Neuropeptide Y stimulates proliferation and migration in the 4T1 breast cancer cell line
Bibliographic record
Abstract
Stress has long been thought of to be associated with increased risk of cancer. Chronic stress is associated with elevated levels of sympathetic neurotransmitter (norepinephrine and neuropeptide Y: NPY) release and immunosuppression. The expression of NPY receptors has been reported in human breast carcinomas. Recently, activation of the NPY Y5 receptor was shown to stimulate cell growth and increase migration in human breast cancer cells; however the effects of NPY have yet to be investigated in a murine model of breast cancer. Thus, the specific aims of the current study were to: (i) characterize NPY receptor expression in 4T1 breast cancer cells and orthotopic tumors grown in BALB/c mice and (ii) investigate the impact of NPY receptor activation on 4T1 cell proliferation and migration in vitro. Positive expression of NPY receptors (Y1R, Y2R and Y5R) was observed in cells and tumor tissue. As well, NPY treatment of 4T1 cells promoted a concentration-dependent increase in proliferation, through increased phosphorylation of ERK 1/2. Using NPY receptor antagonists (Y1R:BIBP3226, Y2R:BIIE0246 and Y5R:L-152,804), we found the proliferative response to be Y5R mediated. Additionally, NPY increased chemotaxis through Y2R and Y5R activation. These data are in congruence with those from human cell lines and highlight the 4T1 cell line as a translatable model of breast cancer in which the effects of NPY can be studied in an immunocompetent system.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".