The proliferative effects of sympathetic nerves and neuropeptide Y in a 4T1 cell breast cancer model
Bibliographic record
Abstract
The functional impact of sympathetically released neuropeptide Y (NPY) on breast cancer has been a question of growing interest due to the expression of NPY receptors in several cancer cell lines. Recently, our group reported that the 4T1 cell line expresses NPY receptors (Y1 &Y2) and mammary tumors grown from this cell line are sympathetically innervated. In the current study we evaluated the effect of NPY on 4T1 cell proliferation using 96‐hr treatment with NPY (10 −12 to 10 −6 M) and observed an increase in proliferation (MTS‐based assay) in treated cells compared to controls (10 −8 : 55%, 10 −7 :122%, 10 −6 : 157%, P < 0.05). Additionally, we examined the effect of chemical sympathectomy (via 6‐hydroxydopamine bromide, 6OHDA) on in vivo tumor growth. 4T1 cells (10 5 )were injected into the sympathectomized inguinal mammary fat pad (200 μg 6OHDA × 2 localized injections, 1 week prior to 4T1 inoculation) and intact fat pad of female BALB/c mice (n = 5/group). Tumor growth was monitored by caliper measures over 21 days and animals were sacrificed and tumors were harvested and weighed. Tumor volume was lower in sympathectomized animals compared to intact animals at all time points (wk1: 70%, wk2: 44% & wk3: 45%, P < 0.05), and final tumor mass was 52% of intact tumors (P < 0.05). These findings suggest that NPY and sympathetic nerves impact cellular proliferation in this model. NSERC & Canadian Breast Cancer Foundation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".