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Record W2064274544 · doi:10.4161/isl.3.4.16166

Electrophysiological identification of mouse islet α-cells: From isolated single α-cells to in situ assessment within pancreas slices

2011· review· en· W2064274544 on OpenAlexafffund
Ya‐Chi Huang, Herbert Y. Gaisano, Yuk‐Man Leung

Bibliographic record

VenueIslets · 2011
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchChina Medical University
KeywordsIsletParacrine signallingElectrophysiologyBiologyCell biologyPopulationGlucose homeostasisPancreasNeuroscienceEndocrinologyInsulinReceptorMedicineBiochemistry

Abstract

fetched live from OpenAlex

Investigation of α-cells has long been constrained by their scarce population and localization at the islet mantle which exposes α-cells to injury by conventional islet isolation and dispersion to single cells that employ damaging enzymatic and mechanical means. To surmount these limitations, we recently reported employing the pancreas slice preparation which enables highly efficient acute in situ electrophysiological (patch clamp) examination of α-cells within its unperturbed native social environment with preserved paracrine regulation. In this review, we compare the electrophysiological properties of α-cells in these three preparations, and discuss the current view of glucose regulation of α-cells. We discuss current genetic mouse models that flurophore-tagged α-cells (GYY) and β-cells (MIP-GFP) which can reliably identify islet cells to facilitate their study. Combining these strategies should enable future studies directed at the precise assessment of the perturbation in intrinsic and paracrine regulation of α-cells contributing to abnormal glucose homeostasis in diabetes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.598
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.317
Teacher spread0.269 · 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.

Study designBench or experimental
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

Citations16
Published2011
Admission routes2
Has abstractyes

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