Raf Kinase Inhibitory Protein (RKIP): Functional Pleiotropy in the Mammalian Brain
Bibliographic record
Abstract
In 1984, a cytosolic protein was isolated from bovine brain and coined phosphatidylethanolamine binding protein (PEBP) to describe its phospholipid-binding potential. Its cellular function remained elusive for more than a decade until it was discovered that PEBP had the ability to suppress the Raf1-mitogen activated protein kinase (MAPK) pathway, earning it the new name of Raf1 kinase inhibitory protein (RKIP). This milestone discovery has paved the way for numerous studies that have now extended the reach of RKIP's function to other signaling cascades, within the context of various physiological and pathophysiological systems. This review will summarize our current knowledge of the neurophysiological roles of RKIP in the mammalian brain, including its function in the circadian clock and synaptic plasticity. It will also discuss evidence for an involvement of RKIP and its derived neuropeptide, hippocampal cholinergic neurostimulating peptide (HCNP), in neural development and differentiation. Implications in certain pathologies such as Alzheimer's disease and brain cancer will be highlighted. By chronicling the diverse functions of RKIP in the brain, we hope that this review will serve as a timely resource that ignites future studies on this versatile, multifaceted protein in the nervous system.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".