Bibliographic record
Abstract
Various stem cell sources are being explored to treat diabetes since the proof-of-concept for cell therapy was laid down by transplanting cadaveric islets as a part of Edmonton protocol in 2000. Human embryonic stem (hES) cells derived pancreatic progenitors have got US-FDA approval to be used in clinical trials to treat type 1 diabetes mellitus (T1DM). However, these progenitors more closely resemble their foetal counterparts and thus whether they will provide long-term regeneration of adult human pancreas remains to be demonstrated. In addition to lifestyle changes and administration of insulin sensitizers, regeneration of islets from endogenous pancreatic stem cells may benefit T2DM patients. The true identity of pancreatic stem cells, whether these exist or not, whether regeneration involves reduplication of existing islets or ductal epithelial cells transdifferentiate, remains a highly controversial area. We have recently demonstrated that a novel population of very small embryonic-like stem cells (VSELs) is involved during regeneration of adult mouse pancreas after partial-pancreatectomy. VSELs (pluripotent stem cells in adult organs) should be appreciated as an alternative for regenerative medicine as these are autologous (thus immune rejection issues do not exist) with no associated risk of teratoma formation. T2DM is a result of VSELs dysfunction with age and uncontrolled proliferation of VSELs possibly results in pancreatic cancer. Extensive brainstorming and financial support are required to exploit the potential of endogenous VSELs to regenerate the pancreas in a patient with diabetes.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".