Kejie Zhou

Bio: Kejie Zhou is an academic researcher from Nanjing Normal University. The author has contributed to research in topics: Computer science & Physics. The author has co-authored 2 publications.

Fabrication of bifunctional G-quadruplex-hemin DNAzymes for colorimetric detection of apurinic/apyrimidinic endonuclease 1 and microRNA-21.

Abstract: G-quadruplex-based complexes have been widely used in various analytical methods due to their outstanding capabilities of generating colorimetric, fluorescent or electrochemical signals. However, since loop sequences in traditional G-quadruplex structures are quite short, it is difficult to establish biosensors solely using G-quadruplex-based complexes. Herein, we attempted to lengthen the loop sequences of G-quadruplex structures and found that G-quadruplex-hemin DNAzymes (G-DNAzymes) with long loops (even 30 nucleotides) maintain high peroxidase activity. In addition, the peroxidase activity is not affected by the hybridization of the long loop with its complementary counterpart. Consequently, G-DNAzyme can be endowed with an additional function by taking the long loop as a recognition element, which may facilitate the construction of diverse colorimetric biosensors. Furthermore, by designing an apurinic/apyrimidinic site or a complementary sequence of microRNA-21 (miRNA-21) in long loops, bifunctional G-DNAzymes can be split in the presence of apurinic/apyrimidinic endonuclease 1 (APE1) or miRNA-21, decreasing their peroxidase activities. Accordingly, APE1 and miRNA-21 are quantified using 3,3',5,5'-tetramethylbenzidine as a chromophore. Using the G-DNAzyme, APE1 can be detected in a linear range from 2.5 to 22.5 U mL-1 with a LOD of 1.8 U mL-1. It is to be noted that benefitting from duplex-specific nuclease-induced signal amplification, the linear range of the miRNA-21 biosensor is broadened to 5 orders of magnitude, while the limit of detection is as low as 73 fM. This work demonstrates that G-DNAzymes with long loops can both generate signals and recognize targets, providing an alternative strategy to design G-quadruplex-based analytical methods.

Improved Faster-RCNN Based Biomarkers Detection in Retinal Optical Coherence Tomography Images

Abstract: Optical coherence tomography (OCT) is an important ophthalmic imaging technique, which can generate high-resolution anatomical images and plays an important role in the detection of retinal biomarkers. However, the appearance of retinal biomarkers is complex, and some of these biomarkers differ greatly among different categories, while many features are similar. In addition, the boundaries of retinal biomarkers are often indistinguishable from the background. In this study, we propose a self-supervised contrastive boundary consistency network (SCB-Net) to detect retinal biomarkers in OCT images. A self-supervised contrastive classification module is proposed to improve the classification ability of the network between different categories of retinal biomarkers. Furthermore, in order to make the boundary of the retinal biomarkers located by the network closer to the ground truth, the boundary consistency is added on the basis of the original regressor to jointly constrain the boundary localization. The experimental results on a local dataset show that our proposed SCB-Net method achieves good detection performance compared with other detection methods.

Contrastive uncertainty based biomarkers detection in retinal optical coherence tomography images

Abstract: Objective. Retinal biomarker in optical coherence tomography (OCT) images plays a key guiding role in the follow-up diagnosis and clinical treatment of eye diseases. Although there have been many deep learning methods to automatically process retinal biomarker, the detection of retinal biomarkers is still a great challenge due to the similar characteristics to normal tissue, large changes in size and shape and fuzzy boundary of different types of biomarkers. To overcome these challenges, a novel contrastive uncertainty network (CUNet) is proposed for retinal biomarkers detection in OCT images. Approach. In CUNet, proposal contrastive learning is designed to enhance the feature representation of retinal biomarkers, aiming at boosting the discrimination ability of network between different types of retinal biomarkers. Furthermore, we proposed bounding box uncertainty and combined it with the traditional bounding box regression, thereby improving the sensitivity of the network to the fuzzy boundaries of retinal biomarkers, and to obtain a better localization result. Main results. Comprehensive experiments are conducted to evaluate the performance of the proposed CUNet. The experimental results on two datasets show that our proposed method achieves good detection performance compared with other detection methods. Significance. We propose a method for retinal biomarker detection trained by bounding box labels. The proposal contrastive learning and bounding box uncertainty are used to improve the detection of retinal biomarkers. The method is designed to help reduce the amount of work doctors have to do to detect retinal diseases.

Smart Programmable Scalable Dual-Mode Diagnostic Logic Nanoflare Strategy for Dual-Tumor Marker Detection.

Abstract: Compared with the single-marker detection scheme, the detection of multiple targets in the complex cell and biological environment can obtain more reliable detection results. Herein, we detected miRNA-21 and APE1 in two modes, AND and OR, respectively, based on gold nanoflares and simple logic components. In both modes, DNAzyme and APE1 can get rich fluorescence recovery results by breaking the DNA strands from the gold nanorods (AuNRs) and unquenching under different conditions. In vivo and in vitro experiments suggest that both nanoflares exhibit excellent biocompatibility and make efficient and sensitive judgments on the two targets. This strategy emphasizes the reuse nature of enzymes, and a small amount of target can generate a large amount of fluorescent signal in the logic device, which greatly reduces the detection limit when monitoring low-abundance targets. Since the short-stranded DNA component of the detection device is simple in composition and easy to program its probe sequence, it can be expanded into a detection system for the detection of other sets of related markers, which increases its potential for clinical application.

A Washing-Free and Easy-to-Operate Fluorescent Biosensor for Highly Efficient Detection of Breast Cancer-Derived Exosomes

Abstract: Traditional detection methods for protein tumor markers in the early screening of breast cancer are restricted by complicated operation procedures and unstable reproducibility. As one of alternative emerging tumor markers, exosomes play an important role in diagnosing and treating cancers at the early stage due to traceability of their origins and great involvement in occurrence and development of cancers. Herein, a washing-free and efficient fluorescent biosensor has been proposed to realize simple and straightforward analysis of breast cancer cell-derived exosomes based on high affinity aptamers and G quadruplex-hemin (G4-hemin). The whole reaction process can be completed by several simple steps, which realizes washing-free and labor-saving. With simplified operation procedures and high repeatability, the linear detection range for this developed fluorescent biosensing strategy to breast cancer cell-derived exosomes is from 2.5 × 105 to 1.00 × 107 particles/ml, and the limit of detection is down to 0.54 × 105 particles/ml.

Label- and enzyme-free plasmon-enhanced single molecule fluorescence detection of HIV DNA fragments based on a catalytic hairpin assembly.

Abstract: We developed a label- and enzyme-free single molecule fluorescence counting strategy for HIV DNA fragments detection. The nucleic acid biosensor consists of a 5' terminal connected with a triangular gold nanoplate, 3' terminal rich in guanine hairpin probe (HP1) and a hairpin probe HP2 complementary to the partial sequence of HP1. Without the existence of the target DNA, the DNA fragment rich in the guanine region is locked in a hairpin structure and cannot form a G-quadruplex, hence NMM exhibits a low fluorescence signal. When the target DNA exists, the hairpin assembly will trigger a strand displacement amplification reaction that produces a great number of G-quadruplexes, and the fluorescence brightness of NMM will be enhanced. The plasmon resonance effect of the triangular gold nanoplates will further amplify the fluorescence signal. This method can analyze the target DNA with high sensitivity and selectivity, and the detection limit is 0.83 fM. The analysis of the HIV DNA fragments in diluted human serum samples was successfully achieved, and the recovery rate was 92%-104%. Because of its easy operation and low cost, it has broad development potential in biochemical analysis and clinical applications.