aZGP1 ELISA kit
- Known as:
- aZGP1 Enzyme-linked immunosorbent assay test reagent
- Catalog number:
- DL-aZGP1-Mu
- Product Quantity:
- 96T
- Category:
- Elisa Kits
- Supplier:
- WDSTD
- Gene target:
- aZGP1 ELISA kit
Related genes to: aZGP1 ELISA kit
- Gene:
- AZGP1 NIH gene
- Name:
- alpha-2-glycoprotein 1, zinc-binding
- Previous symbol:
- -
- Synonyms:
- ZA2G, ZAG
- Chromosome:
- 7q22.1
- Locus Type:
- gene with protein product
- Date approved:
- 1991-09-12
- Date modifiied:
- 2014-11-19
Related products to: aZGP1 ELISA kit
Human ELC ELISA KIT 96 TEST
OxiSelect In Vitro ROS/RNS Assay Kit (Green Fluorescence), Trial Size
OxiSelect Methylglyoxal (MG) Competitive ELISA Kit
OxiSelect Methylglyoxal (MG) Competitive ELISA Kit
OxiSelect TBARS Assay Kit (MDA Quantitation), Trial Size
OxiSelect Total Antioxidant Capacity (TAC) Assay Kit, Trial Size
OxiSelect™ In Vitro ROS RNS Assay Kit (Green Fluorescence), Trial Size(1-3)-beta-D-glucan Sandwich ELISA, Double Antibody(1-Kit )11,12-EET DHET Immunoassay Kit(1-Kit )11,12-EET_DHET Immunoassay Kit(1-Kit) 11,12-DHET Immunoassay Kit(1-Kit) 14,15-DHET Human Urine ELISA Kit(1-Kit) 14,15-DHET Hypertension ELISA Kit(1-Kit) 14,15-DHET sEH activity ELISA Kit(1-Kit) 14,15-EET DHET Hypertension ELISA Kit Related articles to: aZGP1 ELISA kit
- Machine Learning approaches continue to be critical to the modelling of complex biological pathways, but many of the most-used models suffer from being uninterpretable, providing little insight into underlying mechanisms. Interpretable machine learning (IML) offers a pathway to bridge predictive modeling and biological understanding. - Source: PubMed
Publication date: 2026/06/12
Kargarfard NehlehDunne RobertLee CarolWilson LaurenceMcAuley Alexander J - Radon exposure is the second most important risk factor for lung cancer after tobacco smoking and represents a significant but often underestimated public health problem. Due to the absence of specific clinical manifestations at early stages, the identification of molecular biomarkers reflecting early radon-induced carcinogenic processes is of particular importance. The aim of this study was to identify protein biomarkers associated with radon exposure in lung cancer patients residing in settlements of the Akmola and North Kazakhstan regions of Kazakhstan. Indoor radon exposure was assessed using CR-39 detectors to measure radon concentrations in residential dwellings during summer and autumn periods. The study included 57 lung cancer patients and 73 control subjects residing in areas characterized by varying levels of radon exposure. Plasma samples were collected and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins associated with lung cancer and radon exposure. Statistical analyses were performed to evaluate differences between groups and associations between radon exposure and molecular biomarkers. Seasonal variability in indoor radon concentrations was observed, with several settlements demonstrating levels exceeding international reference values. Proteomic analysis identified multiple proteins differentially expressed between lung cancer patients and controls, as well as between radon-exposed and non-exposed lung cancer patients. Several proteins involved in inflammation, lipid metabolism, oxidative stress, and immune regulation pathways demonstrated significant differences in expression levels, suggesting potential associations with radon-induced carcinogenic mechanisms. LC-MS/MS proteomic profiling identified multiple differentially expressed proteins associated with lung cancer and radon exposure after false discovery rate correction. Proteins involved in inflammation, oxidative stress, immune regulation, and lipid metabolism, including ORM2, AZGP1, PRDX2, IRF7, and APOC3, demonstrated significant expression differences between radon-exposed and low-exposure groups. The identified protein biomarkers demonstrated significant associations with both radon exposure and lung cancer status, indicating their potential relevance for early detection and risk assessment of radon-induced lung cancer. The integration of environmental exposure assessment with proteomic profiling may provide new insights into the molecular mechanisms of radon-associated carcinogenesis and support the development of preventive strategies. - Source: PubMed
Publication date: 2026/05/27
Kazhiyakhmetova BaglanAltaeva NursuluBakhtin MeiratTarlykov PavelOmori YasutakaTokonami ShinjiKranrod ChutimaPradana RadhiaMusikawan SaowarakLesbek AnelIbrayeva DanaraSaifulina ElenaAuganova DanaAumalikova MoldirKairullova MadinaShokabayeva AigerimBizhanova DinaraKashkinbayev Yerlan - Electrochemical analysis provides key technical foundations for the advancement of detection technologies, offering advantages such as device miniaturization, rapid responsiveness, cost-effectiveness, and capacity for real-time monitoring. A major challenge currently under investigation is that the interfacial reactions between the electrode surface and analytes hinder the discrimination of specific and nonspecific molecules. This study aimed to introduce a novel molecular detection platform using targeted paired binding and electrochemical sensing for the precise detection of zinc-alpha-2-glycoprotein 1 (AZGP1) in clinical samples. We introduced a biorecognition molecule (BRM) targeting AZGP1 to confer selectivity. An AZGP1-specific aptamer was isolated using the systematic evolution of ligands by the exponential enrichment technique. As a novel BRM, this aptamer demonstrated high sensitivity and specificity toward AZGP1, while also allowing facile chemical synthesis and low-cost modification. Nevertheless, when used for evaluating complex clinical samples, single-material BRMs often show limitations in anti-interference capacity and stability. Although developing antibodies requires immunization of animals and incurs higher storage and transportation costs, these antibodies remain the gold standard for biomolecular recognition in clinical testing applications. We further used a sandwich assay based on biolayer interferometry technology to identify monoclonal antibodies that paired with the aptamer for cooperative AZGP1 binding. This paired biorecognition molecular layer integrated the complementary strengths of antibodies and aptamers, including high sensitivity, programmable modifiability, molecular dynamics selectivity upon target interaction, and stable interfacial sensing signals in electrochemical analysis. - Source: PubMed
Publication date: 2026/06/18
Gao YantingLi XueqinQian HusunYu ZiqiangGao FengjuanHu HonggangLiu Siyao - Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy, with frequent seizures often leading to cognitive, emotional, and psychiatric issues. A prominent pathological change associated with TLE is hippocampal sclerosis (HS), characterized by neuronal loss, gliosis, and increased neuron fibre density. However, the pathogenesis of Temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) remains unclear. This study aimed to investigate the abnormal expression and regulatory mechanism of hub genes in TLE-HS. The source data were obtained from the epilepsy dataset (GSE256068) of the Gene Expression Omnibus GEO database. Then, differential expression gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) were employed to screen for module-related DEGs in TLE-HS, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subsequently, these intersected targets were subjected to cross-validation using three machine learning algorithms- LASSO regression, SVM-RFE, and RF, ultimately identifying three hub genes. Finally, CIBERSORT and ssGSEA algorithms were used to analyze the infiltration status of different immune cell populations in TLE-HS patients, followed by assessing the association between hub genes and immune cell populations. The expression of hub genes was determined using RT-qPCR and western blot. Functional experiments were performed using CCK-8, flow cytometry, and special kits. Results indicated that three hub genes, NADH dehydrogenase (ubiquinone) 1 alpha subcomplex subunit 4-like 2 (NDUFA4L2), Protein-tyrosine Phosphatase 4A3 (PTP4A3), and Zinc-alpha-2-glycoprotein (AZGP1), were identified in TLE-HS, which are associated with the infiltration of specific immune cells. Besides, NDUFA4L2 expression was reduced in kainic acid (KA)-induced HT22 cells compared to the other two hub genes. Thus, NDUFA4L2 was selected for this research. Moreover, NDUFA4L2 overexpression alleviated KA‑induced HT22 cell neurotoxicity, apoptosis, oxidative stress, and mitochondrial dysfunction. In conclusion, NDUFA4L2 upregulation could alleviate KA-induced neurotoxicity oxidative stress, which provided a theoretical foundation and a potential therapeutic target for epilepsy. - Source: PubMed
Publication date: 2026/06/08
Yuan HuimianHe WenlongDu BaoshunLi Jianshe - Type 2 diabetes (T2D) often develops insidiously, and many individuals with prediabetes (preDM) remain undiagnosed. While current diagnostic methods rely on blood sampling, urine-based proteomic biomarkers offer a promising noninvasive alternative for early risk stratification. Here, we applied label-free nanoLC-MS/MS-based proteomics to identify urinary protein biomarkers associated with prediabetes and to evaluate their potential in predicting progression to T2D. The discovery phase included urine samples from 43 control and 58 preDM participants, with protein quantification performed using two independent software platforms to ensure analytical robustness. Candidate proteins showing consistent differential expression were further validated by enzyme-linked immunosorbent assay (ELISA) in an expanded sample set comprising 91 control and 68 preDM subjects. Two proteins─alpha-1-acid glycoprotein 1 (AGP1) and zinc-α2-glycoprotein (ZAG)─were identified as candidate biomarkers. When combined with age and sex, AGP1 and ZAG showed good discriminative performance (AUCs of 0.936 and 0.926, respectively), comparable to fasting blood glucose (AUC = 0.944). Overall, these findings suggest that AGP1 and ZAG may serve as potential urinary biomarkers reflecting early metabolic alterations associated with prediabetes and progression to T2D, although further validation in independent cohorts is warranted. - Source: PubMed
Publication date: 2026/05/05
Liao Wen-LingLiao Hsin-YiChang Chiz-TzungChang Ya-WenChen Chao-JungTsai Fuu-Jen