Vitamin K Metabolism in a Rat Model of Chronic Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Patients with chronic kidney disease (CKD) have very high levels of uncarboxylated, inactive, extra-hepatic vitamin K-dependent proteins measured in circulation, putting them at risk for complications of vitamin K deficiency. The major form of vitamin K found in the liver is phylloquinone (K1). Menaquinone-4 (MK-4) is the form of vitamin K that is preferentially found in extra-hepatic tissues. METHODS: In the present study, we assessed tissue concentrations of K1 and MK-4 and the expression of vitamin K-related genes in a rat model of adenine-induced CKD. RESULTS: It was found that rats with both mild and severe CKD had significantly lower amounts of K1 measured in liver, spleen and heart and higher levels of MK-4 measured in kidney cortex and medulla. All animals treated with high dietary K1 had an increase in tissue levels of both K1 and MK-4; however, the relative increase in K1 differed suggesting that the conversion of K1 to MK-4 may be a regulated/limiting process in some tissues. There was a decrease in the thoracic aorta expression of vitamin K recycling (Vkor) and utilization (Ggcx) enzymes, and a decrease in the kidney level of vitamin K1 to MK-4 bioconversion enzyme Ubiad1 in CKD. CONCLUSION: Taken together, these findings suggest that CKD impacts vitamin K metabolism, and this occurs early in the disease course. Our findings that vitamin K metabolism is altered in the presence of CKD provides further support that sub-clinical vitamin K deficiency may represent a modifiable risk factor for vascular and bone health in this population.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".