Differences in Gene Expression Profiles of Diabetic and Nondiabetic Patients Undergoing Cardiopulmonary Bypass and Cardioplegic Arrest
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus is an independent risk factor for early postoperative mortality and complications after coronary artery bypass grafting (CABG). We sought to compare the cardiac gene expression responses to cardiopulmonary bypass (CPB) and cardioplegic arrest (C) in patients with and without diabetes. METHODS AND RESULTS: Twenty atrial myocardium samples were harvested from 5 type II insulin-dependent diabetic and 5 matched nondiabetic patients undergoing CABG, before and after CPB/C. Oligonucleotide microarray analyses of 12625 genes were performed on the 10 sample pairs using matched pre-CPB tissues as controls. Array results were validated with Northern blotting and immunoblotting. Compared with pre-CPB/C, post-CPB/C myocardial tissues revealed 851 upregulated and 480 downregulated genes with a threshold P< or =0.025 (signal-to-noise ratio, 4.04) in the diabetic group, compared with 480 upregulated and 626 downregulated genes (signal-to-noise ratio, 3.04) in the nondiabetic group (P<0.001). There were 18 genes that were upregulated >4-fold in diabetic and nondiabetic patients (including inflammatory/transcription activators FOS, CYR 61, and IL-6, apoptotic gene NR4A1, stress gene DUSP1, and glucose-transporter gene SLC2A3). However, 28 genes showed such marked upregulation in the diabetic group exclusively (including inflammatory/transcription activators MYC, IL8, IL-1beta, growth factor vascular endothelial growth factor, amphiregulin, and glucose metabolism-involved gene insulin receptor substrate 1), and 27 genes in the nondiabetic group only, including glycogen-binding subunit PPP1R3C. CONCLUSIONS: Gene expression profile after CPB/C is quantitatively and qualitatively different in patients with diabetes. These results have important implications for the design of tailored myocardial protection and operative strategies for diabetic patients undergoing CPB/C.
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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) | 0.000 | 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) | 0.001 | 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 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".