Evidence map›Paper›PMID 37951849›Full record

ArticleJournal of mathematical biology2023

Stochastic dynamics of human papillomavirus delineates cervical cancer progression.

Tuan Anh Phan, Farhana Sarower, Jinqiao Duan, Jianjun Paul Tian

Open access · greenAbstract read
In one paragraph

Article in Journal of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Tuan Anh PhanInstitute for Modeling Collaboration and Innovation, University of Idaho, Moscow, ID, 83844, USA.
Farhana SarowerDepartment of Mathematical Sciences, New Mexico State University, Las Cruces, NM, 88001, USA.
Jinqiao DuanDepartments of Mathematics, School of Sciences, Great Bay University, Dongguan, 523000, Guangdong, China.
Jianjun Paul TianDepartment of Mathematical Sciences, New Mexico State University, Las Cruces, NM, 88001, USA. jtian@nmsu.edu.ORCID http://orcid.org/0000-0003-2292-213X
New Mexico State University · USGreat Bay UniversityUniversity of Idaho · US

Funding

Sequence-structure-function relationships in human visual photopigmentsP20GM104420 · NIGMS · UNIVERSITY OF IDAHO · PI VAN LEUVEN, JAMES · 2015 to 2024
$22.9M
Undergraduate Student Training in Cancer ResearchU54CA132383 · NCI · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI MICHELE Irene SHUSTER · 2007 to 2026
$21.4M
NCI NIH HHS U54 CA132383NIGMS NIH HHS P20 GM104420
6 · The paper itself

Abstract

Starting from a deterministic model, we propose and study a stochastic model for human papillomavirus infection and cervical cancer progression. Our analysis shows that the chronic infection state as random variables which have the ergodic invariant probability measure is necessary for progression from infected cell population to cervical cancer cells. It is shown that small progression rate from infected cells to precancerous cells and small microenvironmental noises associated with the progression rate and viral infection help to establish such chronic infection states. It implicates that large environmental noises associated with viral infection and the progression rate in vivo can reduce chronic infection. We further show that there will be a cervical cancer if the noise associated with precancerous cell growth is large enough. In addition, comparable numerical studies for the deterministic model and stochastic model, together with Hopf bifurcations in both deterministic and stochastic systems, highlight our analytical results.

Indexed as

Precancerous ConditionsUterine Cervical NeoplasmsVirus DiseasesFemaleHuman Papillomavirus VirusesHumansPersistent InfectionStochastic ProcessesCervical cancerChronic infection stateErgodic invariant probability measureStochastic dynamical bifurcation

Identifiers

PMID37951849
PMCPMC11085997
OpenAlexW4388603890

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.