The role of zyxin in regulation of malignancies
Bibliographic record
Abstract
Focal adhesions are highly dynamic multi-protein complexes found at the cell surface and effectively link the cell's internal cytoskeleton to a complex mixture of macromolecules known as the extracellular matrix and mediate transmission of signals from the extracellular matrix to the nucleus. Zyxin is one of the key focal adhesion proteins and is also found to shuttle in the nucleus. Although the mechanism of shuttling to the nucleus unclear, it moves out from the nucleus through a leucine-rich nuclear export signal sequence. It is known to contribute to fundamental cellular activities such as cell migration, adhesion and proliferation by interacting with a variety of cellular proteins. It is also linked with a number of cancers such as melanoma, hepatocellular carcinoma, oral squamous-cell carcinoma, Ewing sarcoma and prostate cancer. However, in many cases, the precise mechanisms by which the absence or presence of zyxin contributes to cancer progression or suppression is unknown. Thus, more work is required to gain insights into how zyxin modulates cellular functions in relationship to cancer. This review summarises the role of zyxin in cancer, with an emphasis on conflicting roles in prostate cancer.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".