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Novel, Blended Polymeric Microspheres for the Controlled Release of Methotrexate: Characterization and In Vivo Antifibrotic Studies

2023· article· en· W4322500073 on OpenAlexafffund
Layla Nabai, Aziz Ghahary, John K. Jackson

Bibliographic record

VenueBioengineering · 2023
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British ColumbiaSpinal Cord Injury BC
FundersFaculty of Pharmaceutical Sciences, University of British ColumbiaCanadian Institutes of Health Research
KeywordsIn vivoPLGACopolymerControlled releaseMaterials scienceLactic acidIn vitroDrug deliveryChemistryBiomedical engineeringBiophysicsNanotechnologyPolymerBiochemistry

Abstract

fetched live from OpenAlex

Low dose methotrexate (MTX) is known to effectively decrease type I collagen production in dermal fibroblasts, while increasing the matrix metalloproteinase-1 (MMP-1) production in vitro. For in vivo use as an antifibrotic agent on wounds, a linear and extended controlled release formulation of MTX is required. The objective of this study was to optimize the fabrication of MTX-loaded polymeric microspheres with such properties, and to test the efficacy for the prevention of fibrosis in vivo. Poly lactic-co-glycolic acid (PLGA), Poly (L-lactic acid) (PLLA) and the diblock copolymer, methoxypolyethylene glycol-block-poly (D, L-lactide) (MePEG-b-PDLLA), were used to fabricate microspheres, which were then characterized in terms of size, drug encapsulation efficiency, and in vitro release profiles. The optimized formulation (PLGA with diblock copolymer) showed high drug encapsulation efficiency (>80%), low burst release (~10%) and a gradual release of MTX. The amphipathic diblock copolymer is known to render the microsphere surface more biocompatible. In vivo, these microspheres were effective in reducing fibrotic tissue which was confirmed by quantitative measurement of type I collagen and α-smooth muscle actin expression, demonstrating that MTX can be efficiently encapsulated in PLGA microspheres to provide a delayed, gradual release in wound beds to reduce fibrosis 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)0.0010.000

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 head0.039
GPT teacher head0.315
Teacher spread0.276 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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