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Record W1880461483 · doi:10.1139/o11-054

Roles of lactoferrin on skin wound healing<sup>1</sup>This article is part of Special Issue entitled Lactoferrin and has undergone the Journal's usual peer review process.

2012· review· en· W1880461483 on OpenAlexvenueno aff
Yoshiharu Takayama, Reiji Aoki

Bibliographic record

VenueBiochemistry and Cell Biology · 2012
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
Fundersnot available
KeywordsLactoferrinWound healingGranulation tissueInflammationFibroblastExtracellular matrixCell biologyImmune systemChemistryImmunologyIn vitroBiologyBiochemistry

Abstract

fetched live from OpenAlex

Skin wound healing is a complex biological process that requires the regulation of different cell types, including immune cells, keratinocytes, fibroblasts, and endothelial cells. It consists of 5 stages: hemostasis, inflammation, granulation tissue formation, re-epithelialization, and wound remodeling. While inflammation is essential for successful wound healing, prolonged or excess inflammation can result in nonhealing chronic wounds. Lactoferrin, an iron-binding glycoprotein secreted from glandular epithelial cells into body fluids, promotes skin wound healing by enhancing the initial inflammatory phase. Lactoferrin also exhibits anti-inflammatory activity that neutralizes overabundant immune response. Accumulating evidence suggests that lactoferrin directly promotes both the formation of granulation tissue and re-epithelialization. Lactoferrin stimulates the proliferation and migration of fibroblasts and keratinocytes and enhances the synthesis of extracellular matrix components, such as collagen and hyaluronan. In an in vitro model of wound contraction, lactoferrin promoted fibroblast-mediated collagen gel contraction. These observations indicate that lactoferrin supports multiple biological processes involved in wound healing.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.788
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.346
Teacher spread0.287 · 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 designNot applicable
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

Citations88
Published2012
Admission routes1
Has abstractyes

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