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Warfarin‐induced vitamin K deficiency is associated with alterations in sphingolipid status in rats

2013· article· en· W69413186 on OpenAlexafffund
Guylaine Ferland, Sahar Tamadon‐Nejad, Bouchra Ouliass

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldNursing
TopicVitamin K Research Studies
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsSphingolipidSphingomyelinCeramideInternal medicineEndocrinologyChemistryVitamin K deficiencyVitaminMedicineCholesterolBiochemistry

Abstract

fetched live from OpenAlex

Vitamin K (VK) is involved in sphingolipid metabolism and menaquinone‐4 (MK‐4), the main K vitamer in brain, is strongly correlated to cerebral sulfatides, sphingomyelin and gangliosides. Warfarin (W), a widely used oral anticoagulant, acts by blocking the VK cycle. In a previous report, we observed W‐induced VK deficiency (model of Price et al. 1982) to result in cognitive deficits, an observation associated with a drastic decrease in brain MK‐4. Here we report that in these rats, W‐tx is associated with an alteration in sphingolipid status. Male Wistar rats were treated with 15 mg W/kg/d (in drinking water) and subcutaneous VK (85 mg/kg), 3X/wk, for 10 wks; control rats were treated with normal water and injected with saline. Sphingolipids (gangliosides, ceramides, cerebrosides, sphingomyelin and sulfatides) were determined by solid phase chomatography and the ganglioside subtypes were further assessed by HPTLC. Compared to the control condition, W‐tx altered ceramides, sphingomyelin, sulfatides and gangliosides in specific brain regions (p<0.05) and resulted in a loss of correlation between sphingolipids and brain MK‐4. W‐tx also resulted in significant changes in gangliosides GD1a and GT1b in key brain regions (p<0.05). In conclusion, W‐induced VK deficiency alters sphingolipid status in brain, a finding that could contribute to the detrimental effects of W on cognition. (Funded by CIHR.)

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.556
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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