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Record W2399723989 · doi:10.1038/srep18104

Mesenchymal stem cell-laden anti-inflammatory hydrogel enhances diabetic wound healing

2015· article· en· W2399723989 on OpenAlexafffund
Shixuan Chen, Junbin Shi, Min Zhang, Yinghua Chen, Xueer Wang, Lei Zhang, Zhihui Tian, Yuan Yan, Qinglin Li, Wen Zhong, Malcolm Xing, Lu Zhang, Lin Zhang

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersNational Institute on Alcohol Abuse and AlcoholismNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsMesenchymal stem cellWound healingGranulation tissueExtracellular matrixAngiogenesisInflammationIn vivoSelf-healing hydrogelsBone marrowMedicineCell therapyChemistryStem cellPathologyBiomedical engineeringCell biologySurgeryCancer researchImmunologyBiology

Abstract

fetched live from OpenAlex

The purpose of this study was to permit bone marrow mesenchymal stem cells (BMSCs) to reach their full potential in the treatment of chronic wounds. A biocompatible multifunctional crosslinker based temperature sensitive hydrogel was developed to deliver BMSCs, which improve the chronic inflammation microenvironments of wounds. A detailed in vitro investigation found that the hydrogel is suitable for BMSC encapsulation and can promote BMSC secretion of TGF-β1 and bFGF. In vivo, full-thickness skin defects were made on the backs of db/db mice to mimic diabetic ulcers. It was revealed that the hydrogel can inhibit pro-inflammatory M1 macrophage expression. After hydrogel association with BMSCs treated the wound, significantly greater wound contraction was observed in the hydrogel + BMSCs group. Histology and immunohistochemistry results confirmed that this treatment contributed to the rapid healing of diabetic skin wounds by promoting granulation tissue formation, angiogenesis, extracellular matrix secretion, wound contraction, and re-epithelialization. These results show that a hydrogel laden with BMSCs may be a promising therapeutic strategy for the management of diabetic ulcers.

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 score0.771
Threshold uncertainty score0.755

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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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

Citations188
Published2015
Admission routes2
Has abstractyes

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