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Record W4381686492 · doi:10.1186/s12964-023-01171-8

Islets in the body are never flat: transitioning from two-dimensional (2D) monolayer culture to three-dimensional (3D) spheroid for better efficiency in the generation of functional hPSC-derived pancreatic β cells in vitro

2023· review· en· W4381686492 on OpenAlexaboutno aff
Abdoulaye Diané, Layla Ibrahim Mohammed, Heba Al-Siddiqi

Bibliographic record

VenueCell Communication and Signaling · 2023
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersQatar National LibraryQatar Biomedical Research Institute, Hamad Bin Khalifa University
KeywordsProgenitor cellCell biologyBiologyTransplantationCell therapyCell cultureCellStem cellIn vivoPancreatic isletsRegeneration (biology)IsletInsulinCancer researchMedicineInternal medicineEndocrinologyBiotechnologyGenetics

Abstract

fetched live from OpenAlex

Diabetes mellitus (DM), currently affecting more than 537 million people worldwide is a chronic disease characterized by impaired glucose metabolism resulting from a defect in insulin secretion, action, or both due to the loss or dysfunction of pancreatic β cells. Since cadaveric islet transplantation using Edmonton protocol has served as an effective intervention to restore normoglycaemia in T1D patients for months, stem cell-derived β cells have been explored for cell replacement therapy for diabetes. Thus, great effort has been concentrated by scientists on developing in vitro differentiation protocols to realize the therapeutic potential of hPSC-derived β cells. However, most of the 2D traditional monolayer culture could mainly generate insulin-producing β cells with immature phenotype. In the body, pancreatic islets are 3D cell arrangements with complex cell-cell and cell-ECM interactions. Therefore, it is important to consider the spatial organization of the cell in the culture environment. More recently, 3D cell culture platforms have emerged as powerful tools with huge translational potential, particularly for stem cell research. 3D protocols provide a better model to recapitulate not only the in vivo morphology, but also the cell connectivity, polarity, and gene expression mimicking more physiologically the in vivo cell niche. Therefore, the 3D culture constitutes a more relevant model that may help to fill the gap between in vitro and in vivo models. Interestingly, most of the 2D planar methodologies that successfully generated functional hPSC-derived β cells have switched to a 3D arrangement of cells from pancreatic progenitor stage either as suspension clusters or as aggregates, suggesting the effect of 3D on β cell functionality. In this review we highlight the role of dimensionality (2D vs 3D) on the differentiation efficiency for generation of hPSC-derived insulin-producing β cells in vitro. Consequently, how transitioning from 2D monolayer culture to 3D spheroid would provide a better model for an efficient generation of fully functional hPSC-derived β cells mimicking in vivo islet niche for diabetes therapy or drug screening. Video Abstract.

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)0.001
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: none
Teacher disagreement score0.796
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.066
GPT teacher head0.293
Teacher spread0.227 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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