Cytochrome P450 Regulation and Drug Biotransformation During Inflammation and Infection
Bibliographic record
Abstract
The expression of cytochrome P450 and related biotransformation is altered during the operation of host defense mechanisms. This has major implications in inflammation and infection when the capacity of the liver and other organs to handle drugs is severely compromised. In most cases individual cytochrome P450 forms are down regulated at the level of gene transcription with a resulting decrease in the corresponding mRNA, protein and enzyme activity. The loss in drug metabolism is channeled predominantly through the production of cytokines which ultimately modify specific transcription factors. Other proposed mechanisms that apply to specific cytochrome P450s involve post translational steps including enzyme modification and increased degradation. When inflammatory responses are confined to the brain there is a loss of cytochrome P450 not only in the brain but also in peripheral tissues. This involves a yet to be identified mode of signaling between the brain and periphery but it does involve the production of cytokines from a peripheral source. In clinical medicine there are numerous examples of a decreased capacity to handle drugs during infections and disease states that involve an inflammatory component. This often results in altered drug responses and increased toxicities. Inflammation mediated alterations in the metabolism of endogenous compounds can lead to altered physiology. Changes in drug handling capacity during inflammation/infection will continue to be one of the many factors that complicate therapeutics.
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) | 0.003 | 0.003 |
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".