Calreticulin regulates Src kinase in osteogenic differentiation from embryonic stem cells
Bibliographic record
Abstract
Calreticulin, the major Ca2+ buffer of the endoplasmic reticulum plays an important role in the choice of fate by embryonic stem cells. Using the embryoid body method of organogenesis, we showed impaired osteogenesis in crt−/− cells vis-à-vis calreticulin-containing osteogenic WT cells. In the non-osteogenic crt−/− cells, c-Src- a non-receptor tyrosine kinase- was activated and its inhibition rescued osteogenesis. Most importantly, we demonstrated that calreticulin-containing cells had lower c-Src kinase activity, and this was accomplished via the Ca2+-homeostatic function of calreticulin. Specifically, lowering cytosolic [Ca2+] in calreticulin-containing osteogenic WT cells with BAPTA-AM, activated c-Src and impaired osteogenic differentiation. Conversely, increasing cytosolic [Ca2+] in crt−/− cells with ionomycin deactivated c-Src kinase and restored osteogenesis. The immediate effector of calreticulin, the Ser/Thr phosphatase calcineurin, was less active in crt−/− cells, however, its activity was rescued upon inhibition of c-Src activity by small molecule inhibitors. Finally, we showed that higher activity of calcineurin correlated with increased level of nuclear Runx2, a transcription factor that is the master regulator of osteogenesis. Collectively, our work has identified a novel pathway involving calreticulin regulated Ca2+ signalling via c-Src in osteogenic differentiation of embryonic stem cells.
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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 | 0.001 |
| 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".