Harnessing the gut to treat diabetes
Bibliographic record
Abstract
The gut contains one of the largest stem cell populations in the body, yet has been largely overlooked as a source of potentially therapeutic cells. The stem cells reside in the crypts located at the base of the protruding villi, reproduce themselves, and repopulate the gut lining as differentiated cells are sloughed off into the lumen. Some studies have demonstrated that gut stem cells can be isolated and maintained in culture, but the field is currently hampered by the lack of clear markers for these cells. Nevertheless, the relative accessibility of the cells and the similar pathways of differentiation of both intestinal and pancreatic endocrine cells make the gut an attractive potential source of cells to treat diabetes. In particular, it may be possible to recapitulate islet development by the introduction of specific factors to gut stem cells. Alternatively, gut endocrine cells might be coaxed to produce insulin and secrete it into the blood in a meal-responsive manner. Several investigations support the feasibility of both approaches as novel potential therapies for diabetes. Utilizing a patient's own gut cells to re-establish endogenous meal-regulated insulin secretion could represent an attractive approach to ultimately cure 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".