Extracellular and intracellular tumor necrosis factor alpha modulates cytosolic and nuclear calcium in human cardiovascular cells
Bibliographic record
Abstract
Tumor necrosis factor alpha (TNFα) and its type 1 receptor (TNFR1) are implicated in several autoimmune diseases, including rheumatoid arthritis, and are associated with complications at the cardiovascular level. Using human cardiomyocytes, vascular smooth muscle, vascular endothelial, and endocardial endothelial cells coupled to indirect immunofluorescence, our results showed the presence of TNFR1 at the levels of the plasma membrane (including the cytosol) and mostly at the level of the nuclear membranes (including the nucleoplasm). The distribution of the receptor is different between cell types; however, the density is significantly higher at the nuclear level in all 4 cell types. The density of the receptor was the highest in contractile cells including the cardiomyocytes and vascular smooth muscle cells, compared with endothelial cells including endocardial endothelial and vascular endothelial cells. Using the Ca2+ probe Fluo-3 coupled to quantitative confocal microscopy, our results showed that the cytokine induced a sustained Ca2+ increase in both the cytosol and nucleoplasm of all 4 cell types. This increase was more significant at the nuclear level, mainly in endothelial cells. Our results demonstrated the presence of TNFR1 at both the cell and nuclear membranes of cardiovascular cells, and that its activation modulated both cytosolic and nuclear Ca2+.
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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".