Physical Activity and Natural Anti-VIP Antibodies: Potential Role in Breast and Prostate Cancer Therapy
Bibliographic record
Abstract
BACKGROUND: There is convincing evidence from numerous clinical and epidemiological studies that physical activity can reduce the risk for breast and prostate cancer. The biological mechanisms underlying this phenomenon remain elusive. Herein we suggest a role for naturally produced antibodies reactive with the vasoactive intestinal peptide (VIP) in the suppression of breast and prostate cancer, which we believe could offer a possible molecular mechanism underlying control of these cancers by physical exercise. METHODOLOGY AND RESULTS: We found that sera from individuals having breast and prostate cancers have decreased titers of VIP natural antibodies as demonstrated by a lower reactivity against peptide NTM1, having similar informational and structural properties as VIP. In contrast, sera collected from elite athletes, exhibited titers of natural NTM1-reactive antibodies that are significantly increased, suggesting that physical activity boosts production of these antibodies. SIGNIFICANCE: Presented results suggest that physical exercise stimulates production of natural anti-VIP antibodies and likely results in suppression of VIP. This, in turn, may play a protective role against breast and prostate cancers. Physical exercise should be further investigated as a potential tool in the treatment of these diseases.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".