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Abstract Prior studies suggested that vitamin E might be beneficial in alleviating atopic dermatitis, but confirming a causal link was hindered by limitations such as sample sizes and unaccounted confounders. The present study aimed to clarify this through Mendelian randomization (MR) analysis. GWAS summary statistics was obtained from public databases encompassing a study on vitamin E and two studies related to atopic dermatitis. Two sets of instrumental variables (IVs) were selected using lenient (p 1). Multiple sensitivity tests showed that MR analyses were not affected by heterogeneity and horizontal pleiotropy. Overall, this MR study supported vitamin E reducing the risk of atopic dermatitis. Consequently, maintaining an adequate intake of vitamin E could potentially serve as an effective preventive measure against atopic dermatitis.

Abstract Background Sleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study. Methods Genome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran’s Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability. Results Forward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003–1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096–2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results. Conclusion This study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

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.

Abstract Background Alzheimer’s disease (AD) represents profound degenerative conditions of the brain that cause significant deterioration in memory and cognitive function. Despite extensive research on the significant contribution of lipid metabolism to AD progression, the precise mechanisms remain incompletely understood. Hence, this study aimed to identify key differentially expressed lipid metabolism-related genes (DELMRGs) in AD progression. Methods Comprehensive analyses were performed to determine key DELMRGs in AD compared to controls in GSE122063 dataset from Gene Expression Omnibus. Additionally, the ssGSEA algorithm was utilized for estimating immune cell levels. Subsequently, correlations between key DELMRGs and each immune cell were calculated specifically in AD samples. The key DELMRGs expression levels were validated via two external datasets. Furthermore, gene set enrichment analysis (GSEA) was utilized for deriving associated pathways of key DELMRGs. Additionally, miRNA-TF regulatory networks of the key DELMRGs were constructed using the miRDB, NetworkAnalyst 3.0, and Cytoscape software. Finally, based on key DELMRGs, AD samples were further segmented into two subclusters via consensus clustering, and immune cell patterns and pathway differences between the two subclusters were examined. Results Seventy up-regulated and 100 down-regulated DELMRGs were identified. Subsequently, three key DELMRGs (DLD, PLPP2, and PLAAT4) were determined utilizing three algorithms [(i) LASSO, (ii) SVM-RFE, and (iii) random forest]. Specifically, PLPP2 and PLAAT4 were up-regulated, while DLD exhibited downregulation in AD cerebral cortex tissue. This was validated in two separate external datasets (GSE132903 and GSE33000). The AD group exhibited significantly altered immune cell composition compared to controls. In addition, GSEA identified various pathways commonly associated with three key DELMRGs. Moreover, the regulatory network of miRNA-TF for key DELMRGs was established. Finally, significant differences in immune cell levels and several pathways were identified between the two subclusters. Conclusion This study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.

Background: Previous observational studies suggested a correlation between particulate matter 2.5 (PM2.5) and infectious diseases, but causality remained uncertain. This study utilized Mendelian randomization (MR) analysis to investigate causal relationships between PM2.5 concentrations and various infectious diseases (COVID-19 infection, hospitalized COVID-19, very severe COVID-19, urinary tract infection, bacterial pneumonia, and intestinal infection). Methods: Inverse variance weighted (IVW) was the primary method for evaluating causal associations. For significant causal estimates, multiple sensitivity tests were further performed: (i) three additional MR methods (MR-Egger, weighted median, and maximum likelihood method) for supplementing IVW; (ii) Cochrane's Q test for assessing heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test for evaluating horizontal pleiotropy; (iv) leave-one-out sensitivity test for determining the stability. Results: PM2.5 concentration significantly increased the risk of hospitalized COVID-19 (OR = 1.91, 95 % CI: 1.06–3.45, P = 0.032) and very severe COVID-19 (OR = 3.29, 95 % CI: 1.48–7.35, P = 3.62E-03). However, no causal effect was identified for PM2.5 concentration on other infectious diseases (P > 0.05). Furthermore, various sensitivity tests demonstrated the reliability of significant causal relationships. Conclusions: Overall, lifetime elevated PM2.5 concentration increases the risk of hospitalized COVID-19 and very severe COVID-19. Therefore, controlling air pollution may help mitigate COVID-19 progression.

Abstract Background Increasing evidence has suggested an association between carotid atherosclerosis (CAS) and periodontitis (PD); however, the mechanisms have not been fully understood. This study aims to investigate the shared genes and molecular mechanisms underlying the co-pathogenesis of CAS and PD. Methods Gene Expression Omnibus (GEO) datasets GSE100927 and GSE10334 were downloaded, and differentially expressed genes (DEGs) shared by both datasets were identified. The functional enrichment analysis of these overlapping DEGs was then conducted. A protein-protein interaction (PPI) network was created using the STRING database and Cytoscape software, and PPI key genes were identified using the cytoHubba plugin. Then, weighted gene co-expression network analysis (WGCNA) was performed on GSE100927 and GSE10334, and the gene modules most correlated with CAS and PD were identified as key modules. The genes in key modules overlapping with PPI key genes were determined to be the key crosstalk genes. Subsequently, the key crosstalk genes were validated in three independent external datasets (GSE43292 [CAS microarray dataset], GSE16134 [PD microarray dataset], and GSE28829 [CAS microarray dataset]). In addition, the immune cell patterns of PD and CAS were evaluated by single-sample gene set enrichment analysis (ssGSEA), and the correlation of key crosstalk genes with each immune cell was calculated. Finally, we investigated the transcription factors (TFs) that regulate key crosstalk genes using NetworkAnalyst 3.0 platform. Results 355 overlapping DEGs of CAS and PD were identified. Functional enrichment analysis highlighted the vital role of immune and inflammatory pathways in CAS and PD. The PPI network was constructed, and eight PPI key genes were identified by cytoHubba, including CD4, FCGR2A, IL1B, ITGAM, ITGAX, LCK, PTPRC, and TNF. By WGCNA, the turquoise module was identified as the most correlated module with CAS, and the blue module was identified as the most correlated module with PD. Ultimately, ITGAM and LCK were identified as key crosstalk genes as they appeared both in key modules and PPI key genes. Expression levels of ITGAM and LCK were significantly elevated in the case groups of the test datasets (GSE100927 and GSE10334) and validation datasets (GSE43292, GSE16134, and GSE28829). In addition, the expression of multiple immune cells was significantly elevated in PD and CAS compared to controls, and the two key crosstalk genes were both significantly associated with CD4 T cells. Finally, SPI1 was identified as a potential key TF, which regulates the two key crosstalk genes. Conclusion This study identified the key crosstalk genes and TF in PD and CAS, which provides new insights for further studies on the co-morbidity mechanisms of CAS and PD from an immune and inflammatory perspective.

BackgroundThe pandemic of COVID-19 has had a profound influence on worldwide healthcare systems. Our study aimed to conduct a bibliometric analysis to explore the impact of COVID-19 on stroke and to highlight the major research trends in this field.MethodsWe searched the original articles and review articles regarding COVID-19 and stroke from the Web of Science collection (WOSCC) database between January 1, 2020 and December 30, 2022. Subsequently, we performed bibliometric analyses and visualization using VOSviewer, Citespace, and Scimago Graphica.ResultsA total of 608 original articles or review articles were included. JOURNAL OF STROKE and CEREBROVASCULAR DISEASES published the most studies on this subject (n = 76), while STROKE was the source of the most-cited references (n = 2,393). The United States is the most influential country in this field, with the highest number of publications (n = 223) and citations (n = 5,042). Shadi Yaghi from New York University is the most prolific author in the field, while Harvard Medical School is the most prolific institution. In addition, through keyword analysis and reference co-citation analysis, three major research topics were identified: (i) the impact of COVID-19 on stroke outcomes (including risk factors, clinical characteristics, mortality, stress, depression, comorbidities, etc.); (ii) the management and care of stroke patients during the COVID-19 pandemic (including thrombolysis, thrombectomy, telemedicine, anticoagulation, vaccination, etc.); and (iii) the potential relationship and pathological mechanism between COVID-19 and stroke (including renin-angiotensin system activation, SARS-CoV-2 virus-induced inflammation leading to endothelial impairment, coagulopathy, etc.).ConclusionOur bibliometric analysis provides a comprehensive overview of the current state of research on COVID-19 and stroke and highlights key areas of focus in the field. Optimizing the treatment of COVID-19-infected stroke patients and elucidating the underlying pathogenic mechanisms of COVID-19 and stroke co-morbidity are key areas of future research that will be beneficial in improving the prognosis of stroke patients during the ongoing COVID-19 epidemic.

Background: Previous studies have suggested that dexmedetomidine may have a protective effect on renal function. However, it is currently unclear whether perioperative dexmedetomidine administration is associated with postoperative acute kidney injury (AKI) incidence risk in hypertensive patients undergoing non-cardiac surgery.Methods: This investigation was a retrospective cohort study. Hypertensive patients undergoing non-cardiac surgery in Third Xiangya Hospital of Central South University from June 2018 to December 2019 were included. The relevant data were extracted through electronic cases. The univariable analysis identified demographic, preoperative laboratory, and intraoperative factors associated with acute kidney injury. Multivariable stepwise logistic regression was used to assess the association between perioperative dexmedetomidine administration and postoperative acute kidney injury after adjusting for interference factors. In addition, we further performed sensitivity analyses in four subgroups to further validate the robustness of the results.Results: A total of 5769 patients were included in this study, with a 7.66% incidence of postoperative acute kidney injury. The incidence of postoperative acute kidney injury was lower in the dexmedetomidine-administered group than in the control group (4.12% vs. 8.06%, p < 0.001). In the multivariable stepwise logistic regression analysis, perioperative dexmedetomidine administration significantly reduced the risk of postoperative acute kidney injury after adjusting for interference factors [odds ratio (OR) = 0.56, 95% confidence interval (CI): 0.36–0.87, p = 0.010]. In addition, sensitivity analysis in four subgroups indicated parallel findings: i) eGRF

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal and irreversible interstitial lung disease. The specific mechanisms involved in the pathogenesis of IPF are not fully understood, while metabolic dysregulation has recently been demonstrated to contribute to IPF. This study aims to identify key metabolism-related genes involved in the progression of IPF, providing new insights into the pathogenesis of IPF.Methods: We downloaded four datasets (GSE32537, GSE110147, GSE150910, and GSE92592) from the Gene Expression Omnibus (GEO) database and identified differentially expressed metabolism-related genes (DEMRGs) in lung tissues of IPF by comprehensive analysis. Then, we performed GO, KEGG, and Reactome enrichment analyses of the DEMRGs. Subsequently, key DEMRGs were identified by machine-learning algorithms. Next, miRNAs regulating these key DEMRGs were predicted by integrating the GSE32538 (IPF miRNA dataset) and the miRWalk database. The Cytoscape software was used to visualize miRNA-mRNA regulatory networks. In addition, the relative levels of immune cells were assessed by the CIBERSORT algorithm, and the correlation of key DEMRGs with immune cells was calculated. Finally, the mRNA expression of the key DEMRGs was validated in two external independent datasets and an in vivo experiment.Results: A total of 101 DEMRGs (51 upregulated and 50 downregulated) were identified. Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE). In the lung tissue of IPF patients, the expression levels of ENPP3, ENTPD1, and PDE7B were upregulated, and the expression levels of GPX3, PNMT, and POLR3H were downregulated. In addition, the miRNA-mRNA regulatory network of key DEMRGs was constructed. Then, the expression levels of key DEMRGs were validated in two independent external datasets (GSE53845 and GSE213001). Finally, we verified the key DEMRGs in the lung tissue of bleomycin-induced pulmonary fibrosis mice by qRT-PCR.Conclusion: Our study identified key metabolism-related genes that are differentially expressed in the lung tissue of IPF patients. Our study emphasizes the critical role of metabolic dysregulation in IPF, offers potential therapeutic targets, and provides new insights for future studies.

BackgroundRecent studies have suggested an association between gut microbiomes (GMs) and epilepsy. However, the GM taxa identified in different studies are variable. In addition, observational studies cannot indicate causality. Therefore, our study aimed to explore the causal association of GMs with epilepsy and identify the most influential GM taxa.MethodsWe conducted a Mendelian randomization (MR) study using summary statistics from genome-wide association studies (GWAS) of 211 GM taxa and epilepsy. The GWAS summary statistics for 211 GM taxa (from phylum to genus level) were generated by the MiBioGen consortium, while the FinnGen consortium provided the GWAS summary statistics for epilepsy. The primary analytical method to assess causality was the inverse-variance weighted (IVW) approach. To complement the IVW method, we also applied four additional MR methods: MR-Egger, weighted median, simple mode, and weighted. In addition, we conducted sensitivity analyses using Cochrane’s Q-test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis.ResultsWe evaluated the causal effect of 211 GM taxa (from phylum to genus level) on epilepsy, generalized epilepsy, and focal epilepsy. After using the Bonferroni method for multiple testing correction, Class Betaproteobacteria [odds ratio (OR) = 1.357, 95% confidence interval (CI): 1.126–1.635, p = 0.001] and Order Burkholderiales (OR = 1.336, 95% CI: 1.112–1.606, p = 0.002). In addition, 21 nominally significant causal relationships were also identified. Further, the MR-Egger intercept test and MR-PRESSO global test suggested that our MR analysis was unaffected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis suggested the robustness of the results.ConclusionThrough the MR study, we analyzed the causal relationship of 211 GM taxa with epilepsy and determined the specific intestinal flora associated with increased epilepsy risk. Our findings may provide helpful biomarkers for disease progression and potential candidate therapeutic targets for epilepsy. In addition, in-depth analysis of large-scale microbiome GWAS datasets based on metagenomics sequencing is necessary for future studies.

BackgroundObservational studies have shown an association between gastroesophageal reflux disease (GERD) and anxiety disorders/depression. However, these evidences may be influenced by confounding factors. Therefore, our study aimed to determine the causal relationship between GERD and anxiety disorders/depression by conducting a bidirectional Mendelian randomization (MR) study.MethodsWe performed a bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) in European individuals. The inverse-variance weighted (IVW) method was used as the primary analytical method to assess causality. In addition, five additional MR methods [maximum likelihood, MR-Egger, weighted median, robust adjusted profile score (MR-RAPS), and mode-based estimate (MR-MBE)] were performed to supplement the IVW results. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability. Finally, a multivariable MR (MVMR) analysis was performed to determine the causal relationship by adjusting for potential confounders.ResultsMR results of the IVW method indicated that GERD significantly increases the risk of anxiety disorders [odds ratio (OR) = 1.35, 95% confidence interval (CI) 1.15–1.59, P = 2.25 × 10–4] and depression (OR = 1.32, 95% CI: 1.15–1.52, P = 1.26 × 10–4). In addition, the MR results of maximum likelihood, MR-Egger, weighted median, MR-RAPS, and MR-MBE remained parallel to the IVW results. Furthermore, sensitivity analysis suggested that the results were robust, with no pleiotropy or heterogeneity detected. Nevertheless, reverse MR analysis showed that anxiety or depression did not increase GERD risk. Finally, MVMR analysis showed that the effect of GERD on increasing the risk of anxiety disorders/depression was independent of confounders.ConclusionThis MR study supports a causal association between GERD and an increased risk of anxiety disorders and depression. Therefore, complementing symptomatic treatment of GERD with psychological assessment and necessary psychological support therapy may help reduce the risk of future anxiety disorders and depression.

BackgroundPrevious studies have shown controversy about whether dried fruit intake is associated with cardiovascular disease. This study aimed to examine the potential causal effect of dried fruit intake on cardiovascular disease by conducting a two-sample Mendelian randomization study.MethodsWe used genome-wide association study (GWAS) summary statistics for MR analysis to explore the causal association of dried fruit intake with CVD. The inverse-variance weighted (IVW) method was used as the main analytical method for MR analysis. In addition, the MR-Egger method and the weighted median method were applied to supplement the IVW method. Furthermore, Cochrane’s Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were used to perform sensitivity analysis.ResultsThe results from the IVW analysis indicated that dried fruit intake could reduce the risk of heart failure [odds ratio (OR) = 0.6014, 95% confidence interval (CI): 0.4243–0.8522, p-value = 0.0043], total ischemic stroke (OR = 0.4547, 95% CI: 0.2950–0.7010, p-value = 0.0004), and small vessel stroke (OR = 0.3499, 95% CI: 0.1466–0.8349, p-value = 0.0180). In addition, the results of two additional methods (MR Egger and Weighted median) were parallel to the effects estimated by IVW. Furthermore, the sensitivity analysis illustrates that our MR analysis was unaffected by heterogeneity and horizontal pleiotropy. Finally, the results of the leave-one-out method showed the robustness of our MR results.ConclusionOur study provides evidence for the benefits of dried fruit intake on CVD. Therefore a reasonable consumption of dried fruit may provide primary prevention.

Background: Dexmedetomidine is a commonly used clinical sedative; however, the drug response varies among individuals. Thus, the purpose of this study was to explore the association between dexmedetomidine response and gene polymorphisms related to drug-metabolizing enzymes and drug response (CYP2A6, UGT2B10, UGT1A4, ADRA2A, ADRA2B, ADRA2C, GABRA1, GABRB2, and GLRA1).Methods: This study was a prospective cohort study. A total of 194 female patients aged 18–60 years, American Society of Anesthesiologists (ASA) score I-II, who underwent laparoscopy at the Third Xiangya Hospital of Central South University, were included. The sedative effect was assessed every 2 min using the Ramsay score, and the patient’s heart rate decrease within 20 min was recorded. Peripheral blood was collected from each participant to identify genetic variants in the candidate genes of metabolic and drug effects using the Sequenom MassARRAY® platform. Furthermore, additional peripheral blood samples were collected from the first 99 participants at multiple time points after dexmedetomidine infusion to perform dexmedetomidine pharmacokinetic analysis by Phoenix® WinNonlin 7.0 software.Results: Carriers of the minor allele (C) of CYP2A6 rs28399433 had lower metabolic enzyme efficiency and higher plasma concentrations of dexmedetomidine. In addition, the participants were divided into dexmedetomidine sensitive or dexmedetomidine tolerant groups based on whether they had a Ramsay score of at least four within 20 min, and CYP2A6 rs28399433 was identified to have a significant influence on the dexmedetomidine sedation sensitivity by logistic regression with Plink software [p = 0.003, OR (95% CI): 0.27 (0.11–0.65)]. C allele carriers were more sensitive to the sedative effects of dexmedetomidine than A allele carriers. GABRA2 rs279847 polymorphism was significantly associated with the degree of the heart rate decrease. In particular, individuals with the GG genotype had a 4-fold higher risk of heart rate abnormality than carriers of the T allele (OR = 4.32, 95% CI: 1.96–9.50, p = 0.00027).Conclusion:CYP2A6 rs28399433 polymorphism affects the metabolic rate of dexmedetomidine and is associated with susceptibility to the sedative effects of dexmedetomidine; GABRA2 rs279847 polymorphism is significantly associated with the degree of the heart rate decrease.

BackgroundStroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce.MethodsIn this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS.ResultsA total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p.ConclusionOur study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.

In this paper, a wideband wide-beam circularly polarized (CP) antenna excited by sequential rotation feeding technology is proposed. The antenna is primarily constituted of a loop radiating element and a reactive impedance structure (RIS) cavity. The loop radiator is stimulated by a curved feeding line through six slots etched on the ground, thereby enabling the antenna to achieve broadband performance. In order to achieve a wide 3-dB axial-ratio beamwidth (ARBW), as well as exhibit less effect on the half-power beamwidth (HPBW), a RIS cavity is introduced beneath the loop radiator. To validate the proposed structure, a prototype was constructed and subjected to a series of tests. The results indicate that the bandwidth of the antenna is 187.5% (0.11 ∼ 3.41 GHz) under a 10-dB return loss. In the frequency band spanning from 1.07 GHz to 2.1 GHz, the AR is less than 3 dB, yielding a bandwidth of 64.98%. Furthermore, at the frequencies of 1.2 GHz, 1.5 GHz, and 1.8 GHz, the proposed antenna demonstrates wide beam characteristics, with the HPBW exceeding 90◦, and the 3-dB ARBW within 162◦ 224◦ . In addition, since no extra feeding network is utilized, the antenna is compact in size. [ABSTRACT FROM AUTHOR]

In this paper, a dual-band circularly polarized (CP) antenna with wide axial ratio and gain beamwidths is proposed for high-precision BDS applications. The radiator consists of four groups of dipoles, eight metal columns, and a reflector. The half-power beamwidth (HPBW) can be effectively increased by bending a portion of the dipole into an arc and loading a series of metal columns on the ground. Besides, a reactive impedance structure (RIS) is inserted and serves as a reflector to improve the axial ratio beamwidth (ARBW) and obtain unidirectional radiation. At the same layer of the dipoles, a four-feed network is presented to provide stable quadrature-phase excitation. For validation, the designed antenna is manufactured, where the overall size is 0.48λ × 0.48λ × 0.12λ. Measurement results suggest that the proposed antenna is capable of operating efficiently within the frequency range of 1.17-1.22 GHz (4.2%) and 1.5-1.65 GHz (9.5%), which covers BDS B1 and B2 bands. Moreover, at four main planes, the measured 3-dB ARBW/HPBW are more than 121°/121° and 150°/198° at 1.207 GHz and 1.561 GHz, respectively. Considering that the proposed CP antenna exhibits wide overlapped beamwidth and small size, it is conducive to high-precision positioning in BDS applications. [ABSTRACT FROM AUTHOR]