3D-Printed ABS and PLA Scaffolds for Cartilage and Nucleus Pulposus Tissue Regeneration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Painful degeneration of soft tissues accounts for high socioeconomic costs. Tissue engineering aims to provide biomimetics recapitulating native tissues. Biocompatible thermoplastics for 3D printing can generate high-resolution structures resembling tissue extracellular matrix. Large-pore 3D-printed acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) scaffolds were compared for cell ingrowth, viability, and tissue generation. Primary articular chondrocytes and nucleus pulposus (NP) cells were cultured on ABS and PLA scaffolds for three weeks. Both cell types proliferated well, showed high viability, and produced ample amounts of proteoglycan and collagen type II on both scaffolds. NP generated more matrix than chondrocytes; however, no difference was observed between scaffold types. Mechanical testing revealed sustained scaffold stability. This study demonstrates that chondrocytes and NP cells can proliferate on both ABS and PLA scaffolds printed with a simplistic, inexpensive desktop 3D printer. Moreover, NP cells produced more proteoglycan than chondrocytes, irrespective of thermoplastic type, indicating that cells maintain individual phenotype over the three-week culture period. Future scaffold designs covering larger pore sizes and better mimicking native tissue structure combined with more flexible or resorbable materials may provide implantable constructs with the proper structure, function, and cellularity necessary for potential cartilage and disc tissue repair 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it