The Role of Pericytes in Neurovascular Unit Remodeling in Brain Disorders
Bibliographic record
Abstract
Neurons are extremely vulnerable cells that tightly rely on the brain's highly dynamic and complex vascular network that assures an accurate and adequate distribution of nutrients and oxygen. The neurovascular unit (NVU) couples neuronal activity to vascular function, controls brain homeostasis, and maintains an optimal brain microenvironment adequate for neuronal survival by adjusting blood-brain barrier (BBB) parameters based on brain needs. The NVU is a heterogeneous structure constituted by different cell types that includes pericytes. Pericytes are localized at the abluminal side of brain microvessels and contribute to NVU function. Pericytes play essential roles in the development and maturation of the neurovascular system during embryogenesis and stability during adulthood. Initially, pericytes were described as contractile cells involved in controlling neurovascular tone. However, recent reports have shown that pericytes dynamically respond to stress induced by injury upon brain diseases, by chemically and physically communicating with neighboring cells, by their immune properties and by their potential pluripotent nature within the neurovascular niche. As such, in this paper, we would like to review the role of pericytes in NVU remodeling, and their potential as targets for NVU repair strategies and consequently neuroprotection in two pathophysiologically distinct brain disorders: ischemic stroke and Alzheimer's disease (AD).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".