Evidence map›Paper›PMID 19835428›Full record

ArticleMathematical biosciences and engineering : MBE2009

Modeling dynamic changes in type 1 diabetes progression: quantifying beta-cell variation after the appearance of islet-specific autoimmune responses.

Patrick Nelson, Noah Smith, Stanca Ciupe, Weiping Zou, Gilbert S Omenn, Massimo Pietropaolo

Open access · hybridAbstract read
In one paragraph

Article in Mathematical biosciences and engineering : MBE, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. 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

6 authors at 3 institutions in 1 country.

Patrick NelsonUniversity of Michigan, Department of Mathematics, Center for Computational Medicine and Bioinformatics, 100 Washtenaw Ave, Ann Arbor, MI 48109-2218, USA. pwn@umich.edu
Noah Smith
Stanca Ciupe
Weiping Zou
Gilbert S Omenn
Massimo Pietropaolo
University of Michigan · USWashtenaw Community College · USDuke University · US

Funding

IMPROVING PREDICTION OF IDDMR01DK053456 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HERMAN, MARK A, REDONDO, MARIA JOSE · 1999 to 2021
$9.5M
EPIDEMIOLOGY OF ISLET CELL AUTOIMMUNITY IN NIDDMR01DK056200 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PIETROPAOLO, MASSIMO T · 2001 to 2009
$3.5M
NIDDK NIH HHS DK56200NIDDK NIH HHS R01 DK053456NIDDK NIH HHS R01 DK056200NIDDK NIH HHS R01 DK53456PHS HHS PA-04-081
6 · The paper itself

Abstract

Type 1 diabetes (T1DM) is a chronic autoimmune disease with a long prodrome, which is characterized by dysfunction and ultimately destruction of pancreatic beta-cells. Because of the limited access to pancreatic tissue and pancreatic lymph nodes during the normoglycemic phase of the disease, little is known about the dynamics involved in the chain of events leading to the clinical onset of the disease in humans. In particular, during T1DM progression there is limited information about temporal fluctuations of immunologic abnormalities and their effect on pancreatic beta-cell function and mass. Therefore, our understanding of the pathoetiology of T1DM relies almost entirely on studies in animal models of this disease. In an effort to elucidate important mechanisms that may play a critical role in the progression to overt disease, we propose a mathematical model that takes into account the dynamics of functional and dysfunctional beta-cells, regulatory T cells, and pathogenic T cells. The model assumes that all individuals carrying susceptible HLA haplotypes will develop variable degrees of T1DM-related immunologic abnormalities. The results provide information about the concentrations and ratios of pathogenic T cells and regulatory T cells, the timing in which beta-cells become dysfunctional, and how certain kinetic parameters affect the progression to T1DM. Our model is able to describe changes in the ratio of pathogenic T cells and regulatory T cells after the appearance of islet antibodies in the pancreas. Finally, we discuss the robustness of the model and its ability to assist experimentalists in designing studies to test complicated theories about the disease.

Indexed as

Models, ImmunologicalAnimalsAutoantibodiesAutoimmunityDiabetes Mellitus, Type 1GlucoseHumansInsulinInsulin-Secreting CellsMathematical ConceptsMiceT-Lymphocytes, RegulatoryAutoantibodiesGlucoseInsulinislet cell antibody

Identifiers

PMID19835428
PMCPMC4620738
OpenAlexW2015725951

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.