Candidate mechanisms accounting for effects of physical activity on breast carcinogenesis
Bibliographic record
Abstract
Evidence is strong that a reduction in risk for breast cancer is associated with moderate to vigorous physical activity (PA); however, there is limited understanding of the role of type, intensity, duration, and frequency of PA and their mechanisms in accounting for this health benefit. The objective of this review is to stimulate investigations of candidate mechanisms that may account for the effects of the intensity and duration of aerobic PA on breast cancer risk and tumor burden. Three hypotheses are considered: 1) the mTOR network hypothesis: PA inhibits carcinogenesis by suppressing the activation of the mTOR signaling network in mammary carcinomas; 2) the hormesis hypothesis: the carcinogenic response to PA is nonlinear and accounted for by a physiological cellular stress response; and 3) the metabolic reprogramming hypothesis: PA limits the amount of glucose and glutamine available to mammary carcinomas thereby inducing apoptosis because tumor-associated metabolic programming is reversed. To link these hypotheses to systemic effects of PA, it is recommended that consideration be given to determining: 1) what contracting muscle releases into circulation or removes from circulation that would directly modulate the carcinogenic process in epithelial cells; 2) whether the effects of muscle contraction on epithelial cell carcinogenesis are exerted in an endocrine, paracrine, autocrine, or intracrine manner; and 3) if the effects of muscle contraction on malignant cells differ from effects on normal or premalignant cells that do not manifest the hallmarks of malignancy.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".