Evidence map›Paper›PMID 35362861›Full record

ArticleAdvances in experimental medicine and biology2022

Current Status, Barriers, and Future Directions for Humanized Mouse Models to Evaluate Stem Cell-Based Islet Cell Transplant.

Kevin Verhoeff, Braulio A Marfil-Garza, Nerea Cuesta-Gomez, Ila Jasra, Nidheesh Dadheech, A M James Shapiro

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Article in Advances in experimental medicine and biology, 2022. 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

6 authors.

Kevin VerhoeffDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.
Braulio A Marfil-GarzaDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.
Nerea Cuesta-GomezAlberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada.
Ila JasraAlberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada.
Nidheesh DadheechAlberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada.
A M James ShapiroAlberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada. jshapiro@ualberta.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Islet cell transplant (ITx) continues to improve, with recently published long-term outcomes suggesting nearly 80% graft survival, leading to improvements in glycemic control, reductions in insulin doses, and near-complete abrogation of severe hypoglycemia. Unfortunately, access to ITx remains limited by immunosuppression requirements and donor supply. Discovery of stem cell-derived functional islet-like clusters with the capacity to reverse diabetes offers a renewable, potentially immunosuppression-free solution for future widespread ITx. Evaluation and optimization of these therapies is ongoing, but may one day provide a realistic cure for type 1 diabetes. However, stem cell-based ITx has unique immunologic questions that remain unanswered. Here, we briefly synthesize current approaches for stem cell-derived ITx, review humanized mice models, and elaborate on the potential of humanized mice models for bridging the gap between current small rodent models and human clinical trials for allogeneic and autologous inducible pluripotent stem cell (iPSC)-based ITx while highlighting limitations and future directions.

Indexed as

Diabetes Mellitus, Type 1Hematopoietic Stem Cell TransplantationIslets of LangerhansIslets of Langerhans TransplantationAnimalsHumansMiceDiabetesHumanized mouse modelImmunosuppressionInducible pluripotent stem cellsIslet cell transplantTransplant

Identifiers

PMID35362861

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.