Metabolic Regulation of Epithelial to Mesenchymal Transition: Implications for Endocrine Cancer
Bibliographic record
Abstract
The last few decades have witnessed an outstanding advancement in our understanding of the hallmarks of endocrine cancers. This includes the epithelial to mesenchymal transition (EMT), a process that alters the morphology and functional characteristics of carcinoma cells. The mesenchymal stem cell like phenotype produced by EMT allows the dislocation of cancer cells from the primary tumor site with inheritance of motility, metastatic and invasive properties. A fundamental driver thought to initiate and propagate EMT is metabolic reprogramming that occur during these transitions. Though there remains a paucity of data regarding the alterations that occur during EMT in endocrine cancers, the contribution of deregulated metabolism is a prominent feature. This mini review focuses on metabolic reprogramming events that occur in cancer cells and in particular those of endocrine origin. It highlights the main metabolic reprogramming outcomes of EMT, encompassing glycolysis, mitochondria oxidative phosphorylation and function, glutamine and lipid metabolism. Comprehending the metabolic changes that occur during EMT will help formulate potential bioenergetic targets as therapies for endocrine cancer metastasis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".