Superwettable interface towards biodetection in confined space

The detection of biomarkers with both high sensitivity and specificity is crucial for the diagnosis and treatment of related diseases. However, many current detections employ ex-situ detection method and non-confined condition, thus have many problems, which may eventually lead to inaccurate detection results. Compared to detection in non-confined space, detection in confined space can better reflect the real in-vivo situation. Therefore, the construction of detection for target molecules in confined space has great significance for both theoretical research and practical application. To realize the detection of target molecules in confined space, the probes should accurately enter the confined space where the target molecules reside and interact with the interface. Thus, how to explore and utilize the properties of the interface (for example, bioinspired superwettability) has always been a hot and difficult topic in this field. Herein, the recent advances and our efforts in recent 10 years on detection of bio-target molecules in confined space with superwettable interface have been introduced from the perspective of the detection methods. The suitable and most widely employed detection methods for target molecules in confined spaces are introduced firstly. Then, recent progresses for related detections based on visual, optical, and electrochemical detection methods are presented successively. Finally, the perspective for detection in confined space is discussed for the future development of biochemical detection.

Automated summary

Accurate detection of biomarkers with high sensitivity and specificity is crucial for the diagnosis and treatment of related diseases. However, many current detection methods have limitations and may result in inaccurate results. Compared to non-confined detection, confined space detection provides a more realistic representation of in-vivo conditions. Therefore, developing detection methods for target molecules in confined spaces is of great significance for both theoretical research and practical applications.