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Record W2073654819 · doi:10.2337/db13-0211

Targeting Purinergic Receptors in Islet Transplantation

2013· letter· en· W2073654819 on OpenAlexafffund
Reid Aikin

Bibliographic record

VenueDiabetes · 2013
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsMcGill University Health Centre
FundersHealth CanadaMcGill University
KeywordsPurinergic receptorIsletTransplantationReceptorMedicineEndocrinologyInternal medicineBiologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Transplanted islets are exposed to a distinctivelyhostile immunological environment. Grafted isletstypically encounter a combination of innate,allogeneic and anti-islet immune responses—the relative contributions of which are not fully understood. The relatively low success rate of islet transplantation compared with other organs suggests that current immu-nomodulatory protocols are inadequate to provide long-term islet graft protection. As the negative consequences of long-term immunosuppression can arguably outweigh the benefits of islet transplantation, there is intense focus on the development of strategies to induce immune tolerance toward grafts, thereby avoiding the requirement of chronic immunosuppression. In this issue of Diabetes, Vergani et al. (1) provide evidence that targeting purinergic receptor sig-naling is a viable strategy for islet allograft protection. Extracellular ATP modulates many aspects of the immune system. For example, ATP signaling is able to promote the

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.013
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0030.003

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.

Opus teacher head0.007
GPT teacher head0.208
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations4
Published2013
Admission routes2
Has abstractyes

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