Molecular Pathways and Crosstalk Characterizing the Cardiorenal Syndrome
Why this work is in the frame
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Bibliographic record
Abstract
The risk of developing cardiovascular diseases (CVD) is dramatically increased in patients with chronic kidney diseases (CKD). Mechanisms leading to this cardiorenal syndrome (CRS) are multifactorial, and combined analyses of both failing organs may provide routes toward developing strategies for early risk assessment, prognosis, and consequently effective therapy. In order to identify molecular mechanisms involved in the crosstalk between the diseased cardiovascular system and kidney, we analyzed tissue specific transcriptomics profiles on atherosclerosis and diabetic nephropathy together with gene sets associated with cardiovascular and chronic kidney diseases that derived from a literature mining approach. We focused on enriched molecular pathways and highlight molecular interactions found within as well as between affected pathways identified for the two organs. Analysis on the level of molecular pathways pointed out the role of PPAR signaling, coagulation, inflammation, and focal adhesion pathways in formation and progression of the CRS. The proteins apolipoprotein A1 (APOA1) and albumin (ALB) turned out to be of particular importance in the context of dyslipidemia, one of the major risk factors for the development of CVD. In summary, our analyses highlight mechanisms associated with dyslipidemia, hemodynamic regulation, and inflammation on the interface between the cardiovascular and the renal system.
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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 | 0.000 |
| 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 it