High resolution analysis of the cytosolic Ca <sup>2+</sup> events in beta cell collectives in situ
Bibliographic record
Abstract
The release of peptide hormones is predominantly regulated by a transient increase in cytosolic Ca 2+ concentration ([Ca 2+ ] c ). To trigger exocytosis, Ca 2+ ions enter the cytosol from intracellular Ca 2+ stores or from the extracellular space. The molecular events of late stages of exocytosis, and their dependence on [Ca 2+ ] c , were extensively described in isolated single cells from various endocrine glands. Notably less work has been done on endocrine cells in situ to address the heterogeneity of [Ca 2+ ] c events contributing to a collective functional response of a gland. For this beta cell collectives in a pancreatic islet are particularly well suited as they are the smallest, experimentally manageable functional unit, where [Ca 2+ ] c dynamics can be simultaneously assessed on both cellular and collective level. Here we measured [Ca 2+ ] c transients across all relevant timescales, from a sub-second to a minute time range, using high-resolution imaging with low-affinity Ca 2+ sensor. We quantified the recordings with a novel computational framework for semi-automatic image segmentation and [Ca 2+ ] c event identification. Our results demonstrate that under physiological conditions the duration of [Ca 2+ ] c events is variable, and segregated into 3 reproducible modes, sub-second, second and tens of seconds time range, and are a result of a progressive temporal summation of the shortest events. Using pharmacological tools we show that activation of intracellular Ca 2+ receptors is both sufficient and necessary for glucose-dependent [Ca 2+ ] c oscillations in beta cell collectives, and that a subset of [Ca 2+ ] c events could be triggered even in the absence of Ca 2+ influx across the plasma membrane. In aggregate, our experimental and analytical platform was able to readily address the involvement of intracellular Ca 2+ receptors in shaping the heterogeneity of [Ca 2+ ] c responses in collectives of endocrine cells in situ.
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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) | 0.000 | 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 | 0.000 |
| 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".