A novel cuproptosis-related diagnostic gene signature and differential expression validation in atherosclerosis
Bibliographic record
Abstract
Atherosclerosis (AS) is a major contributor to morbidity and mortality worldwide. However, the molecular mechanisms and mediator molecules involved remain largely unknown. Copper, which plays an essential role in cardiovascular disease, has been suggested as a potential risk factor. Copper homeostasis is closely related to the occurrence and development of AS. Recently, a new cell death pathway called cuproptosis has been discovered, which is driven by intracellular copper excess. However, no previous studies have reported a relationship between cuproptosis and AS. In this study, we integrated bulk and single-cell sequencing data to screen and identify key cuproptosis-related genes in AS. We used correlation analysis, enrichment analysis, random forest, and other bioinformatics methods to reveal their relationships. Our findings report, for the first time, the involvement of cuproptosis-related genes FDX1, SLC31A1, and GLS in atherogenesis. FDX1 and SLC31A1 were upregulated, while GLS was downregulated in atherosclerotic plaque. Receiver operating characteristic curves demonstrate their potential diagnostic value for AS. Additionally, we confirm that GLS is mainly expressed in vascular smooth muscle cells, and SLC31A1 is mainly localized in macrophages of atherosclerotic lesions in experiments. These findings shed light on the cuproptosis landscape and potential diagnostic biomarkers for AS, providing further evidence about the vital role of cuproptosis in atherosclerosis progression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".