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Record W1496976895 · doi:10.1002/jbm.a.34648

Transient inhibition of connective tissue infiltration and collagen deposition into porous poly(lactic‐<i>co</i>‐glycolic acid) discs

2013· article· en· W1496976895 on OpenAlexafffund
Ryan J. Love, Kim S. Jones

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2013
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConnective tissueMaterials scienceIn vivoBiophysicsBiomedical engineeringCell biologyPathologyBiologyMedicine

Abstract

fetched live from OpenAlex

Connective tissue rapidly proliferates on and around biomaterials implanted in vivo, which impairs the function of the engineered tissues, biosensors, and devices. Glucocorticoids can be utilized to suppress tissue ingrowth, but can only be used for a limited time because they nonselectively arrest cell proliferation in the local environment. The present study examined use of a prolyl-4-hydroxylase inhibitor, 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (1,4-DPCA), to suppress connective tissue ingrowth in porous PLGA discs implanted in the peritoneal cavity for 28 days. The prolyl-4-hydroxylase inhibitor was found to be effective at inhibiting collagen deposition within and on the outer surface of the disc, and also limited connective tissue ingrowth, but not to the extent of glucocorticoid inhibition. Finally, it was discovered that 1,4-DPCA suppressed Scavenger Receptor A expression on a macrophage-like cell culture, which may account for the drug's ability to limit connective tissue ingrowth in vivo.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.019
GPT teacher head0.300
Teacher spread0.281 · 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

Citations7
Published2013
Admission routes2
Has abstractyes

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Same venueJournal of Biomedical Materials Research Part ASame topicBone Tissue Engineering MaterialsFrench-language works237,207