Bibliographic record
Abstract
Cytochrome P450 (CYP450) enzymes have the capability of playing key metabolic roles in several aspects of cancer as a consequence of their unusually broad substrate specificities. CYP450 are also prominent players in the metabolism of anticancer therapeutic drugs, enhancing or diminishing the efficacy of the drugs depending on whether the drug or its metabolites are efficacious. As CYP450 enzymes are also found in lung tissue, lung metabolism can be of importance to the bioactivation of some anticancer agents. The presence of individual forms of CYP450 has been investigated in lung tumor to determine whether intra-tumor metabolism of anticancer agents by CYP450 could occur and thus influence the response of tumor to these agents. Differences in drug metabolism between normal and cancerous lung tissue have been shown to exist, therefore; the variable expression of CYP450 between tumor and normal tissue can provide a basis for selective sensitivity of tissue to anticancer drugs, thereby localizing drug actions to tumor. This review gives a detailed picture of the expression of CYP450 in lung tumor and the role of this enzyme in lung tumor in the fate of anticancer drugs.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".