Multi-parameter, single-cell, kinetic analysis reveals multiple modes of cell death in primary pancreatic beta-cells
Bibliographic record
Abstract
Programmed β-cell death plays an important role in both type 1 and type 2 diabetes. Most of what is known about the mechanisms of β-cell death comes from single time-point, single parameter measurements of bulk populations of mixed cells. Such approaches are inadequate for determining the true extent of the heterogeneity in death mechanisms. Here, we characterized the timing and order of molecular events associated with cell death in single β-cells under multiple diabetic stress conditions, including hyperglycemia, cytokine exposure, nutrient deprivation and endoplasmic reticulum (ER) stress. We simultaneously measured the kinetics of six distinct cell death mechanisms by using a caspase-3 sensor and three vital dyes, together with brightfield imaging. We identified several cell death modes where the order of events that usually define apoptosis were not observed. This we termed 'partial apoptosis'. Remarkably, complete classical apoptosis, defined as cells with plasma membrane blebbing, caspase-3 activity, nuclear condensation and membrane annexin V labeling prior to loss of plasma membrane integrity, was found in only half of the cytokine-treated primary β-cells and never in cells stressed by serum removal. By contrast, in the MIN6 cell line, death occurred almost exclusively through complete classical apoptosis. Ambient glucose modulated the cell death mode and kinetics in primary β-cells. Taken together, our data define the kinetic progression of β-cell death mechanisms under different conditions and illustrate the heterogeneity and plasticity of cell death modes in β-cells. We conclude that apoptosis is not the primary mode of adult primary β-cell death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".