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Record W4409781969 · doi:10.2337/db25-0037

Advances in Cell Replacement Therapies for Diabetes

2025· review· en· W4409781969 on OpenAlexaff
Bernhard J. Hering, Michael R. Rickels, Melena D. Bellin, Jeffrey R. Millman, Alice A. Tomei, Andrés J. Garcı́a, Haval Shirwan, Cherie L. Stabler, Minglin Ma, Yi Peng, Xunrong Luo, Qizhi Tang, Sabarinathan Ramachandran, José Oberholzer, Camillo Ricordi, Timothy J. Kieffer, A. M. James Shapiro

Bibliographic record

VenueDiabetes · 2025
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesDiabetes Research Institute Foundation
KeywordsDiabetes mellitusMedicineIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Islet cell replacement therapies have evolved as a viable treatment option for type 1 diabetes complicated by problematic hypoglycemia and glycemic lability. Refinements of islet manufacturing, islet transplantation procedures, peritransplant recipient management, and immunosuppressive protocols allowed most recipients to achieve favorable outcomes. Subsequent phase 3 trials of transplantation of deceased donor islets documented the effectiveness of transplanted islets in restoring near-normoglycemia, glycemic stability, and protection from severe hypoglycemia, with an acceptable safety profile for the enrolled high-risk population. Health authorities in several countries have approved deceased donor islet transplantation for treating patients with type 1 diabetes and recurrent severe hypoglycemia. These achievements amplified academic and industry efforts to generate pluripotent stem cell-derived β-cells through directed differentiation for β-cell replacement. Preliminary results of ongoing clinical trials suggest that the transplantation of stem cell-derived β-cells can consistently restore insulin independence in immunosuppressed recipients with type 1 diabetes, thus signaling the profound progress made in generating an unlimited and a uniform supply of cells for transplant. Avoiding the risks of chronic immunosuppression represents the next frontier. Several strategies have entered or are approaching clinical investigation, including immune-isolating islets, engineering immune-privileged islet implantation sites, rendering islets immune evasive, and inducing immune tolerance in transplanted islets. Capitalizing on high-dimensional, multiomic technologies for deep profiling of graft-directed immunity and the fate of the graft will provide new insights that promise to translate into sustaining functional graft survival long-term. Leveraging these parallel progression paths will facilitate the wider clinical adoption of cell replacement therapies in diabetes care. ARTICLE HIGHLIGHTS: Transplantation of deceased donor-derived primary human islets has restored near-normoglycemia and protection from severe hypoglycemia in immunosuppressed recipients with type 1 diabetes. Transplantation of embryonic stem cell-derived β-cells has restored insulin independence in immunosuppressed recipients with type 1 diabetes. Clinical trials are underway and planned to evaluate the safety and efficacy of transplantation of mature stem cell-derived β-cells with transient, local, minimal, and/or no-maintenance immunosuppression in recipients with type 1 diabetes. The high-dimensional, multiomic monitoring of immunity to transplanted islets and of the fate of the islet graft will faciliate the identification of determinants of sustained islet graft function and of patients most likely to benefit from cell replacement therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.319
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2025
Admission routes1
Has abstractyes

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