A New Home for Pancreatic Islet Transplants: The Bone Marrow
Bibliographic record
Abstract
Transplantation of pancreatic islets represents a clinical therapeutic option to preserve and/or restore β-cell function in patients with diabetes (1,2). The source of the islets is the patient’s own pancreas (autologous, islet autotransplantation [IAT]) when the goal is preserving pancreatic endocrine function in pediatric and adult individuals undergoing total pancreatectomy due to pancreatitis (3,4) or trauma (5,6). Recently, IAT has been also proposed for enucleable benign (7) and malignant (8) pancreatic neoplasms. Transplantation of deceased-donor (allogeneic) islets is performed for patients with brittle type 1 diabetes and hypoglycemia unawareness as islet transplant alone (ITA) if nonuremic and as simultaneous islet–kidney (SIK) or sequential islet after kidney (IAK) transplantation procedures if uremic (end-stage renal disease) requiring kidney transplantation. Allogeneic islets can be part of cluster organ transplantation (Table 1). In recognition of the excellent metabolic control obtained after islet transplantation even when exogenous insulin treatment is required, reimbursement has been approved in several countries (e.g., Australia, Canada, France, Italy, Switzerland, U.K., Sweden, and the Nordic Network). In the U.S., only IAT is currently reimbursed, while biological licensure by the U.S. Food and Drug Administration should be imminent after recent completion of the Clinical Islet Transplant Consortium registration trials (www.citisletstudy.org). View this table: TABLE 1 Indications for islet cell transplantation Since the 1970s, islets have been embolized into the hepatic portal system by a minimally invasive technique consisting of transhepatic cannulation of the portal vein under ultrasound …
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.065 | 0.025 |
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".