Evidence map›Paper›PMID 36229614›Full record

ArticleNature communications2022

A predictive computational platform for optimizing the design of bioartificial pancreas devices.

Alexander U Ernst, Long-Hai Wang, Scott C Worland, Braulio A Marfil-Garza, Xi Wang, Wanjun Liu, Alan Chiu, Tatsuya Kin, Doug O'Gorman, Scott Steinschneider and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Oxygen dynamics and delivery strategies to enhance beta cell replacement therapy.American journal of physiology. Cell physiology · 2025
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. 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

14 authors.

Alexander U ErnstBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.ORCID 0000-0001-6209-8486
Long-Hai WangBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA. hiwang@ustc.edu.cn.ORCID 0000-0002-6529-7031
Scott C WorlandBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.
Braulio A Marfil-GarzaDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0002-7224-2127
Xi WangBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.
Wanjun LiuBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.
Alan ChiuBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.
Tatsuya KinDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0002-5179-6067
Doug O'GormanDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.
Scott SteinschneiderBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.
Ashim K DattaBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-1397-6892
Klearchos K PapasDepartment of Surgery, University of Arizona, Tucson, AZ, USA.
A M James ShapiroDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0002-6215-0990
Minglin MaBiological and Environmental Engineering, Cornell University, Ithaca, NY, USA. mm826@cornell.edu.ORCID 0000-0002-9553-7526

Funding

Engineering an Islet Thread from zwitterionically modified alginates for type 1 diabetesR01DK105967 · NIDDK · CORNELL UNIVERSITY · PI MA, MINGLIN · 2018 to 2022
$1.9M
NIDDK NIH HHS R01 DK105967
6 · The paper itself

Abstract

The delivery of encapsulated islets or stem cell-derived insulin-producing cells (i.e., bioartificial pancreas devices) may achieve a functional cure for type 1 diabetes, but their efficacy is limited by mass transport constraints. Modeling such constraints is thus desirable, but previous efforts invoke simplifications which limit the utility of their insights. Herein, we present a computational platform for investigating the therapeutic capacity of generic and user-programmable bioartificial pancreas devices, which accounts for highly influential stochastic properties including the size distribution and random localization of the cells. We first apply the platform in a study which finds that endogenous islet size distribution variance significantly influences device potency. Then we pursue optimizations, determining ideal device structures and estimates of the curative cell dose. Finally, we propose a new, device-specific islet equivalence conversion table, and develop a surrogate machine learning model, hosted on a web application, to rapidly produce these coefficients for user-defined devices.

Indexed as

Diabetes Mellitus, Type 1InsulinsIslets of LangerhansIslets of Langerhans TransplantationHumansInsulinPancreasInsulinInsulins

Identifiers

PMID36229614
PMCPMC9561707

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.