α-Linolenic Acid Reduces Growth of Both Triple Negative and Luminal Breast Cancer Cells in High and Low Estrogen Environments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Flaxseed, rich in α-linolenic acid (ALA), is a complementary breast cancer (BC) therapy; however ALA effectiveness and mechanism are unclear. Variation in cellular expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and estrogen (E2) levels may alter ALA effectiveness. This research determined the effect of ALA on growth, apoptosis, and phospholipid fatty acids of 4 BC cell lines with varying receptor expression ± E2. MCF-7 (ER+/PR+/HER2-), BT-474 (ER+/PR+/HER2+), MDA-MB-231 (ER-/PR-/HER2-) and MDA-MB-468 (ER-/PR-/HER2-) cells were incubated with ALA (50-200 μM) ± 1 nM E2 for 48-72 h. ALA dose-dependently reduced growth, measured by trypan blue exclusion, of all cells (55-80% with 75 μM), and this effect was not altered by E2. ALA (75 μM)+E2 induced apoptosis, measured by flow cytometry (up to 111.2%). Decreased growth and increased apoptosis is related to increased cell phospholipid % ALA (up to 25.1%), measured by gas chromatography. ALA is shown for the first time to reduce cell growth and induce apoptosis regardless of receptor expression and E2 environment, by incorporating into BC phospholipids, supporting the use of ALA and ALA-rich foods as a safe, inexpensive complementary therapy for a wide range of BC.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it