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Bone marrow‐derived stem cells in wound healing: a review

2007· review· en· W2074445743 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWound Repair and Regeneration · 2007
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProgenitor cellStem cellWound healingMesenchymal stem cellParacrine signallingBone marrowClinical uses of mesenchymal stem cellsStem cell transplantation for articular cartilage repairRegeneration (biology)MedicineCell biologyEndothelial stem cellImmunologyExtracellular matrixCancer researchAdult stem cellPathologyBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Optimum healing of a cutaneous wound requires a well-orchestrated integration of the complex biological and molecular events of cell migration and proliferation, and of extracellular matrix deposition and remodeling. Several studies in recent years suggest that bone marrow derived stem cells such as mesenchymal stem cells, progenitor cells such as endothelial progenitor cells and fibrocytes may be involved in these processes, contributing to skin cells or releasing regulatory cytokines. Stem/progenitor cells may be mobilized to leave the bone marrow, home to injured tissues and participate in the repair and regeneration. Direct injection of bone marrow derived mesenchymal stem cells or endothelial progenitor cells into injured tissues shows improved repair through mechanisms of differentiation and/or release of paracrine factors. Enhanced understanding of these cells may help develop novel therapies for difficult cutaneous conditions such as non-healing chronic wounds and hypertrophic scarring as well as engineering cutaneous substitutes.

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.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.102
GPT teacher head0.375
Teacher spread0.273 · 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