Editorial: Lipid metabolism and human diseases
Bibliographic record
Abstract
low-density lipoprotein (LDL), metabolic-associated fatty liver disease, coronary artery ectasia, idiopathic pulmonary fibrosis (IDF), coronary artery ectasia (CAE), atherosclerotic cardiovascular disease (ASCVD) Editorial on the Research Topic Lipid metabolism and human diseasesThe metabolism of lipids is crucial to several functional processes in the body, including the storage of energy, regulation of hormones, and transportation of nutrients.These processes are disrupted when lipids become dysregulated, leading to lipid disorders.The Research Topic, Lipid Metabolism and Human Diseases, presents a critical insight into the latest advances and progress made in cardiovascular disease research.The Research Topic featured eight original research articles and four reviews that advanced the understanding of how lipid metabolism contributes to metabolic disorders.The biology of lipoproteins and their roles in the progression of cardiovascular disorders is well documented.Low-density lipoprotein (LDL) plays a central role during cardiovascular homeostasis and primarily mediates the initiation and progression of atherosclerotic cardiovascular disorders (ASCVD).LDL cholesterol (LDL-C) is the main biological marker for LDL and remains the clinical target for ASCVD treatment, despite the fact that ASCVD risks persist in some patients with moderate LDL-C levels (Cromwell et al., 2007).LDL-C stands for cholesterol content in LDL particles (LDL-Ps).Qiao et al., in their article, exhaustively discussed the preference and precision of LDL-Ps over LDL-C in the prognosis of ASCVDs. The prognostic accuracy of LDL-C is affected by variations in lifestyle and drug intervention among individuals, which is why traditional lipid- lowering drugs like statins significantly reduce LDL-C levels and less of LDL-P levels. The article by Qiao et al. further outlined the atherogenic mechanisms of the action of LDL by focusing on subclasses of LDL-Ps, including sdLDL and ox-LDL, summarized the analytical techniques used for their measurement, and examined the advances in using statins and PCSK9i as LDL-lowering therapies.In addition to elucidating the molecular mechanisms of proteins and pathways relevant to lipid metabolism, this Research Topic also covered the metabolic roles of lipids in the pathogenesis of metabolism-associated fatty liver disease (MAFLD) (Jia et al.), Alcohol-Associated Fatty Liver (Ferdouse and Clugston), Coronary Artery Ectasias (Liu
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.020 | 0.020 |
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".