Mild chronic cerebral hypoperfusion induces neurovascular dysfunction, triggering peripheral beta-amyloid brain entry and aggregation
Bibliographic record
Abstract
BACKGROUND: The Blood-brain barrier (BBB) controls brain supply with oxygen and nutrients, and protects the brain from toxic metabolites, such as beta-amyloid (Aβ) peptides. The neurovascular unit (NVU) couples vascular and neuronal functions by controlling BBB parameters based on brain needs. As such, NVU/BBB dysfunction, associated to irregularities in cerebral blood flow (CBF), has been proposed to contribute in the pathogenesis of Alzheimer's disease (AD), mainly by impairing cerebral Aβ clearance. However, the spatiotemporal contribution of the NVU/BBB in the neurodegenerative cascades remains elusive. RESULTS: By using C57BL/6J mice subjected to right common carotid artery (rCCA) permanent ligation in order to induce mild chronic cerebral hypoperfusion, we show here that cerebral hypoperfusion induced NVU dysfunction by reducing ABCB1 protein expression in brain capillaries. ABCB1 reduction was mainly triggered by an enhanced Glycogen Synthase Kinase 3 (GSK3β) activation, which decreased β-catenin nuclear abundance. Moreover, cerebral hypoperfusion triggered early vascular deposition of peripherally applied human Aβ1-42 peptides, which has shifted from highly vascular to the parenchyma 6 weeks later, forming small stable Aβ deposits. Hypoperfusion induced a deregulation in glucose metabolism, as brain reperfusion, or the administration of a high dose of glucose, diminished GSK3β activation, recuperated β-catenin nuclear abundance, reestablished ABCB1 protein expression, and prevented Aβ vascular early deposition. These results demonstrate that mild chronic cerebral hypoperfusion creates a metabolically deregulated microenvironment, thus triggering the brain entry and aggregation of peripherally applied human Aβ1-42 peptides. CONCLUSION: Our study offers new insights on the initiation of the neurodegenerative cascades observed in AD, which could be valuable in developing adequate treatment strategies.
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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) | 0.000 | 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".