Advanced Materials · 2023 · 31 citations · 40 references
EngineeringBioengineeringBiomedical EngineeringBiosensorsMolecular DiagnosticsNanobiotechnologyBiological SensorsBiosensor DesignClinical BiosensingMolecular BiomarkersNanomaterial-based BiosensorsPoint-of-care BiosensingBiosensing PlatformsCancer Biomarker DetectionCarbon Nanotube BiosensorsCarbon Nanotube SensorsCirculating Tumor Dna TestingClinical Diagnostics BiosensorsNucleic Acid Biomarker DetectionUltrasensitive Detection
Ultrasensitive identification of biomarkers in biofluids is essential for the precise diagnosis of diseases. For the gold standard approaches, polymerase chain reaction and enzyme-linked immunosorbent assay, cumbersome operational steps hinder their point-of-care applications. Here, a bionic biomarker entrapment system (BioES) is implemented, which employs a multi-body Y-shaped tetrahedral DNA probe immobilized on carbon nanotube transistors. Clinical identification of endometriosis is successfully realized by detecting an estrogen receptor, ERβ, from the lesion tissue of endometriosis patients and establishing a standard diagnosis procedure. The multi-body Y-shaped BioES achieves a theoretical limit of detection (LoD) of 6.74 aM and a limit of quantification of 141 aM in a complex protein milieu. Furthermore, the BioES is optimized into a multi-site recognition module for enhanced binding efficiency, realizing the first identification of monkeypox virus antigen A35R and unamplified detection of circulating tumor DNA of breast cancer in serum. The rigid and compact probe framework with synergy effect enables the BioES to target A35R and DNA with a LoD down to 991 and 0.21 aM, respectively. Owing to its versatility for proteins and nucleic acids as well as ease of manipulation and ultra-sensitivity, the BioES can be leveraged as an all-encompassing tool for population-wide screening of epidemics and clinical disease diagnosis.
40
MoS<sub>2</sub> Field-Effect Transistor for Next-Generation Label-Free Biosensors
Deblina Sarkar, Wei Liu, Xuejun Xie et al. · ACS Nano · 2014 · 1K citations
Nam Joong Jeon, Jaemin Lee, Jun Hong Noh et al. · Journal of the American Chemical Society · 2013 · 546 citations · Full text
Natural Sciences, Materials Engineering, Materials Science +17