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Record W4386857263 · doi:10.1186/s13287-023-03488-0

Paracrine signalling between keratinocytes and SVF cells results in a new secreted cytokine profile during wound closure

2023· article· en· W4386857263 on OpenAlexaff
Štefan Balkó, Evan Kerr, Edward W. Buchel, Sarvesh Logsetty, Afshin Raouf

Bibliographic record

VenueStem Cell Research & Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsStromal vascular fractionParacrine signallingWound healingMesenchymal stem cellCytokineCell biologyStem cellStromal cellAdipose tissueBiologyImmunologyMedicinePathologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Stromal vascular fraction (SVF) cells, and the adipose-derived mesenchymal stem cells they contain, have shown enhanced wound healing in vitro and in vivo, yet their clinical application has been limited. In this regard, understanding the mechanisms that govern SVF-enhanced wound healing would improve their application in the clinic. Here, we show that the SVF cells and keratinocytes engage in a paracrine crosstalk during wound closure, which results in a new cytokine profile that is distinct from the cytokines regularly secreted by either cell type on their own. We identify 11 cytokines, 5 of which are not regularly secreted by the SVF cells, whose expressions are significantly increased during wound closure by the keratinocytes. This new cytokine profile could be used to accelerate wound closure and initiate re-epithelialization without the need to obtain the SVF cells from the patient.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.125
GPT teacher head0.376
Teacher spread0.251 · 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 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

Citations12
Published2023
Admission routes1
Has abstractyes

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