| Title |
The Dynamics of HPV Infection and Cervical Cancer Cells
|
|---|---|
| Published in |
Bulletin of Mathematical Biology, December 2015
|
| DOI | 10.1007/s11538-015-0124-2 |
| Pubmed ID | |
| Authors |
Tri Sri Noor Asih, Suzanne Lenhart, Steven Wise, Lina Aryati, F. Adi-Kusumo, Mardiah S. Hardianti, Jonathan Forde |
| Abstract |
The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 8 | 16% |
| Student > Master | 6 | 12% |
| Student > Ph. D. Student | 6 | 12% |
| Researcher | 4 | 8% |
| Lecturer | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 17 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 16% |
| Mathematics | 7 | 14% |
| Engineering | 4 | 8% |
| Medicine and Dentistry | 4 | 8% |
| Computer Science | 3 | 6% |
| Other | 9 | 18% |
| Unknown | 16 | 31% |
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 03 February 2016.
All research outputs
#15,355,821
of 22,842,950 outputs
Outputs from Bulletin of Mathematical Biology
#721
of 1,095 outputs
Outputs of similar age
#228,863
of 390,425 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#8
of 16 outputs
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So far Altmetric has tracked 1,095 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 16 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 50% of its contemporaries.