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ACS Applied Materials & Interfaces · 2025 · IF 8.2

Visual Detection Strategy Based on Size-Gradient Coffee Rings on a Superslippery Platform

Yuyan Li,Kunming Xing,Yumin Liu,Kexin Liu,Guangyao Tan,Yingnan Sun,Shusheng Zhang

Superwetting surfaces have attracted considerable attention in analytical fields due to their unique ability to concentrate target analytes within evaporating droplets, characterized by a constant contact angle and a centripetal mobile contact line. While previous studies have underscored the resistance of superslippery surfaces to the coffee-ring effect, our research presents a novel strategy that dynamically introduces the coffee-ring effect on such surfaces for visual detection. By harnessing the synergistic interaction between the coffee-ring effect and the mobile contact line properties of the superslippery surface, our work leverages affinity recognition between the functionalized surface and the target analyte within the droplet to dynamically create defects for contact line pinning, thereby generating coffee rings on the superslippery surface and enabling qualitative visual detection based on their distinct patterns. Moreover, we establish a linear relationship where the coffee-ring’s diameter decreased with increasing initial target concentration, facilitating quantitative detection. As a proof of concept, we demonstrate the naked-eye detection capability of our strategy using streptavidin dilutions ranging from 10–7 to 10–11 M and Escherichia coli concentrations from 108 to 104 CFU/mL, visualized with suspended micro-/nanoparticles. To the best of our knowledge, it is the first time that a superslippery surface is utilized to dynamically create pinning defects for coffee ring formation, enabling both qualitative and quantitative detection. This strategy offers a user-friendly and easily interpretable method, making it particularly advantageous for point-of-care testing.

CAS / MDL: 7220-79-3 61-73-4
研究领域: 分析化学 · 生物医学工程 · 材料科学
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MICROCHEMICAL JOURNAL · 2025 · IF 5.1

tFNA-aptasensor integrating DNA-framework confined affinity recognition and HCR amplification towards accurate profiling of microRNA for COPD analysis

Guobin Huang,Weiting Xu,Jinxin Chi,Chenchen Lin,Jiabin Wang,Xucong Lin

Environmental smog pollution induces chronic obstructive pulmonary disease (COPD), and causes the urgent need of timely, safe and quantitative testing for risk assessment. The miRNA-based bioanalysis offers a non-invasive access to rapid COPD screening, while challenges remain in accurately identifying miRNAs from complex matrices. Herein, a novel bionic aptasensor has been pioneered for meeting the specific and sensitive detection of the miR-155 in serum for COPD diagnosis, integrating tetrahedral framework nucleic acid (tFNA) confined affinity recognition and enzyme-free hybridization chain reaction (HCR) amplification strategy. Precision-designed tFNAs were fabricated and hybridized with FAM-labeled cDNAs, enabling dual-mode recognition mechanism including spatially confined aptamer recognition and bionic molecular sieve size-selective action. Proteins and pre-miRNAs were excluded, and the target microRNA-155 was specifically captured. This triggered a structural switch of tFNAs and activated cDNA-mediated HCR, assembling double-stranded DNA and achieving exponential fluorescence enhancement synergistically produced by SYBR Green I (SGI) and FAM. The optimal limit of detection as 53 fM for miRNA-155 was achieved with laser-induced fluorescence (LIF). Applied to COPD diagnosis, the detections of trace miRNA-155 were satisfactory and the recovery yields were ranged in 96.4 ± 5.2 % ∼106.2 ± 2.1 % ( n  = 3) in the serum of COPD patients. Smoke-exposed model rats were also analyzed, and the miRNA-155 was achieved with a significant concentration up-regulation to light the COPD. It offers a high-performance protocol for meeting the non-invasive rapid screening of COPD, further providing promising technologies for evaluating safety issues of environmentally induced diseases.

研究领域: 生物传感器 · 分子诊断学 · 环境健康 · RNA生物学 · 肺部疾病研究
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