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Detection approaches for multidrug resistance genes of leukemia

Overview of attention for article published in Drug Design, Development and Therapy, April 2017
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1 tweeter

Citations

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12 Mendeley
Title
Detection approaches for multidrug resistance genes of leukemia
Published in
Drug Design, Development and Therapy, April 2017
DOI 10.2147/dddt.s134529
Pubmed ID
Authors

Ying Du, Baoan Chen

Abstract

Leukemia is a clonal malignant hematopoietic stem cell disease. It is the sixth most lethal cancer and accounts for 4% of all cancers. The main form of treatment for leukemia is chemotherapy. While some cancer types with a higher incidence than leukemia, such as lung and gastric cancer, have shown a sharp decline in mortality rates in recent years, leukemia has not followed this trend. Drug resistance is often regarded as the main clinical obstacle to effective chemotherapy in patients diagnosed with leukemia. Many resistance mechanisms have now been identified, and multidrug resistance (MDR) is considered the most important and prevalent mechanism involved in the failure of chemotherapy in leukemia. In order to reverse MDR and improve leukemia prognosis, effective detection methods are needed to identify drug resistance genes at initial diagnosis. This article provides a comprehensive overview of published approaches for the detection of MDR in leukemia. Identification of relevant MDR genes and methods for early detection of these genes will be needed in order to treat leukemia more effectively.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 42%
Student > Ph. D. Student 2 17%
Researcher 2 17%
Student > Doctoral Student 1 8%
Student > Master 1 8%
Other 1 8%
Readers by discipline Count As %
Unspecified 6 50%
Biochemistry, Genetics and Molecular Biology 3 25%
Medicine and Dentistry 2 17%
Agricultural and Biological Sciences 1 8%

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 02 May 2017.
All research outputs
#8,488,503
of 9,756,998 outputs
Outputs from Drug Design, Development and Therapy
#803
of 1,151 outputs
Outputs of similar age
#218,947
of 261,882 outputs
Outputs of similar age from Drug Design, Development and Therapy
#33
of 44 outputs
Altmetric has tracked 9,756,998 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,151 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,882 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 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.