Contrastive uncertainty based biomarkers detection in retinal optical coherence tomography images.

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.

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

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.