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Prioritization of Natural Extracts by LC–MS-PCA for the Identification of New Photosensitizers for Photodynamic Therapy

Overview of attention for article published in Analytical Chemistry, January 2014
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Title
Prioritization of Natural Extracts by LC–MS-PCA for the Identification of New Photosensitizers for Photodynamic Therapy
Published in
Analytical Chemistry, January 2014
DOI 10.1021/ac403709a
Pubmed ID
Authors

Norazwana Samat, Pei Jean Tan, Khozirah Shaari, Faridah Abas, Hong Boon Lee

Abstract

Photodynamic therapy (PDT) is an alternative treatment for cancer that involves administration of a photosensitive drug or photosensitizer that localizes at the tumor tissue followed by in situ excitation at an appropriate wavelength of light. Tumour tissues are then killed by cytotoxic reactive oxygen species generated by the photosensitizer. Targeted excitation and photokilling of affected tissues is achieved through focal light irradiation, thereby minimizing systemic side effects to the normal healthy tissues. Currently, there are only a small number of photosensitizers that are in the clinic and many of these share the same structural core based on cyclic tetrapyrroles. This paper describes how metabolic tools are utilized to prioritize natural extracts to search for structurally new photosensitizers from Malaysian biodiversity. As proof of concept, we analyzed 278 photocytotoxic extracts using a hyphenated technique of liquid chromatography-mass spectrometry coupled with principal component analysis (LC-MS-PCA) and prioritized 27 extracts that potentially contained new photosensitizers for chemical dereplication using an in-house UPLC-PDA-MS-Photocytotoxic assay platform. This led to the identification of 2 new photosensitizers with cyclic tetrapyrrolic structures, thereby demonstrating the feasibility of the metabolic approach.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 2%
Denmark 1 2%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 16%
Researcher 5 12%
Student > Master 5 12%
Student > Doctoral Student 3 7%
Unspecified 2 5%
Other 9 21%
Unknown 12 28%
Readers by discipline Count As %
Chemistry 11 26%
Agricultural and Biological Sciences 6 14%
Biochemistry, Genetics and Molecular Biology 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Medicine and Dentistry 3 7%
Other 3 7%
Unknown 14 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2014.
All research outputs
#20,216,580
of 22,739,983 outputs
Outputs from Analytical Chemistry
#24,256
of 26,401 outputs
Outputs of similar age
#265,363
of 306,020 outputs
Outputs of similar age from Analytical Chemistry
#279
of 317 outputs
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So far Altmetric has tracked 26,401 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.