Hypoxia treatment and resistance training alters microRNA profiling in rats skeletal muscle.

MicroRNAs (miRNAs) may play a crucial regulatory role in the process of muscle atrophy induced by high-altitude hypoxia and its amelioration through resistance training. However, research in this aspect is still lacking. Therefore, this study aimed to employ miRNA microarray analysis to investigate the expression profile of miRNAs in skeletal muscle from an animal model of hypoxia-induced muscle atrophy and resistance training aimed at mitigating muscle atrophy. The study utilized a simulated hypoxic environment (oxygen concentration at 11.2%) to induce muscle atrophy and established a rat model of resistance training using ladder climbing, with a total intervention period of 4 weeks. The miRNA expression profile revealed 9 differentially expressed miRNAs influenced by hypoxia (e.g., miR-341, miR-32-5p, miR-465-5p) and 14 differentially expressed miRNAs influenced by resistance training under hypoxic conditions (e.g., miR-338-5p, miR-203a-3p, miR-92b-3p) (∣log2(FC)∣ ≥ 1.5, p < 0.05). The differentially expressed miRNAs were found to target genes involved in muscle protein synthesis and degradation (such as Utrn, mdm2, eIF4E), biological processes (such as negative regulation of transcription from RNA polymerase II promoter, regulation of transcription, DNA-dependent), and signaling pathways (such as Wnt signaling pathway, MAPK signaling pathway, ubiquitin-mediated proteolysis, mTOR signaling pathway). This study provides a foundation for understanding and further exploring the molecular mechanisms underlying hypoxia-induced rats muscle atrophy and the mitigation of atrophy through resistance training.

Targeting PCSK9 to upregulate MHC-II on the surface of tumor cells in tumor immunotherapy.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9), the last member of the proprotein convertase family, functions as a classic regulator of low-density lipoprotein (LDL) by interacting with low-density lipoprotein receptor (LDLR). Recent studies have shown that PCSK9 can affect the occurrence and development of tumors and can be used as a novel therapeutic target. However, a comprehensive pan-cancer analysis of PCSK9 has yet to be conducted. METHODS: The potential oncogenic effects of PCSK9 in 33 types of tumors were explored based on the datasets of The Cancer Genome Atlas (TCGA) dataset. In addition, the immune regulatory role of PCSK9 inhibition was evaluated via in vitro cell coculture and the tumor-bearing mouse model. Finally, the antitumor efficacy of targeted PCSK9 combined with OVA-II vaccines was verified. RESULTS: Our results indicated that PCSK9 was highly expressed in most tumor types and was significantly correlated with late disease stage and poor prognosis. Additionally, PCSK9 may regulate the tumor immune matrix score, immune cell infiltration, immune checkpoint expression, and major histocompatibility complex expression. Notably, we first found that dendritic cell (DC) infiltration and major histocompatibility complex-II (MHC-II) expression could be upregulated by PCSK9 inhibition and improve CD8+ T cell activation in the tumor immune microenvironment, thereby achieving potent tumor control. Combining PCSK9 inhibitors could enhance the efficacies of OVA-II tumor vaccine monotherapy. CONCLUSIONS: Conclusively, our pan-cancer analysis provided a more comprehensive understanding of the oncogenic and immunoregulatory roles of PCSK9 and demonstrated that targeting PCSK9 could increase the efficacy of long peptide vaccines by upregulating DC infiltration and MHC-II expression on the surface of tumor cells. This study reveals the critical oncogenic and immunoregulatory roles of PCSK9 in various tumors and shows the promise of PCSK9 as a potent immunotherapy target.

Exploring Pyroptosis-related Signature Genes and Potential Drugs in Ulcerative Colitis by Transcriptome Data and Animal Experimental Validation.

Ulcerative colitis (UC) is an idiopathic, relapsing inflammatory disorder of the colonic mucosa. Pyroptosis contributes significantly to UC. However, the molecular mechanisms of UC remain unexplained. Herein, using transcriptome data and animal experimental validation, we sought to explore pyroptosis-related molecular mechanisms, signature genes, and potential drugs in UC. Gene profiles (GSE48959, GSE59071, GSE53306, and GSE94648) were selected from the Gene Expression Omnibus (GEO) database, which contained samples derived from patients with active and inactive UC, as well as health controls. Gene Set Enrichment Analysis (GSEA), Weighted Gene Co-expression Network Analysis (WGCNA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on microarrays to unravel the association between UC and pyroptosis. Then, differential expressed genes (DEGs) and pyroptosis-related DEGs were obtained by differential expression analyses and the public database. Subsequently, pyroptosis-related DEGs and their association with the immune infiltration landscape were analyzed using the CIBERSORT method. Besides, potential signature genes were selected by machine learning (ML) algorithms, and then validated by testing datasets which included samples of colonic mucosal tissue and peripheral blood. More importantly, the potential drug was screened based on this. And these signature genes and the drug effect were finally observed in the animal experiment. GSEA and KEGG enrichment analyses on key module genes derived from WGCNA revealed a close association between UC and pyroptosis. Then, a total of 20 pyroptosis-related DEGs of UC and 27 pyroptosis-related DEGs of active UC were screened. Next, 6 candidate genes (ZBP1, AIM2, IL1ß, CASP1, TLR4, CASP11) in UC and 2 candidate genes (TLR4, CASP11) in active UC were respectively identified using the binary logistic regression (BLR), least absolute shrinkage and selection operator (LASSO), random forest (RF) analysis and artificial neural network (ANN), and these genes also showed high diagnostic specificity for UC in testing sets. Specially, TLR4 was elevated in UC and further elevated in active UC. The results of the drug screen revealed that six compounds (quercetin, cyclosporine, resveratrol, cisplatin, paclitaxel, rosiglitazone) could target TLR4, among which the effect of quercetin on intestinal pathology, pyroptosis and the expression of TLR4 in UC and active UC was further determined by the murine model. These findings demonstrated that pyroptosis may promote UC, and especially contributes to the activation of UC. Pyroptosis-related DEGs offer new ideas for the diagnosis of UC. Besides, quercetin was verified as an effective treatment for pyroptosis and intestinal inflammation. This study might enhance our comprehension on the pathogenic mechanism and diagnosis of UC and offer a treatment option for UC.

Revealing Prdx4 as a potential diagnostic and therapeutic target for acute pancreatitis based on machine learning analysis.

Acute pancreatitis (AP) is a common systemic inflammatory disease resulting from the activation of trypsinogen by various incentives in ICU. The annual incidence rate is approximately 30 out of 100,000. Some patients may progress to severe acute pancreatitis, with a mortality rate of up to 40%. Therefore, the goal of this article is to explore the key genes for effective diagnosis and treatment of AP. The analysis data for this study were merged from two GEO datasets. 1357 DEGs were used for functional enrichment and cMAP analysis, aiming to reveal the pathogenic genes and potential mechanisms of AP, as well as potential drugs for treating AP. Importantly, the study used LASSO and SVM-RFE machine learning to screen the most likely AP occurrence biomarker for Prdx4 among numerous candidate genes. A receiver operating characteristic of Prdx4 was used to estimate the incidence of AP. The ssGSEA algorithm was employed to investigate immune cell infiltration in AP. The biomarker Prdx4 gene exhibited significant associations with a majority of immune cells and was identified as being expressed in NKT cells, macrophages, granulocytes, and B cells based on single-cell transcriptome data. Finally, we found an increase in Prdx4 expression in the pancreatic tissue of AP mice through immunohistochemistry. After treatment with recombinant Prdx4, the pathological damage to the pancreatic tissue of AP mice was relieved. In conclusion, our study identified Prdx4 as a potential AP hub gene, providing a new target for treatment.

Identification and validation of biomarkers related to lipid metabolism in osteoarthritis based on machine learning algorithms.

BACKGROUND: Osteoarthritis and lipid metabolism are strongly associated, although the precise targets and regulatory mechanisms are unknown. METHODS: Osteoarthritis gene expression profiles were acquired from the GEO database, while lipid metabolism-related genes (LMRGs) were sourced from the MigSB database. An intersection was conducted between these datasets to extract gene expression for subsequent differential analysis. Following this, functional analyses were performed on the differentially expressed genes (DEGs). Subsequently, machine learning was applied to identify hub genes associated with lipid metabolism in osteoarthritis. Immune-infiltration analysis was performed using CIBERSORT, and external datasets were employed to validate the expression of these hub genes. RESULTS: Nine DEGs associated with lipid metabolism in osteoarthritis were identified. UGCG and ESYT1, which are hub genes involved in lipid metabolism in osteoarthritis, were identified through the utilization of three machine learning algorithms. Analysis of the validation dataset revealed downregulation of UGCG in the experimental group compared to the normal group and upregulation of ESYT1 in the experimental group compared to the normal group. CONCLUSIONS: UGCG and ESYT1 were considered as hub LMRGs in the development of osteoarthritis, which were regarded as candidate diagnostic markers. The effects are worth expected in the early diagnosis and treatment of osteoarthritis.

Bioinformatics-driven identification of prognostic biomarkers in kidney renal clear cell carcinoma.

Renal cell carcinoma (RCC), particularly the clear cell subtype (ccRCC), poses a significant global health concern due to its increasing prevalence and resistance to conventional therapies. Early detection of ccRCC remains challenging, resulting in poor patient survival rates. In this study, we employed a bioinformatic approach to identify potential prognostic biomarkers for kidney renal clear cell carcinoma (KIRC). By analyzing RNA sequencing data from the TCGA-KIRC project, differentially expressed genes (DEGs) associated with ccRCC were identified. Pathway analysis utilizing the Qiagen Ingenuity Pathway Analysis (IPA) tool elucidated key pathways and genes involved in ccRCC dysregulation. Prognostic value assessment was conducted through survival analysis, including Cox univariate proportional hazards (PH) modeling and Kaplan-Meier plotting. This analysis unveiled several promising biomarkers, such as MMP9, PIK3R6, IFNG, and PGF, exhibiting significant associations with overall survival and relapse-free survival in ccRCC patients. Cox multivariate PH analysis, considering gene expression and age at diagnosis, further confirmed the prognostic potential of MMP9, IFNG, and PGF genes. These findings enhance our understanding of ccRCC and provide valuable insights into potential prognostic biomarkers that can aid healthcare professionals in risk stratification and treatment decision-making. The study also establishes a foundation for future research, validation, and clinical translation of the identified prognostic biomarkers, paving the way for personalized approaches in the management of KIRC.

Potential shared pathogenic mechanisms between endometriosis and inflammatory bowel disease indicate a strong initial effect of immune factors.

Introduction: Over the past decades, immune dysregulation has been consistently demonstrated being common charactoristics of endometriosis (EM) and Inflammatory Bowel Disease (IBD) in numerous studies. However, the underlying pathological mechanisms remain unknown. In this study, bioinformatics techniques were used to screen large-scale gene expression data for plausible correlations at the molecular level in order to identify common pathogenic pathways between EM and IBD. Methods: Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects. Results: 113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1、VCAM1、CLU、C3、CD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPB、CAY-10577、PD-0325901 etc.) targeting therapeutic genes for EM and IBD. Discussion: Our research revealed common pathogenic mechanisms between EM and IBD, particularly emphasizing immune regulation and cell signalling, indicating the significance of immune factors in the occurence and progression of both diseases. By elucidating shared mechanisms, our study provides novel avenues for the prevention and treatment of EM and IBD.

Unveiling the link between lactate metabolism and rheumatoid arthritis through integration of bioinformatics and machine learning.

Rheumatoid arthritis (RA) is a persistent autoimmune condition characterized by synovitis and joint damage. Recent findings suggest a potential link to abnormal lactate metabolism. This study aims to identify lactate metabolism-related genes (LMRGs) in RA and investigate their correlation with the molecular mechanisms of RA immunity. Data on the gene expression profiles of RA synovial tissue samples were acquired from the gene expression omnibus (GEO) database. The RA database was acquired by obtaining the common LMRDEGs, and selecting the gene collection through an SVM model. Conducting the functional enrichment analysis, followed by immuno-infiltration analysis and protein-protein interaction networks. The results revealed that as possible markers associated with lactate metabolism in RA, KCNN4 and SLC25A4 may be involved in regulating macrophage function in the immune response to RA, whereas GATA2 is involved in the immune mechanism of DC cells. In conclusion, this study utilized bioinformatics analysis and machine learning to identify biomarkers associated with lactate metabolism in RA and examined their relationship with immune cell infiltration. These findings offer novel perspectives on potential diagnostic and therapeutic targets for RA.

Pan-cancer analysis of polo-like kinase family genes reveals polo-like kinase 1 as a novel oncogene in kidney renal papillary cell carcinoma.

Background: Polo-like kinases (PLKs) are a kinase class of serine/threonine with five members that play crucial roles in cell cycle regulation. However, their biological functions, regulation, and expression remain unclear. This study revealed the molecular properties, oncogenic role, and clinical significance of PLK genes in pan-cancers, particularly in kidney renal papillary cell carcinoma (KIRP). Methods: We evaluated the mutation landscape, expression level, and prognostic values of PLK genes using bioinformatics analyses and explored the association between the expression level of PLK genes and tumor microenvironment (TME), immune subtype, cancer immunotherapy, tumor stemness, and drug sensitivity. Finally, we verified the prognostic value in patients with KIRP through univariate and multivariate analyses and nomogram construction. Results: PLK genes are extensively altered in pan-cancer, which may contribute to tumorigenesis. These genes are aberrantly expressed in some types of cancer, with PLK1 being overexpressed in 31 cancers. PLK expression is closely associated with the prognosis of various cancers. The expression level of PLK genes is related with sensitivity to diverse drugs and cancer immunity as well as cancer immunotherapy. Importantly, we verified that PLK1 was overexpressed in KIRP tissues and could be an unfavorable prognostic biomarker in patients with KIRP. Hence, PLK1 may serve as an oncogenic gene in KIRP and should be explored in future studies. Conclusions: Our study comprehensively reports the molecular characteristics and biological functions of PLK family gens across human cancers and recommends further investigation of these genes as potential biomarkers and therapeutic targets, especially in KIRP.

Bioinformatics analysis and experimental verification of TIGD1 in non-small cell lung cancer.

Introduction: Non-small cell lung cancer (NSCLC) is a prevalent respiratory system tumor. Triggered transposable element derivative 1 (TIGD1) exhibits significant overexpression in various tumor cells and tissues, suggesting its involvement in cancer progression. Methods: Clinical data and gene expression profiles of lung adenocarcinoma were collected from TCGA, UCSC XENA, and GEO databases. Computational techniques and empirical studies were employed to analyze the role of TIGD1 in NSCLC. Cellular experiments were conducted using the H1299 cell line, including RNA interference, cell viability assays, quantitative PCR, wound-healing assays, western blotting, and plate clone formation assays. Results: Bioinformatics analysis revealed TIGD1's potential as a biomarker for diagnosing and predicting lung cancer. It also indicated promise as a target for immune-related therapy and targeted drug therapy. Cellular studies confirmed TIGD1's involvement in cancer cell proliferation, invasion, and migration. Furthermore, an association between TIGD1 and the PI3K/AKT signaling pathway was suggested. Discussion: The findings suggest that TIGD1 plays a vital role in NSCLC progression, making it a potential diagnostic biomarker and therapeutic target. The association with the PI3K/AKT signaling pathway provides insights into the underlying molecular mechanisms. Integrating computational analysis with empirical studies enhances our understanding of TIGD1's significance in NSCLC and opens avenues for further research into targeted therapies.

Trehalose synthases from the subfamily GH13_16 involved in α-glucan biosynthesis - A focus on their maltokinase domain.

The subfamily GH13_16 trehalose synthase (TreS) converts maltose to trehalose and vice versa. Typically, it consists of three domains, but it may contain a C-terminal extension exhibiting clear sequence features of a maltokinase (MaK). The present in silico study was focused on collection of naturally fused TreS-MaKs and their subsequent detailed bioinformatics analysis. Hence a set of total 3354 unique sequences was compared consisting of 1900 single TreSs, 1426 fused TreS-MaKs and 28 single MaKs. Fused TreS-MaKs were divided into five groups, namely with a standard MaK, with mutations in the maltose-binding site, of the catalytic nucleophile, of the general acid/base and of both catalytic residues. Sequence logos bearing the best conserved sequence regions were prepared for both TreSs and MaKs in an effort to find unique sequence features. In addition, linkers connecting the TreS and MaK parts in the fused enzymes were analysed. This analysis revealed that MaKs in fused enzymes have an extended N-terminal regions compared to single MaKs. Finally, the evolutionary relationships were demonstrated by phylogenetic trees of TreS parts from single TreSs and fused TreS-MaKs from the same organism as well as of single TreSs existing in multiple isoforms in the same organism.

Febuxostat attenuates secondary brain injury caused by cerebral hemorrhage through inhibiting inflammatory pathways.

Objectives: Neuroinflammation is considered an important step in the progression of secondary brain injury (SBI) induced by cerebral hemorrhage (ICH). The nucleotide-binding and oligomerization structural domain-like receptor family of pyridine structural domain-containing 3 (NLRP3) inflammasomes play an important role in the immune pathophysiology of SBI. Febuxostat (Feb) is a xanthine oxidase inhibitor that is approved for the treatment of gout and has been found to have potent anti-inflammatory effects. However, it has been less studied after ICH and we aimed to explore its protective role in ICH. Materials and Methods: We established an autologous blood-brain hemorrhage model in C57BL/6 mice. Functions of co-expressed genes were analyzed by trend analysis and bioinformatics analysis. Enzyme-linked immunosorbent assay were used to assess the inflammatory factor levels. Fluoro-Jade B histochemistry and TUNEL staining were used to detect neuronal apoptosis. Immunofluorescence staining and western blotting were used to detect the expression of NLRP3 inflammasomes. Results: Pretreatment with Feb reduced neuronal cell death and degeneration and alleviated neurobehavioral disorders in vivo. Feb was found to modulate inflammation-related pathways by trend analysis and bioinformatics analysis. In addition, Feb inhibited microglia activation and elevated cytokine levels after ICH. Furthermore, double immunofluorescence staining showed that co-localization of NLRP3 with Iba1 positive cells was reduced after treatment with Feb. Finally, we found that Feb inhibited the activation of the NLRP3/ASC/caspase-1 pathway after ICH. Conclusion: By inhibiting the NLRP3 inflammasome, preconditioning Feb attenuates inflammatory injury after ICH. Our findings may provide new insights into the role of Feb in neuroprotection.

Genipin ameliorates diabetic retinopathy via the HIF-1α and AGEs-RAGE pathways.

BACKGROUND: Traditional Chinese medicine (TCM) is useful in disease treatment and prevention. Genipin is an active TCM compound used to treat diabetic retinopathy (DR). In this study, a network pharmacology (NP)-based approach was employed to investigate the therapeutic mechanisms underlying genipin administration in DR. METHODS: The potential targets of DR were identified using the gene expression omnibus (GEO) database. TCM database screening and NP were used to predict the potential active targets and pathways of genipin in DR. Cell viability was tested in vitro to determine the effects of different doses of glucose and genipin on Human Retinal Microvascular Endothelial Cells (hRMECs). CCK-8, CCK-F, colony formation, CellTiter-Lum, Annexin V-FITC, wound healing, Transwell, tube-forming, reactive oxygen species (ROS), and other assay kits were used to detect the effects of genipin on hRMECs during high levels of glucose. In vivo, a streptozotocin (STZ)-mouse intraocular genipin injection (IOI.) model was used to explore the effects of genipin on diabetes-induced retinal dysfunction. Western blotting was performed to identify the cytokines involved in proliferation, apoptosis, angiogenesis, ROS, and inflammation. The protein expression of the AKT/ PI3K/ HIF-1α and AGEs/ RAGE pathways was also examined. RESULTS: Approximately 14 types of TCM, and nearly 300 active ingredients, including genipin, were identified. The NP approach successfully identified the HIF-1α and AGEs-RAGE pathways, with the EGR1 and UCP2 genes, as key targets of genipin in DR. In the in vitro and in vivo models, we discovered that high glucose increased cell proliferation, apoptosis, angiogenesis, ROS, and inflammation. However, genipin application regulated cell proliferation and apoptosis, inhibited angiogenesis, and reduced ROS and inflammation in the HRMECs exposed to high glucose. Furthermore, the retinal thickness in the genipin-treated group was lower than that in the untreated group. AKT/ PI3K/ HIF-1α and AGEs/ RAGE signaling was increased by high glucose levels; however, genipin treatment decreased AKT/ PI3K and AGEs/ RAGE pathway expressions. Genipin also increased HIF-1α phosphorylation, oxidative phosphorylation of ATP synthesis, lipid peroxidation, and the upregulation of oxidoreductase. Genipin was found to protect HG-induced hRMECs and the retina of STZ-mice, based on; 1 the inhibition of UCP2 and Glut1 decreased intracellular glucose, and glycosylation; 2 the increased presence of HIF-1α, which increased oxidative phosphorylation and decreased substrate phosphorylation; 3 the increase in oxidative phosphorylation from ATP synthesis increased lipid peroxidation and oxidoreductase activity, and; 4 the parallel effect of phosphorylation and glycosylation on vascular endothelial growth factor (VEGF), MMP9, and Scg3. CONCLUSION: Based on NP, we demonstrated the potential targets and pathways of genipin in the treatment of DR and confirmed its effective molecular mechanism in vitro and in vivo. Genipin protects cells and tissues from high glucose levels by regulating phosphorylation and glycosylation. The activation of the HIF-1α pathway can also be used to treat DR. Our study provides new insights into the key genes and pathways associated with the prognosis and pathogenesis of DR.

The Role of Immunocyte Infiltration Regulatory Network Based on hdWGCNA and Single-Cell Bioinformatics Analysis in Intervertebral Disc Degeneration.

Immune infiltration plays a crucial role in intervertebral disc degeneration (IDD). In this study, we explored the immune microenvironment of IDD through single-cell bioinformatics analysis. Three single-cell datasets were integrated into this study. Nucleus pulposus cells (NPCs) were divided into subgroups based on characteristic genes, and the role of each subgroup in the IDD process was analyzed through pseudo-time trajectory analysis. The hub genes were obtained using hdWGCNA, further identified by bulk datasets and pseudo-time sequence. The expression of the hub genes defined the NPCs related to immune infiltration, and the interaction between these NPCs and immunocytes was explored. The NPCs were divided into four subgroups: reserve NPCs, HCL-NPCs, response NPCs, and support NPCs, which, respectively, dominate the four processes of IDD: non, mild, moderate, and severe degeneration. SPP1 and ICAM1 were identified as the nucleus pulposus immune infiltration hub genes. Macrophages and myelocytes played pro-inflammatory roles in the SPP1-ICAM both-up NPC group through the SPP1-CD44 pathway and ICAM1-ITGB2 ligand-receptor pathway, respectively. At the same time, both-up NPCs sought self-help inflammation remission from neutrophils through the ANXA1-FPR1 pathway. The systematic analysis of the differentiation and immune infiltration landscapes helps to understand IDD's overall development process. Our data suggest that SPP1 and ICAM1 may be new targets for the treatment of inflammatory infiltration in IDD.

[Correlation study of NCF2 in chronic rhinosinusitis with nasal polyps].

Objective:After selecting NCF2 based on bioinformatics, clinical experiments were conducted to verify the expression of NCF2 in chronic rhinosinusitis with nasal polyps to study its correlation. Methods:The differentially expressed genes（DEGs） between CRSwNP and non-CRS patients were explored using the CRS-related dataset from the gene expression omnibus GEO database. The weighted gene co-expression network（WGCNA） was used for cluster analysis. The expression and cell distribution of NCF2 in the tissues were determined by single gene enrichment analysis（GSEA）, immune inflammatory infiltration analysis, and principal component（PCA） analysis. The expression degree of NCF2 in the tissues of the subjects was determined by immunohistochemistry, and the percentage of EOS in the peripheral blood of the subjects was detected and the correlation was analyzed. EOS in the tissues of the subjects were counted under a microscope and compared. Results:①The Venn diagram was obtained by crossing the module with the highest correlation between DEGs and WGCNA to determine the core gene NCF2. ②GSEA analysis showed that NCF2 was significantly related to the immunological processes such as allogeneic rejection and asthma. ③The area under the ROC curve was 1, indicating that NCF2 had diagnostic value for CRSwNP. ④NCF2 was highly expressed in nasal polyps, mainly distributed in monocytes and eosinophils. ⑤HE staining showed that the number of EOS in ECRSwNP tissues and the percentage of eosinophils in peripheral blood were higher than those in nonECRSwNP and control groups. ⑥The immunohistochemistry results showed that NCF2 was significantly expressed in the nasal polyps of ECRSwNP patients, which was higher than that in the nasal mucosa of nonECRSwNP group and control group. ⑦The expression of NCF2 in tissues was positively correlated with EOS count in ECRSwNP group and EOS expression in peripheral blood. Conclusion:The expression of NCF2 is increased in eosinophilic chronic rhinosinusitis with nasal polyps, and it is significantly correlated with the expression of eosinophils in peripheral blood and tissues, suggesting that NCF2 may be used as a basis for the intrinsic classification of ECRSwNP and a reference index for clinical diagnosis and treatment.

Xuefu Zhuyu decoction promotes synaptic plasticity by targeting miR-191a-5p/BDNF-TrkB axis in severe traumatic brain injury.

BACKGROUND: Xuefu Zhuyu decoction (XFZYD) is a traditional Chinese herbal formula known for its ability to eliminate blood stasis and improve blood circulation, providing neuroprotection against severe traumatic brain injury (sTBI). However, the underlying mechanism is still unclear. PURPOSE: We aim to investigate the neuroprotective effects of XFZYD in sTBI from a novel mechanistic perspective of miRNA-mRNA. Additionally, we sought to elucidate a potential specific mechanism by integrating transcriptomics, bioinformatics, and conducting both in vitro and in vivo experiments. METHODS: The sTBI rat model was established, and the rats were treated with XFZYD for 14 days. The neuroprotective effects of XFZYD were evaluated using a modified neurological severity score, hematoxylin and eosin staining, as well as Nissl staining. The anti-inflammatory effects of XFZYD were explored using quantitative real-time PCR (qRT-PCR), Western blot analysis, and immunofluorescence. Next, miRNA sequencing of the hippocampus was performed to determine which miRNAs were differentially expressed. Subsequently, qRT-PCR was used to validate the differentially expressed miRNAs. Target core mRNAs were determined using various methods, including miRNA prediction targets, mRNA sequencing, miRNA-mRNA network, and protein-protein interaction (PPI) analysis. The miRNA/mRNA regulatory axis were verified through qRT-PCR or Western blot analysis. Finally, morphological changes in the neural synapses were observed using transmission electron microscopy and immunofluorescence. RESULTS: XFZYD exhibited significant neuroprotective and anti-inflammatory effects on subacute sTBI rats' hippocampus. The analyses of miRNA/mRNA sequences combined with the PPI network revealed that the therapeutic effects of XFZYD on sTBI were associated with the regulation of the rno-miR-191a-5p/BDNF axis. Subsequently, qRT-PCR and Western blot analysis confirmed XFZYD reversed the decrease of BDNF and TrkB in the hippocampus caused by sTBI. Additionally, XFZYD treatment potentially increased the number of synaptic connections, and the expression of the synapse-related protein PSD95, axon-related protein GAP43 and neuron-specific protein TUBB3. CONCLUSIONS: XFZYD exerts neuroprotective effects by promoting hippocampal synaptic remodeling and improving cognition during the subacute phase of sTBI through downregulating of rno-miR-191a-5p/BDNF axis, further activating BDNF-TrkB signaling.

Analysis of m6A-regulated genes and subtype classification in lupus nephritis.

BACKGROUND: Lupus nephritis (LN) is the most common and severe clinical manifestation of systemic lupus erythematosus (SLE). N6-methyladenosine (m6A) is a reversible RNA modification and has been implicated in various biological processes. However, the roles of m6A regulators in LN are not fully demonstrated. METHODS: We downloaded the kidney tissue transcriptome dataset of LN patients and normal controls from the GEO database and extracted the expression levels of m6A regulators. We constructed and compared Random Forest (RF) and Support Vector Machine (SVM) models, and subsequently selected featured genes to develop nomogram models. The m6A subtypes were identified based on significantly differentially expressed m6A regulators, and the m6A gene subtypes were identified based on m6A-associated differential genes, and the two m6A modification patterns were comprehensively evaluated. RESULTS: We obtained the GSE32591 and GSE112943 datasets from the GEO database, including 78 LN samples and 36 normal control samples. We extracted the expression levels of 20 m6A regulators. By RF analysis we identified 7 characteristic m6A regulators and constructed nomogramh models with these 7 genes. We identified two m6A subtypes based on these seven important m6A regulators, and the immune cell infiltration levels of the two subtype clusters were significantly different. We identified two more m6A gene subtypes based on m6A-associated DEGs. We calculated the m6A scores using the principal component analysis (PCA) algorithm and found that the m6A scores of m6A cluster A and gene cluster A were lower than those of m6A cluster B and gene cluster B. In addition, we found that the levels of inflammatory factors were also significantly different between m6A clusters and gene clusters. CONCLUSION: This study confirms that m6A regulators are involved in the LN process through different modes of action and provide new diagnostic and therapeutic targets for LN.

Integrative analyses of whole-transcriptome sequencing reveals CeRNA regulatory network in pulmonary hypertension treated with FGF21.

Noncoding RNAs have been shown to play essential roles in hypoxic pulmonary hypertension (HPH). Our preliminary data showed that HPH is attenuated by fibroblast growth factor 21 (FGF21) administration. Therefore, we further investigated the whole transcriptome RNA expression patterns and interactions in a mice HPH model treated with FGF21. By whole-transcriptome sequencing, differentially expressed mRNAs, miRNAs, lncRNAs, and circRNAs were successfully identified in normoxia (Nx) vs. hypoxia (Hx) and Hx vs. hypoxia + FGF21 (Hx + F21). Differentially expressed mRNAs, miRNAs, lncRNAs, and circRNAs regulated by hypoxia and FGF21 were selected through intersection analysis. Based on prediction databases and sequencing data, differentially co-expressed mRNAs, miRNAs, lncRNAs, and circRNAs were further screened, followed by functional enrichment analysis. MAPK signaling pathway and epigenetic modification were enriched and may play fundamental roles in the therapeutic effects of FGF21. The ceRNA regulatory network of lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA was constructed with miR-7a-5p, miR-449c-5p, miR-676-3p and miR-674-3p as the core. In addition, quantitative real-time PCR experiments were employed to verify the whole-transcriptome sequencing data. The results of luciferase reporter assays highlighted the relationship between miR-449c-5p and XR_878320.1, miR-449c-5p and Stab2, miR-449c-5p and circ_mtcp1, which suggesting that miR-449c-5p may be a key regulator of FGF21 in the treatment of PH. Taken together, this study provides potential biomarkers, pathways, and ceRNA regulatory networks in HPH treated with FGF21 and will provide an experimental basis for the clinical application of FGF21 in PH.

Identification of HIST1H2BH as the hub gene associated with multiple myeloma using integrated bioinformatics analysis.

OBJECTIVES: Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy. METHODS: Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines. RESULTS: A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines. CONCLUSIONS: We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.

Bioinformatics and Functional Analysis of OsASMT1 Gene in Response to Abiotic Stress.

The study aimed to elucidate the functional characteristics of OsASMT1 gene under copper (Cu) or sodium chloride (NaCl) stress. Bioinformatics scrutiny unveiled that OsASMT1 is situated on chromosome 9. Its protein architecture, comprising dimerization and methyltransferase domains, showed significant similarities to OsASMT2 and OsASMT3. High expression in roots and panicles, along with abiotic stress putative cis-regulatory elements in the promoter, indicated potential stress responsiveness. Real-time quantitative PCR confirmed OsASMT1 induction under Cu and NaCl stress in rice. Surprisingly, yeast expressing OsASMT1 did not exhibit enhanced resistance to abiotic stresses. The results of subcellular localization analysis indicated that OsASMT1 plays a role in the cytoplasm. While OsASMT1 responded to Cu and NaCl stress in rice, its heterologous expression in yeast failed to confer abiotic stress resistance, highlighting the need for further investigation of its functional implications.