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Record W2893972833 · doi:10.1002/lipd.12085

The Growth‐Inhibiting Effects of Beef Fatty Acids on MCF‐7 Cells Are Influenced Mostly by the Depot Location and Inconsistently by the Biohydrogenation Intermediate Content

2018· article· en· W2893972833 on OpenAlexaff
Payam Vahmani, D. C. Rolland, Katherine E. Gzyl, Danica D. S. Baines, M.E.R. Dugan

Bibliographic record

VenueLipids · 2018
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsConjugated linoleic acidLinoleic acidPolyunsaturated fatty acidFood scienceGrowth inhibitionChemistryCell growthFatty acidBiologyBiochemistry

Abstract

fetched live from OpenAlex

Biohydrogenation intermediates (BHI) including conjugated linoleic acid (CLA) isomers are formed during ruminal biohydrogenation of polyunsaturated fatty acids (PUFA) in ruminants. Although many studies have examined the anticarcinogenic effects of CLA, few studies have reported the anticarcinogenic properties of BHI in their natural form found in dairy and beef fats. The present study compared the growth-inhibitory effects of fatty acids from beef perirenal fat (PRF) or subcutaneous fat (SCF) with low or high levels of BHI in MCF-7 human breast cancer cells. Cells were exposed for 72 h to media containing increasing doses (50 to 400 μM) of different beef fat treatments. Fatty-acid analysis showed that BHI were readily incorporated into cell phospholipids (PL) in a treatment-dependent manner, but higher BHI in PL did not consistently inhibit growth. Culturing with low-BHI PRF or high-BHI PRF did not lead to growth inhibition, but low-BHI SCF inhibited growth, and inhibition was further increased by high-BHI SCF. Other classes of fatty acids may, therefore, be interacting with BHI resulting in differential effects on growth inhibition in human breast cancer cells.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.265
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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