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Record W4387498551 · doi:10.3390/cells12202423

The Current Status of Allogenic Islet Cell Transplantation

2023· review· en· W4387498551 on OpenAlexaffabout
Zofia Czarnecka, Nidheesh Dadheech, Haide Razavy, Rena Pawlick, A. M. James Shapiro

Bibliographic record

VenueCells · 2023
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransplantationImmunosuppressionIsletInduced pluripotent stem cellMedicineIslet cell transplantationImmunologyType 1 diabetesEmbryonic stem cellBiologyBioinformaticsDiabetes mellitusInternal medicineEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Type 1 Diabetes (T1D) is an autoimmune destruction of pancreatic beta cells. The development of the Edmonton Protocol for islet transplantation in 2000 revolutionized T1D treatment and offered a glimpse at a cure for the disease. In 2022, the 20-year follow-up findings of islet cell transplantation demonstrated the long-term safety of islet cell transplantation despite chronic immunosuppression. The Edmonton Protocol, however, remains limited by two obstacles: scarce organ donor availability and risks associated with chronic immunosuppression. To overcome these challenges, the search has begun for an alternative cell source. In 2006, pluripotency genomic factors, coined "Yamanaka Factors," were discovered, which reprogram mature somatic cells back to their embryonic, pluripotent form (iPSC). iPSCs can then be differentiated into specialized cell types, including islet cells. This discovery has opened a gateway to a personalized medicine approach to treating diabetes, circumventing the issues of donor supply and immunosuppression. In this review, we present a brief history of allogenic islet cell transplantation from the early days of pancreatic remnant transplantation to present work on encapsulating stem cell-derived cells. We review data on long-term outcomes and the ongoing challenges of allogenic islet cell and stem cell-derived islet cell transplant.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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.

Opus teacher head0.062
GPT teacher head0.341
Teacher spread0.280 · 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
GenreReview

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

Citations30
Published2023
Admission routes2
Has abstractyes

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