Controlling the degradation kinetics of porous iron by poly(lactic-co-glycolic acid) infiltration for use as temporary medical implants
Bibliographic record
Abstract
Iron and its alloy have been proposed as biodegradable metals for temporary medical implants. However, the formation of iron oxide and iron phosphate on their surface slows down their degradation kinetics in both in vitro and in vivo scenarios. This work presents new approach to tailor degradation behavior of iron by incorporating biodegradable polymers into the metal. Porous pure iron (PPI) was vacuum infiltrated by poly(lactic-co-glycolic acid) (PLGA) to form fully dense PLGA-infiltrated porous iron (PIPI) and dip coated into the PLGA to form partially dense PLGA-coated porous iron (PCPI). Results showed that compressive strength and toughness of the PIPI and PCPI were higher compared to PPI. A strong interfacial interaction was developed between the PLGA layer and the iron surface. Degradation rate of PIPI and PCPI was higher than that of PPI due to the effect of PLGA hydrolysis. The fast degradation of PIPI did not affect the viability of human fibroblast cells. Finally, this work discusses a degradation mechanism for PIPI and the effect of PLGA incorporation in accelerating the degradation of iron.
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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) | 0.000 | 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".