Renewable Human Cell Model for Type 1 Diabetes Research: EndoC-βH5/HUVEC Coculture Spheroids
Bibliographic record
Abstract
In vitro drug screening for type 1 diabetes therapies has largely been conducted on human organ donor islets for proof of efficacy. While native islets are the ultimate target of these drugs (either in situ or for transplantation), significant benefit can be difficult to ascertain due to the highly heterogeneous nature of individual donors and the overall scarcity of human islets for research. We present an in vitro coculture model based on immortalized insulin-producing beta-cell lines with human endothelial cells in 3D spheroids that aims to recapitulate the islet morphology in an effort towards developing a standardized cell model for in vitro diabetes research. Human insulin-producing immortalized EndoC-βH5 cells are cocultured with human endothelial cells in varying ratios to evaluate 3D cell culture models for type 1 diabetes research. Insulin secretion, metabolic activity, live cell fluorescence staining, and gene expression assays were used to compare the viability and functionality of spheroids composed of 100% beta-cells, 1 : 1 beta-cell/endothelial, and 1 : 3 beta-cell/endothelial. Monoculture and βH5/HUVEC cocultures formed compact spheroids within 7 days, with average diameter ~140 μm. This pilot study indicated that stimulated insulin release from 0 to 20 mM glucose increased from ~8-fold for monoculture and 1 : 1 coculture spheroids to over 20-fold for 1 : 3 EndoC-βH5/HUVEC spheroids. Metabolic activity was also ~12% higher in the 1 : 3 EndoC-βH5/HUVEC group compared to other groups. Stimulating monoculture beta-cell spheroids with 20 mM glucose +1 μg/mL glycine-modified INGAP-P increased the insulin stimulation index ~2-fold compared to glucose alone. Considering their availability and consistent phenotype, EndoC-βH5-based spheroids present a useful 3D cell model for in vitro testing and drug screening applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".