Adenosine triphosphate induces proliferation of human neural stem cells: Role of calcium and p70 ribosomal protein S6 kinase
Bibliographic record
Abstract
Human neural stem cells (NSCs) grown in culture responded to extracellularly applied adenosine triphosphate (ATP), and the rate of proliferation increased as shown by immunocytochemical and RT-PCR analysis. Activation of P2 purinoceptors by ATP is coupled to the release of intracellular calcium ([Ca(2+)](i)) from thapsigargin-sensitive intracellular stores. ATP-induced proliferation was blocked by thapsigargin, an inhibitor of the endoplasmic reticulum Ca(2+)-ATPase. Neither EGTA, a calcium chelator, nor caffeine had any effect on ATP-induced [Ca(2+)](i) increases. Multiblot kinase analysis, by which activation of 24 different kinases could be determined, showed that application of ATP to NSCs predominantly activated p70 ribosomal protein S6 kinase (p70 S6 kinase). As well, rapamycin, a p70 S6 kinase inhibitor, blocked the ATP-mediated proliferative response in NSCs. After outlining a role for p70 S6 kinase in ATP-mediated NSC proliferation, we examined the possibility that phosphatidylinositol 3-kinase (PI3-kinase) acts upstream of p70 S6 kinase. The application of wortmannin, a PI3-kinase inhibitor, decreased both ATP-mediated p70 S6 kinase activation and NSC proliferation. From these results, we conclude that ATP application to NSCs induces release of Ca(2+) from intracellular Ca(2+) stores and that this increase in intracellular Ca(2+) in turn promotes NSC proliferation. The increase in NSC proliferation observed following ATP application can also be mediated by PI3-kinase-dependent p70 S6 kinase activation.
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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) | 0.001 | 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".