Bibliographic record
Abstract
This review is focused on lamin A/C, a nuclear protein with multiple functions in normal and diseased cells. Its functions, as known to date, are summarized. This summary includes its role in maintaining a cell's structural stability, cell motility, mechanosensing, chromosome organization, gene regulation, cell differentiation, DNA damage repair, and telomere protection. As lamin A/C has a variety of critical roles within the cell, mutations of the lamin A/C gene and incorrect processing of the protein results in a wide variety of diseases, ranging from striated muscle disorders to accelerated aging diseases. These diseases, collectively termed laminopathies, are also touched upon. Finally, we review the existing evidence of lamin A/C's deregulation in cancer. Lamin A/C deregulation leads to various traits, including genomic instability and increased tolerance to mechanical insult, which can lead to more aggressive cancer and poorer prognosis. As lamin A/C's expression in specific cancers varies widely, currently known lamin A/C expression in various cancers is reviewed. Additionally, Lamin A/C's potential as a biomarker in various cancers and as an aid in more accurately diagnosing intermediate Gleason score prostate cancers is also discussed.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".