Preparation and characterization of a highly macroporous biodegradable composite tissue engineering scaffold
Bibliographic record
Abstract
A unique composite scaffold for bone-tissue engineering applications has been prepared by combining biodegradable poly(lactide-co-glycolide) (PLGA) with bioresorbable calcium phosphate (CaP) cement particles through the process of particle fusion and phase separation/particle leaching. The scaffold is characterized by a highly interconnected macroporosity, with macropores of 0.8-1.8 mm and porosities ranging from 81% to 91%, and improved mechanical properties with respect to the polymer alone, producing excellent dimensional stability. The scaffold properties were controlled by adjusting the processing parameters, including PLGA molar mass and concentration, CaP/PLGA ratio, and porogen size. The differences in mechanical properties between dry, wet/room temperature, and wet/37 degrees C testing conditions, of which the latter are more relevant for materials to be employed in a biological milieu, were investigated. Thus, a scaffold made from PLGA IV 1.13, PLGA concentration 12.5%, and CaP/PLGA ratio 2:1 exhibited significantly different compressive strengths of 0.16 MPa and 0.04 MPa when tested under dry and wet/37 degrees C conditions, respectively. .
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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 | 0.001 | 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".