scholarly journals Using RNA-Seq to Explore the Hub Genes in the Trigeminal Root Entry Zone of Rats by Compression Injury

2021 ◽  
pp. E573-E581
Keyword(s):  
Animal Model ◽  
Male Rats ◽  
Receptor Interaction ◽  
Rna Seq ◽  
Compression Injury ◽  
Hub Genes ◽  
Entry Zone ◽  
Kegg Analysis ◽  
Root Entry Zone ◽  
Trigeminal Root

BACKGROUND: Mechanical compression on the trigeminal root entry zone (TREZ) by microvascular is the main etiology of primary trigeminal neuralgia (TN). OBJECTIVES: To study the pathogenesis of TN, hub genes screening in the TREZ of TN in an animal model was performed. STUDY DESIGN: A double blind, randomized study was designed in a controlled animal trial. SETTING: The research took place in the Laboratory of Clinical Applied Anatomy at the School of Basic Medical Science of Fujian Medical University. METHODS: Twelve male rats were randomly divided into a sham operation group and a TN animal model group. TN animal model was induced by chronic compression of trigeminal nerve root (CCT) operation. Gene expression in the TREZ were analyzed by RNA sequencing (RNA-Seq) technique. KEGG analysis, GO analysis, and PPI analysis were performed in the DEGs. Key signaling pathways analyzing by GSEA and the hub genes in the DEGs were also studied. Reverse transcription real-time polymerase chain reaction (RT-qPCR) was used to verify the RNA-Seq results. RESULTS: Transcriptome data showed that 352 genes up-regulated and 59 genes down-regulated in DEGs on post-operation day 21, after CCT operation in the TN group. KEGG analysis revealed that, “neuroactive ligand receptor interaction” and “cytokine cytokine receptor interaction” may be related to the pathogenesis of TN. GO analysis showed “regulation of signing receptor activity”, “chemokine activity”, and “carbohydrate binging” may be related to TN. The RT-qPCR results were consistent with the test results, indicating that the transcriptome sequencing results were reliable. LIMITATIONS: Although the incidence of TN in female rats was higher than in male rats, we only used male SD rats to establish the TN animal model, to avoid the effect of estrogen on experimental results. This study only presents some respects of RNA-Seq technique and, therefore, did not identify the DEGs at the protein level. The relationship between the DEGs at different levels shoud be done in the future. CONCLUSIONS: Based on the results of RNA-seq, this study discovered 6 hub genes in the TREZ that are closely related to the TN animal model, which provide a potential breakthrough point to explore the pathogenesis of TN. KEY WORDS: Animal model, compression injury, hub gene, rat, RNA-seq, transcriptome, trigeminal neuralgia, trigeminal root entry zone

Glial Plasticity in the Trigeminal Root Entry Zone of a Rat Trigeminal Neuralgia Animal Model

2019 ◽  
Vol 44 (8) ◽  
pp. 1893-1902 ◽  
Author(s):  
DaoShu Luo ◽  
Ren Lin ◽  
LiLi Luo ◽  
QiuHua Li ◽  
Ting Chen ◽  
...  
Keyword(s):  
Animal Model ◽  
Trigeminal Neuralgia ◽  
Entry Zone ◽  
Root Entry Zone ◽  
Trigeminal Root

scholarly journals Trigeminal Root Entry Zone Lesions in Non-multiple Sclerosis

2018 ◽  
Vol 57 (22) ◽  
pp. 3339-3340
Author(s):  
Arifumi Matsumoto ◽  
Kinya Hisanaga ◽  
Isao Nagano
Keyword(s):  
Multiple Sclerosis ◽  
Entry Zone ◽  
Root Entry Zone ◽  
Trigeminal Root

Diagnostic relevance of trigeminal evoked potentials following infraorbital nerve stimulation

1991 ◽  
Vol 75 (2) ◽  
pp. 244-250 ◽  
Author(s):  
Massimo Leandri ◽  
Emilio Favale
Keyword(s):  
Trigeminal Neuralgia ◽  
Infraorbital Nerve ◽  
Entry Zone ◽  
Content Type ◽  
Maxillary Nerve ◽  
Root Entry Zone ◽  
Idiopathic Trigeminal Neuralgia ◽  
Parasellar Region ◽  
Trigeminal Root ◽  
The Brain

✓ A new tool in neurophysiological exploration of the trigeminal nerve has recently been introduced. It has been demonstrated that stimulation of the infraorbital nerve trunk gives rise to very reliable scalp responses reflecting the activity of the afferent pathway between the maxillary nerve and the brain stem. The authors demonstrate that alterations of such trigeminal evoked responses fit with documented pathological processes at various locations along the trigeminal pathway (maxillary sinus, parasellar region, and within the brainstem parenchyma). They report the findings in 68 patients suffering from “idiopathic” trigeminal neuralgia. Alterations of the response were detected in 33 cases, suggesting that some damage of the nerve had taken place either at the root entry zone into the pons (23 cases) or slightly distal to it (10 cases). Such results support the hypothesis that trigeminal neuralgia may be due to a compression of the trigeminal root at the pons entry zone.

Cluster Headache-Like Pain in Multiple Sclerosis

Cephalalgia ◽  
1999 ◽  
Vol 19 (8) ◽  
pp. 732-734 ◽  
Author(s):  
M Leandri ◽  
G Craccu ◽  
A Gottlieb
Keyword(s):  
Multiple Sclerosis ◽  
Trigeminal Neuralgia ◽  
Cluster Headache ◽  
Evoked Potentials ◽  
Simultaneous Occurrence ◽  
Entry Zone ◽  
Root Entry Zone ◽  
Trigeminal Root

We describe a case with simultaneous occurrence of cluster headache-like pain and multiple sclerosis. Both neuroimaging and neurophysiology (trigeminal evoked potentials) revealed a demyelination plaque in the pons, at the trigeminal root entry zone, on the side of pain. Although that type of lesion is usually associated with trigeminal neuralgia pain, we hypothesize that in this case it may be linked with the concomitant cluster headache, possibly by activation of trigemino-vascular mechanisms.

scholarly journals Flow cytometry analysis of immune and glial cells in a trigeminal neuralgia rat model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Junjin Lin ◽  
Luxi Zhou ◽  
Zhaoke Luo ◽  
Madeha Ishag Adam ◽  
Li Zhao ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Trigeminal Neuralgia ◽  
Rat Model ◽  
Complement C3 ◽  
Compression Injury ◽  
Root Entry Zone ◽  
Significant Difference ◽  
Post Operation ◽  
Trigeminal Root ◽  
Infiltrating Lymphocytes

AbstractMicrovascular compression of the trigeminal root entry zone (TREZ) is the main cause of most primary trigeminal neuralgia (TN), change of glial plasticity was previously studied in the TREZ of TN rat model induced by chronic compression. To better understand the role of astrocytes and immune cells in the TREZ, different cell markers including glial fibrillary acidic protein (GFAP), complement C3, S100A10, CD45, CD11b, glutamate-aspartate transporter (GLAST), Iba-1 and TMEM119 were used in the TN rat model by immunohistochemistry and flow cytometry. On the post operation day 28, GFAP/C3-positive A1 astrocytes and GFAP/S100A10-positive A2 astrocytes were activated in the TREZ after compression injury, there were no statistical differences in the ratios of A1/A2 astrocytes between the sham and TN groups. There was no significant difference in Iba-1-positive cells between the two groups. The ratios of infiltrating lymphocytes (CD45+CD11b−) (p = 0.0075) and infiltrating macrophages (CD45highCD11b+) (p = 0.0388) were significantly higher than those of the sham group. In conclusion, different subtypes A1/A2 astrocytes in the TREZ were activated after compression injury, infiltrating macrophages and lymphocytes increased, these neuroimmune cells in the TREZ may participate in the pathogenesis of TN rat model.

scholarly journals Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

2021 ◽  
Author(s):  
Congcong Wang ◽  
Jianping Guo ◽  
Xiaoyang Zhao ◽  
Jia Jia ◽  
Wenting Xu ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Receptor Interaction ◽  
Analysis Tool ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Prognostic Assessment ◽  
Scheme Selection

Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by CytoHubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA. Results: Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1. Conclusion: we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.

scholarly journals Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Maryum Nisar ◽  
Rehan Zafar Paracha ◽  
Iqra Arshad ◽  
Sidra Adil ◽  
Sabaoon Zeb ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Early Stage ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Hub Genes

Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.

Sign in / Sign up

Export Citation Format

Share Document