Novel, Blended Polymeric Microspheres for the Controlled Release of Methotrexate: Characterization and In Vivo Antifibrotic Studies
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".