Evidence map›Paper›PMID 42094425›Full record

ArticlebioRxiv : the preprint server for biology2026

Predictive control of human pancreatic cell fate using a digital model of

Enrique E Sanchez-Castro, Matthew Ishahak, Tai Le, Marlie M Maestas, Diana C Hernandez-Rincon, Noyonika Mukherjee, Kameron Bradley, James Lu, Sarah E Gale, Jeffrey R Millman

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

10 authors.

Enrique E Sanchez-CastroDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Matthew IshahakDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Tai LeDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Marlie M MaestasDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Diana C Hernandez-RinconDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Noyonika MukherjeeDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Kameron BradleyDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
James LuDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Sarah E GaleDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.
Jeffrey R MillmanDivision of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine; St. Louis, MO, USA.ORCID 0000-0003-0426-3492

Funding

DIABETES &RELATED METABOLIC DISEASEST32DK007120 · NIDDK · WASHINGTON UNIVERSITY · PI MARCO COLONNA, Maria Sara Remedi · 1986 to 2026
$15.7M
Renewal of the Human Islet Research Enhancement Center (HIREC) for the Type-1-Diabetes-Focused Human Islet Research Network (HIRN).U24DK104162 · NIDDK · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI John S. Kaddis, Joyce Carol Niland · 2019 to 2026
$12.3M
Studying the mechanisms of initiation and progression of Beta cell death in T1DUG3DK142188 · NIDDK · SCRIPPS RESEARCH INSTITUTE, THE · PI CHRISTOPHER C. W. HUGHES, Jeffrey Robert Millman · 2025 to 2026
$2.4M
NIDDK NIH HHS T32 DK007120NIDDK NIH HHS U24 DK104162NIDDK NIH HHS UG3 DK142188
6 · The paper itself

Abstract

The controlled generation of mature stem cell-derived islets (SC-islets) remains a barrier to scalable cell therapy for diabetes. Here, we develop a predictive digital model defining the cell-state-specific regulatory logic governing fate specification during human SC-islet differentiation. We integrate 400,603 cells from 9 original single-cell multiomic datasets and 52 public single-cell RNA-seq and ATAC-seq datasets across 4 cell lines and 7 differentiation protocols. This model resolves transcriptional and chromatin accessibility dynamics while enabling time-resolved inference and

Indexed as

diabetesembryonic stem cellspancreatic differentiationpancreatic isletspluripotent stem cellspredictive modelingsingle-cell multiomicsingle-cell sequencingstem cell-derived isletstranscription factors

Identifiers

PMID42094425
PMCPMC13142414

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.