Evidence map›Paper›PMID 41849446›Full record

ArticlePloS one2026

PID-controller enhanced artificial β-cells.

Lin Liu, Bruna Jacobson, Darko Stefanovic

Abstract read
In one paragraph

Article in PloS one, 2026. 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
–field-weighted citation impact
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.

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

3 authors.

Lin LiuDepartment of Computer Science, University of New Mexico, Albuquerque, New Mexico, United States of America.ORCID https://orcid.org/0009-0008-4312-7411
Bruna JacobsonDepartment of Computer Science, University of New Mexico, Albuquerque, New Mexico, United States of America.ORCID https://orcid.org/0000-0001-7718-9794
Darko StefanovicDepartment of Computer Science, University of New Mexico, Albuquerque, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-5619-3599

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional management of diabetes via injection or external insulin pumps suffers from inconvenience and inability to accurately maintain blood glucose levels. A potential solution to these problems consists of implanting synthetic artificial β-cells that can sense glucose and transcribe insulin protein. Experimental results from Xie et al. show these cells are able to release insulin and somewhat improve postprandial glucose levels in diabetic mice. However, they fail to achieve the degree of glucose regulation as in healthy mice. In our analysis, we explain that this artificial β-cell system has a major disadvantage: it is a high-dimensional dynamic system but with little tuning space. Here, we propose an analytical model of a PID-controller-based enhanced artificial β-cell design to solve this issue. Our numerical simulations show that a model of PID-controlled engineered artificial β-cells can shut down production of insulin in time and maintain a proper glycemia level, in addition to adding more tuning space. These enhanced models of PID-controller-based artificial β-cell are thus able to perform better in regulating glucose levels in Type 1 diabetic mice compared with artificial β-cells without PID-control.

Indexed as

Artificial CellsInsulin-Secreting CellsAnimalsBlood GlucoseComputer SimulationDiabetes Mellitus, ExperimentalDiabetes Mellitus, Type 1InsulinMiceModels, BiologicalBlood GlucoseInsulin

Identifiers

PMID41849446
PMCPMC12998882

What OpenQuestion holds

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Registered trials

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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.