Cancer Systems and Integrative Biology
Springer US
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Isolation and Identification of Plasma Extracellular Vesicles Protein Biomarkers.
|
|---|---|
| Book title |
Cancer Systems and Integrative Biology
|
| Published in |
Methods in molecular biology, January 2023
|
| DOI | 10.1007/978-1-0716-3163-8_14 |
| Pubmed ID | |
| Book ISBNs |
978-1-07-163162-1, 978-1-07-163163-8
|
| Authors |
Lihon, Michelle V, Hadisurya, Marco, Wu, Xiaofeng, Iliuk, Anton, Tao, W Andy, Lihon, Michelle V., Tao, W. Andy |
| Abstract |
Extracellular vesicles (EVs) have emerged as a valuable source for disease biomarkers and an alternative drug delivery system due to their ability to carry cargo and target specific cells. Proper isolation, identification, and analytical strategy are required for evaluating their potential in diagnostics and therapeutics. Here, a method is detailed to isolate plasma EVs and analyze their proteomic profiling, combining EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and mass spectrometry qualitative and quantitative strategies for EV proteome characterization. The pipeline provides a highly effective EV-based proteome analysis technique that can be applied for EV characterization and evaluation of EV-based diagnosis and therapy. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 2 | 33% |
| Student > Ph. D. Student | 1 | 17% |
| Student > Doctoral Student | 1 | 17% |
| Student > Master | 1 | 17% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 50% |
| Unspecified | 2 | 33% |
| Unknown | 1 | 17% |
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 16 May 2023.
All research outputs
#16,492,007
of 24,267,449 outputs
Outputs from Methods in molecular biology
#5,714
of 13,666 outputs
Outputs of similar age
#250,023
of 446,503 outputs
Outputs of similar age from Methods in molecular biology
#263
of 669 outputs
Altmetric has tracked 24,267,449 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 13,666 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 42nd percentile – i.e., 42% 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 446,503 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 669 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.