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Maternal Exposure to Hesperidin and Naringin Flavanones Exerts Transient Effects to Tibia Bone Microstructure in Female CD‐1 Offspring

2017· article· en· W4389019038 on OpenAlexafffundabout
Sandra M. Sacco, Caitlin Saint, Paul J. LeBlanc, Wendy E. Ward

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsBrock University
FundersCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsOffspringNaringinMedicineInternal medicineBone mineralEndocrinologyWeaningCortical bonePhysiologyLactationHesperidinPregnancyOsteoporosisBiologyAnatomyPathology

Abstract

fetched live from OpenAlex

Background Food bioactives may provide a dietary strategy to support healthy bone development. In a developing mouse model, early life but not maternal exposure to soy isoflavones sets a trajectory for higher bone mineral density (BMD), improved bone structure and greater bone strength in female offspring at adulthood. Other bioactives such as citrus flavanones (i.e. hesperidin, (HSP); naringin, (NAR)) have been shown to exert bone‐sparing effects in adult and aging rodents but whether maternal or early life exposure to citrus flavanones changes the trajectory of bone development to result in stronger, healthier bones at adulthood has not been investigated. Objective To determine whether maternal and early life exposure to a diet with HSP and NAR results in improved bone microstructure, higher BMD, and greater biomechanical bone strength in female mouse offspring at adulthood. Methods 5‐wk‐old female CD‐1 mice were fed the AIN‐93G control (CON, n=10) diet alone or with 0.5% HSP + 0.25% NAR (HSP+NAR, n=8) for 5 weeks preconception, and through pregnancy and lactation. HSP and NAR were added to CON diet at the expense of cornstarch, at doses reflecting moderate (400 mL) to high (1 L) orange or grapefruit juice consumption. At weaning, all female offspring were fed CON diet until 6 months of age. At 2, 4 and 6 months of age, right tibias were scanned using in vivo micro‐computed tomography (μCT) to assess trabecular and cortical bone microstructure. Ex vivo μCT scanning of the second lumbar vertebrae (LV2) and femurs was performed to assess site‐specific effects and to determine bone microstructure at skeletal sites rich in trabecular and cortical bone, respectively. Dual energy x‐ray absorptiometry (pSabre, Orthometrix) and biomechanical strength testing (Model 4442, Instron Corp.) were used to assess BMD (whole tibia and femur, LV2) and strength properties (tibia and femur midpoints, LV2), respectively. Results Litter size and weight at postnatal age of 9, 16 and 21 days were similar (p>0.05) between CON and HSP+NAR groups. Food intake and body weights remained similar (p>0.05) between CON and HSP+NAR offspring throughout the study. At 2 and 4 months of age, compromised trabecular (bone volume fraction, trabecular number and separation, connectivity density) but not cortical bone microstructure was observed at the proximal tibias of HSP+NAR versus CON offspring (p<0.05). At 6 months, these differences in trabecular structure at the proximal tibia had disappeared; BMD, trabecular or cortical bone microstructure, and biomechanical bone strength did not differ (p>0.05) between HSP+NAR and CON offspring at all skeletal sites assessed. Conclusion Maternal and early life exposure to HSP+NAR does not enhance bone development in female CD‐1 offspring. Compromised trabecular bone structure during early life does not persist into adulthood, and BMD and strength of the tibia is not altered at 6 months of age, representing adulthood. Support or Funding Information This research was funded by the Canadian Institutes of Health Research (Grant #130544) and the Canada Foundation for Innovation (Grant #222084) for purchase of the micro‐computed tomography system.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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 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".

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Citations1
Published2017
Admission routes3
Has abstractyes

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