Sphingolipids in Atherosclerosis: Chimeras in Structure and Function
Bibliographic record
Abstract
Atherosclerosis-a systemic inflammatory disease-is the number one cause of mortality and morbidity worldwide. As such, the prevention of disease progression is of global interest in order to reduce annual deaths at a significant scale. Atherosclerosis is characterized by plaque formation in the arteries, resulting in vascular events such as ischemic stroke or myocardial infarction. A better understanding of the underlying pathophysiological processes at the cellular and molecular level is indispensable to identify novel therapeutic targets that may alleviate disease initiation or progression. Sphingolipids-a lipid class named after the chimeric creature sphinx-are considered to play a critical and, metaphorically, equally chimeric regulatory role in atherogenesis. Previous studies identified six common sphingolipids, namely dihydroceramide (DhCer), ceramide (Cer), sphingosine-1-phosphate (S1P), sphingomyelin (SM), lactosylceramide (LacCer), and glucosylceramide (GluCer) in carotid plaques, and demonstrated their potential as inducers of plaque inflammation. In this review, we point out their specific roles in atherosclerosis by focusing on different cell types, carrier molecules, enzymes, and receptors involved in atherogenesis. Whereas we assume mainly atheroprotective effects for GluCer and LacCer, the sphingolipids DhCer, Cer, SM and S1P mediate chimeric functions. Initial studies demonstrate the successful use of interventions in the sphingolipid pathway to prevent atherosclerosis. However, as atherosclerosis is a multifactorial disease with a variety of underlying cellular processes, it is imperative for future research to emphasize the circumstances in which sphingolipids exert protective or progressive functions and to evaluate their therapeutic benefits in a spatiotemporal manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".