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Record W4412994432 · doi:10.1080/19382014.2026.2659457

Human and mouse regenerative macrophages enhance beta cell survival, function, and proliferation

2025· preprint· en· W4412994432 on OpenAlexafffund
Mahdis Monajemi, Alexandra S. Craciun, Qing Huang, Lei Dai, Majid Mojibian, Sarah Q. Crome, C. Bruce Verchere, Megan K. Levings

Bibliographic record

VenueIslets · 2025
Typepreprint
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsToronto General HospitalUniversity of TorontoBC Children's HospitalUniversity Health NetworkUniversity of British Columbia
FundersBreakthrough T1D CanadaCanadian Institutes of Health ResearchUniversity of AlbertaCanadian Blood ServicesBC Children's Hospital
KeywordsFunction (biology)Cell biologyBETA (programming language)Cell growthMacrophageBiologyComputer scienceIn vitroGenetics

Abstract

fetched live from OpenAlex

Abstract Aims/hypothesis Type 1 diabetes is an autoimmune disease caused by immune-mediated destruction of insulin-producing pancreatic beta cells. Interestingly, individuals with long-standing type 1 diabetes have residual beta cells, suggesting the existence of regenerative mechanisms that help maintain beta cell survival. Islet-resident macrophages have an important role in type 1 diabetes, and during disease progression can adopt a tissue-regenerating phenotype which may support beta cells. However, the specific roles of macrophages in beta cell survival, function, and proliferation remains poorly defined. This study aimed to elucidate how different macrophage subtypes influence beta cell survival, function, and proliferation. Methods Mouse and human islets were isolated from the pancreas and co-cultured in vitro with macrophages. To investigate whether macrophages enhance beta cell survival and function, beta cell apoptosis was measured using flow cytometry, and insulin secretion was assessed using a glucose-stimulated insulin secretion assay. We also examined whether macrophages further increased beta cell proliferation in the presence of harmine, a DYRK1A inhibitor. Finally, we evaluated the effect of islet co-culture on macrophage phenotype by flow cytometry and cytokine secretion analysis. Results We found that regenerative, but not pro-inflammatory, macrophages enhanced beta cell survival and function through mechanisms that did not require direct cell contact. Direct contact between macrophages and islets further promoted a regenerative phenotype in macrophages, characterized by increased CD206 expression and secretion of anti-inflammatory factors. Additionally, regenerative macrophages promoted beta cell proliferation in the presence of harmine. Conclusions Our findings demonstrate that regenerative macrophages support pancreatic beta cell survival, function, and proliferation. Harnessing the regenerative properties of macrophages could offer a novel strategy to promote beta cell survival and function, thereby improving outcomes for individuals with type 1 diabetes. Research in Context What is already known about this subject? Macrophages are the predominant resident immune cells within pancreatic islets in non-diabetic individuals; they contribute to tissue homeostasis and immune surveillance. Depending on their activation state, macrophages can exert either beneficial (pro-regenerative) or harmful (pro-inflammatory) effects on beta cell function. What is the key question? How do different macrophage subtypes regulate islet survival, regeneration, and function? What are the new findings? Co-culturing mouse or human islets with regenerative macrophages enhanced beta cell survival and function. When added in the presence of a DYRK1A inhibitor (harmine), they also promoted beta cell proliferation. Regenerative macrophage-derived factors promoted mouse islet function via a contact independent mechanism. Mouse islets enhanced the regenerative phenotype of macrophages. How might this impact on clinical practice in the foreseeable future? Leveraging the regenerative potential of macrophages represents a novel therapeutic approach to enhance beta cells, ultimately improving outcomes for individuals with type 1 diabetes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.284
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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