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Record W2019646023 · doi:10.1155/2011/594851

Improving Islet Engraftment by Gene Therapy

2011· article· en· W2019646023 on OpenAlexaff
Xiaojie Wang, Mark Meloche, C. Bruce Verchere, Dawei Ou, Alice Mui, Garth L. Warnock

Bibliographic record

VenueJournal of Transplantation · 2011
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIsletMedicineApoptosisGene silencingTransplantationHypoxia (environmental)RevascularizationDiabetes mellitusCancer researchBioinformaticsGeneImmunologyInternal medicineEndocrinologyBiologyMyocardial infarctionGenetics

Abstract

fetched live from OpenAlex

Islet cell transplantation is currently the only feasible long-term treatment option for patients with type 1 diabetes. However, the majority of transplanted islets experience damage and apoptosis during the isolation process, a blood-mediated inflammatory microenvironment in the portal vein upon islet infusion, hypoxia induced by the low oxygenated milieu, and poor-revascularization-mediated lack of nutrients, and impaired hormone modulation in the local transplanted site. Strategies using genetic modification methods through overexpression or silencing of those proteins involved in promoting new formation of blood vessels or inhibition of apoptosis may overcome these hurdles and improve islet engraftment outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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 designBench or experimental
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

Citations19
Published2011
Admission routes1
Has abstractyes

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