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Record W3183193106 · doi:10.1139/cjpp-2021-0006

The S1PR1 agonist SEW2871 promotes the survival of skin flap

2021· article· en· W3183193106 on OpenAlexvenueno aff
Dongdong Zhang, Dongxu Qi, Yi Xu, Chunhe Hu, Xiao Zhang, Qingjian Yang, Zikun Shang, Guisheng Zhang

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsnot available
Fundersnot available
KeywordsS1PR1Protein kinase BAngiogenesisAgonistMAPK/ERK pathwayKinaseSkin flapHsp27NeovascularizationReceptorCell biologyCancer researchMedicinePharmacologySignal transductionHeat shock proteinChemistryBiologyVascular endothelial growth factor ASurgeryInternal medicineVascular endothelial growth factorBiochemistryHsp70VEGF receptors

Abstract

fetched live from OpenAlex

Skin flap transfer is an important method to repair and reconstruct various tissue defects; however, avascular necrosis largely affects the success of flap transfer. The sphingosine 1-phosphate receptor 1 (S1PR1) agonist SEW2871 has been proven to ameliorate ischemic injury; however, its effect on flap survival has not been reported. In this study, an experimental skin flap model was established in rats to investigate the roles of SEW2871. The results indicated that SEW2871 greatly increased the survival of the skin flap, alleviated pathological injury, promoted the angiogenesis, and inhibited cells apoptosis in skin flap tissues. SEW2871 activated S1PR1 downstream signaling pathways, including heat shock protein 27 (HSP27), extracellular regulated protein kinases (ERK), and protein kinase B (Akt). In addition, SEW2871 promoted the expression of S1PR1. These findings may provide novel insights for skin flap transfer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicSphingolipid Metabolism and SignalingFrench-language works237,207