Pertussis toxin induces angiogenesis in brain microvascular endothelial cells
Bibliographic record
Abstract
Pertussis toxin (PTX) is an ancillary adjuvant used to elicit experimental allergic encephalomyelitis (EAE), the principal autoimmune model of multiple sclerosis. One mechanism whereby PTX potentiates EAE is to increase blood-brain barrier (BBB) permeability. To elucidate further the mechanism of action of PTX on the BBB, we investigated the genomic and proteomic responses of isolated mouse brain endothelial cells (MBEC) following intoxication. Among approximately 14,000 mouse genes tracked by cDNA microarray, 34 showed altered expression in response to PTX. More than one-third of these genes have roles in angiogenesis. Accordingly, we show that intoxication of MBEC induces tube formation in vitro and angiogenesis in vivo. The global effect of PTX on signaling protein levels and phosphorylation in MBEC was investigated by using Kinex antibody microarrays. In total, 113 of 372 pan-specific and 58 of 258 phospho-site-specific antibodies revealed changes >or=25% following intoxication. Increased STAT1 Tyr-701 and Ser-727 phosphorylation; reduced phosphorylation of the activating phospho-sites in Erk1, Erk2, and MAPKAPK2; and decreased phosphorylation of arrestin beta1 Ser-412 and Hsp27 Ser-82 were confirmed by Kinetworks multi-immunoblotting. The importance of signal transduction pathways on PTX-induced MBEC tube formation was evaluated pharmacologically. Inhibition of phospholipase C, MEK1, and p38 MAP kinase had little effect, whereas inhibition of cAMP-dependent protein kinase, protein kinase C, and phosphatidylinositol 3-kinase partially blocked tube formation. Taken together, these findings are consistent with the concept that PTX may lead to increased BBB permeability by altering endothelial plasticity and angiogenesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".