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Post-translational modifications in tumor biomarkers: the next challenge for aptamers?

Overview of attention for article published in Analytical & Bioanalytical Chemistry, January 2018
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  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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4 tweeters

Citations

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2 Dimensions

Readers on

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28 Mendeley
Title
Post-translational modifications in tumor biomarkers: the next challenge for aptamers?
Published in
Analytical & Bioanalytical Chemistry, January 2018
DOI 10.1007/s00216-018-0861-9
Pubmed ID
Authors

Ana Díaz-Fernández, Rebeca Miranda-Castro, Noemí de-los-Santos-Álvarez, María Jesús Lobo-Castañón

Abstract

Advances in proteomics have fueled the search for novel cancer biomarkers with higher selectivity. Differential expression of low abundant proteins has been the usual way of finding those biomarkers. The existence of a selective receptor for each biomarker is compulsory for their use in diagnostic/prognostic assays. Antibodies are the receptors of choice in most cases although aptamers are becoming familiar because of their facile and reproducible synthesis, chemical stability as well as comparable affinity and selectivity. In recent years, it has been reported that the pattern of post-translational modifications, altered under neoplastic disease, is a better predictive biomarker than the total protein level. Among others, abnormal glycosylation is attracting great attention. Lectins and antibodies are being used for identification and detection of the carbohydrate moiety with low level of discrimination among various glycoproteins. Such level of selectivity is critical to bring next-generation biomarkers to the clinic. Aptamers that can be rationally tailored for a certain molecule domain can become the golden receptor to specifically detect aberrant glycosylation at each protein or even at each glycosylation site, providing new diagnostic tools for early detection of cancer. Graphical abstract Aptamers may specifically differentiate normal from aberrant glycoproteins.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 29%
Student > Master 6 21%
Unspecified 5 18%
Researcher 5 18%
Other 1 4%
Other 3 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 29%
Unspecified 7 25%
Agricultural and Biological Sciences 4 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Engineering 2 7%
Other 5 18%

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 28 February 2018.
All research outputs
#7,891,116
of 12,576,527 outputs
Outputs from Analytical & Bioanalytical Chemistry
#2,499
of 4,843 outputs
Outputs of similar age
#193,598
of 344,099 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#81
of 223 outputs
Altmetric has tracked 12,576,527 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,843 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 43rd percentile – i.e., 43% 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 344,099 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.