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Record W1877883307 · doi:10.1039/c5tb01308a

Surfaces having dual affinity for plasminogen and tissue plasminogen activator: in situ plasmin generation and clot lysis

2015· article· en· W1877883307 on OpenAlexaff
Qi Liu, Dan Li, Wenjun Zhan, Yafei Luan, Hui Du, Xiaoli Liu, John L. Brash, Hong Chen

Bibliographic record

VenueJournal of Materials Chemistry B · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPlasminIn situLysisTissue plasminogen activatorPlasminogen activatorMaterials scienceFibrinolysisChemistryBiochemistryMedicineEnzymeInternal medicine

Abstract

fetched live from OpenAlex

) (for Plg), were attached in sequence via covalent bonding and host-guest interactions, respectively. The resulting surfaces were shown to have high binding capacities for both t-PA and Plg while resisting nonspecific protein adsorption. Pre-loading with t-PA followed by Plg uptake from plasma generated plasmin and thus endowed the surface with fibrinolytic activity. In general the incorporation of dual affinity ligands to achieve surface-promoted bioactivity is a promising approach for the development of biofunctional materials. The method reported herein for the sequential attachment of plasminogen and t-PA affinity ligands can be extended to systems of multiple ligands generally.

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 score0.002
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.048
GPT teacher head0.295
Teacher spread0.248 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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