Encapsulation of factor IX–engineered mesenchymal stem cells in fibrinogen–alginate microcapsules enhances their viability and transgene secretion
Bibliographic record
Abstract
Cell microencapsulation holds significant promise as a strategy for cellular therapies; however, inadequate survival and functionality of the enclosed cells limit its application in hemophilia treatment. Here, we evaluated the use of alginate-based microcapsules to enhance the viability and transgene secretion of human cord blood-derived mesenchymal stem cells in three-dimensional cultures. Given the positive effects of extracellular matrix molecules on mesenchymal stem cell growth, we tested whether fibrinogen-supplemented alginate microcapsules can improve the efficiency of encapsulated factor IX-engineered mesenchymal stem cells as a treatment of hemophilia B. We found that fibrinogen-supplemented alginate microcapsules (a) significantly enhanced the viability and proliferation of factor IX-engineered mesenchymal stem cells and (b) increased factor IX secretion by mesenchymal stem cells compared to mesenchymal stem cells in nonsupplemented microcapsules. Moreover, we observed the osteogenic, but not chondrogenic or adipogenic, differentiation capability of factor IX-engineered cord blood mesenchymal stem cells and their efficient factor IX secretion while encapsulated in fibrinogen-supplemented alginate microcapsules. Thus, the use of engineered mesenchymal stem cells encapsulated in fibrinogen-modified microcapsules may have potential application in the treatment of hemophilia or other protein deficiency diseases.
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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".