106
J. Eur. Opt. Society-Rapid Publ. 22, 10( 2026)
of Cy5-cDNA upon Ara h1 binding induces a change in FRET signal for quantitative detection. The recoveries of the actual sample assay reached 95.7-106.3 %, providing a new strategy for allergen analysis in complex matrices.
FRET technology has become an important tool for studying molecular interactions due to its nanoscale distance sensitivity and efficient energy transfer characteristics. From in vivo tumor metabolism monitoring, food safety detection, and allergen analysis, FRET technology continues to expand its application boundaries through innovative donor receptor design and multidisciplinary integration. In recent years, with the development of new fluorescent materials( such as AIE polymer microspheres) and nanosensors, the detection sensitivity, anti-interference ability and dynamic monitoring performance of FRET have been significantly improved. In the future, further optimizing the specificity and stability of FRET probe and deepening its application in multimodal imaging and clinical diagnosis will open up broader prospects for life science and medical research.
3 Conclusions and outlook
Although the above technologies have made significant progress, it is often difficult for a single technology to meet the demand for high-throughput and high-precision detection of complex samples. The future development of optical detection technology will show a trend of multidimensional innovation, mainly in the following aspects: first, in terms of detection sensitivity, the application of new nanomaterials( such as two-dimensional materials, metal-organic frameworks) and quantum dots will break through the existing detection limits. Secondly, the synergistic integration of microfluidic chip and optical detection will significantly enhance the system response speed and achieve dynamic monitoring with millisecond time resolution. In terms of specificity enhancement, intelligent analysis strategies based on machine learning algorithms, such as deep neural network-assisted Raman spectral resolution, will dramatically improve the recognition accuracy of complex samples. In the future, cross technology integration will become the key direction to improve the detection performance. Fluorescence plasmon combination, such as metal enhanced fluorescence technology, can significantly improve the fluorescence signal intensity and stability by combining the field enhancement effect of LSPR; Chemiluminescence – nanomaterial synergy and nanoenzyme catalyzed chemiluminescence reaction can further reduce the detection limit and expand the ability of multiple detection; AI assisted analysis and machine learning algorithm can be used for rapid analysis of multimodal data and improve the identification accuracy of complex samples. With the cross innovation of technology, the development of detection technology in the future will tend to be“ highly sensitive, multimodal, intelligent and portable”. Through multi technology collaboration and engineering design, the existing bottlenecks will be gradually solved, providing stronger tools for life science, clinical diagnosis, public safety and other fields.
Acknowledgments
Fuqiang Ma was supported by Shandong Provincial Laboratory Project [ SYS202209 ].
Funding
This work was supported by Shandong Provincial Laboratory Project [ SYS202209 ].
Conflicts of interest The authors have nothing to disclose.
Data availability statement This article did not generate any new datasets.
Author contribution statement
Conceptualization, Maojie Jiang and Fuqiang Ma; Data curation, Yanna Lin, Peng Yin, Xiangyu Jiang; Formal analysis, Mengjie Huang and Baihui Zhang; Investigation, Maojie Jiang, Yanna Lin and Xuan Fang; Writing – Original Draft Preparatio, Maojie Jiang; Writing – Review and Editing, Maojie Jiang and Fuqiang Ma; Visualization, MaojieJiangandPengYin; Fundingacquisition, Fuqiang Ma. All authors have read and agreed to the published version of the manuscript.
References
1 Chiu ML, Lawi W, Snyder ST, Wong PK, Liao JC, Gau V, Matrix effects – a challenge toward automation of molecular analysis, JALA-J. Lab Autom. 15( 3), 233 – 242( 2010). https:// doi. org / 10.1016 / j. jala. 2010.02.001.
2 Sapsford KE, Bradburne C, Delehanty JB, Medintz IL, Sensors for detecting biological agents, Mater. Today 11( 3), 38 – 49( 2008). https:// doi. org / 10.1016 / S1369 – 7021( 08) 70018-X.
3 Papakostas GI, Shelton RC, Kinrys G, Henry ME, Bakow BR, Lipkin SH, et al., Assessment of a multi-assay, serumbased biological diagnostic test for major depressive disorder: A pilot and replication study, Mol. Psychiatr. 18( 3), 332 – 339( 2013). https:// doi. org / 10.1038 / mp. 2011.166.
4 Yang SM, Lv S, Zhang W, Cui Y, Microfluidic point-of-care( POC) devices in early diagnosis: A review of opportunities and challenges, Sensors 22( 4), 1620( 2022). https:// doi. org / 10.3390 / s22041620.
5 Noor ASM, Talah A, Rosli MAA, Thirunavakkarasu P, Tamchek N, Increased sensitivity of Au-Pd nanolayer on tapered optical fiber sensor for detecting aqueous ethanol, J. Eur. Opt. Soc.-Rapid Publ. 13( 1), 28( 2017). https:// doi. org / 10.1186 / s41476 – 017-0056 – 6.
6 Minkovich VP, Sotsky AB, Tapered photonic crystal fibers coated with ultra-thin films for highly sensitive bio-chemical sensing, J. Eur. Opt. Soc.-Rapid Publ. 15, 7( 2019). https:// doi. org / 10.1186 / s41476-019-0103-6.
7 Fischer F, Frenner K, Granai M, Fend F, Herkommer A, Data-driven development of sparse multi-spectral sensors for urological tissue differentiation, J. Eur. Opt. Soc. 19( 1), 8( 2023). https:// doi. org / 10.1051 / jeos / 2023030. 8 Bouquet G, Kaspersen K, Haugholt KH. Optical measurement instrument for detection of powdery mildew and grey mould in protected crops, J. Eur. Opt. Soc. 20, 1( 2024). https:// doi. org / 10.1051 / jeos / 2024024.