Subcutaneous Pig Islet Xenografts: Getting Under Your Skin to Cure Diabetes?
Bibliographic record
Abstract
There is a growing body of evidence from non-human primate (NHP) studies to suggest that it will soon be possible to cure diabetes in humans by transplantation of pig islets. Although pig-to-NHP models based on the Edmonton protocol have provided the most compelling data (1, 2), they also share its drawbacks: significant early loss of functional islet mass after infusion into the liver and the requirement for long-term immunosuppression to maintain graft function. It is clear that further advances will depend on reducing the immunosuppressive burden on the recipient, by providing greater protection to islet xenografts from innate and adaptive immunity. The three main approaches to this problem have been genetic modification of the donor pig, investigation of alternative transplant sites, and encapsulation. Proponents of encapsulation argue that coating islets with alginate-based polymers can immunoprotect xenografts to the extent that immunosuppression may no longer be necessary. This is supported by a number of rodent studies showing that microencapsulation promotes at least a prolongation of pig islet xenograft survival in untreated recipients (e.g., Ref. 3). Unfortunately, with the possible exception of a 1996 study (4) that is yet to be replicated, there has been no convincing demonstration that encapsulated pig islets reverse hyperglycemia in diabetic NHPs for longer than a few days or weeks. However, this may be about to change, with a report in this issue describing a promising new technique (5). The standard procedure for encapsulation and transplantation of pig islets is to incorporate them into microcapsules, which are then injected into the peritoneal cavity. Dufrane et al. (5) made two significant changes: first, they seeded the islets into monolayer cellular devices (MCDs) comprising an acellular human collagen matrix enclosed within alginate (Fig. 1), and second, they transplanted the MCDs under the skin of the abdomen. The results were striking. Diabetes was corrected in five monkeys for 17 to 31 weeks in the absence of immunosuppression. Two recipients retransplanted after the failure of their first grafts became normoglycemic for a further 14 to 19 weeks. Despite a strong anti-pig humoral response, there was no evidence for passage of antibodies across the alginate layer.FIGURE 1.: The monolayer cellular device (MCD) allows passage of nutrients including glucose and blocks passage of immune cells and antibodies. Entry of smaller molecules such as cytokines and reactive oxygen species (ROS) may not be prevented.Apart from the demonstrated efficacy of the MCDs, there are considerable advantages associated with the subcutaneous transplant site, including the relative ease and noninvasiveness of the procedure and the ability to completely remove the graft should problems arise. Balancing these are practical questions related to how well the method will translate to the clinical setting. For example, how large will the MCDs need to be to correct diabetes in human recipients? Will they be susceptible to accidental breakage because of their position under the skin? Further development of the MCD method will require an understanding of the cause(s) of graft failure. This is an important question that the authors failed to adequately address, noting only that devices removed after graft dysfunction showed no signs of structural degradation. Possible mechanisms include beta cell “exhaustion” or hypoxic death, absence of appropriate environmental cues in the subcutaneous site, or the action of small molecules such as cytokines and reactive oxygen species released by immune cells and capable of crossing the alginate barrier (Fig. 1). An immune component seems likely because second grafts failed 9 to 10 weeks faster than first grafts. How might these problems be overcome? Genetic manipulation is one option. Islets could be protected from hypoxia and oxidative stress by overexpression of antioxidant enzymes (6), and deletion of Gal may reduce graft immunogenicity and, thus, blunt the immune response. Engineering of the graft to secrete immunomodulatory proteins such as CTLA4-Ig (“local” immunosuppression) is another approach well suited to islets but not applicable here because these molecules would be unable to escape the MCD because of their size. It seems likely that at least some level of systemic immunosuppression will still be required, even if it is relatively benign. Nevertheless, the idea of an easily replaceable device that provides long-lasting glycemic control with minimal immunosuppression is an attractive one.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".