Acute Inflammatory Response Following Increased Blood-Brain Barrier Permeability Induced by Focused Ultrasound is Dependent on Microbubble Dose
Bibliographic record
Abstract
Rationale: Focused ultrasound (FUS), in conjunction with circulating microbubbles (MBs), can be used to transiently increase the permeability of the blood-brain barrier (BBB) in a targeted manner, allowing therapeutic agents to enter the brain from systemic circulation.While promising preclinical work has paved the way for the initiation of 3 human trials, there remains concern regarding neuroinflammation following treatment.The aim of this study was to assess the magnitude of this response following sonication and explore the influence of MB dose.Methods: Differential expression of NFκB signaling pathway genes was assessed in rats at 6 h and 4 days following a FUS-mediated increase in BBB permeability.Three sonication schemes were tested: (1) a clinical imaging dose of MBs + peak negative pressure (PNP) controlled by acoustic feedback, (2) 10x clinical imaging dose of MBs + constant PNP of 0.290 MPa, and (3) 10x clinical imaging dose of MBs + PNP controlled by acoustic feedback.Follow-up magnetic resonance imaging (MRI) was performed to assess edema and hemorrhage.Hematoxylin and eosin histology was used to evaluate general tissue health.Results: MB dose has a significant impact on the expression of several key genes involved in acute inflammation and immune activation, including Tnf, Birc3, and Ccl2.At a clinical imaging dose of MBs, there were no significant changes detected in the expression of any NFκB signaling pathway genes.Conversely, a high MB dose resulted in a clear activation of the NFκB signaling pathway, accompanied by edema, neuronal degeneration, neutrophil infiltration, and microhemorrhage.Results also suggest that post-FUS gadolinium enhancement may hold predictive value in assessing the magnitude of inflammatory response.Conclusion: While a significant and damaging inflammatory response was observed at high MB doses, it was demonstrated that FUS can be used to induce increased BBB permeability without an associated upregulation of NFκB signaling pathway gene expression.This emphasizes the importance of employing optimized FUS parameters to mitigate the chances of causing injury to the brain at the targeted locations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".