Poly(A)<sup>+</sup> mRNA‐binding protein Tudor‐SN regulates stress granules aggregation dynamics
Bibliographic record
Abstract
Stress granules (SGs) and processing bodies (PBs) comprise the main types of cytoplasmic RNA foci during stress. Our previous data indicate that knockdown of human Tudor staphylococcal nuclease (Tudor-SN) affects the aggregation of SGs. However, the precise molecular mechanism has not been determined fully. In the present study, we demonstrate that Tudor-SN binds and colocalizes with many core components of SGs, such as poly(A)(+) mRNA binding protein 1, T-cell internal antigen-1-related protein and poly(A)(+) mRNA, and SG/PB sharing proteins Argonaute 1/2, but not PB core proteins, such as decapping enzyme 1 a/b, confirming that Tudor-SN is an SG-specific protein. We also demonstrate that the Tudor-SN granule actively communicates with the nuclear and cytosolic pool under stress conditions. Tudor-SN can regulate the aggregation dynamics of poly(A)(+) mRNA-containing SGs and selectively stabilize the SG-associated mRNA during cellular stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".