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Record W2075229580 · doi:10.1002/mnfr.201300928

Low vitamin <scp>D</scp> status throughout life results in an inflammatory prone status but does not alter bone mineral or strength in healthy 3‐month‐old <scp>CD</scp>‐1 male mice

2014· article· en· W2075229580 on OpenAlexaff
Raha Jahani, Kristina A. Fielding, Jianmin Chen, Christopher Villa, Laura M. Castelli, Wendy E. Ward, Elena M. Comelli

Bibliographic record

VenueMolecular Nutrition & Food Research · 2014
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsBrock UniversityUniversity of Toronto
Fundersnot available
KeywordsVitamin D and neurologyWeaningEndocrinologyInternal medicineCalcitriol receptorOffspringVitaminBone mineralMedicineLactationBiologyPhysiologyOsteoporosisPregnancy

Abstract

fetched live from OpenAlex

SCOPE: The aim of this study was to assess if exposure to different levels of dietary vitamin D pre- and postweaning impacts the intestinal-bone axis. METHODS AND RESULTS: Female CD1 mice were exposed to high (5000 IU vitamin D3 /kg diet, H) or low (25 IU vitamin D3 /kg diet, L) vitamin D diet (modified AIN-93G) during pregnancy and lactation. At weaning (postnatal day 21), a subset of the male offspring was sacrificed and another subset was assigned to receive their dams' respective diet (HH and LL) or the other diet (HL and LH) until sacrifice at 3 months of age. Lower level of vitamin D resulted in reduced vitamin D receptor and increased expression of pro-inflammatory genes in the colon at 3 months, lower numbers of colonic Bacteroides/Prevotella at postnatal day 21 and higher serum LPS concentration at adulthood. There was a programming effect of vitamin D on LPS levels. Mineral content, density, and strength of femurs and vertebrae were not affected. CONCLUSION: Our findings suggest that low vitamin D exposure results in an inflammatory-prone status that may contribute to or be a risk factor for several diseases including inflammatory bowel disease, obesity, diabetes, and cardiovascular diseases.

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)0.005
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
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 score0.393
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.003
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 head0.034
GPT teacher head0.343
Teacher spread0.309 · 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.

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

Citations38
Published2014
Admission routes1
Has abstractyes

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