Guinea pig CD97 ELISA kit
- Known as:
- Guinea pig CD97 Enzyme-linked immunosorbent assay test reagent
- Catalog number:
- e05c0579
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Blue gene shanghai
- Gene target:
- Guinea pig CD97 ELISA kit
Related genes to: Guinea pig CD97 ELISA kit
- Gene:
- ADGRE5 NIH gene
- Name:
- adhesion G protein-coupled receptor E5
- Previous symbol:
- CD97
- Synonyms:
- TM7LN1
- Chromosome:
- 19p13.12
- Locus Type:
- gene with protein product
- Date approved:
- 1995-11-29
- Date modifiied:
- 2015-03-03
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- Diagnosis of seronegative rheumatoid arthritis (SNRA) is difficult due to the lack of diagnostic markers. The study aims to construct a novel diagnostic model based on long noncoding RNAs (lncRNAs) expression and laboratory indicators to provide a new idea for diagnostic methods of SNRA. Differentially expressed lncRNAs in peripheral blood cells of RA patients were screened through eukaryotic long noncoding RNA sequencing and validated by quantitative real-time PCR. Meanwhile, the correlation between lncRNAs expression and laboratory indicators was analyzed. The diagnostic value was evaluated by receiver operating characteristic curve analysis. Finally, combined with laboratory indicators, a diagnostic model for SNRA was constructed based on logistic regression and visualized by nomogram. Expression of ADGRE5, FAM157A, PTPN6 and PTPRE in peripheral blood was significantly increased in RA than healthy donors. Meanwhile, we analyzed the relationship between lncRNAs and erythrocyte sedimentation rate, C-reactive protein and CD4 + T cell-related cytokines and transcription factors. Results showed that FAM157A and PTPN6 were positively related to RORγt, and negatively related to GATA3. Moreover, PTPRE has potential discrimination ability between SNRA and healthy donor (AUC = 0.6709). Finally, we constructed a diagnostic model based on PTPRE, neutrophil count and red blood cell distribution width (RDW). The AUC of the model was 0.939 and well-fitted calibration curves. Decision curve analysis indicated the model had better predict performance in SNRA diagnosis. Our study constructed a novel diagnostic model based on PTPRE, neutrophil count and RDW which may serve as a potential tool for the diagnosis of SNRA. - Source: PubMed
Publication date: 2024/04/25
Xia JinfangGao HualiTang JifengJiang RenquanXiao LianboSheng HuimingLin Jinpiao - Liver metastasis (LM) is an important factor leading to colorectal cancer (CRC) mortality. However, the effect of T-cell exhaustion on LM in CRC is unclear. Single-cell sequencing data derived from the Gene Expression Omnibus database. Data were normalized using the Seurat package and subsequently clustered and annotated into different cell clusters. The differentiation trajectories of epithelial cells and T cells were characterized based on pseudo-time analysis. Single-sample gene set enrichment analysis (ssGSEA) was used to calculate enrichment scores for different cell clusters and to identify enriched biological pathways. Finally, cell communication analysis was performed. Nine cell subpopulations were identified from CRC samples with LM. The proportion of T cells increased in LM. T cells can be subdivided into NK/T cells, regulatory T cells (Treg) and exhausted T cells (Tex). In LM, cell adhesion and proliferation activity of Tex were promoted. Epithelial cells can be categorized into six subpopulations. The transformation of primary CRC into LM involved two evolutionary branches of Tex cells. Epithelial cells two were at the beginning of the trajectory in CRC but at the end of the trajectory in CRC with LM. The receptor ligands CEACAM5 and ADGRE5-CD55 played critical roles in the interactions between Tex and Treg cell-epithelial cell, which may promote the epithelial-mesenchymal transition process in CRC. Tex cells are able to promote the process of LM in CRC, which in turn promotes tumour development. This provides a new perspective on the treatment and diagnosis of CRC. - Source: PubMed
Ling TianlongZhang ChengLiu YeJiang ChunhuiGu Lei - The Adhesion G protein receptor E5 (ADGRE5) gene is involved in a wide range of biological functions in human tumors; however, its specific molecular mechanism and significance in the analysis of human tumors have not yet been determined. Here, we provide a comprehensive genomic architecture of ADGRE5 in the tumor immune microenvironment and its clinical relevance across a broad range of solid tumors. - Source: PubMed
Publication date: 2024/03/07
Zhang XiangjianZhang XinxinYang QiuhuiHan RuokuoFadhul WalaaSachdeva AlishaZhang Xianbo - Neoadjuvant immunotherapy with anti-programmed death-1 (neo-antiPD1) has revolutionized perioperative methods for improvement of overall survival (OS), while approaches for major pathologic response patients' (MPR) recognition along with methods for overcoming non-MPR resistance are still in urgent need. - Source: PubMed
Publication date: 2024/01/26
Li JianMeng ZhouwenliCao ZhengqiLu WenqingYang YiLi ZimingLu Shun - Adhesion G protein-coupled receptors (aGPCRs) are evolutionarily ancient receptors involved in a variety of physiological and pathophysiological processes. Modulators of aGPCR, particularly antagonists, hold therapeutic promise for diseases like cancer and immune and neurological disorders. Hindered by the inactive state structural information, our understanding of antagonist development and aGPCR activation faces challenges. Here, we report the cryo-electron microscopy structures of human CD97, a prototypical aGPCR that plays crucial roles in immune system, in its inactive apo and G13-bound fully active states. Compared with other family GPCRs, CD97 adopts a compact inactive conformation with a constrained ligand pocket. Activation induces significant conformational changes for both extracellular and intracellular sides, creating larger cavities for Stachel sequence binding and G13 engagement. Integrated with functional and metadynamics analyses, our study provides significant mechanistic insights into the activation and signaling of aGPCRs, paving the way for future drug discovery efforts. - Source: PubMed
Publication date: 2024/01/11
Mao ChunyouZhao Ru-JiaDong Ying-JunGao MingxinChen Li-NanZhang ChaoXiao PengGuo JiaQin JiaoShen Dan-DanJi Su-YuZang Shao-KunZhang HuibingWang Wei-WeiShen QingyaSun Jin-PengZhang Yan