TRUSS, TNF‐R1, and TRPC ion channels synergistically reverse endoplasmic reticulum Ca<sup>2+</sup> storage reduction in response to m1 muscarinic acetylcholine receptor signaling
Bibliographic record
Abstract
Although most signaling responses initiated by tumor necrosis factor-alpha (TNF-alpha) occur in a Ca(2+)-independent fashion, TNF-alpha receptor signaling augments Ca(2+) entry induced by Galpha(q/11) G-protein coupled receptors (GPCRs) in endothelial cells and increases trans-endothelial permeability. The signaling events involved in GPCR-induced Ca(2+) influx have been characterized and involve store-operated Ca(2+) entry facilitated by the Ca(2+) permeable ion channel, transient receptor potential canonical 4 (TRPC4). Little is known about the mechanisms by which TNF-alpha receptor signaling augments GPCR-induced Ca(2+) entry. TNF-alpha Receptor Ubiquitous Signaling and Scaffolding protein (TRUSS) is a tumor necrosis factor receptor-1 (TNF-R1)-associated protein whose gene name is TRPC4-associated protein (TRPC4AP). The goal of our study was to test the hypothesis that TRUSS serves to link TNF-R1 and GPCR-signaling pathways at the level of TRPC4 by: (i) determining if TRUSS and TNF-R1 interact with TRPC4, and (ii) investigating the role of TRUSS, TNF-R1, and TRPC4 in GPCR-induced Ca(2+) signaling. Here, we show that TRUSS and TNF-R1 interact with a sub-family of TRPC channels (TRPC1, 4, and 5). In addition, we show that TRUSS and TNF-R1 function together with TRPC4 to elevate endoplasmic reticulum Ca(2+) filling in the context of reduced endoplasmic reticulum Ca(2+) storage initiated by G-protein coupled m1 muscarinic acetylcholine receptor (m1AchR) signaling. Together, these findings suggest that TNF-R1, TRUSS, and TRPC4 augment Ca(2+) loading of endoplasmic reticulum Ca(2+) stores in the context of m1AchR stimulation and provide new insights into the mechanisms that connect TNF-R1 to GPCR-induced Ca(2+) signaling.
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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) | 0.001 | 0.001 |
| 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".