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Mendeley readers
Attention Score in Context
| Title |
Pharmacokinetics and pharmacodynamics of VEGF-neutralizing antibodies
|
|---|---|
| Published in |
BMC Systems Biology, November 2011
|
| DOI | 10.1186/1752-0509-5-193 |
| Pubmed ID | |
| Authors |
Stacey D Finley, Marianne O Engel-Stefanini, PI Imoukhuede, Aleksander S Popel |
| Abstract |
Vascular endothelial growth factor (VEGF) is a potent regulator of angiogenesis, and its role in cancer biology has been widely studied. Many cancer therapies target angiogenesis, with a focus being on VEGF-mediated signaling such as antibodies to VEGF. However, it is difficult to predict the effects of VEGF-neutralizing agents. We have developed a whole-body model of VEGF kinetics and transport under pathological conditions (in the presence of breast tumor). The model includes two major VEGF isoforms VEGF121 and VEGF165, receptors VEGFR1, VEGFR2 and co-receptors Neuropilin-1 and Neuropilin-2. We have added receptors on parenchymal cells (muscle fibers and tumor cells), and incorporated experimental data for the cell surface density of receptors on the endothelial cells, myocytes, and tumor cells. The model is applied to investigate the action of VEGF-neutralizing agents (called "anti-VEGF") in the treatment of cancer. |
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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 66 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 19% |
| Researcher | 10 | 15% |
| Student > Master | 10 | 15% |
| Student > Bachelor | 9 | 13% |
| Student > Doctoral Student | 5 | 7% |
| Other | 8 | 12% |
| Unknown | 12 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 20 | 30% |
| Agricultural and Biological Sciences | 12 | 18% |
| Medicine and Dentistry | 10 | 15% |
| Biochemistry, Genetics and Molecular Biology | 8 | 12% |
| Chemistry | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 11 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 21 October 2020.
All research outputs
#8,270,860
of 25,394,764 outputs
Outputs from BMC Systems Biology
#306
of 1,132 outputs
Outputs of similar age
#69,187
of 245,181 outputs
Outputs of similar age from BMC Systems Biology
#17
of 49 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 72% of its peers.
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 245,181 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 49 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 65% of its contemporaries.