MétaCan
Menu
Back to cohort
Record W6889144964 · doi:10.25417/uic.22730516

The future treatment for type 1 diabetes: Pig islet- or stem cell-derived β cells?

2023· article· en· W6889144964 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Illinois Chicago · 2023
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsXenotransplantationAllotransplantationInduced pluripotent stem cellIsletStem cellTransplantationEconomic shortageType 1 diabetes

Abstract

fetched live from OpenAlex

Replacement of β cells is only a curative approach for type 1 diabetes (T1D) patients to avoid the threat of iatrogenic hypoglycemia. In this pursuit, islet allotransplantation under Edmonton's protocol emerged as a medical miracle to attain hypoglycemia-free insulin independence in T1D. Shortage of allo-islet donors and post-transplantation (post-tx) islet loss are still unmet hurdles for the widespread application of this therapeutic regimen. The long-term survival and effective insulin independence in preclinical studies have strongly suggested pig islets to cure overt hyperglycemia. Importantly, CRISPR-Cas9 technology is pursuing to develop "humanized" pig islets that could overcome the lifelong immunosuppression drug regimen. Lately, induced pluripotent stem cell (iPSC)-derived β cell approaches are also gaining momentum and may hold promise to yield a significant supply of insulin-producing cells. Theoretically, personalized β cells derived from a patient's iPSCs is one exciting approach, but β cell-specific immunity in T1D recipients would still be a challenge. In this context, encapsulation studies on both pig islet as well as iPSC-β cells were found promising and rendered long-term survival in mice. Oxygen tension and blood vessel growth within the capsules are a few of the hurdles that need to be addressed. In conclusion, challenges associated with both procedures, xenotransplantation (of pig-derived islets) and stem cell transplantation, are required to be cautiously resolved before their clinical application.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.231
Teacher spread0.206 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Illinois ChicagoSame topicPancreatic function and diabetesFrench-language works237,207