Homeostatic calcium fluxes, ER calcium release, SOCE, and calcium oscillations in cultured astrocytes are interlinked by a small calcium toolkit
Bibliographic record
Abstract
How homeostatic ER calcium fluxes shape cellular calcium signals is still poorly understood. Here we used dual-color calcium imaging (ER-cytosol) and transcriptome analysis to link candidates of the calcium toolkit of astrocytes with homeostatic calcium signals. We found molecular and pharmacological evidence that P/Q-type channel Cacna1a contributes to depolarization-dependent calcium entry in astrocytes. For stimulated ER calcium release, the cells express the phospholipase Cb3, IP3 receptors Itpr1 and Itpr2, but no ryanodine receptors (Ryr1–3). After IP3-induced calcium release, Stim1/2 – Orai1/2/3 most likely mediate SOCE. The Serca2 (Atp2a2) is the candidate for refilling of the ER calcium store. The cells highly express adenosine receptor Adora1a for IP3-induced calcium release. Accordingly, adenosine induces fast ER calcium release and subsequent ER calcium oscillations. After stimulation, calcium refilling of the ER depends on extracellular calcium. In response to SOCE, astrocytes show calcium-induced calcium release, notably even after ER calcium was depleted by extracellular calcium removal in unstimulated cells. In contrast, spontaneous ER-cytosol calcium oscillations were not fully dependent on extracellular calcium, as ER calcium oscillations could persist over minutes in calcium-free solution. Additionally, cell-autonomous calcium oscillations show a second-long spatial and temporal delay in the signal dynamics of ER and cytosolic calcium. Our data reveal a rather strong contribution of homeostatic calcium fluxes in shaping IP3-induced and calcium-induced calcium release as well as spatiotemporal components of intracellular calcium oscillations.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".