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Record W4401759337 · doi:10.1038/s42255-024-01114-8

Regulated and adaptive in vivo insulin secretion from islets only containing β-cells

2024· article· en· W4401759337 on OpenAlexfundno aff
Marta Perez-Frances, Eva Bru-Tarí, Christian M. Cohrs, Maria Valentina Abate, Léon van Gurp, Kenichiro Furuyama, Stephan Speier, Fabrizio Thorel, Pedro L. Herrera

Bibliographic record

VenueNature Metabolism · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of Alberta
KeywordsIsletInsulinGlucose homeostasisInternal medicineEndocrinologyPancreatic isletsBiologyInsulin oscillationSecretionCell biologyInsulin resistanceMedicine

Abstract

fetched live from OpenAlex

Insulin-producing β-cells in pancreatic islets are regulated by systemic cues and, locally, by adjacent islet hormone-producing 'non-β-cells' (namely α-cells, δ-cells and γ-cells). Yet whether the non-β-cells are required for accurate insulin secretion is unclear. Here, we studied mice in which adult islets are exclusively composed of β-cells and human pseudoislets containing only primary β-cells. Mice lacking non-β-cells had optimal blood glucose regulation, enhanced glucose tolerance, insulin sensitivity and restricted body weight gain under a high-fat diet. The insulin secretion dynamics in islets composed of only β-cells was comparable to that in intact islets. Similarly, human β-cell pseudoislets retained the glucose-regulated mitochondrial respiration, insulin secretion and exendin-4 responses of entire islets. The findings indicate that non-β-cells are dispensable for blood glucose homeostasis and β-cell function. These results support efforts aimed at developing diabetes treatments by generating β-like clusters devoid of non-β-cells, such as from pluripotent stem cells differentiated in vitro or by reprograming non-β-cells into insulin producers in situ.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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.

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

Citations20
Published2024
Admission routes1
Has abstractyes

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