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Triple Encapsulation and Controlled Release of Vancomycin, Rifampicin and Silver from Poly (Methyl Methacrylate) or Poly (Lactic-Co-Glycolic Acid) Nanofibers

2024· article· en· W4398252651 on OpenAlex
John K. Jackson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioengineering · 2024
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPLGANanofiberMethyl methacrylateGlycolic acidDrug deliveryVancomycinControlled releaseMaterials scienceLactic acidPolymerBacteriaNanotechnologyPolymerizationStaphylococcus aureusNanoparticleComposite material

Abstract

fetched live from OpenAlex

Although the incidence of infections in orthopedic surgeries, including periprosthetic surgeries, remains low at approximately 1–2%, the number of surgeries and the incidence of drug-resistant bacteria is increasing. The cost and morbidity associated with revision surgeries are huge. More effective drug combinations and delivery methods are urgently needed. In this paper, three anti-infective drugs (vancomycin, rifampicin, and silver sulfadiazine) have been jointly and effectively electrospun in thin (0.1 mm) flexible nanofiber mats of either poly (methyl methacrylate) (PMMA) or poly (lactic-co-glycolic acid) (PLGA). The inclusion of poly (ethylene glycol) (PEG) enabled optimal drug release with a reduced water contact angle for wetting. The controlled release of these three agents from 20% PEG (w/w to polymer)-blended PMMA or PLGA nanofiber mats may allow for the prophylactical prevention of implant-related infections or provide methods to treat orthopedic infections at the time of revision surgeries. These combinations of drugs provide excellent additive or synergistic antibiotic action against a broader spectrum of bacteria than each drug alone.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.564

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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