Chemokine Signaling Research Articles

Identification and validation of coagulation and fibrinolytic-related diagnostic biomarkers for ulcerative colitis by bioinformatics analysis.

Abnormalities in coagulation and fibrinolytic status have been demonstrated to be relevant to inflammatory bowel disease. Nevertheless, there is no study to methodically examine the role of the coagulation and fibrinolysis-related genes in the diagnosis of ulcerative colitis (UC). UC-related datasets (GSE169568 and GSE94648) were originated from the Gene Expression Omnibus database. The biomarkers related to coagulation and fibrinolysis were identified through combining differentially expressed analysis and machine learning algorithms. Moreover, Gene Set Enrichment Analysis and immune analysis were carried out. A total of 4 biomarkers (MAP2K1, CREBBP, TAF1, and HP) were identified, and biomarkers were markedly enriched in pathways related to immunity, such as T-cell receptor signaling pathway, primary immunodeficiency, chemokine signaling pathway, etc. In total, the infiltrating abundance of 4 immune cells between UC and control was markedly different, namely eosinophils, macrophage M0, resting mast cells, and regulatory T cells. And all biomarkers were significantly relevant to eosinophils. Our findings detected 4 coagulation and fibrinolysis-related biomarkers (MAP2K1, CREBBP, TAF1, and HP) for UC, which contributed to the advancement of UC for further clinical investigation.

Differential expression of plasma cytokines in sepsis patients and their clinical implications.

Sepsis, which is characterized by acute systemic inflammation and is associated with high rates of morbidity and mortality, presents a significant challenge in health care. Some scholars have found that the sequential organ failure assessment (SOFA) and quick SOFA scores are not ideal for predicting severe sepsis and mortality. Microbial culture takes a long time (2-3 d) and provides no information for early diagnosis and treatment. Therefore, new diagnostic methods for sepsis need to be explored. To assess cytokine levels in the plasma of sepsis patients and identify potential biomarkers for diagnosing sepsis. Ten sepsis patients admitted to the emergency department within 24 h of onset were enrolled as the observation group, whereas ten noninfected patients served as the control group. Of the 10 noninfected patients, 9 hypertension combined with cerebral infarction, 1 patients with vertiginous syndrome. Plasma Cytokines were measured using the Bio-Plex Pro™ Human Chemokine Panel 40-plex. Differentially expressed cytokines in plasma of sepsis and nonsepsis patients were analyzed using Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Interleukin (IL)-16, granulocyte-macrophage granulocyte-macrophage colony-stimulating factor (GM-CSF), CX3CL1, CXCL9, CXCL16, CCL25, and CCL23 plasma levels were significantly increased in sepsis patients. GO analysis revealed that these cytokines were mainly associated with cellular structures such as intermediates, nuclear plaques, adhesion plaques, lateral plasma membranes, and cell matrix junctions. These genes were involved in various molecular functions, such as cytokine activity, receptor ligand activity, and signal receptor activator activity, contributing to various biological functions, such as leukocyte chemotaxis, migration, and chemotaxis. KEGG analysis indicated involvement in cytokine cytokine receptor interactions, chemokine signaling pathways, virus-protein interactions with cytokines and cytokine receptors, and the tumor necrosis factor signaling pathway. Elevated serum levels of IL-16, GM-CSF, CX3CL1, CXCL9, CXCL16, CCL25, and CCL23 in sepsis patients suggest their potential as diagnostic biomarkers for sepsis.

Exploring the relationship between lipid metabolism and cognition in individuals living with stable-phase Schizophrenia: a small cross-sectional study using Olink proteomics analysis

BackgroundCognitive impairment is a core symptom of schizophrenia. Metabolic abnormalities impact cognition, and although the influence of blood lipids on cognition has been documented, it remains unclear. We conducted a small cross-sectional study to investigate the relationship between blood lipids and cognition in patients with stable-phase schizophrenia. Using Olink proteomics, we explored the potential mechanisms through which blood lipids might affect cognition from an inflammatory perspective.MethodsA total of 107 patients with stable-phase schizophrenia and cognitive impairment were strictly included. Comprehensive data collection included basic patient information, blood glucose, blood lipids, and body mass index. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and the MATRICS Consensus Cognitive Battery (MCCB). After controlling for confounding factors, we identified differential metabolic indicators between patients with mild and severe cognitive impairment and conducted correlation and regression analyses. Furthermore, we matched two small sample groups of patients with lipid metabolism abnormalities and used Olink proteomics to analyze inflammation-related differential proteins, aiming to further explore the association between lipid metabolism abnormalities and cognition.ResultsThe proportion of patients with severe cognitive impairment (SCI) was 34.58%. Compared to patients with mild cognitive impairment (MCI), those with SCI performed worse in the Attention/Alertness (t = 2.668, p = 0.009) and Working Memory (t = 2.496, p = 0.014) cognitive dimensions. Blood lipid metabolism indicators were correlated with cognitive function, specifically showing that higher levels of TG (r = -0.447, p < 0.001), TC (r = -0.307, p = 0.002), and LDL-C (r = -0.607, p < 0.001) were associated with poorer overall cognitive function. Further regression analysis indicated that TG (OR = 5.578, P = 0.003) and LDL-C (OR = 5.425, P = 0.001) may be risk factors for exacerbating cognitive impairment in individuals with stable-phase schizophrenia. Proteomics analysis revealed that, compared to individuals with stable-phase schizophrenia and normal lipid metabolism, those with hyperlipidemia had elevated levels of 10 inflammatory proteins and decreased levels of 2 inflammatory proteins in plasma, with these changes correlating with cognitive function. The differential proteins were primarily involved in pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway.ConclusionBlood lipids are associated with cognitive function in individuals with stable-phase schizophrenia, with higher levels of TG, TC, and LDL-C correlating with poorer overall cognitive performance. TG and LDL-C may be risk factors for exacerbating cognitive impairment in these patients. From an inflammatory perspective, lipid metabolism abnormalities might influence cognition by activating or downregulating related proteins, or through pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway.

Exploring shared mechanisms between ulcerative colitis and psoriasis and predicting therapeutic natural compounds through bioinformatics and molecular docking

IntroductionPrevious studies have suggested a potential correlation between psoriasis (PS) and ulcerative colitis (UC). However, studies exploring the shared mechanisms of both diseases remain limited. Current treatments primarily involve using immunosuppressive drugs, which can lead to potential side effects and drug resistance. Traditional Chinese medicine has demonstrated favorable efficacy in treating UC and PS with fewer side effects. This study aims to elucidate the shared biological mechanisms underlying UC and PS and to predict natural compounds effective for treating both disorders. MethodWe collected and validated differentially expressed genes associated with UC and PS from the Gene Expression Omnibus database. A protein-protein interaction network was constructed using the STRING database, aiding in identifying core targets. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were utilized to analyze the functions and genomic enrichment of the identified core targets. The CIBERSORT method was employed to assess the correlation of core targets with immune cells. Compounds with potential therapeutic values were selected from the Coremine and TCMSP databases, and their therapeutic efficacy was predicted via molecular docking. ResultsIn UC and PS, 20 common core targets were identified, with matrix metalloproteinase 9 (MMP9), matrix metalloproteinase 1 (MMP1), cluster of differentiation 274 (CD274), C-X-C motif chemokine ligand 10 (CXCL10), and topoisomerase II alpha (TOP2A) emerging as the most relevant targets shared between both conditions. Elevated levels of macrophages and dendritic cells were observed in UC and PS, with CXCL10 exhibiting the closest association with macrophages. UC and PS shared common signaling pathways, including IL-17, TNF, and chemokine signaling pathways, among others. Molecular docking revealed that quercetin, baicalen, irisolidone, rutaecarpine, epigallocatechin-3-gallate, and others held potential as natural compounds for treating both disorders. ConclusionMMP9, MMP1, and CXCL10, central mediators in the inflammatory pathways of UC and PS, establish a shared mechanism by triggering cytokine and chemokine activation, leading to tissue damage and positioning them as promising therapeutic targets for both conditions. Compounds such as quercetin, luteolin, irisolidone, rutaecarpine, and so on may be key drugs for treating both conditions. These findings suggest the potential advancement of therapeutic strategies and the enhancement of patient care by exploring shared mechanisms and predicting promising natural compounds for treating UC and PS.

Abstract P393: Isolevuglandins Regulate Chromatin Accessibility in Hypertensive Human Monocytes

Background: Isolevuglandins (isoLGs) are products of lipid peroxidation that are formed in the presence of reactive oxygen species. IsoLGs are increased in circulating CD14 + monocytes in patients with hypertension and contribute to inflammatory activation. When adducted to histones, isoLGs prevent nucleosome assembly. Moreover, isoLGs induce disassembly of pre-formed nucleosomes. IsoLGs can be induced in cell culture with tert-butyl hydroperoxide (tBHP) and are efficiently scavenged by ethyl-2-hydroxybenzylamine (Et-2HOBA). We hypothesized that isoLGs regulate chromatin accessibility in hypertensive (HTN) monocytes. Methods: Human CD14 + monocytes were isolated from 3 normotensive (NT) and 5 HTN subjects. HTN monocytes were treated with vehicle. NT monocytes were treated with vehicle, tBHP, or co-treated with tBHP and Et-2HOBA. Cells were cultured for 24 hours and submitted for bulk ATAC sequencing to assess regions of open chromatin across the genome. Data were analyzed using Partek Flow software. Reads were aligned to the GRCh38 human genome. Differences in chromatin accessibility were determined by DESeq2 analysis and were considered significant at an adjusted P-value of 0.05 and fold change of 1.5. Reads were filtered to focus on accessible chromatin at transcription start sites (TSS). First, chromatin accessibility of HTN monocytes was compared to NT monocytes. Second, to determine chromatin regions with isoLG-regulated accessibility that are associated with hypertension, we compared control and tBHP+Et2HOBA treated cells to a combined HTN and tBHP treated group. Results: HTN monocytes exhibited increased chromatin accessibility at 131 TSS and decreased accessibility at 56 TSS compared to NT monocytes. Chromatin accessibility was increased at 205 TSS and decreased at 183 TSS in response to both hypertension and isoLGs. Gene set enrichment revealed a significant increase in chromatin accessibility in genes regulating chemokine signaling, RAS signaling, lysosomal activity, and focal adhesion. Conclusions: We determined that significant differences in chromatin accessibility are present in HTN monocytes compared to NT monocytes. IsoLGs regulate chromatin accessibility in HTN monocytes. Moreover, isoLGs regulate accessibility of the TSS of genes involved in inflammation and cell migration. These findings implicate isoLGs as novel post-translational histone modifications that regulate chromatin accessibility and contribute to inflammation in hypertension.

Lactylation signature identifies liver fibrosis phenotypes and traces fibrotic progression to hepatocellular carcinoma.

Precise staging and classification of liver fibrosis are crucial for the hierarchy management of patients. The roles of lactylation are newly found in the progression of liver fibrosis. This study is committed to investigating the signature genes with histone lactylation and their connection with immune infiltration among liver fibrosis with different phenotypes. Firstly, a total of 629 upregulated and 261 downregulated genes were screened out of 3 datasets of patients with liver fibrosis from the GEO database and functional analysis confirmed that these differentially expressed genes (DEGs) participated profoundly in fibrosis-related processes. After intersecting with previously reported lactylation-related genes, 12 DEGs related to histone lactylation were found and narrowed down to 6 core genes using R algorithms, namely S100A6, HMGN4, IFI16, LDHB, S100A4, and VIM. The core DEGs were incorporated into the Least absolute shrinkage and selection operator (LASSO) model to test their power to distinguish the fibrotic stage. Advanced fibrosis presented a pattern of immune infiltration different from mild fibrosis, and the core DEGs were significantly correlated with immunocytes. Gene set and enrichment analysis (GSEA) results revealed that core DEGs were closely linked to immune response and chemokine signaling. Samples were classified into 3 clusters using the LASSO model, followed by gene set variation analysis (GSVA), which indicated that liver fibrosis can be divided into status featuring lipid metabolism reprogramming, immunity immersing, and intermediate of both. The regulatory networks of the core genes shared several transcription factors, and certain core DEGs also presented dysregulation in other liver fibrosis and idiopathic pulmonary fibrosis (IPF) cohorts, indicating that lactylation may exert comparable functions in various fibrotic pathology. Lastly, core DEGs also exhibited upregulation in HCC. Lactylation extensively participates in the pathological progression and immune infiltration of fibrosis. Lactylation and related immune infiltration could be a worthy focus for the investigation of HCC developed from liver fibrosis.

Identification and expression analysis of NOD-like receptor gene family in response to Aeromonas hydrophila and poly I:C challenge in Chinese soft-shelled turtle (Pelodiscus sinensis)

Nucleotide-binding domain (NOD)-like receptors (NLRs), a type of pattern recognition receptor (PRR), specifically recognize pathogen-associated molecular patterns and damage-associated molecular patterns, playing crucial roles in the immune system. Herein, the composition, expression pattern, and co-expressed pathways of NLRs in Pelodiscus sinensis (PsNLRs) were analyzed. Eight PsNLRs, located on seven chromosomes, were first identified from the genome. Phylogenetic analysis revealed that PsNLRs were most closely related to the NLRs of the western painted turtle and the green sea turtle, and could be clustered into four subfamilies. Besides, the expression profile of PsNLRs exhibited tissue-specificity after infection with Aeromonas hydrophila or poly I:C. Nonetheless, PsCIITA and PsNLRP3.2 displayed infection-specific expression patterns, whereas other PsNLRs showed similar expression patterns during A. hydrophila and poly I:C infections. Weighted gene co-expression network analysis found that six PsNLRs were generated in the turquoise module, in which several immune-related signaling pathways were enriched, including “NOD-like receptor signaling pathway”, “NF-κB signaling pathway”, “PI3K-Akt signaling pathway”, “Chemokine signaling pathway”, “Antigen processing and presentation”, and ”Toll-like receptor signaling pathway”. Additionally, three immune-related genes, NF-κB1, TRAF3, and PIK3CG, were identified as hub genes. These results indicated that PsNLRs may play key roles in regulating immune responses in P. sinensis. Overall, an in-depth study of the NLR gene family in P. sinensis would yield insights into developing strategies to combat bacterial and viral infections.

Leveraging PARP-1/2 to Target Distant Metastasis.

Poly (ADP-Ribose) Polymerase (PARP) inhibitors have changed the outcomes and therapeutic strategy for several cancer types. As a targeted therapeutic mainly for patients with BRCA1/2 mutations, PARP inhibitors have commonly been exploited for their capacity to prevent DNA repair. In this review, we discuss the multifaceted roles of PARP-1 and PARP-2 beyond DNA repair, including the impact of PARP-1 on chemokine signalling, immune modulation, and transcriptional regulation of gene expression, particularly in the contexts of angiogenesis and epithelial-to-mesenchymal transition (EMT). We evaluate the pre-clinical role of PARP inhibitors, either as single-agent or combination therapies, to block the metastatic process. Efficacy of PARP inhibitors was demonstrated via DNA repair-dependent and independent mechanisms, including DNA damage, cell migration, invasion, initial colonization at the metastatic site, osteoclastogenesis, and micrometastasis formation. Finally, we summarize the recent clinical advancements of PARP inhibitors in the prevention and progression of distant metastases, with a particular focus on specific metastatic sites and PARP-1 selective inhibitors. Overall, PARP inhibitors have demonstrated great potential in inhibiting the metastatic process, pointing the way for greater use in early cancer settings.

Non-endothelial expression of endomucin in the mouse and human choroid

Endomucin (EMCN) is a 261 amino acid transmembrane glycoprotein that is highly expressed by venous and capillary endothelial cells where it plays a role in VEGF-mediated angiogenesis and regulation of immune cell recruitment. However, it is better known as a histological marker, where it has become widespread due to the commercial availability of high-quality antibodies that work under a wide range of conditions and in many tissues. The specificity of EMCN staining has been well-validated in retinal vessels, but while it has been used extensively as a marker in other tissues of the eye, including the choroid, the pattern of expression has not been described in detail. Here, in addition to endothelial expression in the choriocapillaris and deeper vascular layers, we characterize a population of EMCN-positive perivascular cells in the mouse choroid that did not co-localize with cells expressing other endothelial markers such as PECAM1 or PODXL. To confirm that these cells represented a new population of EMCN-expressing stromal cells, we then performed single cell RNA sequencing in choroids from adult wild-type mice. Analysis of this new dataset confirmed that, in addition to endothelial cells, Emcn mRNA expression was present in choroidal pericytes and a subset of fibroblasts, but not vascular smooth muscle cells. Besides Emcn, no known endothelial gene expression was detected in these cell populations, confirming that they did not represent endothelial-stromal doublets, a common technical artifact in single cell RNA seq datasets. Instead, choroidal Emcn-expressing fibroblasts exhibited high levels of chemokine and interferon signaling genes, while Emcn-negative fibroblasts were enriched in genes encoding extracellular matrix proteins. Emcn expressing fibroblasts were also detected in published datasets from mouse brain and human choroid, suggesting that stromal Emcn expression was not unique to the choroid and was evolutionarily conserved. Together, these findings highlight unique fibroblast and pericyte populations in the choroid and provide new context for the role of EMCN in the eye.

Potential biomarkers and immune characteristics for polycythemia vera-related atherosclerosis using bulk RNA and single-cell RNA datasets: a combined comprehensive bioinformatics and machine learning analysis.

Polycythemia vera (PV) is a myeloproliferative disease characterized by significantly higher hemoglobin levels and positivity for JAK2 mutation. Thrombosis is the main risk event of this disease. Atherosclerosis (AS) can markedly increase the risk of arterial thrombosis in patients with PV. The objectives of our study were to identify potential biomarkers for PV-related AS and to explore the molecular biological association between PV and AS. We extracted microarray datasets from the Gene Expression Omnibus (GEO) dataset for PV and AS. Common differentially expressed genes (CGs) were identified by differential expression analysis. Functional enrichment and protein-protein interaction (PPI) networks were constructed from the CG by random forest models using LASSO regression to identify pathogenic genes and their underlying processes in PV-related AS. The expression of potential biomarkers was validated using an external dataset. A diagnostic nomogram was constructed based on potential biomarkers to predict PV-related AS, and its diagnostic performance was assessed using ROC, calibration, and decision curve analyses. Subsequently, we used single-cell gene set enrichment analysis (GSEA) to analyze the immune signaling pathways associated with potential biomarkers. We also performed immune infiltration analysis of AS with "CIBERSORT" and calculated Pearson's correlation coefficients for potential biomarkers and infiltrating immune cells. Finally, we observed the expression of potential biomarkers in immune cells based on the single-cell RNA dataset. Fifty-two CGs were identified based on the intersection between up-regulated and down-regulated genes in PV and AS. Most biological processes associated with CGs were cytokines and factors associated with chemotaxis of immune cells. The PPI analysis identified ten hub genes, and of these, CCR1 and MMP9 were selected as potential biomarkers with which to construct a diagnostic model using machine learning methods and external dataset validation. These biomarkers could regulate Toll-like signaling, NOD-like signaling, and chemokine signaling pathways associated with AS. Finally, we determined that these potential biomarkers had a strong correlation with macrophage M0 infiltration. Further, the potential biomarkers were highly expressed in macrophages from patients with AS. We identified two CGs (CCR1 and MMP9) as potential biomarkers for PV-related AS and established a diagnostic model based on them. These results may provide insight for future experimental studies for the diagnosis and treatment of PV-related AS.

ILC2-derived LIF licences progress from tissue to systemic immunity

Migration and homing of immune cells are critical for immune surveillance. Trafficking is mediated by combinations of adhesion and chemokine receptors that guide immune cells, in response to chemokine signals, to specific locations within tissues and the lymphatic system to support tissue-localized immune reactions and systemic immunity1,2. Here we show that disruption of leukaemia inhibitory factor (LIF) production from group 2 innate lymphoid cells (ILC2s) prevents immune cells leaving the lungs to migrate to the lymph nodes (LNs). In the absence of LIF, viral infection leads to plasmacytoid dendritic cells (pDCs) becoming retained in the lungs where they improve tissue-localized, antiviral immunity, whereas chronic pulmonary allergen challenge leads to marked immune cell accumulation and the formation of tertiary lymphoid structures in the lung. In both cases immune cells fail to migrate to the lymphatics, leading to highly compromised LN reactions. Mechanistically, ILC2-derived LIF induces the production of the chemokine CCL21 from lymphatic endothelial cells lining the pulmonary lymphatic vessels, thus licensing the homing of CCR7+ immune cells (including dendritic cells) to LNs. Consequently, ILC2-derived LIF dictates the egress of immune cells from the lungs to regulate tissue-localized versus systemic immunity and the balance between allergen and viral responsiveness in the lungs.

Spatial transcriptomics reveals organized and distinct immune activation in cutaneous granulomatous disorders

BackgroundNon-infectious (inflammatory) cutaneous granulomatous disorders include cutaneous sarcoidosis (CS), granuloma annulare (GA), necrobiosis lipoidica (NL), and necrobiotic xanthogranuloma (NXG). These disorders share macrophage predominant inflammation histologically, but the inflammatory architecture and the pattern of extracellular matrix alteration varies. The underlying molecular explanations for these differences remain unclear. ObjectiveTo understand spatial gene expression characteristics in these disorders. MethodsWe performed spatial transcriptomics in cases of CS, GA, NL, and NXG to compare patterns of immune activation and other molecular features in a spatially resolved fashion. ResultsCS is characterized by a polarized, spatially organized T helper (Th) 1 predominant response with classical macrophage activation. GA is characterized by a mixed, but spatially organized pattern of Th1 and Th2 polarization with both classical and alternative macrophage activation. NL showed concomitant activation of Th1, Th2, and Th17 immunity with a mixed pattern of macrophage activation. Activation of type 1 immunity was shared among, CS, GA, and NL and included upregulation of IL-32. NXG showed upregulation of CXCR4-CXCL12/14 chemokine signaling and exaggerated alternative macrophage polarization. Histologic alteration of extracellular matrix correlated with hypoxia and glycolysis programs and type 2 immune activation. ConclusionsInflammatory cutaneous granulomatous disorders show distinct and spatially organized immune activation that correlate with hallmark histologic changes.

Investigation of transcriptional and immunological disparities among patient groups with varied prognostic risk factors in cholangiocarcinoma.

This study explores molecular features associated with better prognosis in cholangiocarcinoma (CCA). The transcriptomic and whole-exome sequencing data obtained from paired tissues of 70 were analyzed, grouping them based on progression-free survival (PFS), differentiation degree, and lymph node metastasis. Among the 70 patients, the TP53 gene mutation frequency was the highest (53%), while FLG gene mutation occurred exclusively in the long PFS group. In the comparison between long and short survival groups, the short PFS group exhibited higher monocyte infiltration levels (p = 0.0287) and upregulation of genes associated with cancer-related transcriptional misregulation, chemokine signaling, and cytokine-cytokine receptor interactions. Differences in immune cell infiltration and gene expression were significant across differentiation and lymph node metastasis groups. Particularly noteworthy was the marked increase in CD8 T cell and NK cell infiltration (p = 0.0291, 0.0459) in the lymph node metastasis group, significantly influences prognosis. Additionally, genes related to platinum resistance, Th17 cell differentiation, and Th1 and Th2 cell differentiation pathways were overexpressed in this group. In summary, higher monocyte infiltration levels in the short PFS group, along with elevated expression of genes associated with cancer-related pathways, suggest a poorer prognosis. The significant increase in CD8 T cell and NK cell infiltration reflects an enhanced anti-tumor immune response, underscoring the relevance of immune infiltration levels and gene expression in predicting outcomes for CCA patients. In this study, we elucidated the pertinent molecular mechanisms and pathways that influence the prognosis of CCAs through comprehensive multi-omics analysis.

Identification of PLAC8 as a Potential Biomarker for the Diagnosis of Interstitial Cystitis.

Interstitial cystitis is a diagnosis of exclusion due to the complexity of its etiology and pathology, which is a chronic disease with an unknown etiology. To our knowledge, few studies were performed to identify predictive biomarkers for interstitial cystitis. This study aimed to identify and validate potential biomarkers for Interstitial Cystitis (IC). The interstitial cystitis datasets were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by using the R package and were subjected to functional and pathway enrichment analysis. Key biomarkers of interstitial cystitis were identified by using Lasso regression analysis and the SVM-RFE algorithm. The diagnostic value of key biomarkers was validated in internal and external datasets, and pathways that relate to biomarkers of interstitial cystitis were screened. The ssGSEA was employed to identify the immune cells closely related to biomarkers. The expression of PLAC8 in patients with interstitial cystitis was detected by Immune-Histochemistry (IHC). Sixteen differentially expressed genes associated with interstitial cystitis were identified, which were primarily linked to the biological process of the chemokine signaling pathway. PLAC8, identified as a biomarker for interstitial cystitis, was validated to express a significantly different between IC and normal bladder tissues. PLAC8-related pathways were analyzed, with a focus on NF-κB, TNF, Toll-like receptor, chemokine, IL-17, and JAK-STAT signaling pathways. PLAC8 was proved to be closely related to immune activations, which is similar to the pathogenesis of IC, which is a chronic dysregulated immune disease. Meanwhile, we also observed a higher level of PLAC8 in IC tissues. PLAC8 has promising application prospects as a biomarker for interstitial cystitis diagnosis. These findings could aid in the diagnosis and treatment of interstitial cystitis.

AD16 attenuates neuroinflammation induced by cerebral ischemia through down-regulating astrocytes A1 polarization

A1 polarization of astrocytes mediated prolonged inflammation contributing to brain injury in ischemic stroke. We have previously shown that AD16 protects against neonatal hypoxic-ischemic brain damage in vivo and oxygen-glucose deprivation in vitro. More recently, AD16 has demonstrated safety, tolerability, and favorable pharmacokinetics in a randomized controlled phase I trial. In this study, we utilized a rat model of transient middle cerebral artery occlusion (tMCAO) to explore whether the anti-inflammatory compound AD16 protects against ischemic brain injury by regulating A1 polarization and its underlying mechanisms. Our results showed that AD16 treatment significantly reduced the brain infarcted volume and improved neurological function in tMCAO rats. GO analysis results show that differential genes among the Sham, tMCAO and AD16 treatment groups are involved in the regulation of cytokine and inflammatory response. KEGG enrichment pathways analysis mainly enriched in cytokine-cytokine receptor interaction, viral protein interaction with cytokine-cytokine receptor, TNF, chemokine, NF-κB and IL-17 signaling pathway. Furthermore, AD16 treatment decreased the permeability of the blood-brain barrier and suppressed neuroinflammation. AD16 treatment also significantly reduced the polarization of A1 and inhibited NF-κB and JAK2/STAT3 signaling pathways. This study demonstrates that AD16 protects against brain injury in ischemic stroke by reducing A1 polarization to suppress neuroinflammation through downregulating NF-κB and JAK2/STAT3 signaling. Our findings uncover a potential molecular mechanism for AD16 and suggest that AD16 holds promising therapeutic potential against cerebral ischemia.

Key genes and immune infiltration patterns and the clinical implications in psoriasis patients.

Psoriasis is an immune-mediated skin disease, closely related to immune regulation. The aim was to understand the pathogenesis of psoriasis further, reveal potential therapeutic targets, and provide new clues for its diagnosis, treatment, and prevention. Expression profiling data were obtained from the Gene Expression Omnibus (GEO) database for skin tissues from healthy population and psoriasis patients. Differentially expressed genes (DEGs) were selected for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analysis separately. Machine learning algorithms were used to obtain characteristic genes closely associated with psoriasis. Receiver operating characteristic (ROC) curve was used to assess the diagnostic value of the characteristic genes for psoriasis. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to calculate the proportion of immune cell infiltration. Correlation analysis was used to characterize the connection between gene expression and immune cell, Psoriasis Area and Severity Index (PASI). A total of 254 DEGs were identified in the psoriasis group, including 185 upregulated and 69 downregulated genes. GO was mainly enriched in cytokine-mediated signaling pathway, response to virus, and cytokine activity. KEGG was mainly focused on cytokine-cytokine receptor interaction and IL-17 signaling pathway. GSEA was mainly in chemokine signaling pathway and cytokine-cytokine receptor interaction. The machine learning algorithm screened nine characteristic genes C10orf99, GDA, FCHSD1, C12orf56, S100A7, INA, CHRNA9, IFI44, and CXCL9. In the validation set, the expressions of these nine genes increased in the psoriasis group, and the AUC values were all>0.9, consistent with those of the training set. The immune infiltration results showed increased proportions of macrophages, T cells, and neutrophils in the psoriasis group. The characteristic genes were positively or negatively correlated to varying degrees with T cells and macrophages. Nine characteristic genes were highly expressed in the moderate to severe psoriasis group and positively correlated with PASI scores. High levels of nine characteristic genes C10orf99, GDA, FCHSD1, C12orf56, S100A7, INA, CHRNA9, IFI44, and CXCL9 were risk factors for psoriasis, the differential expression of which was related to the regulation of immune system activity and PASI scores, affecting the proportions of different immune cells and promoting the occurrence and development of psoriasis.

Study on the Effect of Rhubarb and Its Active Components on Pyroptosis in DKD by Regulating STAT3/Caspase-11 Axis

Rhubarb has been found to have a certain protective effect on improving the kidney function. However, the specific mechanism is still unclear. In this study, network pharmacology, molecular docking spontaneous binding technology and molecular biology experiments were used to verify the mechanism of rhubarb and its active ingredients in the treatment of DKD. A total of 10 active compounds and 121 (larger than average) target proteins were collected. The target proteins with higher degree value were screened by PPI according to degree value as follows: AKT1, STAT3, EGFR, NFKB1, SRC, etc. GO and KEGG enrichment analysis suggest that rhubarb therapy for DKD mainly involves Pathways in cancer, Prostate cancer, Proteoglycans in cancer, Chemokine signaling pathway, PI3K-Akt signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, EGFR tyrosine kinase inhibitor resistance signaling pathway and so on. Furthermore, molecular docking results suggest that hydrogen bonding, salt bridge and hydrophobic interactions contribute to spontaneous binding of the compound to the target protein. Experimental verification shows that rhubarb and aloe emodin affect the mechanism of pyroptosis in diabetic kidney disease by regulating STAT3/Caspase11 axis. In conclusion, this study comprehensively elaborated the active compounds, potential targets and molecular experimental mechanisms of rhubarb to provide the basic experimental theory for clinical treatment of DKD.

Identification of steroid-induced osteonecrosis of the femoral head biomarkers based on immunization and animal experiments

BackgroundSteroid-induced osteonecrosis of femoral head (SONFH) is a severe health risk, and this study aims to identify immune-related biomarkers and pathways associated with the disease through bioinformatics analysis and animal experiments.MethodUsing SONFH-related datasets obtained from the GEO database, we performed differential expression analysis and weighted gene co-expression network analysis (WGCNA) to extract SONFH-related genes. A protein-protein interaction (PPI) network was then constructed, and core sub-network genes were identified. Immune cell infiltration and clustering analysis of SONFH samples were performed to assess differences in immune cell populations. WGCNA analysis was used to identify module genes associated with immune cells, and hub genes were identified using machine learning. Internal and external validation along with animal experiments were conducted to confirm the differential expression of hub genes and infiltration of immune cells in SONFH.ResultsDifferential expression analysis revealed 502 DEGs. WGCNA analysis identified a blue module closely related to SONFH, containing 1928 module genes. Intersection analysis between DEGs and blue module genes resulted in 453 intersecting genes. The PPI network and MCODE module identified 15 key targets enriched in various signaling pathways. Analysis of immune cell infiltration showed statistically significant differences in CD8 + t cells, monocytes, macrophages M2 and neutrophils between SONFH and control samples. Unsupervised clustering classified SONFH samples into two clusters (C1 and C2), which also exhibited significant differences in immune cell infiltration. The hub genes (ICAM1, NR3C1, and IKBKB) were further identified using WGCNA and machine learning analysis. Based on these hub genes, a clinical prediction model was constructed and validated internally and externally. Animal experiments confirmed the upregulation of hub genes in SONFH, with an associated increase in immune cell infiltration.ConclusionThis study identified ICAM1, NR3C1, and IKBKB as potential immune-related biomarkers involved in immune cell infiltration of CD8 + t cells, monocytes, macrophages M2, neutrophils and other immune cells in the pathogenesis of SONFH. These biomarkers act through modulation of the chemokine signaling pathway, Toll-like receptor signaling pathway, and other pathways. These findings provide valuable insights into the disease mechanism of SONFH and may aid in future drug development efforts.

Irradiated tumor cell-released microparticles enhance the therapeutic efficacy of PD-1 inhibitors by promoting M1-TAMs polarization in NSCLC brain metastases

Brain metastases (BMs) are the most common sites of metastasis in patients with non-small cell lung cancer (NSCLC). However, BMs are not responsive to immunotherapy because of the blood-brain barrier. This is because intracranial immune cells such as M2 tumor-associated macrophages (TAMs) accumulate, creating an immunosuppressive tumor microenvironment. In this study, we focused on irradiated tumor cell-released microparticles (RT-MPs) that can cross the blood-brain barrier and influence the intracranial immune microenvironment. Using animal models of BMs, we observed that RT-MPs could penetrate the blood-brain barrier and be swallowed by TAMs. Then the microenvironment of TAMs is shifted from the M2 phenotype to the M1 phenotype, thereby modulating the interactions between TAMs and tumor cells. Single-cell sequencing analysis demonstrated that TAMs, after internalizing RT-MPs, active chemokine signaling pathways and secrete more chemokines, such as CCL5, CXCL2, CXCL1, CCL3, CCL4, and CCL22, attracting more CD4+ T cells and CD8+ T cells, improving immune-mediated killing, and enhancing subsequent combination anti-PD-1 therapy. These findings provide a preclinical foundation for exploring alternative treatments for patients with immunoresistant NSCLC BMs.

Identification and validation of aging-related genes in neuropathic pain using bioinformatics.

Neuropathic pain (NP) is a debilitating and refractory chronic pain with a higher prevalence especially in elderly patients. Cell senescence considered a key pathogenic factor in NP. The objective of this research is to discover genes associated with aging in peripheral blood of individuals with NP using bioinformatics techniques. Two cohorts (GSE124272 and GSE150408) containing peripheral blood samples of NP were downloaded from the GEO database. By merging the two cohorts, differentially expressed aging-related genes (DE-ARGs) were obtained by intersection with aging-related genes. The potential biological mechanisms of DE-ARGs were further analyzed through GO and KEGG. Three machine learning methods, namely, LASSO, SVM-RFE, and Random Forest, were utilized to identify diagnostic biomarkers. A Nomogram model was developed to assess their diagnostic accuracy. The validation of biomarker expression and diagnostic effectiveness was conducted in three distinct pain cohorts. The CIBERSORT algorithm was employed to evaluate the immune cell composition in the peripheral blood of patients with NP and investigate its association with the expression of diagnostic biomarkers. This study identified a total of 24 DE-ARGs, mainly enriched in "Chemokine signaling pathway," "Inflammatory mediator regulation of TRP channels," "HIF-1 signaling pathway" and "FOXO signaling pathway". Three machine learning algorithms identified a total of four diagnostic biomarkers (CEBPA, CEACAM1, BTG3 and IL-1R1) with good diagnostic performance and the similar expression difference trend in different types of pain cohorts. The expression levels of CEACAM1 and IL-1R1 exhibit a positive correlation with the percentage of neutrophils. Using machine learning techniques, our research identified four diagnostic biomarkers related to aging in peripheral blood, providing innovative approaches for the diagnosis and treatment of NP.