Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tilapia, a teleost fish species with large anatomically discrete islet organs (Brockmann bodies; BBs) that can be easily harvested without expensive and fickle islet isolation procedures, make an excellent donor species for experimental islet xenotransplantation research. When transplanted into streptozotocin-diabetic nude or severe combined immunodeficient mice, BBs provide long-term normoglycemia and mammalian-like glucose tolerance profiles. However, when transplanted into euthymic recipients, the mechanism of islet xenograft rejection appears very similar to that of islets from "large animal" donor species such as the very popular fetal/neonatal porcine islet cell clusters (ICCs). Tilapia islets are more versatile than ICCs and can be transplanted (1) into the renal subcapsular space, the cryptorchid or noncryptorchid testis, or intraportally as neovascularized cell transplants; (2) as directly vascularized organ transplants; or (3) intraperitoneally after microencapsulation. Unlike the popular porcine ICCs, BBs function immediately after transplantation; thus, their rejection can be assessed on the basis of loss of function as well as other parameters. We have also shown that transplantation of tilapia BBs into nude mice can be used to study the possible implications of cross-species physiological incompatibilities in xenotransplantation. Unfortunately, tilapia BBs might be unsuitable for clinical islet xenotransplantation because tilapia insulin differs from human insulin by 17 amino acids and, thus, would be immunogenic and less biologically active in humans. Therefore, we have produced transgenic tilapia that express a "humanized" tilapia insulin gene. Future improvements on these transgenic fish may allow tilapia to play an important role in clinical islet xenotransplantation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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