Endoplasmic reticulum calcium pumps and cancer
Bibliographic record
Abstract
Endoplasmic reticulum calcium homeostasis is involved in a multitude of signaling, as well as "house-keeping" functions that control cell growth, differentiation or apoptosis in every human/eukaryotic cell. Calcium is actively accumulated in the endoplasmic reticulum by Sarco/Endoplasmic Reticulum Calcium transport ATPases (SERCA enzymes). SERCA-dependent calcium transport is the only calcium uptake mechanism in this organelle, and therefore the regulation of SERCA function by the cell constitutes a key mechanism to adjust calcium homeostasis in the endoplasmic reticulum depending on the cell type and its state of differentiation. The direct pharmacological modulation of SERCA activity affects cell differentiation and survival. SERCA expression levels can undergo significant changes during cell differentiation or tumorigenesis, leading to modified endoplasmic reticulum calcium storage. In several cell types such as cells of hematopoietic origin or various epithelial cells, two SERCA genes (SERCA2 and SERCA3) are simultaneously expressed. Expression levels of SERCA3, a lower calcium affinity calcium pump are highly variable. In several cell systems SERCA3 expression is selectively induced during differentiation, whereas during tumorigenesis and blastic transformation SERCA3 expression is decreased. These observations point at the existence of a cross-talk, via the regulation of SERCA3 levels, between endoplasmic reticulum calcium homeostasis and the control of cell differentiation, and show that endoplasmic reticulum calcium homeostasis itself can undergo remodeling during differentiation. The investigation of the anomalies of endoplasmic reticulum differentiation in tumor and leukemia cells may be useful for a better understanding of the contribution of calcium signaling to the establishment of malignant phenotypes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".