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Influence of papain urea copper chlorophyllin on wound matrix remodeling

2007· article· en· W2026780325 on OpenAlexfundno aff
Dale Telgenhoff, Kan Lam, Sarah Ramsay, V. Vasquez, Kristine Villareal, Paul Slusarewicz, Paul Attar, Braham Shroot

Bibliographic record

VenueWound Repair and Regeneration · 2007
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsnot available
FundersAir Force Research LaboratoryUniversity of Calgary
KeywordsDermisPapainEpidermis (zoology)ChlorophyllinChemistryWound healingUreaAnatomyBiochemistryBiologyImmunologyEnzyme

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the dermal and epidermal alterations associated with wound healing in wounds treated with papain urea copper chlorophyllin (PUC), papain-urea, copper chlorophyllin, or urea base ointment and compare these with moist wound care using a porcine full-thickness infected wound model. All the wounds were evaluated postsurgery for erythema, transepidermal water loss, microscopic morphology, and changes in protein expression. Examination of stained paraffin sections revealed an increase in the number of keratinocytes present in the epidermis of the PUC and papain-treated pigs, relative to moist control. This increase in keratinocyte number corresponded to an increase in the movement of the keratinocytes into the underlying dermis in the form of rete pegs. In the dermis, there appeared to be an increase in blood vessel formation, collagen I deposition, and mature collagen in the papain and PUC treated tissues. The quality of healing appears to be enhanced based on the number of keratinocytes present in the epidermis, the extensive rete peg formation, the increase in vasculature, and the increase in collagen birefringence.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.299
Teacher spread0.284 · 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

Citations28
Published2007
Admission routes1
Has abstractyes

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