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Record W2070009788 · doi:10.1002/mnfr.200600187

Soy isoflavones and fatty acids: Effects on bone tissue postovariectomy in mice

2007· article· en· W2070009788 on OpenAlexaff
Wendy E. Ward, Debbie Fonseca

Bibliographic record

VenueMolecular Nutrition & Food Research · 2007
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOvariectomized ratOsteoporosisDaidzeinBone mineralInternal medicineEndocrinologyIsoflavonesFish oilBone densityMedicinePolyunsaturated fatty acidOsteocalcinOsteopeniaGenisteinChemistryEstrogenBiologyBiochemistryFatty acidEnzyme

Abstract

fetched live from OpenAlex

Osteoporosis is a silent disease that leads to fragility fractures that can diminish quality of life and contribute to death. With no ideal drug treatment available to manage osteoporosis, soy isoflavones (ISO), and omega-3 long chain PUFAs in fish oil (FO) may be integral in a dietary strategy that prevents bone loss. The overall objective of this study was to determine if combining ISO with omega-3 long chain PUFAs resulted in greater protection against the loss of bone mineral and skeletal weakening in ovariectomized mice. Ovariectomized CD-1 mice were randomized to control diet or a diet containing ISO alone (250 mg of genistein + 250 mg of daidzein/kg diet), FO alone (7% menhaden oil), or ISO + FO. Each dietary intervention prevented the loss of bone mineral density (BMD) in the femur and preserved femur strength, but only FO, either alone or combined with ISO, resulted in a higher BMD of lumbar vertebra (LV). Most notably, FO + ISO resulted in a higher peak load of LV4, indicating that vertebra were more resistant to fracture. Whether a dietary strategy providing FO in combination with ISO attenuates bone loss in postmenopausal women awaits investigation.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.017
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.370
Teacher spread0.342 · 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

Citations23
Published2007
Admission routes1
Has abstractyes

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