The DOI matches its Crossref record; 337 of the 337 references it cites were found in a registry or an index.
Trends and targets in antiviral phototherapy
Open accessAbstract
Photodynamic therapy (PDT) is a well-established treatment option in the treatment of certain cancerous and pre-cancerous lesions. Though best-known for its application in tumor therapy, historically the photodynamic effect was first demonstrated against bacteria at the beginning of the 20^th century. Today, in light of spreading antibiotic resistance and the rise of new infections, this photodynamic inactivation (PDI) of microbes, such as bacteria, fungi, and viruses, is gaining considerable attention. This review focuses on the PDI of viruses as an alternative treatment in antiviral therapy, but also as a means of viral decontamination, covering mainly the literature of the last decade. The PDI of viruses shares the general action mechanism of photodynamic applications: the irradiation of a dye with light and the subsequent generation of reactive oxygen species (ROS) which are the effective phototoxic agents damaging virus targets by reacting with viral nucleic acids, lipids and proteins. Interestingly, a light-independent antiviral activity has also been found for some of these dyes. This review covers the compound classes employed in the PDI of viruses and their various areas of use. In the medical area, currently two fields stand out in which the PDI of viruses has found broader application: the purification of blood products and the treatment of human papilloma virus manifestations. However, the PDI of viruses has also found interest in such diverse areas as water and surface decontamination, and biosafety.
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Cites
BODIPY Dyes and Their Derivatives: Syntheses and Spectroscopic Properties
Loudet, A., & Burgess, K. (2007) · Chemical Reviews · doi:10.1021/cr078381n · Cited by 5,238
Photodynamic therapy of cancer: An update
Agostinis, P., Berg, K., Cengel, K. A., Foster, T. H., Girotti, A. W., Gollnick, S. O., Hahn, S. M., Hamblin, M. R., Juzeniene, A., Kessel, D., et al. (2011) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20114 · Cited by 5,145
Dougherty, T. J., Gomer, C. J., Henderson, B. W., Jori, G., Kessel, D., Korbelik, M., Moan, J., & Peng, Q. (1998) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/90.12.889 · Cited by 4,716
Gomer, C. J. (1988) · Cited by 4,169
J Antimicrob Chemother 1994; 33: 350–351
O'SHAUGHNESSY, E. M., & DAS, S. S. (1994) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/33.2.350 · Cited by 3,746
Nanoparticles in Photodynamic Therapy
Lucky, S. S., Soo, K. C., & Zhang, Y. (2015) · Chemical Reviews · doi:10.1021/cr5004198 · Cited by 2,980
Photosensitized singlet oxygen and its applications
DeRosa, M. (2002) · Coordination Chemistry Reviews · doi:10.1016/s0010-8545(02)00034-6 · Cited by 2,931
Photodynamic therapy and anti-tumour immunity
Castano, A. P., Mroz, P., & Hamblin, M. R. (2006) · Nature Reviews Cancer · doi:10.1038/nrc1894 · Cited by 2,676
Fluorescent indicators based on BODIPY
Boens, N., Leen, V., & Dehaen, W. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15132k · Cited by 2,262
BODIPY dyes in photodynamic therapy
Kamkaew, A., Lim, S. H., Lee, H. B., Kiew, L. V., Chung, L. Y., & Burgess, K. (2013) · Chem. Soc. Rev. · doi:10.1039/c2cs35216h · Cited by 2,104
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Organic photosensitizers for antimicrobial phototherapy
Nguyen, V.-N., Zhao, Z., Tang, B. Z., & Yoon, J. (2022) · Chemical Society Reviews · doi:10.1039/d1cs00647a · Cited by 462
Uliana, M. P., da Cruz Rodrigues, A., Ono, B. A., Pratavieira, S., de Oliveira, K. T., & Kurachi, C. (2022) · Molecules · doi:10.3390/molecules27185769 · Cited by 16
Metadata
- Authors
- Wiehe, A., O’Brien, J. M., & Senge, M. O.
- Venue
- Photochemical & Photobiological Sciences
- Published
- 2019-11
- Volume
- 18
- Issue
- 11
- Pages
- 2565-2612
- ISSN
- 1474-905X (ISSN-L)
- 1474-9092
- OpenAlex
- W2967503052
- Cited by
- 257
- References
- 337
- FWCI
- 28.17
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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