Fluorescence Imaging of Receptor Activator of Nuclear Factor Kappa-B Ligand-Mediated Calcium Oscillations in Osteoclasts
Bibliographic record
Abstract
Background: Numerous bone diseases are caused by abnormal activity of osteoclasts, cells responsible for physiological bone degradation. Understanding the mechanisms of osteoclast formation and activation is important for developing diagnostic tools and treatments for various bone diseases. Receptor activator of nuclear factor κB ligand (RANKL), a key osteoclastogenic cytokine, induces changes in intracellular Ca2+ con- centration ([Ca2+]i) that can be visualized and measured with a fluorescent Ca2+ binding dye. The objective of the study was to characterize the changes in [Ca2+]i induced by acute application of RANKL in osteoclast precursors. Methods: We performed calcium imaging in osteoclast precursors generated from RAW 264.7 cells loaded with Fura-2 fluorescent dye using an inverted microscope, Nikon TE2000-U. Data was collected with Volocity software and analysed in Excel and MATLAB. Results: In osteoclast precursors, RANKL induced oscillations in [Ca2+]i within 2 minutes of exposure. The main frequency of oscillations was approximately 37.7 mHz. However, no significant change in the mean level of intracellular Ca2+ was observed. Interestingly, when ATP was applied to RANKL-treated osteoclast precursors, it induced a long-lasting increase in [Ca2+]i compared to control cells. Limitations: The limitations of our study included the small number of replicates and the short duration of fluorescence recording under each condition. Conclusions: Short exposure of osteoclast precursors to RANKL not only induced oscillations in calcium con- centration, but also modulated cellular response to the subsequent application of ATP.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".