scholarly journals A dual-quenched ECL immunosensor for ultrasensitive detection of retinol binding protein 4 based on luminol@AuPt/ZIF-67 and MnO2@CNTs

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wei Gong ◽  
Suqing Yang ◽  
Fen Zhang ◽  
Fengshun Tian ◽  
Junman Chen ◽  
...  

Abstract Background Retinol binding protein 4 (RBP4) has been regarded as an important serological biomarker for type 2 diabetes mellitus (T2DM). Hence, the construction of a highly sensitive detection method for RBP4 is the key to early prevention and multidisciplinary intervention of T2DM. In this work, a dual-quenched electrochemiluminescence (ECL) immunosensor has been fabricated for ultrasensitive detection of RBP4 by combining zeolitic imidazolate framework-67/AuPt-supported luminol (luminol@AuPt/ZIF-67) with MnO2 nanosheets-grown on carbon nanotubes (MnO2@CNTs). Results AuPt/ZIF-67 hybrids with high-efficiency peroxidase-like activity could provide multipoint binding sites for luminol and antibodies and significantly boost the amplified initial signal of the ECL immunosensor. Upon glutathione/H2O2 coreactants system, MnO2@CNTs composites could quench the initial signal by inhibiting mimic peroxidase activity of luminol@AuPt/ZIF-67. Moreover, the absorption spectrum of the MnO2@CNTs composites completely overlaps with the emission spectrum of luminol, which can further reduce initial signal by ECL resonance energy transfer (ECL-RET). Conclusions Benefiting from the above-mentioned properties, the designed immunoassay sensitivity exhibited excellent sensitivity and relative stability for RBP4 detection range from 0.0001 to 100 ng mL−1 with a low detection limit of 43 fg mL−1. Therefore, our ECL immunosensor provides an alternative assaying strategy for early diagnosis of T2DM. Graphic abstract

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Chuyao Jin ◽  
Lizi Lin ◽  
Na Han ◽  
Zhiling Zhao ◽  
Zheng Liu ◽  
...  

Abstract Background To assess the association between plasma retinol-binding protein 4 (RBP4) levels both in the first trimester and second trimester and risk of gestational diabetes mellitus (GDM). Methods Plasma RBP4 levels and insulin were measured among 135 GDM cases and 135 controls nested within the Peking University Birth Cohort in Tongzhou. Multivariable linear regression analysis was conducted to assess the influence of RBP4 levels on insulin resistance. Conditional logistic regression models were used to compute the odds ratio (OR) and 95% confidence interval (CI) between RBP4 levels and risk of GDM. Results The GDM cases had significantly higher levels of RBP4 in the first trimester than controls (medians: 18.0 μg/L vs 14.4 μg/L; P < 0.05). Plasma RBP4 concentrations in the first and second trimester were associated with fasting insulin, homeostasis model assessment for insulin resistance (HOMA-IR), and the quantitative insulin sensitivity check index (QUICKI) in the second trimester (all P < 0.001). With adjustment for diet, physical activity, and other risk factors for GDM, the risk of GDM increased with every 1-log μg/L increment of RBP4 levels, and the OR (95% CI) was 3.12 (1.08–9.04) for RBP4 in the first trimester and 3.38 (1.03–11.08) for RBP4 in the second trimester. Conclusions Plasma RBP4 levels both in the first trimester and second trimester were dose-dependently associated with increased risk of GDM.


2021 ◽  
pp. 1-8
Author(s):  
Yuanhao Wu ◽  
Fan Wang ◽  
Tingting Wang ◽  
Yin Zheng ◽  
Li You ◽  
...  

<b><i>Background:</i></b> Arteriovenous fistula (AVF) is the most common vascular access for patients undergoing hemodialysis (HD). Neointimal hyperplasia (NIH) might be a potential mechanism of AVF dysfunction. Retinol-binding protein 4 (RBP4) may play an important role in the pathogenesis of NIH. The aim of this study was to investigate whether AVF dysfunction is associated with serum concentrations of RBP4 in HD subjects. <b><i>Methods:</i></b> A cohort of 65 Chinese patients undergoing maintenance HD was recruited between November 2017 and June 2019. The serum concentrations of RBP4 of each patient were measured with the ELISA method. Multivariate logistic regression was used to analyze data on demographics, biochemical parameters, and serum RBP4 level to predict AVF dysfunction events. The cutoff for serum RBP4 level was derived from the highest score obtained on the Youden index. Survival data were analyzed with the Cox proportional hazards regression analysis and Kaplan-Meier method. <b><i>Results:</i></b> Higher serum RBP4 level was observed in patients with AVF dysfunction compared to those without AVF dysfunction events (174.3 vs. 168.4 mg/L, <i>p</i> = 0.001). The prevalence of AVF dysfunction events was greatly higher among the high RBP4 group (37.5 vs. 4.88%, <i>p</i> = 0.001). In univariate analysis, serum RBP4 level was statistically significantly associated with the risk of AVF dysfunction (OR = 1.015, 95% CI 1.002–1.030, <i>p</i> = 0.030). In multivariate analysis, each 1.0 mg/L increase in RBP4 level was associated with a 1.023-fold-increased risk of AVF dysfunction (95% CI for OR: 1.002–1.045; <i>p</i> = 0.032). The Kaplan-Meier survival analysis indicated that the incidence of AVF dysfunction events in the high RBP4 group was significantly higher than that in the low-RBP4 group (<i>p</i> = 0.0007). Multivariate Cox regressions demonstrated that RBP4 was an independent risk factor for AVF dysfunction events in HD patients (HR = 1.015, 95% CI 1.001–1.028, <i>p</i> = 0.033). <b><i>Conclusions:</i></b> HD patients with higher serum RBP4 concentrations had a relevant higher incidence of arteriovenous dysfunction events. Serum RBP4 level was an independent risk factor for AVF dysfunction events in HD patients.


Amyloid ◽  
2017 ◽  
Vol 24 (sup1) ◽  
pp. 120-121 ◽  
Author(s):  
Marios Arvanitis ◽  
Steven Simon ◽  
Gloria Chan ◽  
Denise Fine ◽  
Paula Beardsley ◽  
...  

Gene ◽  
2013 ◽  
Vol 526 (2) ◽  
pp. 170-175 ◽  
Author(s):  
Hua-Dong Yin ◽  
Elizabeth R. Gilbert ◽  
Shi-Yi Chen ◽  
Di-Yan Li ◽  
Zhi-Chao Zhang ◽  
...  

2010 ◽  
Vol 43 (3) ◽  
pp. 320-323 ◽  
Author(s):  
Beverly J. Tepper ◽  
Youn-Kyung Kim ◽  
Varsha Shete ◽  
Elena Shabrova ◽  
Loredana Quadro

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