MétaCan
Menu
Back to cohort
Record W2022397532 · doi:10.1007/s00018-012-1152-9

Cutaneous wound healing: recruiting developmental pathways for regeneration

2012· review· en· W2022397532 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCellular and Molecular Life Sciences · 2012
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsWound healingRegeneration (biology)Wnt signaling pathwaySkin repairHedgehogBiologySonic hedgehogMedicinePathologyCell biologySignal transductionImmunology

Abstract

fetched live from OpenAlex

Following a skin injury, the damaged tissue is repaired through the coordinated biological actions that constitute the cutaneous healing response. In mammals, repaired skin is not identical to intact uninjured skin, however, and this disparity may be caused by differences in the mechanisms that regulate postnatal cutaneous wound repair compared to embryonic skin development. Improving our understanding of the molecular pathways that are involved in these processes is essential to generate new therapies for wound healing complications. Here we focus on the roles of several key developmental signaling pathways (Wnt/β-catenin, TGF-β, Hedgehog, Notch) in mammalian cutaneous wound repair, and compare this to their function in skin development. We discuss the varying responses to cutaneous injury across the taxa, ranging from complete regeneration to scar tissue formation. Finally, we outline how research into the role of developmental pathways during skin repair has contributed to current wound therapies, and holds potential for the development of more effective treatments.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.160
GPT teacher head0.356
Teacher spread0.195 · 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