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Zinc, a regulator of islet function and glucose homeostasis

2009· review· en· W2005227623 on OpenAlexafffund
Nadeeja Wijesekara, Fabrice Chimienti, Michael B. Wheeler

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2009
Typereview
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsIsletGlucose homeostasisZincEndocrinologyInternal medicineDiabetes mellitusPancreasInsulinHomeostasisBiologyPancreatic isletsRegulatorInsulin resistanceChemistryMedicineBiochemistryGene

Abstract

fetched live from OpenAlex

It is well known that zinc is required in pancreatic beta-cells in the process of insulin biosynthesis and the maturation of insulin secretory granules. In fact, the zinc level in pancreatic islets is amongst the highest in the body and reduction in its levels in the pancreas has been associated with diabetes. High concentrations of zinc can also be toxic because of enhanced oxidative damage. The link between zinc, diabetes and islet dysfunction has recently been reiterated by genomewide association studies that identified an islet cell membrane zinc transporter, SLC30A8 (ZnT8), as one of the risk loci for type 2 diabetes. Here we explore the importance of both zinc and ZnT8 to islet biology and whole body glucose homeostasis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.292
Teacher spread0.270 · 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
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

Citations160
Published2009
Admission routes2
Has abstractyes

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