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Record W2071495812 · doi:10.3390/molecules181215094

Maternal High Fat Feeding Does Not Have Long-Lasting Effects on Body Composition and Bone Health in Female and Male Wistar Rat Offspring at Young Adulthood

2013· article· en· W2071495812 on OpenAlexafffund
Paula M. Miotto, Laura M. Castelli, Foyinsola Amoye, Paul J. LeBlanc, Sandra J. Peters, Brian D. Roy, Wendy E. Ward

Bibliographic record

VenueMolecules · 2013
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchBrock University
KeywordsOffspringWeaningLactationFemurEndocrinologyBiologyPregnancyInternal medicineBone mineralLean body massComposition (language)PhysiologyMedicineAnimal scienceOsteoporosisBody weight

Abstract

fetched live from OpenAlex

High fat diets adversely affect body composition, bone mineral and strength, and alter bone fatty acid composition. It is unclear if maternal high fat (HF) feeding permanently alters offspring body composition and bone health. Female rats were fed control (CON) or HF diet for 10 weeks, bred, and continued their diets throughout pregnancy and lactation. Male and female offspring were studied at weaning and 3 months, following consumption of CON diet. At weaning, but not 3 months of age, male and female offspring from dams fed HF diet had lower lean mass and higher fat and bone mass, and higher femur bone mineral density (females only) than offspring of dams fed CON diet. Male and female offspring femurs from dams fed HF diet had higher monounsaturates and lower n6 polyunsaturates at weaning than offspring from dams fed CON diet, where females from dams fed HF diet had higher saturates and lower n6 polyunsaturates at 3 months of age. There were no differences in strength of femurs or lumbar vertebrae at 3 months of age in either male or female offspring. In conclusion, maternal HF feeding did not permanently affect body composition and bone health at young adulthood in offspring.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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 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

Citations22
Published2013
Admission routes2
Has abstractyes

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