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Record W2101219849 · doi:10.1096/fj.12-209627

Pharmacological blockade of adenosine A <sub>2A</sub> receptors diminishes scarring

2012· article· en· W2101219849 on OpenAlexaff
Miguel Pérez‐Aso, Luis Chiriboga, Bruce N. Cronstein

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsYork University
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Cancer InstituteNational Institutes of Health
KeywordsScarsFibrosisBlockadeAdenosine A2A receptorAdenosineMyofibroblastWound healingMedicineAdenosine receptorReceptorChemistryInternal medicinePathologyImmunologyAgonist

Abstract

fetched live from OpenAlex

Adenosine A2A receptor (A2AR) stimulation promotes wound healing and is required for the development of fibrosis in murine models of scleroderma and cirrhosis. Nonetheless, the role of A2AR in the formation of scars following skin trauma has not been explored. Here, we examined the effect of pharmacological blockade of A2AR, with the selective adenosine A2AR-antagonist ZM241385 (2.5 mg/ml), in a murine model of scarring that mimics human scarring. We found that application of the selective adenosine A2AR antagonist ZM241385 decreased scar size and enhanced the tensile strength of the scar. Within the scar itself, collagen alignment and composition (marked reduction in collagen 3), but not periostin, biglycan, or fibronectin accumulation, was improved by application of ZM241385. Moreover, A2AR blockade reduced the number of myofibroblasts and angiogenesis but not macrophage infiltration in the scar. Taken together, our work strongly suggests that pharmacological A2AR blockade can be used to diminish scarring while improving the collagen composition and tensile strength of the healed wound.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.045
GPT teacher head0.327
Teacher spread0.282 · 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

Citations44
Published2012
Admission routes1
Has abstractyes

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