CD50
- Known as:
- CD50
- Catalog number:
- 10-452-C100
- Product Quantity:
- 0.1 mg
- Category:
- -
- Supplier:
- Exbio
- Gene target:
- CD50
Related genes to: CD50
- Gene:
- ICAM3 NIH gene
- Name:
- intercellular adhesion molecule 3
- Previous symbol:
- -
- Synonyms:
- CDW50, ICAM-R, CD50
- Chromosome:
- 19p13.2
- Locus Type:
- gene with protein product
- Date approved:
- 1994-05-19
- Date modifiied:
- 2016-01-15
Related products to: CD50
Anti-CD50 (azide-free) AntibodyAnti-CD50 azide-free antibodyAntibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-04, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-04, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Antibodies: Mouse Monoclonal to CD50 _ ICAM-3, Species Reactivity: Human, Clone: MEM-171, Isotype: IgG1Anti_Human, mab CD50 Source Mouseanti_ICAM_3, Leukocytes Recognition human CD50 antigen Clone ICO_60anti_ICAM_3, Leukocytes Recognition human CD50 antigen Clone ICO_60 Related articles to: CD50
- Severe fever with thrombocytopenia syndrome virus (SFTSV), also known as Dabie bandavirus, is the pathogen causing severe fever with thrombocytopenia syndrome (SFTS). Human cell receptors are the first barriers to viral entry, proliferation, and host immune response. This study explored the association between single nucleotide polymorphisms (SNPs) in genes encoding receptors or related molecules that mediate SFTSV cell entry, such as dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN), DC-SIGN-related protein (DC-SIGNR), and non-muscle myosin heavy chain IIA (NMMHC-IIA), and SFTSV infection susceptibility in the Chinese Han population, as well as the underlying potential biological mechanisms. From September 2020 to December 2022, 454 subjects from the First Affiliated Hospital with Nanjing Medical University were enrolled and divided into SFTSV-infected and uninfected groups based on SFTSV RNA and antibody test results. TaqMan SNP genotyping was performed on (rs7248637, rs4804800, and rs11465421), (rs2277998), and (rs2269529 and rs2269530). Logistic regression was used to assess the association between the candidate SNPs and SFTSV infection susceptibility, and the online bioinformatics tools were employed to explore potential biological functions of positive SNPs. Logistic regression analysis showed that individuals carrying the rs2277998 AA genotype were more susceptible to SFTSV infection, and bioinformatics analysis generated the hypothesis that this locus might be involved in influencing gene transcription and expression, which warrants further functional validation. rs2277998 is significantly associated with SFTSV infection susceptibility in the Chinese Han population. The exact regulatory mechanisms require further experimental validation.IMPORTANCESevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by severe fever with thrombocytopenia syndrome virus (SFTSV). Host genetic variation may modulate both disease susceptibility and severity by altering key functional proteins. Our study was the first to explore the association between single nucleotide polymorphisms (SNPs) in host genes encoding receptors or related molecules that mediate SFTSV cell entry, such as dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN), DC-SIGN-related protein (DC-SIGNR), and non-muscle myosin heavy chain IIA (NMMHC-IIA), and SFTSV infection susceptibility in the Chinese Han population. The results showed that the homozygous mutation of rs2277998 AA genotype was associated with a significantly higher risk of SFTSV infection in the Chinese Han population, with predictions pointing to a potential, yet unverified, role in regulating the gene transcription and expression, which may provide a new scientific basis for SFTSV prevention and treatment. - Source: PubMed
Publication date: 2026/07/15
Wang MinRen ChengruiDeng GuoqiangShen YanCheng PengQian LiqinQi YongTan WeilongChai YinchuChen YutingZeng TianYin WenZhu ChuanlongYue Ming - While antitumor immunity in lung cancer is typically evaluated within the tumor microenvironment and regional lymphoid organs, immune features in non-tumorous lung tissue-particularly at sites distant from the primary tumor-may also reflect host-related pulmonary immune characteristics. However, the clinical relevance of immune cell abundance in such tumor-distant lung parenchyma remains unclear. Therefore, this study aimed to investigate whether immune cell abundance in tumor-distant non-tumorous lung tissue is associated with clinicopathological features and postoperative outcomes in patients with non-small cell lung cancer (NSCLC). - Source: PubMed
Publication date: 2026/06/23
Aoki MasayaKamimura GoMorizono ShoichiroNonaka YutoTokunaga TakuyaHarada-Takeda AyaMaeda KokiNagata ToshiyukiIshihara YukaMurakami GenUeda Kazuhiro - C-type lectin receptors (CLRs) are one of the major classes of pattern recognition receptors. They mediate numerous biological events, including cell adhesion, pathogen recognition, and innate immune responses. Initial recognition of a pathogen by specific CLRs shapes the inflammatory landscape of the host, and the resulting immune response can be protective but can also contribute to immune-mediated pathology. Understanding the binding of CLRs to their ligands has gained increasing attention and triggered research in the fields of structural biology, pathogen recognition, and immune signaling. Of critical importance for understanding the factors that affect binding and, therefore, being able to therapeutically exploit CLRs as druggable targets, is the identification of binding epitopes and drug-like analogs. Hence, informed tailoring of candidate molecules can enhance affinities, exploit avidity, and enable the design of novel ligands. This review surveys the extensive diversity that has been generated in the area of synthetic myeloid CLR ligands, focusing on the dendritic cell-specific ICAM3-grabbing non-integrin receptor (DC-SIGN), macrophage-inducible C-type lectin (Mincle), dendritic cell-associated C-type lectin-1 (Dectin-1), and langerin. Context is rendered via the description of binding modes, signaling pathways, and therapeutic opportunities, which facilitates the identification of current limitations and potential future directions of the field. - Source: PubMed
Suri JamesLepenies Bernd - : Brain metastasis is associated with poor prognosis in lung adenocarcinoma (LUAD). Anoikis resistance may contribute to tumor cell survival during metastatic dissemination and brain colonization; however, robust biomarkers for prognostic stratification and brain metastasis-associated classification remain limited. This study aimed to investigate anoikis-related molecular features in LUAD brain metastasis and develop a machine learning-based signature for prognostic assessment and exploratory classification of primary and brain-metastatic LUAD samples. : We integrated single-cell and multi-cohort bulk transcriptomic data. Single-cell analysis was performed to characterize anoikis-related cellular states and intercellular communication in primary and brain-metastatic LUAD samples. In the bulk transcriptomic analysis, TCGA-LUAD was used for prognostic feature selection and risk-model construction, and GSE26939 was used for external prognostic validation. The classification performance of the fixed signature for distinguishing primary LUAD from brain-metastatic LUAD samples was further evaluated in GSE161116 and GSE271259. Immune microenvironment features were assessed, and an LLM-assisted exploratory drug-screening strategy combined with molecular docking was used to prioritize candidate compounds. : Single-cell analysis suggested that metastatic epithelial cells exhibited enhanced anoikis-related activity, accompanied by macrophage-associated SPP1-CD44 and MIF-(CD74+CXCR4) communication patterns. Machine learning-based feature selection identified an eight-gene signature consisting of , , , , , , , and . The signature showed prognostic value in TCGA-LUAD and GSE26939 and demonstrated exploratory classification performance in distinguishing primary LUAD from brain-metastatic LUAD samples. High-risk patients exhibited immune microenvironment alterations and enrichment of tumor progression-related pathways. LLM-assisted compound prioritization and molecular docking highlighted resveratrol and SB431542 as hypothesis-generating candidates with predicted interactions with core targets. : This study identified an anoikis-related eight-gene signature for LUAD prognostic stratification and exploratory brain metastasis-associated classification. The findings suggest the potential involvement of anoikis-related tumor-microenvironment interactions in LUAD brain metastasis and provide candidate genes and compounds for further experimental validation. - Source: PubMed
Publication date: 2026/06/17
Wu JunhongZhang BaijunLiu Hengrui - Carotid plaque is an early manifestation of atherosclerosis and is closely associated with the risk of myocardial ischaemia, ischaemic stroke and other atherosclerotic cardiovascular diseases (ASCVDs). To identify new protein biomarkers associated with carotid plaque, which will enhance early warning of ASCVDs DESIGN: Nested case-control study within a prospective cohort, with external assessment of transportability in an independent population-based cohort. - Source: PubMed
Publication date: 2026/06/25
Jin BolinLin ChunyingWu ChaoqunChen BowangHan YiZhang XiaoyanBai XuekeYang YangCui JianlanXu WeiSong LijuanYang HaoHe WenyanZhang YanGao YanLi Xi