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Harnessing the gut to treat diabetes

2004· review· en· W2032280075 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePediatric Diabetes · 2004
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of British Columbia
FundersCanadian Diabetes Association
KeywordsMedicineDiabetes mellitusIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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.

Opus teacher head0.032
GPT teacher head0.304
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it