Layer-by-layer paper-stacking nanofibrous membranes to deliver adipose-derived stem cells for bone regeneration
Bibliographic record
Abstract
Bone tissue engineering through seeding of stem cells in three-dimensional scaffolds has greatly improved bone regeneration technology, which historically has been a constant challenge. In this study, we researched the use of adipose-derived stem cell (ADSC)-laden layer-by-layer paper-stacking polycaprolactone/gelatin electrospinning nanofibrous membranes for bone regeneration. Using this novel paper-stacking method makes oxygen distribution, nutrition, and waste transportation work more efficiently. ADSCs can also secrete multiple growth factors required for osteogenesis. After the characterization of ADSC surface markers CD29, CD90, and CD49d using flow cytometry, we seeded ADSCs on the membranes and found cells differentiated, with significant expression of the osteogenic-related proteins osteopontin, osteocalcin, and osteoprotegerin. During 4 weeks in vitro, the ADSCs cultured on the paper-stacking membranes in the osteogenic medium exhibited the highest osteogenic-related gene expressions. In vivo, the paper-stacking scaffolds were implanted into the rat calvarial defects (5 mm diameter, one defect per parietal bone) for 12 weeks. Investigating with microcomputer tomography, the ADSC-laden paper-stacking membranes showed the most significant bone reconstruction, and from a morphological perspective, this group occupied 90% of the surface area of the defect, produced the highest bone regeneration volume, and showed the highest bone mineral density of 823.06 mg/cm(3). From hematoxylin and eosin and Masson staining, the new bone tissue was most evident in the ADSC-laden scaffold group. Using quantitative polymerase chain reaction analysis from collected tissues, we found that the ADSC-laden paper-stacking membrane group presented the highest osteogenic-related gene expressions of osteocalcin, osteopontin, osteoprotegerin, bone sialoprotein, runt-related transcription factor 2, and osterix (two to three times higher than the control group, and 1.5 times higher than the paper-stacking membrane group in all the genes). It is proposed that ADSC-laden layer-by-layer paper-stacking scaffolds could be used as a way of promoting bone defect treatment.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 teacher head, 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".