Presenilin-1 Holoprotein is an Interacting Partner of Sarco Endoplasmic Reticulum Calcium-ATPase and Confers Resistance to Endoplasmic Reticulum Stress
Bibliographic record
Abstract
Presenilin-1 (PSEN1) is a primary component of the gamma-secretase complex, and total levels of its holoprotein and endoproteolytic fragments are tightly regulated. We examined the effects of several types of endoplasmic reticulum (ER) stress on quantitative changes in the levels of PSEN1 mRNA, holoprotein, and fragments. The ER stress-inducing chemical compounds tunicamycin, brefeldin-A, thapsigargin, and staurosporine were added to the culture media of various human cell lines. Tunicamycin treatment caused a doubling of PSEN1 holoprotein production in HEK293 cells and an increase in holoprotein production to approximately 180% in GOTO human neuroblastoma and KNS-42 human glioma cell lines, without changing the amounts of PSEN1 N- or C-terminal fragments. The elevated holoprotein level in HEK293 cells was accompanied by an increase in PSEN1 mRNA expression. HEK293 cells that stably overexpressed PSEN1 holoprotein showed increased resistance to ER stress induced by tunicamycin, but they did not show resistance to ER stress caused by thapsigargin, a specific inhibitor of sarco ER calcium-ATPase (SERCA). In wild-type HEK293 cells under ER stress induced by tunicamycin, an increased amount of SERCA interacted with PSEN1 holoprotein. PSEN1 production varied among cell types and circumstances. The results suggested that the holoprotein forms a complex with the SERCA channel and participates in the regulation of intracellular calcium homeostasis. These findings provide support for the calcium hypothesis of Alzheimer's disease.
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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".