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Record W4361275504 · doi:10.1016/j.cdnut.2023.100071

Maternal Exposure to Red Rooibos Does Not Alter Bone Development in Male or Female Sprague-Dawley Rat Offspring

2023· article· en· W4361275504 on OpenAlexafffund
Jenalyn L. Yumol, Michael D. McAlpine, Wendy E. Ward

Bibliographic record

VenueCurrent Developments in Nutrition · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOffspringLactationWeaningPregnancyEndocrinologyBone mineralInternal medicineMedicinePhysiologyBiologyOsteoporosis

Abstract

fetched live from OpenAlex

Maternal diet during pregnancy and/or throughout lactation provides a potential opportunity for nutritional programming of offspring bone development. Objectives of this study were to determine whether maternal consumption of red rooibos (RR) throughout pregnancy and lactation improved bone mineral density (BMD), bone structure, and bone strength in offspring and to determine potential sex-specific responses. Female Sprague-Dawley rats were randomly assigned to control water or RR in water (2600 mg/kg body weight/d) from prepregnancy through to the end of lactation. At weaning, offspring were fed AIN-93G diet until age 3 mo. Longitudinal assessment of the tibia demonstrated that maternal exposure to RR did not alter the trajectory of BMD or bone structure in male or female offspring compared with sex-specific controls at age 1, 2, or 3 mo or bone strength at age 3 mo. In conclusion, maternal exposure to RR did not program bone development in male or female 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)0.001
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 score0.105
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.065
GPT teacher head0.366
Teacher spread0.301 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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