Cytochrome P450 enzymes and the heart
Bibliographic record
Abstract
The cytochrome P450 monooxygenase system (CYP) is a multigene superfamily of heme-thiolate enzymes, which are important in the metabolism of foreign and endogenous compounds. Genetic variations, drug interactions, or pathophysiological factors can lead to reduced, absent, or increased enzymatic activity. This altered CYP activity greatly influences an individual's response to therapeutic treatment. What is not known is the impact of these changes on the many functional roles of CYP in physiological and pathophysiological processes of the heart. Many extrahepatic tissues, like heart, contain active P450 enzymes but lack information regarding their role in cellular injury or homeostasis. Much of our current knowledge about cardiac CYP has been limited to studies investigating the role of fatty acid metabolites in heart. Traditional risk factors including diabetes, smoking, and hypertension have well established links to cardiovascular disease. And new evidence strongly suggests exposure to chemicals and other environmental agents has a profound impact on the cardiovascular system. These risk factors can independently affect the expression and activity of CYP enzymes. Therefore, altered CYP activity is important from a detoxification as well as a bioactivation perspective. Considering CYP, interactions are greatly dependent on inherited differences or acquired changes in enzyme activity further research into their potential impact on pathogenesis, risk assessment, and therapy of heart disease is warranted. This review explores the expression of CYP isoforms, their functional roles, and the effects of genetic variation in the heart.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".