Anti-Human CD8a PE 100 tests
- Known as:
- Antibody toHuman CD8a PE 100 tests
- Catalog number:
- 12-0087-42
- Category:
- -
- Supplier:
- eBioscience
- Gene target:
- Anti-Human CD8a 100 tests
Related genes to: Anti-Human CD8a PE 100 tests
- Gene:
- CD8A NIH gene
- Name:
- CD8a molecule
- Previous symbol:
- CD8
- Synonyms:
- -
- Chromosome:
- 2p11.2
- Locus Type:
- gene with protein product
- Date approved:
- 1986-01-01
- Date modifiied:
- 2019-04-23
Related products to: Anti-Human CD8a PE 100 tests
Related articles to: Anti-Human CD8a PE 100 tests
- Heat stroke is the most severe heat-related illness, characterized by an inflammatory response, oxidative stress, ferroptosis, and immune dysfunction. However, the broader role of ferroptosis in the pathophysiological processes of heat stroke remains unclear, and its potential connection with immune regulation has not yet been fully elucidated. This study uses bioinformatics analysis of heat stress datasets and molecular validation in patient samples to investigate key signaling pathways altered in heat stress (GSE90763) and validate their associations in heat stroke patients, aiming to clarify their connections with ferroptosis and immune regulation. - Source: PubMed
Publication date: 2026/07/17
Cui QiXu ZhongyanLei DaxinYu ChaoLuo YulingZheng JieWang Fukun - This study aims to explore the potential mechanisms contributing to recurrent pregnancy loss (RPL) and identify potential biomarkers. We analyzed endometrial samples from 39 RPL and 22 healthy controls using proteomics, identifying differentially expressed proteins (DEPs) with DEqMS and quantifying immune cell infiltration with CIBERSORT. We also examined a decidual scRNA-seq dataset (CRA002181) to identify macrophage marker genes, performed WGCNA to correlate macrophage infiltration with protein expression, and conducted functional enrichment analysis. Immunofluorescence staining was conducted to quantify the proportions of CD3+, CD8a+, CD68+, and CD206+ cells, and Western blot analysis was performed to determine MMP9 expression in endometrial tissues from RPL and controls. M2 macrophages and CD8+ T cells were enriched in the endometrium of RPL. Proteomic analysis of endometrial tissues from RPL identified 310 DEPs associated with immune response, cell adhesion, and secretory granule processes. From the scRNA-seq dataset, 295 macrophage marker genes were identified. WGCNA revealed that the brown module exhibited the highest correlation with macrophage infiltration. MMP9 emerged as the sole intersecting candidate, showing marked downregulation in RPL. Mendelian randomization analysis showed that genetically predicted higher circulating MMP9 levels decrease RPL risk (OR 0.75, 95% CI 0.57-0.98; p=0.036). Additionally, RPL patients showed significantly higher proportions of CD3+CD8a+ cells (p<0.05) and CD68+CD206+ cells (p=0.265), and decreased MMP9 protein expression (p<0.05), compared with controls. In conclusion, this study indicates that an imbalance in endometrial M2 macrophage and CD8+ T cell immune infiltration is associated with RPL. MMP9 may represent a potential predictive biomarker for RPL. - Source: PubMed
Publication date: 2026/07/14
Wang RuifangDing NanMu FangxiangZhang WeiWang Fang - Liver metastases from breast cancer (BCLM) are associated with aggressive disease and poor survival outcomes. Liver-directed locoregional therapies (LRT) based on radiation are limited by resistance and relapse. While liquid biopsy enables systemic monitoring, it provides limited insight into the tumor microenvironment and mechanisms of resistance. In this hypothesis-generating study, high-throughput plasma proteomics alongside digital spatial profiling of matched tumor tissues was employed to link systemic signals with local tumor biology, aiming to elucidate mechanisms underlying therapy response. - Source: PubMed
Publication date: 2026/07/13
Öcal ElifRiese JanikSchneider UrsulaKühnel Mark PJonigk DannyHirner-Eppeneder HeidrunCorradini StefanieÖcal OsmanGoldberg S NahumSeidensticker MaxRicke JensWildgruber MoritzAlunni-Fabbroni Marianna - Prognostic assessment of tumor patients in the surgical intensive care unit (SICU) remains challenging due to the complex interplay between systemic inflammation and immune dysfunction. In this study, we performed integrative transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) from 112 SICU patients with solid tumors, aiming to identify immune-related signatures predictive of 30-day survival. High-throughput RNA sequencing quantified 19,832 expressed genes, while computational immune deconvolution using CIBERSORTx estimated relative fractions of 22 immune cell types. Differential expression analysis revealed 432 upregulated and 287 downregulated genes in non-survivors, with notable elevation of CXCL10 (27.5 ± 4.6 TPM vs. 12.3 ± 3.1 TPM in survivors, p = 0.002) and IL6 (19.4 ± 3.9 vs. 9.1 ± 2.7 TPM, p = 0.004), accompanied by reduced CD8A (12.3 ± 3.6 vs. 28.1 ± 4.2 TPM, p = 0.006) and GZMB (7.2 ± 1.9 vs. 15.4 ± 3.0 TPM, p = 0.008). Correspondingly, high-risk patients demonstrated decreased cytotoxic T lymphocyte fractions (12.3% ± 3.6% vs. 27.8% ± 4.2%, p = 2.6 × 10) and NK cells (5.2% ± 1.3% vs. 11.1% ± 2.1%, p = 1.9 × 10) with increased neutrophils (45.2% ± 5.1% vs. 31.7% ± 4.8%, p = 3.2 × 10). A Prognostic Immune Score (PIS), constructed based on 12 key immune-related genes, achieved a concordance index of 0.81, effectively stratifying patients into high- and low-risk groups with 30-day survival rates of 42.5% and 86.1%, respectively (log-rank p < 0.001). Subgroup analyses confirmed that the PIS retained predictive accuracy across tumor types and APACHE II strata, underscoring its robustness. These findings demonstrate that integrative transcriptomic and immune profiling provides a quantitative framework for early risk stratification in SICU tumor patients and identifies actionable biomarkers for potential immunomodulatory interventions. - Source: PubMed
Publication date: 2026/06/23
Chen ChangjinZhong HengquanOuyang SongmaoLai JiyingWu Chaoyu - The risk profile of valvular heart disease (VHD) and its underlying mechanisms remain poorly understood. This study aimed to develop and validate a multi-omics-based risk prediction model, and to elucidate potential biological mechanisms. Using data from the UK Biobank, Cox proportional hazards and machine learning models (XGBoost and LightGBM) were evaluated for predicting VHD and its subtypes (aortic valve stenosis, AVS; aortic valve regurgitation, AVR; mitral valve regurgitation, MVR). Cox models based on key clinical factors showed the best predictive performance (C-index of 0.75-0.81), which was further enhanced by incorporating proteomic data (all C-index > 0.81) but not by genomic or metabolomic data. Notably, a simplified 10-year model comprising only four top proteins maintained favorable performance (C-index of 0.75-0.82). Cluster analysis identified blood pressure and lipid levels as leading modifiable risk factors for VHD onset. Functional enrichment analysis revealed that VHD is primarily associated with protease inhibition, AVS with fibrotic and matrix metabolic pathways, and MVR with immune-inflammatory activation. Mendelian randomization and Bayesian colocalization analyses suggested causal associations between CNTN5 and CD8A with risks of AVS and MVR, whilst IGFBP7 showed a reverse-direction association with AVS. These findings highlight promising avenues for early diagnostic biomarkers and potential precision-targeted therapies. - Source: PubMed
Publication date: 2026/07/06
Jiang ZhihaoLiu YangSong MingyuChen NingYu CanqingLv JunWan Eric Yuk FaiQi LuLi LimingSun DianjianyiZheng Bang