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A study of Docetaxel-induced effects in MCF-7 cells by means of Raman microspectroscopy

Overview of attention for article published in Analytical & Bioanalytical Chemistry, March 2012
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Title
A study of Docetaxel-induced effects in MCF-7 cells by means of Raman microspectroscopy
Published in
Analytical & Bioanalytical Chemistry, March 2012
DOI 10.1007/s00216-012-5887-9
Pubmed ID
Authors

Katharina Hartmann, Melanie Becker-Putsche, Thomas Bocklitz, Katharina Pachmann, Axel Niendorf, Petra Rösch, Jürgen Popp

Abstract

Chemotherapies feature a low success rate of about 25%, and therefore, the choice of the most effective cytostatic drug for the individual patient and monitoring the efficiency of an ongoing chemotherapy are important steps towards personalized therapy. Thereby, an objective method able to differentiate between treated and untreated cancer cells would be essential. In this study, we provide molecular insights into Docetaxel-induced effects in MCF-7 cells, as a model system for adenocarcinoma, by means of Raman microspectroscopy combined with powerful chemometric methods. The analysis of the Raman data is divided into two steps. In the first part, the morphology of cell organelles, e.g. the cell nucleus has been visualized by analysing the Raman spectra with k-means cluster analysis and artificial neural networks and compared to the histopathologic gold standard method hematoxylin and eosin staining. This comparison showed that Raman microscopy is capable of displaying the cell morphology; however, this is in contrast to hematoxylin and eosin staining label free and can therefore be applied potentially in vivo. Because Docetaxel is a drug acting within the cell nucleus, Raman spectra originating from the cell nucleus region were further investigated in a next step. Thereby we were able to differentiate treated from untreated MCF-7 cells and to quantify the cell-drug response by utilizing linear discriminant analysis models.

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The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
India 1 2%
Portugal 1 2%
Sweden 1 2%
Unknown 51 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 20%
Researcher 11 20%
Student > Bachelor 6 11%
Student > Master 6 11%
Professor > Associate Professor 5 9%
Other 6 11%
Unknown 10 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 20%
Chemistry 6 11%
Engineering 6 11%
Computer Science 5 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Other 12 22%
Unknown 11 20%
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 March 2012.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Analytical & Bioanalytical Chemistry
#5,669
of 9,618 outputs
Outputs of similar age
#110,543
of 168,677 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#73
of 107 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,618 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.