Does exercise pose a challenge to glucoregulation after clinical islet transplantation?
Bibliographic record
Abstract
Islet transplantation (ITx) is effective in preventing severe hypoglycemia by restoring glucose-dependent insulin secretion in type 1 diabetes (T1D), but may not normalize glucose regulation. Studies suggest that physical activity plays a role in maintaining β-cell mass and function in individuals with type 2 diabetes and animal models of diabetes. This could indicate that physical activity plays a role in graft survival in ITx recipients. This review's objective is to assess current knowledge related to physical activity in ITx recipients. Responses to other challenges in blood glucose control (i.e., hypoglycemia) in human ITx recipients were examined to provide in-depth background information. To identify studies involving exercise in ITx recipients, a systematic search was performed using PubMed, Medline, and Embase, which revealed 277 English language publications. Publications were excluded if they did not involve ITx recipients; did not involve physical activity or hypoglycemia; or did not report on glucose, insulin, or counterregulatory hormones. During induced hypoglycemia, studies indicate normal suppression of insulin in ITx individuals compared with healthy non-T1D controls. Studies involving exercise in ITx animals have conflicting results, with time since transplantation and transplantation site (spleen, liver, kidney, peritoneal cavity) as possible confounders. No study examining blood glucose responses to physical activity in human ITx recipients was identified. A small number of induced-hypoglycemia studies in humans, and exercise studies in animals, would suggest that glucoregulation is greatly improved yet is still imperfect in this population and that ITx does not fully restore counterregulatory responses to challenges in blood glucose homeostasis.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".