Three‐yr follow‐up of a type 1 diabetes mellitus patient with an islet xenotransplant
Bibliographic record
Abstract
In order to alleviate the shortage of human donors, the use of porcine islets of Langerhans for xenotransplantation in diabetic patients has been proposed as a solution. To overcome rejection, we have developed a procedure for protecting the islets by combining them with Sertoli cells and placing them in a novel subcutaneous device, that generates an autologous collagen covering. A type 1 diabetic woman was closely monitored for 10 months, and then transplanted in two devices with two months of difference and a third time after 22 months. Here we present a three-yr follow-up. The close monitoring induced a rapid decrease in exogenous insulin requirements, which stabilized between 19 and 28 IU/d for nine months. After transplantation, the requirements reduced further to below 6 IU/d and for some weeks she was insulin free. Glycosylated hemoglobin levels decreased concomitantly. Porcine insulin could be detected in the serum after a glucose challenge and insulin positive cells inside a removed device after two yr. No complications have arisen and no porcine endogenous retrovirus infection has been detected through PCR and RT-PCR. This case demonstrates the feasibility of using the xenotransplantation of porcine cells to alleviate metabolic complications and insulin requirements in type 1 diabetic patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".