Warfarin‐induced vitamin K deficiency is associated with alterations in sphingolipid status in rats
Bibliographic record
Abstract
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.)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".