The PTGS2/COX2-PGE2 signaling cascade in inflammation: Pro or anti? A case study with type 1 diabetes mellitus

Study on quality control methods and pharmacodynamic material basis of different specifications of Corydalis Rhizoma produced in Zhejiang Province

ETHNOPHARMACOLOGICAL RELEVANCE

The quality control methods of different specifications of Corydalis Rhizoma in Zhejiang China (ZJ CR) are the same, so the quality of each specification couldnot be guaranteed. To clarify the quality control methods and pharmacodynamic material basis of ZJ CR with different specifications could provide reference for the quality control of ZJ CR.

AIM OF THE STUDY

The purpose of this study was to establish a quality control method for ZJ CR with different specifications and to screen out the pharmacodynamic material basis of ZJ CR with different specifications.

MATERIALS AND METHODS

Firstly, according to the existing grading standards, the medicinal materials were divided into specifications, and the character indexes of ZJ CR with different specifications were established. The quality indexes were established by HPLC, network pharmacology and literature retrieval. The correlation between the trait indexes and quality indexes of ZJ CR with different specifications was analyzed, and the best quality control method was established. Further combined with the pharmacodynamic indexes of ZJ CR with different specifications, the pharmacodynamic material basis of ZJ CR with different specifications was screened out by spectrum-effect analysis. The correlation between trait indexes and pharmacodynamic indexes was analyzed to verify the rationality of grade standard.

RESULTS

The three specifications of ZJ CR were CR (Diameter ≥1.1 cm), CR (Diameter <1.1 cm), and CR (No size distinction). Diameter, width, thickness, grain weight, volume and 50 g grain number could be used as the trait indexes of ZJ CR. Protopine (CR1), palmatine hydrochloride (CR2), berberine hydrochloride (CR3), dehydrocorydaline (CR4), tetrahydropalmatine (CR5), tetrahydroberberine (CR6), corydaline (CR7), stylopine (CR8) and isoimperatorin (CR9) were identified. Total components, core components (CR5, CR6, CR7 and CR8), alcohol-soluble extracts (ASE) could be used as quality indexes. The best quality control methods of the three specifications respectively were: the larger the diameter and grain weight, the smaller the number of 50 g grains; The larger the diameter, the smaller the volume, thickness, width and number of 50 g particles; The larger the grain weight and volume, the smaller the number of 50 g grains. The main analgesic components of the three specifications respectively were: CR1, CR2 and core components; CR2, CR4; CR8, CR9. The larger the diameter and the less the number of 50 g grains, the better the analgesic effect of ZJ CR, and the grade standard was reasonable.

CONCLUSIONS

This study showed that the quality control methods and pharmacodynamic material basis of ZJ CR with different specifications were different, which may be caused by the differences in traits and the contribution of main active ingredients. This study constructed an evaluation model combining external traits, internal quality and overall efficacy, and provided theoretical support for the rationality of ZJ CR grade standard.

Mechanism of Xing 9 ling tablet candy for alcoholic liver disease based on network pharmacology

Xing 9 Ling tablet candy (X9LTC) effectively treats alcoholic liver disease (ALD), but its potential mechanism and molecular targets remain unstudied. We aimed to address this gap using network pharmacology. Furthermore, high-performance liquid chromatography (HPLC) and database analysis revealed a total of 35 active ingredients and 311 corresponding potential targets of X9LTC. Protein interaction analysis revealed PTGS2, JUN, and FOS as its core targets. Enrichment analysis indicated that chemical carcinogenesis-receptor activation, IL-17 and TNF signaling pathway were enriched by multiple core targets, which might be the main pathway of action. Further molecular docking validation showed that the core targets had good binding activities with the identified compounds. Animal experiments showed that X9LTC could reduce the high expression of ALT, AST and TG in the serum of ALD mice, alleviate the lesions in liver tissues, and reverse the high expression of PTGS2, JUN, and FOS proteins in the liver tissues. In this study, we established a method for the determination of X9LTC content for the first time, and predicted its active ingredient and mechanism of action in treating ALD, providing theoretical basis for further research.

Deciphering the gut microbiota's (Coprococcus and Subdoligranulum) impact on depression: Network pharmacology and molecular dynamics simulation

Depression, a prevalent mental health condition, significantly impacts global mental impairment rates. While antidepressants are commonly used, treatment-resistant depression (TRD) poses a challenge. Emerging research highlights the role of the gut microbiota in depression through the gut-brain axis. This study identifies key genes associated with depression influenced by specific gut microbiota, Coprococcus and Subdoligranulum. Using bioinformatics tools, potential targets were elucidated, and molecular docking studies were performed. Furthermore, gene expression analysis identified hub-genes related to depression, intersecting with metabolite targets. Protein-protein interaction analysis revealed pivotal targets such as PTGS2 and MMP9. Molecular docking demonstrated 3-Indolepropionic acid's superior affinity over (R)-3-(4-Hydroxyphenyl)lactate. Physicochemical properties and toxicity profiles were compared, suggesting favorable attributes for 3-Indolepropionic acid. Molecular dynamics simulations confirmed stability and interactions of compounds with target proteins. This comprehensive approach sheds light on the complex interplay between gut microbiota, genes, and depression, emphasizing the potential for microbiota-targeted interventions in mental health management.

Integrated metabolomics and serum-feces pharmacochemistry-based network pharmacology to reveal the mechanisms of an herbal prescription against ulcerative colitis

BACKGROUND

CDD-2103 is an herbal prescription used to treat ulcerative colitis (UC). This study aimed to uncover its mechanism by integrating metabolomics and serum-feces pharmacochemistry-based network pharmacology.

METHODS

A DSS-induced chronic colitis mice model was used to evaluate the anti-colitis effect of CDD-2103. Serum and feces metabolomics were conducted to identify differential metabolites and pathways. In the serum-feces pharmacochemistry study, biological samples were collected from rats treated with CDD-2103. Then, network pharmacology was utilized to predict the targets of the identified compounds. Critical genes were extracted through the above-integrated analysis. The interactions between targets, CDD-2103, and its compounds were validated through molecular docking, immunoblotting, and enzyme activity assays.

RESULTS

CDD-2103 alleviated ulcerous symptoms and colonic injuries in colitis mice. Metabolomics study identified differential metabolites associated with tryptophan, glycerophospholipid, and linoleic acid metabolisms. The serum-feces pharmacochemistry study revealed twenty-three compounds, which were subjected to network pharmacology analysis. Integration of these results identified three key targets (AHR, PLA2, and PTGS2). Molecular docking showed strong affinities between the compounds and targets. PTGS2 was identified as a hub gene targeted by most CDD-2103 compounds. Immunoblotting and enzyme activity assays provided further evidence that CDD-2103 alleviates UC, potentially through its inhibitory effect on cyclooxygenase-2 (COX-2, encoded by PTGS2), with alkaloids and curcuminoids speculated as crucial anti-inflammatory compounds.

CONCLUSION

This integrated strategy reveals the mechanism of CDD-2103 and provides insights for developing herbal medicine-based therapies for UC.

Cross-species transcriptomics identifies obesity associated genes between human and mouse studies

BACKGROUND

Fundamentally defined by an imbalance in energy consumption and energy expenditure, obesity is a significant risk factor of several musculoskeletal conditions including osteoarthritis (OA). High-fat diets and sedentary lifestyle leads to increased adiposity resulting in systemic inflammation due to the endocrine properties of adipose tissue producing inflammatory cytokines and adipokines. We previously showed serum levels of specific adipokines are associated with biomarkers of bone remodelling and cartilage volume loss in knee OA patients. Whilst more recently we find the metabolic consequence of obesity drives the enrichment of pro-inflammatory fibroblast subsets within joint synovial tissues in obese individuals compared to those of BMI defined 'health weight'. As such this present study identifies obesity-associated genes in OA joint tissues which are conserved across species and conditions.

METHODS

The study utilised 6 publicly available bulk and single-cell transcriptomic datasets from human and mice studies downloaded from Gene Expression Omnibus (GEO). Machine learning models were employed to model and statistically test datasets for conserved gene expression profiles. Identified genes were validated in OA tissues from obese and healthy weight individuals using quantitative PCR method (N = 38). Obese and healthy-weight patients were categorised by BMI > 30 and BMI between 18 and 24.9 respectively. Informed consent was obtained from all study participants who were scheduled to undergo elective arthroplasty.

RESULTS

Principal component analysis (PCA) was used to investigate the variations between classes of mouse and human data which confirmed variation between obese and healthy populations. Differential gene expression analysis filtered on adjusted p-values of p < 0.05, identified differentially expressed genes (DEGs) in mouse and human datasets. DEGs were analysed further using area under curve (AUC) which identified 12 genes. Pathway enrichment analysis suggests these genes were involved in the biosynthesis and elongation of fatty acids and the transport, oxidation, and catabolic processing of lipids. qPCR validation found the majority of genes showed a tendency to be upregulated in joint tissues from obese participants. Three validated genes, IGFBP2 (p = 0.0363), DOK6 (0.0451) and CASP1 (0.0412) were found to be significantly different in obese joint tissues compared to lean-weight joint tissues.

CONCLUSIONS

The present study has employed machine learning models across several published obesity datasets to identify obesity-associated genes which are validated in joint tissues from OA. These results suggest obesity-associated genes are conserved across conditions and may be fundamental in accelerating disease in obese individuals. Whilst further validations and additional conditions remain to be tested in this model, identifying obesity-associated genes in this way may serve as a global aid for patient stratification giving rise to the potential of targeted therapeutic interventions in such patient subpopulations.

Identification of novel biomarkers related to neutrophilic inflammation in COPD

Background

Chronic obstructive pulmonary disease (COPD) is one of the most prevalent chronic respiratory diseases and the fourth cause of mortality globally. Neutrophilic inflammation has a vital role in the occurrence and progression of COPD. This study aimed to identify the novel hub genes involved in neutrophilic inflammation in COPD through bioinformatic prediction and experimental validation.

Methods

Both the single-cell RNA sequencing (scRNA-seq) dataset (GSE173896) and the RNA sequencing (RNA-seq) dataset (GSE57148) were downloaded from the Gene Expression Omnibus (GEO) database. The Seurat package was used for quality control, dimensions reduction, and cell identification of scRNA-seq. The irGSEA package was used for scoring individual cells. The Monocle2 package was used for the trajectory analysis of neutrophils. The CIBERSORT algorithm was used for analysis of immune cell infiltration in the lungs of COPD patients and controls in RNA-seq dataset, and weighted gene co-expression network analysis (WGCNA) correlated gene modules with neutrophil infiltration. The Mendelian randomization (MR) analysis explored the causal relationship between feature DEGs and COPD. The protein-protein interaction (PPI) network of novel hub genes was constructed, and real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate novel hub genes in clinical specimens.

Results

In scRNA-seq, the gene sets upregulated in COPD samples were related to the neutrophilic inflammatory response and TNF-α activation of the NF-κB signaling pathway. In RNA-seq, immune infiltration analysis showed neutrophils were upregulated in COPD lung tissue. We combined data from differential and modular genes and identified 51 differential genes associated with neutrophilic inflammation. Using MR analysis, 6 genes were explored to be causally associated with COPD. Meanwhile, 11 hub genes were identified by PPI network analysis, and all of them were upregulated. qRT-PCR experiments validated 9 out of 11 genes in peripheral blood leukocytes of COPD patients. Furthermore, 5 genes negatively correlated with lung function in COPD patients. Finally, a network of transcription factors for NAMPT and PTGS2 was constructed.

Conclusion

This study identified nine novel hub genes related to the neutrophilic inflammation in COPD, and two genes were risk factors of COPD, which may serve as potential biomarkers for the clinical severity of COPD.

Gαz-independent and -dependent Improvements With EPA Supplementation on the Early Type 1 Diabetes Phenotype of NOD Mice

Prostaglandin E2 (PGE2) is a key mediator of inflammation and is derived from the omega-6 polyunsaturated fatty acid, arachidonic acid (AA). In the β-cell, the PGE2 receptor, Prostaglandin EP3 receptor (EP3), is coupled to the unique heterotrimeric G protein alpha subunit, Gɑz to reduce the production of cyclic adenosine monophosphate (cAMP), a key signaling molecule that activates β-cell function, proliferation, and survival pathways. Nonobese diabetic (NOD) mice are a strong model of type 1 diabetes (T1D), and NOD mice lacking Gɑz are protected from hyperglycemia. Therefore, limiting systemic PGE2 production could potentially improve both the inflammatory and β-cell dysfunction phenotype of T1D. Here, we sought to evaluate the effect of eicosapentaenoic acid (EPA) feeding, which limits PGE2 production, on the early T1D phenotype of NOD mice in the presence and absence of Gαz. Wild-type and Gαz knockout NOD mice were fed a control or EPA-enriched diet for 12 weeks, beginning at age 4 to 5 weeks. Oral glucose tolerance, splenic T-cell populations, islet cytokine/chemokine gene expression, islet insulitis, measurements of β-cell mass, and measurements of β-cell function were quantified. EPA diet feeding and Gɑz loss independently improved different aspects of the early NOD T1D phenotype and coordinated to alter the expression of certain cytokine/chemokine genes and enhance incretin-potentiated insulin secretion. Our results shed critical light on the Gαz-dependent and -independent effects of dietary EPA enrichment and provide a rationale for future research into novel pharmacological and dietary adjuvant therapies for T1D.

Integration of single-cell RNA sequencing of endothelial cells and proteomics to unravel the role of ICAM1-PTGS2 communication in apical periodontitis: A laboratory investigation

AIM

Endothelial cells (EDs) play a key role in angiogenesis and are associated with granulomatous lesions in patients with chronic apical periodontitis (CAP). This study aimed to investigate the diversity of EDs using single-cell ribonucleic acid sequencing (scRNA-seq) and to evaluate the regulation of intercellular adhesion molecule 1 (ICAM1) on the ferroptosis-related protein, prostaglandin-endoperoxide synthase 2 (PTGS2), in CAP.

METHODOLOGY

EDs from the uploaded scRNA-seq data of five CAP samples (GSE181688 and GSE197680) were categorized using distinct marker genes. The interactions between vein EDs (veinEndo) and other cell types were analysed using CellPhoneDB. Differentially expressed proteins in the proteomics of human umbilical vein EDs (HUVECs) and THP-1-derived macrophages infected with Porphyromonas gingivalis were compared with the differentially expressed genes (DEGs) of VeinEndo in scRNA-seq of CAP versus healthy control periodontal tissues. The protein-protein interaction of ICAM1-PTGS2 in macrophages and HUVECs was validated by adding recombinant ICAM1, ICAM1 inhibitor and PTGS2 inhibitor using real-time polymerase chain reaction (PCR), western blotting, and immunofluorescence staining.

RESULTS

EDs in patients with CAP were divided into eight subclusters: five vein ED, capillaries, arterials and EC (PLA). There were 29 mutually upregulated DEGs and two mutually downregulated DEGs in vein cells in the scRNA-seq data, as well as differentially expressed proteins in the proteomics of HUVECs. Real-time PCR and immunofluorescence staining showed that ICAM1 and PTGS2 were highly expressed in CAP, infected HUVECs, and macrophages. Recombinant protein ICAM1 may improve PTGS2 expression, reactive oxygen species (ROS), and Fe2+ levels and decrease glutathione peroxidase 4 (GPX4) and SLC7A11 protein levels. ICAM1 inhibitor may inverse the above changes.

CONCLUSIONS

scRNA-seq revealed the diversity of EDs in CAP and identified the possible regulation of ICAM1 by the ferroptosis-related protein, PTGS2, in infected HUVECs and macrophages, thus providing a basis for therapeutic approaches that target the inflammatory microenvironment of CAP.

Deciphering the Systemic Impact of Herbal Medicines on Allergic Rhinitis: A Network Pharmacological Approach

Allergic rhinitis (AR) is a systemic allergic disease that has a considerable impact on patients' quality of life. Current treatments include antihistamines and nasal steroids; however, their long-term use often causes undesirable side effects. In this context, traditional Asian medicine (TAM), with its multi-compound, multi-target herbal medicines (medicinal plants), offers a promising alternative. However, the complexity of these multi-compound traits poses challenges in understanding the overall mechanisms and efficacy of herbal medicines. Here, we demonstrate the efficacy and underlying mechanisms of these multi-compound herbal medicines specifically used for AR at a systemic level. We utilized a modified term frequency-inverse document frequency method to select AR-specific herbs and constructed an herb-compound-target network using reliable databases and computational methods, such as the Quantitative Estimate of Drug-likeness for compound filtering, STITCH database for compound-target interaction prediction (with a high confidence score threshold of 0.7), and DisGeNET and CTD databases for disease-gene association analysis. Through this network, we conducted AR-related targets and pathway analyses, as well as clustering analysis based on target-level information of the herbs. Gene ontology enrichment analysis was conducted using a protein-protein interaction network. Our research identified 14 AR-specific herbs and analyzed whether AR-specific herbs are highly related to previously known AR-related genes and pathways. AR-specific herbs were found to target several genes related to inflammation and AR pathogenesis, such as PTGS2, HRH1, and TBXA2R. Pathway analysis revealed that AR-specific herbs were associated with multiple AR-related pathways, including cytokine signaling, immune response, and allergic inflammation. Additionally, clustering analysis based on target similarity identified three distinct subgroups of AR-specific herbs, corroborated by a protein-protein interaction network. Group 1 herbs were associated with the regulation of inflammatory responses to antigenic stimuli, while Group 2 herbs were related to the detection of chemical stimuli involved in the sensory perception of bitter taste. Group 3 herbs were distinctly associated with antigen processing and presentation and NIK/NF-kappa B signaling. This study decodes the principles of TAM herbal configurations for AR using a network pharmacological approach, providing a holistic understanding of drug effects beyond specific pathways.

Unraveling the Mechanism of Xiaochaihu Granules in Alleviating Yeast-Induced Fever Based on Network Analysis and Experimental Validation

Xiaochaihu granules (XCHG) are extensively used to treat fever. Nevertheless, the underlying mechanism remains elusive. This study aimed to explore the potential of XCHG in mitigating yeast-induced fever and the underlying metabolic pathways. The chemical composition of XCHG was ascertained using ultra-fast liquid chromatography/quadrupole-time-of-flight tandem mass spectrometry (UFLC-Q-TOF-MS/MS), followed by integrated network analysis to predict potential targets. We then conducted experimental validation using pharmacological assays and metabolomics analysis in a yeast-induced mouse fever model. The study identified 133 compounds in XCHG, resulting in the development of a comprehensive network of herb-compound-biological functional modules. Subsequently, molecular dynamic (MD) simulations confirmed the stability of the complexes, including γ-aminobutyric acid B receptor 2 (GABBR2)-saikosaponin C, prostaglandin endoperoxide synthases (PTGS2)-lobetyolin, and NF-κB inhibitor IκBα (NFKBIA)-glycyrrhizic acid. Animal experiments demonstrated that XCHG reduced yeast-induced elevation in NFKBIA's downstream regulators [interleukin (IL)-1β and IL-8], inhibited PTGS2 activity, and consequently decreased prostaglandin E2 (PGE2) levels. XCHG also downregulated the levels of 5-hydroxytryptamine (5-HT), γ-aminobutyric acid (GABA), corticotropin releasing hormone (CRH), and adrenocorticotrophin (ACTH). These corroborated the network analysis results indicating XCHG's effectiveness against fever in targeting NFKBIA, PTGS2, and GABBR2. The hypothalamus metabolomics analysis identified 14 distinct metabolites as potential antipyretic biomarkers of XCHG. In conclusion, our findings suggest that XCHG alleviates yeast-induced fever by regulating inflammation/immune responses, neuromodulation, and metabolism modules, providing a scientific basis for the anti-inflammatory and antipyretic properties of XCHG.

Integrating Network Pharmacology and Experimental Verification to Explore the Pharmacological Mechanisms of Radix Paeoniae Rubra Against Glioma

Glioma has a high mortality and can hardly be completely cured. Radix Paeoniae Rubra (RPR) is a prevalent component in traditional Chinese medicine used for tumor treatments. We explored the mechanism of RPR in treating glioma using network pharmacology and experiments. A network pharmacology approach was used to screen active ingredients, targets of RPR and glioma. We then constructed a herb-active ingredient-target-pathway network and conducted protein-protein interaction (PPI) network analysis, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was also performed. Using CCK-8, colony formation, and xenograft experiments, we evaluated the effect of RPR on glioma. The involved pathway and proteins were identified by Western blot. From public databases, we identified nine active RPR ingredients and 40 overlapping targets among 109 RPR targets and 1360 glioma-associated targets. The PPI analysis revealed ten targets, such as AKT1, TP53, and VEGFA, which were identified as hub genes. The results from GO and KEGG analysis highlighted the involvement of the PI3K/AKT pathway. A herb-active ingredient-target-pathway network was constructed. By docking molecular structures, six suitable conformations have been identified. The RPR extract demonstrated anti-tumor properties by inhibiting glioma cell proliferation in vitro and in vivo, likely achieved by suppressing the phosphorylation of the PI3K/AKT signaling pathway. RPR concurrently downregulated the phosphorylation level of AKT1 and the protein expression level of VEGFA, while upregulating the expression of P53 in the U251 cell line. Utilizing network pharmacology and molecular docking, our study not only predicted the impact of RPR on glioma but also delineated the herb-active ingredient-target-pathway network. Experimentally, we confirmed that RPR may exert its anti-tumor properties by inhibiting the phosphorylation of the PI3K/AKT pathway, including AKT1, and by regulating the expression levels of VEGFA and P53.

Identifying inflammation-related targets of natural lactones using network pharmacology, molecular modeling and in vitro approaches

Natural lactones have been used in traditional and folklore medicine for centuries owing to their anti-inflammatory properties. The study uses a multifaceted approach to identify lead anti-inflammatory lactones from the SISTEMATX natural products database. The study analyzed the natural lactone database, revealing 18 lactones linked to inflammation targets. The primary targets were PTGES, PTGS1, COX-2, ALOX5 and IL1B. STX 12273 was the best hit, with the lowest binding energy and potential for inhibiting the COX-2 enzyme. The study suggested natural lactone, STX 12273, from the SISTEMATX database with anti-inflammatory potential and postulated its use for inflammation treatment or prevention.Communicated by Ramaswamy H. Sarma.

Network pharmacology combined with Mendelian randomization analysis to identify the key targets of renin-angiotensin-aldosterone system inhibitors in the treatment of diabetic nephropathy

Background

Diabetic Nephropathy (DN) is one of the microvascular complications of diabetes. The potential targets of renin-angiotensin-aldosterone system (RAAS) inhibitors for the treatment of DN need to be explored.

Methods

The GSE96804 and GSE1009 datasets, 729 RAAS inhibitors-related targets and 6,039 DN-related genes were derived from the public database and overlapped with the differentially expressed genes (DN vs. normal) in GSE96804 to obtain the candidate targets. Next, key targets were screened via the Mendelian randomization analysis and expression analysis. The diagnostic nomogram was constructed and assessed in GSE96804. Additionally, enrichment analysis was conducted and a 'core active ingredient-key target-disease pathway' network was established. Finally, molecular docking was performed.

Results

In total, 60 candidate targets were derived, in which CTSC and PDE5A were screened as the key targets and had a causal association with DN as the protective factors (P < 0.05, OR < 1). Further, a nomogram exhibited pretty prediction efficiency. It is indicated that Benadryl hydrochloride might play a role in the DN by affecting the pathways of 'cytokine cytokine receptor interaction', etc. targeting the CTSC. Moreover, PDE5A might be involved in 'ECM receptor interaction', etc. for the effect of NSAID, captopril, chlordiazepoxide on DN. Molecular docking analysis showed a good binding ability of benadryl hydrochloride and CTSC, NSAID and PDE5A. PTGS2, ITGA4, and ANPEP are causally associated with acute kidney injury.

Conclusion

CTSC and PDE5A were identified as key targets for RAAS inhibitors in the treatment of DN, which might provide some clinical significance in helping to diagnose and treat DN. Among the targets of RAAS inhibitors, PTGS2, ITGA4 and ANPEP have a causal relationship with acute kidney injury, which is worthy of further clinical research.

Delineation and authentication of ferroptosis genes in ventilator-induced lung injury

BACKGROUND

Mechanical ventilation, a critical support strategy for individuals enduring severe respiratory failure and general anesthesia, paradoxically engenders ventilator-induced lung injury (VILI). Ferrostatin-1 mitigates lung injury via ferroptosis inhibition, yet the specific ferroptosis genes contributing significantly to VILI remain obscure.

METHODS

Leveraging the Gene Expression Omnibus database, we acquired VILI-associated datasets and identified differentially expressed genes (DEGs). To identify the hub genes, we constructed a protein-protein interaction network and used three parameters from CytoHubba. Consequently, we identified hub genes and ferroptosis genes as ferroptosis hub genes for VILI (VFHGs). We conducted enrichment analysis and established receiver operating characteristic (ROC) curves for VFHGs. Subsequently, to confirm the correctness of the VFHGs, control group mice and VILI mouse models, as well as external dataset validation, were established. For further research, a gene-miRNA network was established. Finally, the CIBERSORT algorithm was used to fill the gap in the immune infiltration changes in the lung during VILI.

RESULTS

We identified 64 DEGs and 4 VFHGs (Il6,Ptgs2,Hmox1 and Atf3) closely related to ferroptosis. ROC curves demonstrated the excellent diagnostic performance of VFHGs in VILI. PCR and external dataset validation of the VILI model demonstrated the accuracy of VFHGs. Subsequently, the gene-miRNA network was successfully established. Ultimately, an Immune cell infiltration analysis associated with VILI was generated.

CONCLUSIONS

The results emphasize the importance of 4 VFHGs and their involvement in ferroptosis in VILI, confirming their potential as diagnostic biomarkers for VILI.