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Record W2074302372 · doi:10.1530/eje-14-0870

Vitamin D3 increases in abdominal subcutaneous fat tissue after supplementation with vitamin D3

2015· article· en· W2074302372 on OpenAlexaff
Allan Didriksen, Anders Burild, Jette Jakobsen, Ole‐Martin Fuskevåg, Rolf Jorde

Bibliographic record

VenueEuropean Journal of Endocrinology · 2015
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsShared Health
FundersNovo Nordisk Fonden
KeywordsInternal medicineEndocrinologyVitaminMedicineAbdominal fatSubcutaneous fatVitamin D and neurologyAdipose tissueObesity

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective was to assess the amount of vitamin D3 stored in adipose tissue after long-term supplementation with high dose vitamin D3. DESIGN: A cross-sectional study on 29 subjects with impaired glucose tolerance who had participated in a randomized controlled trial with vitamin D3 20 000 IU (500 μg) per week vs placebo for 3-5 years. METHODS: Abdominal subcutaneous fat tissue was obtained by needle biopsy for the measurements of vitamin D3 and 25-hydroxyvitamin D3 (25(OH)D3). Body fat was measured with dual-energy X-ray absorptiometry, and serum 25(OH)D3 level was quantified. RESULTS: In the subjects given vitamin D3, the median concentrations of serum 25(OH)D3, fat vitamin D3, and fat 25(OH)D3 were 99 nmol/l, 209 ng/g, and 3.8 ng/g, respectively; and correspondingly in the placebo group 62 nmol/l, 32 ng/g, and 2.5 ng/g. If assuming an equal amount of vitamin D3 stored in all adipose tissue in the body, the median body store was 6.6 mg vitamin D3 and 0.12 mg 25(OH)D3 in those given vitamin D3. CONCLUSIONS: Subcutaneous adipose tissue may store large amounts of vitamin D3. The clinical importance of this storage needs to be determined.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.025
GPT teacher head0.308
Teacher spread0.283 · 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

Citations86
Published2015
Admission routes1
Has abstractyes

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