Evidence map›Paper›PMID 24565418›Full record

ArticleBMC medical genomics2013

The effect of unhealthy β-cells on insulin secretion in pancreatic islets.

Yang Pu, Saangho Lee, David C Samuels, Layne T Watson, Yang Cao

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 2 institutions in 1 country.

Yang Pu
Saangho Lee
David C Samuels
Layne T Watson
Yang Cao
Virginia Tech · USCenter for Human Genetics · US

Funding

Stochastic Models of Cell Cycle Regulation in EukaryotesR01GM078989 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI PECCOUD, JEAN M, TYSON, JOHN J. · 2006 to 2018
$5.3M
NIGMS NIH HHS GM078989
6 · The paper itself

Abstract

backgroundInsulin secreted by pancreatic islet β-cells is the principal regulating hormone of glucose metabolism and plays a key role in controlling glucose level in blood. Impairment of the pancreatic islet function may cause glucose to accumulate in blood, and result in diabetes mellitus. Recent studies have shown that mitochondrial dysfunction has a strong negative effect on insulin secretion.

methodsIn order to study the cause of dysfunction of pancreatic islets, a multiple cell model containing healthy and unhealthy cells is proposed based on an existing single cell model. A parameter that represents the function of mitochondria is modified for unhealthy cells. A 3-D hexagonal lattice structure is used to model the spatial differences among β-cells in a pancreatic islet. The β-cells in the model are connected through direct electrical connections between neighboring β-cells.

resultsThe simulation results show that the low ratio of total mitochondrial volume over cytoplasm volume per β-cell is a main reason that causes some mitochondria to lose their function. The results also show that the overall insulin secretion will be seriously disrupted when more than 15% of the β-cells in pancreatic islets become unhealthy.

conclusionAnalysis of the model shows that the insulin secretion can be reinstated by increasing the glucokinase level. This new discovery sheds light on antidiabetic medication.

Indexed as

AlgorithmsModels, BiologicalAnimalsCell MembraneComputer SimulationCytoplasmGlucokinaseGlucoseGlycolysisHumansInsulinInsulin-Secreting CellsInsulin SecretionIslets of LangerhansMitochondriaGlucokinaseGlucoseInsulin

Identifiers

PMID24565418
PMCPMC3981690
OpenAlexW2045448203

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.