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Record W6989861186

Characterization of fatty acid profile in breast tissues from Manitoba breast cancer patients

2010· dissertation· en· W6989861186 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2010
Typedissertation
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerLinoleic acidFatty acidPolyunsaturated fatty acidBreast tissueLinolenic acidCancer
DOInot available

Abstract

fetched live from OpenAlex

This study was carried out to investigate the fatty acid composition of tumoral, marginal and normal breast tissue in female breast cancer patients. Patients were recruited from St. Boniface General Hospital. A pre-operative blood sample was drawn. After surgery, sections were obtained from tumoral, marginal and normal breast tissues for histology and biochemical analysis. Extracted lipids from marginal tissue were significantly higher than those in normal or tumoral tissue. The lipid profile in tumoral tissue was significantly different in terms of fatty acid composition compared to normal and marginal tissue with less linoleic and alpha linolenic acid and more long chain polyunsaturated fatty acid of omega-3 and omega-6 series. Marginal tissue showed significantly less alpha linolenic acid compared to normal tissue. An inverse correlation existed between plasma level of 22:6 n-3 and breast cancer stage. We found different lipid profile in tumoral tissue compared to normal and marginal tissue.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2010
Admission routes1
Has abstractyes

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