Porous polylactide/chitosan scaffolds for tissue engineering
Bibliographic record
Abstract
Novel porous scaffolds were fabricated using biodegradable polylactide/chitosan blends. A combinational technique involving solvent-extracting, liquid-solid separation, and freeze-drying paths were employed. The processing parameters were optimized in order to produce desired porous scaffolds and thus obtained scaffolds showed well distributed and interconnected porous structures with controllable porosities varying from around 50-85% and regulative pore sizes being distributed within a region between 2 and 190 microm. These scaffolds exhibited remarkably improved hydrophilicity based on the measurements for their swelling index. The results obtained from in vitro incubation of scaffolds in phosphate buffered saline solutions at 37 degrees C during various periods up to 10 weeks indicated that chitosan component inside the scaffolds, on the one hand, effectively buffered the acidic degradation products of polylactide/chitosan scaffolds and on the other hand, the degradation of the scaffolds was also conspicuously delayed. These porous scaffolds maintained well-defined compressive mechanical properties and by well-blending polylactide with chitosan component, improved toughness on the resultant porous scaffolds was also observed.
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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 | 0.001 |
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".