LINCing Senescence and Nuclear Envelope Changes
Bibliographic record
Abstract
The nuclear envelope (NE) has emerged as a nexus for cellular organization, signaling, and survival. Beyond its role as a barrier to separate the nucleoplasm from the cytoplasm, the NE's role in supporting and maintaining a myriad of other functions has made it a target of study in many cellular processes, including senescence. The nucleus undergoes dramatic changes in senescence, many of which are driven by changes in the NE. Indeed, Lamin B1, a key NE protein that is consistently downregulated in senescence, has become a marker for senescence. Other NE proteins have also been shown to play a role in senescence, including LINC (linker of nucleoskeleton and cytoskeleton) complex proteins. LINC complexes span the NE, forming physical connections between the cytoplasm to the nucleoplasm. In this way, they integrate nuclear and cytoplasmic mechanical signals and are essential not only for a variety of cellular functions but are needed for cell survival. However, LINC complex proteins have been shown to have a myriad of functions in addition to forming a LINC complex, often existing as nucleoplasmic or cytoplasmic soluble proteins in a variety of isoforms. Some of these proteins have now been shown to play important roles in DNA repair, cell signaling, and nuclear shape regulation, all of which are important in senescence. This review will focus on some of these roles and highlight the importance of LINC complex proteins in senescence.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".