Bibliographic record
Abstract
The triple-negative breast cancer (TNBC) subtype is the most difficult to treat and has a higher risk of metastasis. Cancer cell metastasis requires the involvement of the actin cytoskeleton. The molecule interacting with CasL protein 1 (MICAL1) is a monooxygenase enzyme that facilitates the local disassociation of actin monomers to promote actin filamentation. The epidermal growth factor receptor (EGFR) is a tyrosine kinase that promotes cell invasion, migration, growth, and survival. Metastatic characteristics are promoted in TNBC during aberrant EGFR signalling, via the mitogenactivated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/Akt pathways. This thesis will examine how MICAL1 influences motility, morphology, and EGFR signalling in TNBC cell lines. Results from this thesis demonstrate that MICAL1 contributes to confined cell migration and cell size. Further, results demonstrate that MICAL1 negatively modulates MAPK signalling during EGF stimulation. In effect, this thesis forwards MICAL1 as a likely contributor of TNBC cell metastasis.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".