Encapsulation of Recombinant Cells with a Novel Magnetized Alginate for Magnetic Resonance Imaging
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Bibliographic record
Abstract
Implanting recombinant cells encapsulated in alginate microcapsules to express therapeutic proteins has been proven effective in treating several mouse models of human diseases (neurological disorders, dwarfism, hemophilia, lysosomal storage disease, and cancer). In anticipation of clinical application, we have reported the synthesis and characterization of a magnetized ferrofluid alginate that potentially allows tracking of these microcapsules in vivo by magnetic resonance imaging (MRI). We now report the properties of these ferrofluid microcapsules important for applications in gene therapy. When a mouse myoblast cell line was encapsulated in these microcapsules, it showed similar viability as in regular unmodified alginate capsules, both in vitro and in vivo, in mice. The permeability of these magnetized microcapsules, a critical parameter for immunoisolation devices, was comparable to that of classic alginate in the transit of various recombinant molecules of various molecular masses (human factor IX, 65 kDa; murine IgG, 150 kDa; and beta-glucuronidase, 300 kDa). When followed by MRI in vitro and in vivo, the ferrofluid microcapsules remained intact and visible for extended periods, allowing quantitative monitoring of microcapsules. At autopsy, the ferrofluid microcapsules were mostly free within the intraperitoneal cavities, with no overt inflammatory response. Serological analyses demonstrated a high level of biocompatibility comparable to that of unmodified alginate. In conclusion, ferrofluid-enhanced alginate microcapsules are comparable to classic alginate microcapsules in permeability and biocompatibility. Their visibility and stability to MRI monitoring permitted qualitative and quantitative tracking of the implanted microcapsules without invasive surgery. These properties are important advantages for the application of immunoisolation devices in human gene therapy.
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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