Non-classical monocytes promote neurovascular repair in cerebral small vessel disease associated with microinfarctions via CX3CR1
Bibliographic record
Abstract
Cerebral small vessel disease (cSVD) constitutes a major risk factor for dementia. Monocytes play important roles in cerebrovascular disorders. Herein, we aimed to investigate the contribution of non-classical C-X3-C motif chemokine receptor (CX3CR)1 monocytes to cSVD pathobiology and therapy. To this end, we generated chimeric mice in which CX3CR1 in non-classical monocytes was either functional (CX3CR1 GFP/+ ) or dysfunctional (CX3CR1 GFP/GFP ). cSVD was induced in mice via the micro-occlusion of cerebral arterioles, and novel immunomodulatory approaches targeting CX3CR1 monocyte production were used. Our findings demonstrate that CX3CR1 GFP/+ monocytes transiently infiltrated the ipsilateral hippocampus and were recruited to the microinfarcts 7 days after cSVD, inversely associated with neuronal degeneration and blood-brain barrier (BBB) disruption. Dysfunctional CX3CR1 GFP/GFP monocytes failed to infiltrate the injured hippocampus and were associated with exacerbated microinfarctions and accelerated cognitive decline, accompanied with an impaired microvascular structure. Pharmacological stimulation of CX3CR1 GFP/+ monocyte generation attenuated neuronal loss and improved cognitive functions by promoting microvascular function and preserving cerebral blood flow (CBF). These changes were associated with elevated levels of pro-angiogenic factors and matrix stabilizers in the blood circulation. The results indicate that non-classical CX3CR1 monocytes promote neurovascular repair after cSVD and constitute a promising target for the development of new therapies.
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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".