Rational Design of Dendritic Mesoporous Silica Nanoparticles’ Surface Chemistry for Quantum Dot Enrichment and an Ultrasensitive Lateral Flow Immunoassay
Source abstract
Abstract
Lateral flow immunoassays (LFIAs) have drawn much attention in point-of-care diagnostic applications, and the development of high-performance label materials is the key. In this study, the impact of the surface chemistry of dendritic mesoporous silica nanoparticles (DMSNs) on their enrichment performance toward quantum dots (QDs) and signal amplification of the resultant DMSNs-QDs as label materials have been investigated. A series of DMSNs with controllable amino/thiol group densities have been synthesized. It is demonstrated that the amino groups are beneficial for QD fluorescence preservation, owing to the amino-based surface passivation, while the thiol groups are responsible for increasing the loading capacity of QDs due to the thiol–metal coordination. The optimized DMSNs-QDs labels with an amino density of 153 μmol g–1 and a thiol density of 218 μmol g–1 displayed sufficient QD fluorescence preservation (89.4%) and high QD loading capacity (1.55 g g–1). Ultrasensitive detection of serum amyloid A (SAA) with a detection limit of 10 pg mL–1 with the naked eye was achieved, which is 1 order of magnitude higher than that reported in the literature. This study provides insights into the development of advanced label materials and an ultrasensitive LFIA for future bioassay applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Biosensors and Analytical Detection · Advanced biosensing and bioanalysis techniques · Advanced Biosensing Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland 4072, Australia
School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241, P. R. China
Funding
Advance Queensland · Australian Research Council
References (62)
Show source-provided references
1. 10.1080/0197152800805577710.1080/01971528008055777 ↗
2. 10.1007/s00216-008-2287-210.1007/s00216-008-2287-2 ↗
3. 10.1039/C8AN00307F10.1039/C8AN00307F ↗
4. 10.1021/acssensors.0c0115310.1021/acssensors.0c01153 ↗
5. 10.1038/nature0860510.1038/nature08605 ↗
6. 10.1016/j.bios.2018.01.03710.1016/j.bios.2018.01.037 ↗
7. 10.1016/S1470-2045(01)00560-510.1016/S1470-2045(01)00560-5 ↗
8. 10.1016/j.tibtech.2015.03.00210.1016/j.tibtech.2015.03.002 ↗
9. 10.1039/C7TB01049D10.1039/C7TB01049D ↗
10. 10.1021/ac201331r10.1021/ac201331r ↗
11. 10.1021/acs.analchem.0c0348410.1021/acs.analchem.0c03484 ↗
12. 10.1007/s11671-010-9578-110.1007/s11671-010-9578-1 ↗
13. 10.1016/j.bios.2016.09.04310.1016/j.bios.2016.09.043 ↗
14. 10.1021/acs.analchem.6b0142710.1021/acs.analchem.6b01427 ↗
15. 10.1039/c1jm10090d10.1039/c1jm10090d ↗
16. 10.1021/am501278210.1021/am5012782 ↗
17. 10.1021/am503517s10.1021/am503517s ↗
18. 10.1002/adfm.20170538010.1002/adfm.201705380 ↗
19. 10.1021/acs.analchem.7b0086910.1021/acs.analchem.7b00869 ↗
20. 10.1039/D0AN00035C10.1039/D0AN00035C ↗
21. 10.1021/acs.analchem.9b0022310.1021/acs.analchem.9b00223 ↗
22. 10.1021/la051973l10.1021/la051973l ↗
23. 10.1021/la052197k10.1021/la052197k ↗
24. 10.1021/acs.analchem.8b0515410.1021/acs.analchem.8b05154 ↗
25. 10.1002/adfm.20110293010.1002/adfm.201102930 ↗
26. 10.1016/j.bios.2019.11171910.1016/j.bios.2019.111719 ↗
27. 10.1016/j.bios.2016.12.03610.1016/j.bios.2016.12.036 ↗
28. 10.1021/acsami.8b1455410.1021/acsami.8b14554 ↗
29. 10.1039/c2jm00080f10.1039/c2jm00080f ↗
30. 10.1021/jp030811010.1021/jp0308110 ↗
31. 10.1002/ppsc.20150025410.1002/ppsc.201500254 ↗
32. 10.1021/acs.chemmater.9b0002810.1021/acs.chemmater.9b00028 ↗
33. Gao X. · 2005 · 6110.1385/1-59259-901-X:061 ↗
34. 10.1039/b915139g10.1039/b915139g ↗
35. 10.1021/la900614e10.1021/la900614e ↗
36. 10.1146/annurev-physchem-040513-10364910.1146/annurev-physchem-040513-103649 ↗
37. 10.1016/j.talanta.2011.06.02110.1016/j.talanta.2011.06.021 ↗
38. Yao Q. X. · 2012 · 586
39. 10.1007/s11095-012-0766-910.1007/s11095-012-0766-9 ↗
40. 10.1021/la501571u10.1021/la501571u ↗
41. 10.1016/j.jcis.2019.12.10410.1016/j.jcis.2019.12.104 ↗
42. 10.1016/j.snb.2020.12835010.1016/j.snb.2020.128350 ↗
43. 10.1002/anie.20200686110.1002/anie.202006861 ↗
44. 10.1016/0927-7757(95)03119-X10.1016/0927-7757(95)03119-X ↗
45. 10.1021/jp100442v10.1021/jp100442v ↗
46. 10.1021/ja804306c10.1021/ja804306c ↗
47. 10.1021/acsami.9b0152710.1021/acsami.9b01527 ↗
48. 10.1016/0021-9797(88)90137-310.1016/0021-9797(88)90137-3 ↗
49. 10.1006/jcis.1994.132910.1006/jcis.1994.1329 ↗
50. 10.1021/ja00257a03910.1021/ja00257a039 ↗
51. 10.1126/science.248.4957.84010.1126/science.248.4957.840 ↗
52. 10.1021/la960465w10.1021/la960465w ↗
53. 10.2147/IJN.S11520810.2147/IJN.S115208 ↗
54. 10.1021/ja202941510.1021/ja2029415 ↗
55. 10.1021/la051898e10.1021/la051898e ↗
56. 10.1021/cm052382j10.1021/cm052382j ↗
57. 10.1002/1520-6017(200010)89:10<1286::AID-JPS6>3.0.CO;2-O10.1002/1520-6017(200010)89:10<1286::AID-JPS6>3.0.CO;2-O ↗
58. 10.1021/la052797j10.1021/la052797j ↗
59. 10.1021/acs.accounts.9b0049010.1021/acs.accounts.9b00490 ↗
60. Shnoudeh A. J. · 2019 · 52710.1016/B978-0-12-814427-5.00015-9 ↗
61. Zhang Y. · 2019 · 25
62. 10.1016/j.snb.2019.12711810.1016/j.snb.2019.127118 ↗