Evidence that tilapia islets do not express α‐(1,3)gal: implications for islet xenotransplantation
Bibliographic record
Abstract
BACKGROUND: Cell therapy for diabetes using teleost fish islet tissue has emerged as an intriguing alternative to the use of islet tissue from mammalian pancreases. The islet tissue, called Brockman bodies (BBs), is anatomically distinct from the pancreatic exocrine tissue and can be easily identified and isolated. Islets harvested from Nile tilapia (Oreochromis niloticus), when transplanted into streptozotocin-diabetic nude mice, produce long-term normoglycemia and achieve mammalian-like glucose tolerance profiles. We asked whether tilapia express the alpha-(1,3)gal epitope, the immunodominant target of human xenogeneic responses. METHODS AND RESULTS: Immunostaining with the alpha-(1,3)gal-specific IB4 lectin on tilapia BB, liver, heart, spleen, and head kidney was negative, as was staining with murine anti-alpha-gal-specific monoclonal antibodies. Absence of alpha-gal-specific binding of IB4 or murine anti-gal mAbs to dispersed BBs was confirmed by fluorescent-activated cell sorter analysis. Tilapia BB cell membranes failed to reduce binding of anti-alpha-(1,3)gal-specific mAb in an enzyme-linked immunosorbent assay (ELISA) inhibition assay, while porcine and murine tissue lysates did. Tilapia BB cell lysates were shown to be devoid of alpha-1,3 galactosyltransferase activity by ELISA. Transplantation of tilapia BBs into diabetic alpha-gal knockout (gal KO) mice was not associated with accelerated xenograft rejection when compared with wild type control recipients (mean survival time 6.5 days vs. 7.2 days). Tilapia BBs failed to induce a rise in anti-gal IgG and IgM titers in gal KO mice, while the transplant of wild type mouse islets into gal KO mice caused a significant rise in anti-gal IgG and IgM antibodies. CONCLUSIONS: We conclude that tilapia BBs are devoid of alpha-gal expression, and may offer an alternative to swine as a donor species for islet xenotransplantation.
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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) | 0.003 | 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; 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".