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Record W2137602698 · doi:10.1186/1475-2840-11-37

Vascular stem cells in diabetic complications: evidence for a role in the pathogenesis and the therapeutic promise

2012· review· en· W2137602698 on OpenAlexafffund
Emily C. Keats, Zia A. Khan

Bibliographic record

VenueCardiovascular Diabetology · 2012
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
FundersLawson Health Research InstituteCanadian Diabetes AssociationHeart and Stroke Foundation of Canada
KeywordsMedicineProgenitor cellPathogenesisStem cellDiabetes mellitusMesenchymal stem cellEndothelial stem cellHaematopoiesisImmunologyBioinformaticsPathologyEndocrinologyCell biologyBiology

Abstract

fetched live from OpenAlex

Long standing diabetes leads to structural and functional alterations in both the micro- and the macro-vasculature. Vascular endothelial cells (ECs) are the primary target of the hyperglycemia-induced adverse effects. Vascular stem cells that give rise to endothelial progenitor cells (EPCs) and mesenchymal progenitor cells (MPCs) represent an attractive target for cell therapy for diabetic patients. A number of studies have reported EPC dysfunction as a novel participant in the culmination of the diabetic complications. The controversy behind the identity of EPCs and the similarity between these progenitor cells to hematopoietic cells has led to conflicting results. MPCs, on the other hand, have not been examined for a potential role in the pathogenesis of the complications. These multipotent cells, however, do show a therapeutic role. In this article, we summarize the vascular changes that occur in diabetic complications highlighting some of the common features, the key findings that illustrate an important role of vascular stem cells (VSCs) in the pathogenesis of chronic diabetic complications, and provide mechanisms by which these cells can be used for therapy.

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)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.164
GPT teacher head0.365
Teacher spread0.201 · 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 designOther design
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

Citations32
Published2012
Admission routes2
Has abstractyes

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