The Roles of Integrin α5β1 in Human Cancer
Bibliographic record
Abstract
Cell adhesion to the extracellular matrix has important roles in tissue integrity and human health. Integrins are heterodimeric cell surface receptors that are composed by two non-covalently linked alpha and beta subunits that mainly participate in the interaction of cell-cell adhesion and cell-extracellular matrix and regulate cell motility, adhesion, differentiation, migration, proliferation, etc. In mammals, there have been eighteen α subunits and 8 β subunits and so far 24 distinct types of αβ integrin heterodimers have been identified in humans. Integrin α5β1, also known as the fibronectin receptor, is a heterodimer with α5 and β1 subunits and has emerged as an essential mediator in many human carcinomas. Integrin α5β1 alteration is closely linked to the progression of several types of human cancers, including cell proliferation, angiogenesis, tumor metastasis, and cancerogenesis. In this review, we will introduce the functions of integrin α5β1 in cancer progression and also explore its regulatory mechanisms. Additionally, the potential clinical applications as a target for cancer imaging and therapy are discussed. Collectively, the information reviewed here may increase the understanding of integrin α5β1 as a potential therapeutic target for 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 | 0.002 |
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".