Induction of Selective Blood-Tumor Barrier Permeability and Macromolecular Transport by a Biostable Kinin B1 Receptor Agonist in a Glioma Rat Model
Bibliographic record
Abstract
Treatment of malignant glioma with chemotherapy is limited mostly because of delivery impediment related to the blood-brain tumor barrier (BTB). B1 receptors (B1R), inducible prototypical G-protein coupled receptors (GPCR) can regulate permeability of vessels including possibly that of brain tumors. Here, we determine the extent of BTB permeability induced by the natural and synthetic peptide B1R agonists, LysdesArg(9)BK (LDBK) and SarLys[dPhe(8)]desArg(9)BK (NG29), in syngeneic F98 glioma-implanted Fischer rats. Ten days after tumor inoculation, we detected the presence of B1R on tumor cells and associated vasculature. NG29 infusion increased brain distribution volume and uptake profiles of paramagnetic probes (Magnevist and Gadomer) at tumoral sites (T(1)-weighted imaging). These effects were blocked by B1R antagonist and non-selective cyclooxygenase inhibitors, but not by B2R antagonist and non-selective nitric oxide synthase inhibitors. Consistent with MRI data, systemic co-administration of NG29 improved brain tumor delivery of Carboplatin chemotherapy (ICP-Mass spectrometry). We also detected elevated B1R expression in clinical samples of high-grade glioma. Our results documented a novel GPCR-signaling mechanism for promoting transient BTB disruption, involving activation of B1R and ensuing production of COX metabolites. They also underlined the potential value of synthetic biostable B1R agonists as selective BTB modulators for local delivery of different sized-therapeutics at (peri)tumoral sites.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".