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Record W2025146633 · doi:10.1097/mot.0b013e32834254f1

Stem cells of the skin and cornea: their clinical applications in regenerative medicine

2010· review· en· W2025146633 on OpenAlexafffund
Stéphanie Proulx, Julie Fradette, Robert Gauvin, Danielle Larouche, Lucie Germain

Bibliographic record

VenueCurrent Opinion in Organ Transplantation · 2010
Typereview
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsStem cellCorneaRegenerative medicineTissue engineeringCorneal epitheliumMedicineTransplantationStromaCorneal DiseasesPathologySurgeryBiologyOphthalmologyCell biologyBiomedical engineering

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The use of stem cells is of great interest for the treatment of various pathologies and ultimately for the restoration of organ function. Progress pointing towards future treatments of skin and corneal epithelial stem cell defects are reviewed, including the transplantation of living tissue-engineered substitutes. RECENT FINDINGS: This article focuses on substitutes optimized for permanent replacement of skin and cornea. New skin substitutes for burn care are currently under development. More complex tissue-engineered skin substitutes in which stroma, adipose tissue, capillaries, and neurons are combined with the epithelium are being developed. Some dermal/epidermal substitutes have been applied to the treatment of patients. Cultured corneal epithelial cells have been characterized and more complete corneal substitutes are being designed. Long-term clinical results on the transplantation of cultured corneal stem cells for the treatment of limbal stem cell deficiency have been reported. SUMMARY: Advances in tissue engineering for the development of substitutes that will benefit patients suffering from skin or corneal stem cell deficiencies are reviewed. These products are often a combination of cells, scaffolds and other factors. Key considerations in the development of corneal and skin substitutes for clinical applications are discussed.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.146
GPT teacher head0.422
Teacher spread0.276 · 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 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

Citations11
Published2010
Admission routes2
Has abstractyes

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