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Record W2593391971 · doi:10.2337/db16-1068

Cotransplantation of Mesenchymal Stem Cells With Neonatal Porcine Islets Improve Graft Function in Diabetic Mice

2017· article· en· W2593391971 on OpenAlexafffund
Julie A. Hayward, Cara E. Ellis, Karen Seeberger, Timothy Lee, Bassem Salama, Aillette Mulet‐Sierra, Purushothaman Kuppan, Adetola B. Adesida, Gregory S. Korbutt

Bibliographic record

VenueDiabetes · 2017
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchStem Cell Network
KeywordsMesenchymal stem cellIsletInsulinBone marrowMedicineTransplantationStem cellDiabetes mellitusImmune systemInternal medicineEndocrinologyImmunologyBiologyPathologyCell biology

Abstract

fetched live from OpenAlex

Mesenchymal stem cells (MSCs) possess immunoregulatory, anti-inflammatory, and proangiogenic properties and, therefore, have the potential to improve islet engraftment and survival. We assessed the effect human bone marrow–derived MSCs have on neonatal porcine islets (NPIs) in vitro and determined islet engraftment and metabolic outcomes when cotransplanted in a mouse model. NPIs cocultured with MSCs had greater cellular insulin content and increased glucose-stimulated insulin secretion. NPIs were cotransplanted with or without MSCs in diabetic B6.129S7-Rag1tm1Mom/J mice. Blood glucose and weight were monitored until reversal of diabetes; mice were then given an oral glucose tolerance test. Islet grafts were assessed for the degree of vascularization and total cellular insulin content. Cotransplantation of NPIs and MSCs resulted in significantly earlier normoglycemia and vascularization, improved glucose tolerance, and increased insulin content. One experiment conducted with MSCs from a donor with an autoimmune disorder had no positive effects on transplant outcomes. Cotransplantation of human MSCs with NPIs demonstrated a beneficial metabolic effect likely as a result of earlier islet vascularization and improved islet engraftment. In addition, donor pathology of MSCs can influence the functional capacity of MSCs.

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 score0.166
Threshold uncertainty score0.597

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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

Citations45
Published2017
Admission routes2
Has abstractyes

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