MétaCan
Menu
Back to cohort
Record W2921438307 · doi:10.1111/iwj.13093

Surfactants: Role in biofilm management and cellular behaviour

2019· article· en· W2921438307 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

VenueInternational Wound Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsUniversity of Toronto
FundersMedline Industries
KeywordsBiofilmWound healingPoloxamerWound careMedicineMatrix metalloproteinaseIntensive care medicineBacteriaChemistrySurgeryBiology

Abstract

fetched live from OpenAlex

Appropriate and effective wound cleaning represents an important process that is necessary for preparing the wound for improved wound healing and for helping to dislodge biofilms. Wound cleaning is of paramount importance to wound bed preparation for helping to enhance wound healing. Surfactant applications in wound care may represent an important area in the cleaning continuum. However, understanding of the role and significance of surfactants in wound cleansing, biofilm prevention and control, and enhancing cellular viability and proliferation is currently lacking. Despite this, some recent evidence on poloxamer-based surfactants where the surfactants are present in high concentration have been shown to have an important role to play in biofilm management; matrix metalloproteinase modulation; reducing inflammation; and enhancing cellular proliferation, behaviour, and viability. Consequently, this review aims to discuss the role, mode of action, and clinical significance of the use of medically accepted surfactants, with a focus on concentrated poloxamer-based surfactants, to wound healing but, more specifically, the role they may play in biofilm management and effects on cellular repair.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.275
Teacher spread0.264 · 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