MétaCan
Menu
Back to cohort
Record W4386265229 · doi:10.1039/d3tb01417g

Designing polymers for cartilage uptake: effects of architecture and molar mass

2023· article· en· W4386265229 on OpenAlexafffund
Jue Gong, Jordan Nhan, Jean‐Philippe St‐Pierre, Elizabeth R. Gillies

Bibliographic record

VenueJournal of Materials Chemistry B · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of OttawaWestern University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationArthritis Society
KeywordsMolar massCartilagePolymerMolarMaterials scienceArchitectureBiomedical engineeringChemical engineeringComposite materialOrthodonticsEngineeringAnatomyMedicine

Abstract

fetched live from OpenAlex

-(3-aminopropyl)methacrylamide (APMA) with linear, 4-arm, or 8-arm structures and varying degrees of polymerization (DP) by reversible addition fragmentation chain-transfer (RAFT) polymerization. Uptake and retention of the polycations in bovine articular cartilage was assessed. While all polycations penetrated cartilage, uptake and retention generally increased with DP before decreasing for the highest DP. In addition, uptake and retention were higher for the linear polycations compared to the 4-arm and 8-arm polycations. In general, the polycations were well tolerated by bovine chondrocytes, but the highest DP polycations imparted greater cytotoxicity. Overall, this study reveals that linear polymer architectures may be more favorable for binding to the cartilage matrix and that the DP can be tuned to maximize uptake while minimizing cytotoxicity.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.238
Teacher spread0.230 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Materials Chemistry BSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207