Bibliographic record
Abstract
Historically discovered for its role in blood coagulation, there is now convincing evidence that vitamin K has important actions in the nervous system. As a unique cofactor to the γ-glutamyl carboxylase enzyme, vitamin K contributes to the biological activation of proteins Gas6 and protein S, ligands for the receptor tyrosine kinases of the TAM family (Tyro3, Axl, and Mer). Functionally, Gas6 has been involved in a wide range of cellular processes that include cell growth, survival, and apoptosis. In brain, vitamin K also participates in the synthesis of sphingolipids, an important class of lipids present in high concentrations in brain cell membranes. In addition to their structural role, sphingolipids are now known to partake in important cellular events such as proliferation, differentiation, senescence and cell-cell interactions. In recent years, studies have linked alterations in sphingolipid metabolism to age-related cognitive decline and neurodegenerative diseases such as Alzheimer's disease (AD). Emerging data also point to unique actions of the K vitamer menaquinone-4 (MK-4) against oxidative stress and inflammation. Finally, there is now data to suggest that vitamin K has the potential to influence psychomotor behavior and cognition. This review presents an overview of what is known of the role of vitamin K in brain function.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".