journal article·2025-01-31

Accelerating Pathogenic β-Amyloid Polypeptide Aggregate Dissociation by Optimizing Recruitment and Oxidization Processes on a MoS2/BiVO4 Composite Photoanode

Xinshang Li, Jiayi Liu, Jialin Gu, He Wang, Wenquan Zhou, Wenjuan Li, Jiangang Jiang

ACS Applied Nano Materials· Volume 8· Issue 4
Publisher page

Abstract

Pathogenic and stubborn β-amyloid polypeptide aggregates (APAs) have been well-known for inducing the infamous neurodegenerative Alzheimer’s disease (AD). However, the unsatisfactory performance of the present catalysts has prevented efficient AD cures through promising photoelectrochemical therapy (PECT) improved by photodynamic therapy. Herein, a biocompatible and efficient MoS 2 /BiVO 4 photoanode was fabricated by spin-coating and hydrothermal processes. Under the synergistic effect of constructing an internal heterojunction, controlling porous morphology, and introducing sulfur vacancy, superficial recruitment and irreversible oxidization processes were significantly optimized in vitro experiments. In the present experiment, 78.17% of APAs were effectively dissociated by MoS 2 /BiVO 4 within 60 min. To our knowledge, excellent dissociating performance is considered the highest hourly efficiency in current research. In addition, dissociated APAs lost their original cytotoxicity, while MoS 2 /BiVO 4 exhibited adequate stabilities. Building on this, MoS 2 /BiVO 4 showed enough application potential in approaching PECT. In conclusion, the remarkable contribution of optimizing recruitment and oxidization processes has been proven beneficial in accelerating APA dissociation, and we hope our research on high removal efficiency can provide an instructive example to the subsequent research and clinical treatment of AD in the future.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Alzheimer's disease research and treatments · Cholinesterase and Neurodegenerative Diseases · Advanced Nanomaterials in Catalysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Science, Northwest A&F University, Yangling, Shaanxi 712100, China

School of Basic Medicine, Shandong University, Jinan, Shandong 250012, China

Funding

Northwest A and F University · National Natural Science Foundation of China · Natural Science Foundation of Shaanxi Province · Ministry of Education of the People's Republic of China · Commercial research funds

References (84)

Show source-provided references
1. 10.3233/JAD-23900110.3233/JAD-239001 ↗
2. Gauthier, S.; Rosa-Neto, P.; Morais, J. A.; Webster, C. World Alzheimer Report 2021: Journey through the Diagnosis of Dementia, 2022.10.1016/j.jns.2023.121394 ↗
3. Gauthier, S.; Webster, C.; Servaes, S.; Morais, J. A.; Rosa-Neto, P. World Alzheimer Report 2022: Life after Diagnosis: Navigating Treatment, Care and Support, 2022.
4. Ren, R.; Qi, J.; Lin, S.; Liu, X.; Yin, P.; Wang, Z.; Tang, R.; Wang, J.; Huang, Q.; Li, J. The China Alzheimer Report 2022.10.1136/gpsych-2022-100751 ↗
5. 10.1016/0006-291X(84)91209-910.1016/0006-291X(84)91209-9 ↗
6. 10.1002/j.1460-2075.1985.tb04000.x10.1002/j.1460-2075.1985.tb04000.x ↗
7. 10.1126/science.221853110.1126/science.2218531 ↗
8. 10.1126/science.107299410.1126/science.1072994 ↗
9. 10.1038/nrd350510.1038/nrd3505 ↗
10. 10.1016/j.redox.2017.10.01410.1016/j.redox.2017.10.014 ↗
11. 10.1038/ncomms999710.1038/ncomms9997 ↗
12. 10.1039/C6TB01351A10.1039/C6TB01351A ↗
13. 10.1016/j.biomaterials.2016.05.00510.1016/j.biomaterials.2016.05.005 ↗
14. 10.1002/smll.20170098310.1002/smll.201700983 ↗
15. 10.1016/j.actbio.2017.11.04810.1016/j.actbio.2017.11.048 ↗
16. 10.1002/adfm.20180281310.1002/adfm.201802813 ↗
17. 10.1021/ja504031d10.1021/ja504031d ↗
18. 10.1002/anie.20150431010.1002/anie.201504310 ↗
19. 10.1002/adhm.20150096410.1002/adhm.201500964 ↗
20. 10.1002/adhm.20160113310.1002/adhm.201601133 ↗
21. 10.1002/smll.20160313910.1002/smll.201603139 ↗
22. 10.1007/s12274-017-1930-710.1007/s12274-017-1930-7 ↗
23. 10.1021/acsami.8b1107810.1021/acsami.8b11078 ↗
24. 10.1021/cr900300p10.1021/cr900300p ↗
25. 10.1002/aenm.20220372010.1002/aenm.202203720 ↗
26. 10.1016/j.cej.2023.14265210.1016/j.cej.2023.142652 ↗
27. 10.1126/science.123243710.1126/science.1232437 ↗
28. 10.1038/nbt.341510.1038/nbt.3415 ↗
29. 10.1002/ana.2395110.1002/ana.23951 ↗
30. 10.1212/WNL.000000000000082310.1212/WNL.0000000000000823 ↗
31. 10.1186/s40035-015-0034-010.1186/s40035-015-0034-0 ↗
32. 10.1038/s41586-024-07334-y10.1038/s41586-024-07334-y ↗
33. 10.1126/science.116709310.1126/science.1167093 ↗
34. 10.1016/j.neuron.2009.03.01110.1016/j.neuron.2009.03.011 ↗
35. 10.1002/smll.20220669510.1002/smll.202206695 ↗
36. 10.1016/j.jechem.2024.05.04710.1016/j.jechem.2024.05.047 ↗
37. 10.1038/s41560-017-0057-010.1038/s41560-017-0057-0 ↗
38. 10.1038/ncomms976910.1038/ncomms9769 ↗
39. 10.1039/C7TA00156H10.1039/C7TA00156H ↗
40. 10.1016/j.jcat.2018.07.02710.1016/j.jcat.2018.07.027 ↗
41. 10.1002/aenm.20170153610.1002/aenm.201701536 ↗
42. 10.1002/smll.20160153610.1002/smll.201601536 ↗
43. 10.1021/acs.chemrev.5b0049810.1021/acs.chemrev.5b00498 ↗
44. 10.1002/aenm.20150175410.1002/aenm.201501754 ↗
45. 10.1039/C8EN01283K10.1039/C8EN01283K ↗
46. 10.1039/C8TA12012A10.1039/C8TA12012A ↗
47. 10.1002/anie.20201255010.1002/anie.202012550 ↗
48. 10.1002/aenm.20230422310.1002/aenm.202304223 ↗
49. 10.1002/anie.20110536410.1002/anie.201105364 ↗
50. 10.1021/nl204361210.1021/nl2043612 ↗
51. 10.1002/adma.20120399910.1002/adma.201203999 ↗
52. 10.1039/C4EE01932F10.1039/C4EE01932F ↗
53. 10.1002/adma.20221169010.1002/adma.202211690 ↗
54. 10.1021/acssuschemeng.8b0017010.1021/acssuschemeng.8b00170 ↗
55. 10.1016/j.jcis.2018.08.07810.1016/j.jcis.2018.08.078 ↗
56. 10.1016/j.apcatb.2019.11846610.1016/j.apcatb.2019.118466 ↗
57. 10.1016/j.chemosphere.2020.12827910.1016/j.chemosphere.2020.128279 ↗
58. 10.1021/cg901212510.1021/cg9012125 ↗
59. 10.1002/aenm.20150216110.1002/aenm.201502161 ↗
60. 10.1016/j.nanoen.2020.10464810.1016/j.nanoen.2020.104648 ↗
61. 10.1002/aenm.20180219810.1002/aenm.201802198 ↗
62. 10.1021/ja201269b10.1021/ja201269b ↗
63. 10.1021/am404843b10.1021/am404843b ↗
64. 10.1002/adma.20130268510.1002/adma.201302685 ↗
65. 10.1002/aenm.20150164510.1002/aenm.201501645 ↗
66. 10.1016/j.apcatb.2021.12063610.1016/j.apcatb.2021.120636 ↗
67. 10.1002/anie.20201359310.1002/anie.202013593 ↗
68. 10.1038/s41467-023-43689-y10.1038/s41467-023-43689-y ↗
69. 10.1016/j.apcatb.2020.11937710.1016/j.apcatb.2020.119377 ↗
70. 10.1016/j.apsusc.2022.15297110.1016/j.apsusc.2022.152971 ↗
71. 10.1016/j.apcatb.2024.12402310.1016/j.apcatb.2024.124023 ↗
72. 10.1016/j.jhazmat.2020.12443610.1016/j.jhazmat.2020.124436 ↗
73. 10.1021/acs.est.9b0562710.1021/acs.est.9b05627 ↗
74. 10.1016/j.watres.2017.09.02810.1016/j.watres.2017.09.028 ↗
75. 10.1002/anie.20210906810.1002/anie.202109068 ↗
76. 10.1021/acsnano.0c0607810.1021/acsnano.0c06078 ↗
77. 10.1002/anie.20191052110.1002/anie.201910521 ↗
78. 10.1016/j.bbapap.2005.06.00510.1016/j.bbapap.2005.06.005 ↗
79. 10.1016/S0009-8981(03)00003-210.1016/S0009-8981(03)00003-2 ↗
80. 10.1081/DMR-10010233610.1081/DMR-100102336 ↗
81. 10.1126/science.111156810.1126/science.1111568 ↗
82. 10.1021/acsami.1c2286910.1021/acsami.1c22869 ↗
83. 10.1021/ja036813f10.1021/ja036813f ↗
84. 10.1021/acsomega.2c0746810.1021/acsomega.2c07468 ↗