microarray data to identify genes that contribute to the development of OSCC. We also predicted the transcription factors involved in the regulation of differential gene expression in OSCC. Our results showed that PI3K, EGFR, STAT1, and CPBP are important contributors to the changes in cellular physiology that occur during the development of OSCC. Therefore, these genes represent potential diagnostic biomarkers and therapeutic targets for OSCC.

Transcriptome-based gene expression profiling identifies differentially expressed genes critical for salt stress response in radish (Raphanus sativus L.).

KEY MESSAGE: Transcriptome-based gene expression analysis identifies many critical salt-responsive genes in radish and facilitates further dissecting the molecular mechanism underlying salt stress response. Salt stress severely impacts plant growth and development. Radish, a moderately salt-sensitive vegetable crop, has been studied for decades towards the physiological and biochemical performances under salt stress. However, no systematic study on isolation and identification of genes involved in salt stress response has been performed in radish, and the molecular mechanism governing this process is still indistinct. Here, the RNA-Seq technique was applied to analyze the transcriptomic changes on radish roots treated with salt (200 mM NaCl) for 48 h in comparison with those cultured in normal condition. Totally 8709 differentially expressed genes (DEGs) including 3931 up- and 4778 down-regulated genes were identified. Functional annotation analysis indicated that many genes could be involved in several aspects of salt stress response including stress sensing and signal transduction, osmoregulation, ion homeostasis and ROS scavenging. The association analysis of salt-responsive genes and miRNAs exhibited that 36 miRNA-mRNA pairs had negative correlationship in expression trends. Reverse-transcription quantitative PCR (RT-qPCR) analysis revealed that the expression profiles of DEGs were in line with results from the RNA-Seq analysis. Furthermore, the putative model of DEGs and miRNA-mediated gene regulation was proposed to elucidate how radish sensed and responded to salt stress. This study represents the first comprehensive transcriptome-based gene expression profiling under salt stress in radish. The outcomes of this study could facilitate further dissecting the molecular mechanism underlying salt stress response and provide a valuable platform for further genetic improvement of salt tolerance in radish breeding programs.

Expression profiling reveals functionally redundant multiple-copy genes related to zinc, iron and cadmium responses in Brassica rapa.

Genes underlying environmental adaptability tend to be over-retained in polyploid plant species. Zinc deficiency (ZnD) and iron deficiency (FeD), excess Zn (ZnE) and cadmium exposure (CdE) are major environmental problems for crop cultivation, but little is known about the differential expression of duplicated genes upon these stress conditions. Applying Tag-Seq technology to leaves of Brassica rapa grown under FeD, ZnD, ZnE or CdE conditions, with normal conditions as a control, we examined global gene expression changes and compared the expression patterns of multiple paralogs. We identified 812, 543, 331 and 447 differentially expressed genes under FeD, ZnD, ZnE and CdE conditions, respectively, in B. rapa leaves. Genes involved in regulatory networks centered on the transcription factors bHLH038 or bHLH100 were differentially expressed under (ZnE-induced) FeD. Further analysis revealed that genes associated with Zn, Fe and Cd responses tended to be over-retained in the B. rapa genome. Most of these multiple-copy genes showed the same direction of expression change under stress conditions. We conclude that the duplicated genes involved in trace element responses in B. rapa are functionally redundant, making the regulatory network more complex in B. rapa than in Arabidopsis thaliana.

Particulate matter-induced gene expression patterns in human-derived cells based on 11 public gene expression datasets.

BACKGROUND: Exposure to particulate matter (PM) and house dust mite (HDM) can change the expression patterns of inflammation-, oxidative stress-, and cell death-related genes. We investigated the changes in gene expression patterns owing to PM exposure. OBJECTIVE: This study examined the changes in gene expression patterns following PM exposure. METHODS: We searched for differentially expressed genes (DEGs) following PM exposure using five cell line-based RNA-seq or microarray datasets and six human-derived datasets. The enrichment terms of the DEGs were assessed. RESULTS: DEG analysis yielded two gene sets. Thus, enrichment analysis was performed for each gene set, and the enrichment terms related to respiratory diseases were presented. The intersection of six human-derived datasets and two gene sets was obtained, and the expression patterns following PM exposure were observed. CONCLUSIONS: Two gene sets were obtained for cells treated with PM and their expression patterns were presented following verification in human-derived cells. Our findings suggest that exposure to PM2.5 and HDM may reveal changes in genes that are associated with diseases, such as allergies, highlighting the importance of mitigating PM2.5 and HDM exposure for disease prevention.

Identification of novel hub genes for Alzheimer's disease associated with the hippocampus using WGCNA and differential gene analysis.

Background: Alzheimer's disease (AD) is a common, refractory, progressive neurodegenerative disorder in which cognitive and memory deficits are highly correlated with abnormalities in hippocampal brain regions. There is still a lack of hippocampus-related markers for AD diagnosis and prevention. Methods: Differently expressed genes were identified in the gene expression profile GSE293789 in the hippocampal brain region. Enrichment analyses GO, KEGG, and GSEA were used to identify biological pathways involved in the DEGs and AD-related group. WGCNA was used to identify the gene modules that are highly associated with AD in the samples. The intersecting genes of the genes in DEGs and modules were extracted and the top ten ranked hub genes were identified. Finally GES48350 was used as a validation cohort to predict the diagnostic efficacy of hub genes. Results: From GSE293789, 225 DEGs were identified, which were mainly associated with calcium response, glutamatergic synapses, and calcium-dependent phospholipid-binding response. WGCNA analysis yielded dark green and bright yellow modular genes as the most relevant to AD. From these two modules, 176 genes were extracted, which were taken to be intersected with DEGs, yielding 51 intersecting genes. Then 10 hub genes were identified in them: HSPA1B, HSPB1, HSPA1A, DNAJB1, HSPB8, ANXA2, ANXA1, SOX9, YAP1, and AHNAK. Validation of these genes was found to have excellent diagnostic performance. Conclusion: Ten AD-related hub genes in the hippocampus were identified, contributing to further understanding of AD development in the hippocampus and development of targets for therapeutic prevention.

Enhanced clustering-based differential expression analysis method for RNA-seq data.

RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering has been widely used to classify DEGs with similar expression patterns, but rarely used to identify DEGs themselves. We recently reported that the clustering-based method (called MBCdeg1 and 2) for identifying DEGs has great potential. However, these methods left room for improvement. This study reports on the improvement (named MBCdeg3). We compared a total of six competing methods: three conventional R packages (edgeR, DESeq2, and TCC) and three versions of MBCdeg (i.e., MBCdeg1, 2, and 3) corresponding to three different normalization algorithms. As MBCdeg3 performs well in many simulation scenarios of RNA-seq count data, MBCdeg3 replaces MBCdeg1 and 2 in our previous report. •MBCdeg3 is a method for both identification and classification of DEGs from RNA-seq count data.•MBCdeg3 is available as a function of R, which is common in the field of expression analysis.•MBCdeg3 performs well in a variety of simulation scenarios for RNA-seq count data.

Ectoine enhances recombinant antibody production in Chinese hamster ovary cells by promoting cell cycle arrest.

Chinese hamster ovary (CHO) cells represent the most preferential host cell system for therapeutic monoclonal antibody (mAb) production. Enhancing mAb production in CHO cells can be achieved by adding chemical compounds that regulate the cell cycle and cell survival pathways. This study investigated the impact of ectoine supplementation on mAb production in CHO cells. The results showed that adding ectoine at a concentration of 100 mM on the 3rd day of cultivation improved mAb production by improving cell viability and extending the culture duration. RNA sequencing analysis revealed differentially expressed genes associated with cell cycle regulation, cell proliferation, and cellular homeostasis, in particular promotion of cell cycle arrest, which was then confirmed by flow cytometry analysis. Ectoine-treated CHO cells exhibited an increase in the number of cells in the G0/G1 phase. In addition, the cell diameter was also increased. These findings support the hypothesis that ectoine enhances mAb production in CHO cells through mechanisms involving cell cycle arrest and cellular homeostasis. Overall, this study highlights the potential of ectoine as a promising supplementation strategy to enhance mAb production not only in CHO cells but also in other cell lines.

Discovery of differentially expressed proteins for CAR-T therapy of ovarian cancers with a bioinformatics analysis.

Target antigens are crucial for developing chimeric antigen receptor (CAR)-T cells, but their application to ovarian cancers is limited. This study aimed to identify potential genes as CAR-T-cell antigen candidates for ovarian cancers. A differential gene expression analysis was performed on ovarian cancer samples from four datasets obtained from the GEO datasets. Functional annotation, pathway analysis, protein localization, and gene expression analysis were conducted using various datasets and tools. An oncogenicity analysis and network analysis were also performed. In total, 153 differentially expressed genes were identified in ovarian cancer samples, with 60 differentially expressed genes expressing plasma membrane proteins suitable for CAR-T-cell antigens. Among them, 21 plasma membrane proteins were predicted to be oncogenes in ovarian cancers, with nine proteins playing crucial roles in the network. Key genes identified in the oncogenic pathways of ovarian cancers included MUC1, CXCR4, EPCAM, RACGAP1, UBE2C, PRAME, SORT1, JUP, and CLDN3, suggesting them as recommended antigens for CAR-T-cell therapy for ovarian cancers. This study sheds light on potential targets for immunotherapy in ovarian cancers.

Identification of potential biomarkers and pathways for sepsis using RNA sequencing technology and bioinformatic analysis.

Long non-coding RNAs (lncRNAs) has been proven by many to play a crucial part in the process of sepsis. To obtain a better understanding of sepsis, the molecular biomarkers associated with it, and its possible pathogenesis, we obtained data from RNA-sequencing analysis using serum from three sepsis patients and three healthy controls (HCs). Using edgeR (one of the Bioconductor software package), we identified 1118 differentially expressed mRNAs (DEmRNAs) and 1394 differentially expressed long noncoding RNAs (DElncRNAs) between sepsis patients and HCs. We identified the biological functions of these disordered genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analyses. The GO analysis showed that the homophilic cell adhesion via plasma membrane adhesion molecules was the most significantly enriched category. The KEGG signaling pathway analysis indicated that the differentially expressed genes (DEGs) were most significantly enriched in retrograde endocannabinoid signaling. Using STRING, a protein-protein interaction network was also created, and Cytohubba was used to determine the top 10 hub genes. To examine the relationship between the hub genes and sepsis, we examined three datasets relevant to sepsis that were found in the gene expression omnibus (GEO) database. PTEN and HIST2H2BE were recognized as hub gene in both GSE4607, GSE26378, and GSE9692 datasets. The receiver operating characteristic (ROC) curves indicate that PTEN and HIST2H2BE have good diagnostic value for sepsis. In conclusion, this two hub genes may be biomarkers for the early diagnosis of sepsis, our findings should deepen our understanding of the pathogenesis of sepsis.

Identification of key genes and pathways associated with sex differences in rheumatoid arthritis based on bioinformatics analysis.

INTRODUCTION: Women are more likely than men to develop the chronic, progressive autoimmune disease known as rheumatoid arthritis (RA). Although there may be a complex interplay between sex-based differences and autoimmune dysfunction. Their function in RA is largely unknown, though. The purpose of this study was to pinpoint the crucial genes and metabolic pathways that control biological variations in RA between men and women. METHODS: First, the Gene Expression Omnibus database's gene expression information for GSE39340 and GSE55457 was downloaded (GEO). R software was used to find each of the individually identified differentially expressed genes (DEGs) between the sexes. DEGs that overlapped were found. The interactions between the overlapping DEGs were then further examined using a protein-protein interaction (PPI) network. The Kyoto Encyclopedia of Genes and Genomes and Gene Ontology tools, respectively, were used to perform enrichment analyses. RESULTS: According to our findings, there were 1169 DEGs that overlapped between RA males and females, comprising 845 up-regulated genes and 324 down-regulated genes. Ten hub genes, including PIK3R1, RAC1, HRAS, PTPN11, UQCRB, NDUFV1, EGF, UBA1, UBE2G1, and UBE2E1, were discovered in the PPI network. According to a functional enrichment analysis, these genes were primarily enriched in neurodegenerative illnesses, including various disease pathways, MAPK signaling, insulin signaling, and autophagy. CONCLUSION: The current data point to the possibility that the MAPK pathway and autophagy may be significant contributors to sex differences in RA. PTPN11, EGF, and UBA1 may be important genes linked to the gender development of RA and are anticipated to be therapeutic targets for the disease. Key Points • Our research point to the possibility that the MAPK pathway and autophagy may be significant contributors to sex differences in RA. • PTPN11, EGF, and UBA1 may be important genes linked to the gender development of RA and are anticipated to be therapeutic targets for the disease. • These findings may aid in the development of novel diagnostic and treatment techniques for RA in men and women.

Endometrial transcriptome profiling of patients with recurrent implantation failure during hormone replacement therapy cycles.

Background: The molecular mechanisms underlying window of implantation (WOI) displacement in patients with recurrent implantation failure (RIF) remain unclear. This study aims to explore the transcriptomic signatures of endometrium with normal and displaced WOIs and to identify the causes of endometrial receptivity (ER) abnormalities and WOI displacement in RIF patients. Methods: In this study, 40 RIF patients were recruited and underwent personalized embryo transfer (pET) guided by the predicted results of endometrial receptivity diagnosis (ERD) model. Transcriptome analysis of endometrium from patients with clinical pregnancies after pET was performed to identify differentially expressed genes (DEGs) associated with WOI displacement. Gene expression data from HRT and natural cycle endometrium were compared to identify specific gene expression patterns of ER-related genes during WOI. Results: The ERD results indicated that 67.5% of RIF patients (27/40) were non-receptive in the conventional WOI (P+5) of the HRT cycle. The clinical pregnancy rate in RIF patients improved to 65% (26/40) after ERD-guided pET, indicating the effectiveness of transcriptome-based WOI prediction. Among the 26 patients with clinical pregnancy, the gene expression profiles of P+5 endometrium from advanced (n=6), normal (n=10) and delayed (n=10) WOI groups were significantly different from each other. Furthermore, 10 DEGs identified among P+5 endometrium of 3 groups were involved in immunomodulation, transmembrane transport and tissue regeneration, which could accurately classify the endometrium with different WOIs. Additionally, a large number of ER-related genes showed significant correlation and similar gene expression patterns in P+3, P+5, and P+7 endometrium from HRT cycles and LH+5, LH+7, and LH+9 endometrium from natural cycles. Conclusion: Our study shows that ER-related genes share similar gene expression patterns during WOI in both natural and HRT cycles, and their aberrant expression is associated with WOI displacements. The improvement of pregnancy outcomes in RIF patients by adjusting ET timing according to ERD results demonstrates the importance of transcriptome-based endometrial receptivity assessment and the clinical efficiency of ERD model.