Altered Protein Expression of Cardiac CYP2J and Hepatic CYP2C, CYP4A, and CYP4F in a Mouse Model of Type II Diabetes—A Link in the Onset and Development of Cardiovascular Disease?
Bibliographic record
Abstract
Arachidonic acid can be metabolized by cytochrome P450 (CYP450) enzymes in a tissue- and cell-specific manner to generate vasoactive products such as epoxyeicosatrienoic acids (EETs-cardioprotective) and hydroxyeicosatetraenoic acids (HETEs-cardiotoxic). Type II diabetes is a well-recognized risk factor for developing cardiovascular disease. A mouse model of Type II diabetes (C57BLKS/J-db/db) was used. After sacrifice, livers and hearts were collected, washed, and snap frozen. Total proteins were extracted. Western blots were performed to assess cardiac CYP2J and hepatic CYP2C, CYP4A, and CYP4F protein expression, respectively. Significant decreases in relative protein expression of cardiac CYP2J and hepatic CYP2C were observed in Type II diabetes animals compared to controls (CYP2J: 0.80 ± 0.03 vs. 1.05 ± 0.06, n = 20, p < 0.001); (CYP2C: 1.56 ± 0.17 vs. 2.21 ± 0.19, n = 19, p < 0.01). In contrast, significant increases in relative protein expression of both hepatic CYP4A and CYP4F were noted in Type II diabetes mice compared to controls (CYP4A: 1.06 ± 0.09 vs. 0.18 ± 0.01, n = 19, p < 0.001); (CYP4F: 2.53 ± 0.22 vs. 1.10 ± 0.07, n = 19, p < 0.001). These alterations induced by Type II diabetes in the endogenous pathway (CYP450) of arachidonic acid metabolism may increase the risk for cardiovascular disease by disrupting the fine equilibrium between cardioprotective (CYP2J/CYP2C-generated) and cardiotoxic (CYP4A/CYP4F-generated) metabolites of arachidonic acid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".