MétaCan
Menu
Back to cohort
Record W3033497266 · doi:10.1002/star.201900254

Synthesis and Evaluation of Chitosan‐Heparin‐Minocycline Composite Membranes for Potential Antibacterial Applications

2020· article· en· W3033497266 on OpenAlexaff
Linfeng Wu, Lu Xiao, Brian R Morrow, Feng Li, Liang Hong

Bibliographic record

VenueStarch - Stärke · 2020
Typearticle
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMinocyclineMembraneChitosanChemistryMaterials scienceBiofilmNuclear chemistryBiochemistryBiologyBacteriaAntibiotics

Abstract

fetched live from OpenAlex

Abstract In this study, novel antibacterial composite membranes, namely Chitosan‐Heparin‐Minocycline composite membranes, are prepared from chitosan, heparin, minocycline, and CaCl 2 via ion pairing and complexation. These membranes are characterized using Fourier‐transform infrared spectroscopy, scanning electron microscopy, and energy‐dispersive X‐ray spectroscopy. Release kinetics of minocycline from these membranes is evaluated in vitro. Their antibacterial activities are assessed using agar disk diffusion and biofilm assays in vitro. The chemical and physical characterization confirms the successful synthesis of composite membranes. The two types of minocycline‐containing membranes achieve sustained release of minocycline for 17 days and 4 weeks in simulated body fluid, respectively. They demonstrate sustained potent antimicrobial effects against Staphylococcus aureus and Aggregatibacter actinomycetemcomitans in agar disk diffusion assays. Biofilm assays reveal that both minocycline‐containing composite membranes significantly reduce viability of Aggregatibacter actinomycetemcomitans in 7‐day biofilms. These results suggest that these minocycline‐containing composite membranes can be exploited for antibacterial applications in medicine and dentistry.

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)0.000
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 score0.012
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

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 head0.035
GPT teacher head0.299
Teacher spread0.263 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueStarch - StärkeSame topicAntimicrobial agents and applicationsFrench-language works237,207