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Record W2773003121 · doi:10.14740/jocmr3209w

The Effect of Ongoing Vitamin D and Low-Fat Milk Intake on Bone Metabolism in Female High-School Endurance Runners

2018· article· en· W2773003121 on OpenAlexvenueno aff
Aoi Ikedo, Takuma Arimitsu, Toshiyuki Kurihara, Kumiko Ebi, Satoshi Fujita

Bibliographic record

VenueJournal of Clinical Medicine Research · 2018
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineVitamin D and neurologyEndocrinologyBone remodelingParathyroid hormoneBone resorptionCalciumBone mineralVitaminvitamin D deficiencyOsteoporosis

Abstract

fetched live from OpenAlex

BACKGROUND: Vitamin D and calcium are essential nutrients for bone health. In addition, vitamin D suppresses inflammatory cytokines and increases bone resorption. Therefore, improvements in bone health by calcium and vitamin D supplementation have the potential to not only improve calcium metabolism but also suppress inflammation associated with exercise training. The purpose of this study was to determine whether ongoing vitamin D supplementation and low-fat milk intake by female high-school endurance runners would improve bone metabolism by suppressing inflammatory cytokines and the parathyroid hormone (PTH). METHODS: Twenty female high-school runners were assigned to a vitamin D supplement and low-fat milk intake group (MKD) or a control group (CON). Participants in the MKD group consumed a vitamin D supplement (1,000 IU/day) and low-fat milk (Ca 315 mg/day) for 6 months. Bone mineral density measurements, blood samples, and questionnaires (regarding menses and diet) were carried out. The UMIN Clinical Trials Registry number is UMIN000027854. RESULTS: The 25-hydroxyvitamin D (25(OH)D) concentration in MKD was sustained and PTH concentration was decreased regardless of the state of menses. The correlation coefficients of 25(OH)D or PTH concentrations and bone metabolism markers were analyzed by partial correlation coefficient via adjusting the model for frequency of menses. CTX and 25(OH)D concentration were significantly and inversely correlated at baseline (r = -0.61, P < 0.01), 3 months (r = -0.54, P = 0.02), and 6 months (r = -0.53, P = 0.02). CTX and PTH were significantly and positively correlated at 3 months (r = 0.63, P < 0.01) and 6 months (r = 0.52, P = 0.02). The bone alkaline phosphatase (BAP)/CTX ratio and 25(OH)D concentration were significantly and positively correlated at 3 months (r = 0.59, P = 0.01) and 6 months (r = 0.56, P = 0.01). The BAP/CTX ratio and PTH were significantly and inversely correlated at 3 months (r = -0.59, P = 0.01) and 6 months (r = -0.58, P < 0.01). CONCLUSIONS: This study suggested that vitamin D and low-fat milk supplementation improves bone metabolism by sustaining the 25(OH)D concentration and decreasing the PTH concentration in female high-school endurance runners regardless of the state of menses.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.083
GPT teacher head0.486
Teacher spread0.404 · 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 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

Citations7
Published2018
Admission routes1
Has abstractyes

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