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Transplantation Models to Characterize the Mechanisms of Stem Cell–Induced Islet Regeneration

2013· article· en· W1523723900 on OpenAlexafffund
Gillian I. Bell, Ayesh K. Seneviratne, Grace N. Nasri, David A. Hess

Bibliographic record

VenueCurrent Protocols in Stem Cell Biology · 2013
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsBiologyRegeneration (biology)IsletStem cellTransplantationCell biologyImmunologyInternal medicineEndocrinologyInsulinMedicine

Abstract

fetched live from OpenAlex

This unit describes our current knowledge regarding the isolation human bone marrow-derived progenitor cells for the paracrine stimulation of islet regeneration after transplantation into immunodeficient mouse models of diabetes. By using high aldehyde dehydrogenase (ALDH(hi) ) activity, a conserved function in multiple stem cell lineages, a mixed population of hematopoietic, endothelial, and mesenchymal progenitor cells can be efficiently purified using flow cytometry. We describe in vitro approaches to characterize and expand these distinct cell types. Importantly, these cell types can be transplanted into immunodeficient mice rendered beta-cell deficient by streptozotocin (STZ) treatment, in order monitor functional recovery from hyperglycemia and to characterize endogenous islet regeneration via paracrine mechanisms. Herein, we provide detailed protocols for: (1) isolation and characterization of ALDH(hi) cells for the establishment of hematopoietic and multipotent-stromal progenitor lineages; (2) intravenous and intrapancreatic transplantation of human stem cell subtypes for the quantification of glycemic recovery in STZ-treated immunodeficient mice; and (3) immunohistochemical characterization of islet recovery via the stimulation of islet neogenic, beta-cell proliferative, and islet revascularization programs. Collectively, these systems can be used to support the pre-clinical development of human progenitor cell-based therapies to treat diabetes via islet regeneration.

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 score0.025
Threshold uncertainty score0.439

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 head0.089
GPT teacher head0.311
Teacher spread0.222 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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