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Record W2015708711 · doi:10.1038/ncomms6116

Optical control of insulin release using a photoswitchable sulfonylurea

2014· article· en· W2015708711 on OpenAlexaff
Johannes Broichhagen, Matthias Schönberger, Simon C. Cork, James A. Frank, Piero Marchetti, Marco Bugliani, A. M. James Shapiro, Stefan Trapp, Guy A. Rutter, David J. Hodson, Dirk Trauner

Bibliographic record

VenueNature Communications · 2014
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Alberta
FundersStudienstiftung des Deutschen VolkesEuropean Foundation for the Study of DiabetesMedical Research CouncilDiabetes UKWellcome Trust
KeywordsSulfonylureaHypoglycemiaInsulinSulfonylurea receptorBeta cellPotassium channelType 2 Diabetes MellitusDiabetes mellitusEndocrinologyInternal medicineMedicineType 2 diabetesGlucose homeostasisPharmacologyChemistryInsulin resistanceIsletGlibenclamide

Abstract

fetched live from OpenAlex

Sulfonylureas are widely prescribed for the treatment of type 2 diabetes mellitus (T2DM). Through their actions on ATP-sensitive potassium (KATP) channels, sulfonylureas boost insulin release from the pancreatic beta cell mass to restore glucose homeostasis. A limitation of these compounds is the elevated risk of developing hypoglycemia and cardiovascular disease, both potentially fatal complications. Here, we describe the design and development of a photoswitchable sulfonylurea, JB253, which reversibly and repeatedly blocks KATP channel activity following exposure to violet-blue light. Using in situ imaging and hormone assays, we further show that JB253 bestows light sensitivity upon rodent and human pancreatic beta cell function. Thus, JB253 enables the optical control of insulin release and may offer a valuable research tool for the interrogation of KATP channel function in health and T2DM.

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 score0.001
Threshold uncertainty score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.354
Teacher spread0.301 · 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

Citations129
Published2014
Admission routes1
Has abstractyes

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