IL-8 ELISA
- Known as:
- Interleukin-8 Enzyme-linked immunosorbent assay test
- Catalog number:
- kap1301
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Diasource
- Gene target:
- IL-8 ELISA
Related genes to: IL-8 ELISA
- Gene:
- CXCL8 NIH gene
- Name:
- C-X-C motif chemokine ligand 8
- Previous symbol:
- IL8
- Synonyms:
- SCYB8, LUCT, LECT, MDNCF, TSG-1, IL-8, NAP-1, 3-10C, MONAP, AMCF-I, LYNAP, NAF, b-ENAP, GCP-1, K60, GCP1, NAP1
- Chromosome:
- 4q13.3
- Locus Type:
- gene with protein product
- Date approved:
- 1989-06-30
- Date modifiied:
- 2016-10-05
- Gene:
- CXCR1 NIH gene
- Name:
- C-X-C motif chemokine receptor 1
- Previous symbol:
- CMKAR1, IL8RA
- Synonyms:
- CKR-1, CDw128a, CD181
- Chromosome:
- 2q35
- Locus Type:
- gene with protein product
- Date approved:
- 1992-11-09
- Date modifiied:
- 2016-03-14
- Gene:
- CXCR2 NIH gene
- Name:
- C-X-C motif chemokine receptor 2
- Previous symbol:
- IL8RB
- Synonyms:
- CMKAR2, CD182
- Chromosome:
- 2q35
- Locus Type:
- gene with protein product
- Date approved:
- 1991-08-19
- Date modifiied:
- 2016-03-14
- Gene:
- CXCR2P1 NIH gene
- Name:
- C-X-C motif chemokine receptor 2 pseudogene 1
- Previous symbol:
- IL8RBP, CXCR2P
- Synonyms:
- -
- Chromosome:
- 2q35
- Locus Type:
- pseudogene
- Date approved:
- 1992-11-27
- Date modifiied:
- 2016-03-14
Related products to: IL-8 ELISA
Related articles to: IL-8 ELISA
- Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a heterogeneous condition with limited ideal therapeutic options. Acupuncture has shown clinical benefits for CP/CPPS, yet its molecular basis remains insufficiently characterized. - Source: PubMed
Publication date: 2026/04/17
Liang ChengWang HaoChang HongyuanLiu MingWang Fu - - Source: PubMed
Publication date: 2026/04/22
Zhang ChengZhao ZhipengShi Dan - Developing reliable biomarkers capable of differentiating Parkinson's disease from other neurological conditions is crucial for both patient care and research. In this study, we leveraged recent advances in high-throughput proteomic technology and machine learning to develop candidate biomarkers for Parkinson's disease. Using the Olink Explore 3072 assay, we obtained plasma proteomic profiles from 698 study participants, comprising Parkinson's disease cases (n = 149), neurologically healthy controls (n = 230), and participants with other neurological conditions (n = 319). The study cohort was split into Training Set (n = 560) and Test Set (n = 138). We conducted differential protein abundance analysis and pathway enrichment analysis, and subsequently applied the Boruta algorithm to identify differentially abundant proteins that are predictive of Parkinson's disease. To create a diagnostic biomarker panel, we trained a stacking ensemble machine learning (ML) model on the Training Set (n = 118 Parkinson's patients, n = 184 healthy controls, and n = 258 individuals with other neurological disorders) using eleven proteins (APOH, ARG1, CCN1, CXCL1, CXCL8, DDC, GRAP2, IL1RAP, OSM, PRL, and SPRY2) as model features. We used the Shapley Additive Explanations (SHAP) framework and network analysis to evaluate predictive importance and biological relevance of each protein in the ML model. The model demonstrated high accuracy in the held-out Test Set (n = 138) and three external cohorts-the UK Biobank (n = 43,969), the Parkinson's Disease Biomarkers Program (n = 138), and the Parkinson's Progression Markers Initiative (n = 385), with areas under the receiver operating characteristic curve of 0.939, 0.789, 0.909, 0.816, respectively. Additionally, network and pathway analyses helped interpret the model, revealing activity related to inflammatory mediators, ErbB signaling, T-cell receptor signaling, and lipid metabolism. Our findings highlight the potential of plasma protein biomarkers to improve Parkinson's disease diagnosis and deepen biological understanding of this complex neurological disorder. Our model demonstrates high specificity and reliability across multiple independent cohorts, indicating the significant potential of proteomics-based biomarkers and the clinical utility of ML-supported diagnosis in Parkinson's disease care. The model also helps to elucidate potential novel risk factors and pathways associated with Parkinson's disease. - Source: PubMed
Publication date: 2026/04/22
Adewale BoluwatifeChia RuthMoaddel RuinLandeck NatalieRasheed MemoonaAlba CamilleReho PaoloVasta RosarioCalvo AndreaMoglia CristinaCanosa AntonioManera UmbertoSnyder AllisonLee Yi-JungGrassano MaurizioGao ChristineZhu MinBrunetti MauraCasale FedericoArvind Kumar Dawson Ted MRosenthal Liana SHall Anna JPantelyat Alexander YDing JinhuiGibbs J RaphaelEgan Josephine MCandia JuliánTanaka ToshikoFerrucci LuigiChiò AdrianoNarendra Derek PKwan Justin YEhrlich Debra JDalgard Clifton LTraynor Bryan JScholz Sonja W - To investigate the molecular mechanisms of Jianpi Yanggan Pill (JPYGP) in treating Diarrhea-predominant irritable bowel syndrome (IBS-D) using an integrated network pharmacology approach combined with experimental validation. - Source: PubMed
Publication date: 2026/03/15
Ma KeHua XiaokunLi ZhipengZhang ShenghuaZhu TingJin LinxiLi WeipingShao JingranLi XiangWen WeiboLuan Yunpeng - Shiga toxin-producing () is a leading foodborne pathogen responsible for hemolytic uremic syndrome (HUS). This pathogen poses a severe threat to global public health. MicroRNAs (miRNAs) are increasingly recognized as essential post-transcriptional regulators and therapeutic targets. Despite this, their exact regulatory networks and roles in STEC pathogenesis remain largely unknown. - Source: PubMed
Publication date: 2026/04/02
Zheng BailiSu XiaoyueLi YongchaoFu QiangMa XuelianZhou BaoPeng BingChen RulongLiu Yingyu