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Record W4296251828 · doi:10.3390/ebj3030040

An Evaluation of the Treatment of Full-Thickness Wounds Using Adipose Micro-Fragments within a Liquid Dermal Scaffold

2022· article· en· W4296251828 on OpenAlexafffund
Sara Sheikh‐Oleslami, Ida Hassanpour, Nafise Amiri, Reza B. Jalili, Ruhangiz T. Kilani, Aziz Ghahary

Bibliographic record

VenueEuropean Burn Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScaffoldAdipose tissueProgenitor cellIn vivoBiomedical engineeringWound healingViability assayCell biologyAdipocyteTissue engineeringChemistryCellStem cellMedicineSurgeryBiologyBiotechnologyBiochemistry

Abstract

fetched live from OpenAlex

In full-thickness wounds, inflammation, lack of matrix deposition, and paucity of progenitor cells delay healing. As commercially available solid (sheet) scaffolds are unable to conform to wounds of varying shapes and sizes, we previously generated a nutritious, injectable, liquid skin substitute that can conform to wound topography. In combination with adipose micro-fragments as a viable source of progenitor cells, a composite, in situ forming skin substitute was tested for the treatment of silicon ring splinted full-thickness wounds in rats. The in vitro survivability and migratory capacity of adipocytes derived from rat micro-fragmented fat cultured in our scaffold was examined with a Live/Dead assay, showing viability and migration after 7 and 14 days. In vivo, the efficacy of our scaffold alone (LDS) or with adipose micro-fragments (LDS+A) was compared to a standard dressing protocol (NT). LDS and LDS+A showed ameliorated wound healing, including complete epithelialization and less immune cell infiltration, compared to the NT control. Our findings demonstrate that a 3D liquid skin scaffold is a rich environment for adipocyte viability and migration, and that the addition of adipose micro-fragments to this scaffold can be used as a rich source of cells for treating full-thickness wounds.

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)0.002
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 score0.654
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.066
GPT teacher head0.332
Teacher spread0.266 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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