A critical overview of the influence of inflammation and infection on P-glycoprotein expression and activity in the brain
Bibliographic record
Abstract
BACKGROUND: P-glycoprotein is a blood-brain barrier efflux transporter that limits drug accumulation in the brain. OBJECTIVE: To review recent in vivo and in vitro investigations that examined the influence of inflammation, infection and related clinical neuroinflammatory disorders on P-glycoprotein expression and activity in the brain. METHODS: Critical overview of English-language studies. RESULTS/CONCLUSIONS: Inflammation and infection produce dynamic changes in P-glycoprotein expression and activity in the blood-brain barrier. In vitro, blood-brain barrier P-glycoprotein activity is downregulated after short-term exposure to inflammatory mediators whereas its activity is upregulated following more prolonged exposure. In vivo studies in both humans and animals have linked CNS inflammation, peripheral inflammation and related clinical neuroinflammatory disorders with alterations in the expression and activity of blood-brain barrier P-glycoprotein. The direction and degree of change in P-glycoprotein activity depends on the in vivo or in vitro model examined, the cell type examined (e.g., endothelial or glial), the inflammatory mediator utilized, the anatomic site in which the inflammatory response was first generated, the time points chosen for observation and the substrates analyzed. Alterations in P-glycoprotein activity affect drug activity in the CNS and seem clinically important.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".