Pericytes as mediators of infiltration of macrophages in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is a neurodegenerative condition of the central nervous system (CNS). It is associated with blood-brain barrier (BBB) breakdown and intravasation of leukocytes, particularly monocyte-derived macrophages, into the CNS. Pericytes are mural cells that are encased within the basement membrane of vasculature, and they contribute functionally to the neurovascular unit. These cells play an important role in maintaining BBB integrity and CNS homeostasis. However, the critical role of pericytes in mediating inflammation in MS or its models is unclear. Whether pericytes infiltrate into the CNS parenchyma in MS also needs clarification. METHODS: CNS samples from the experimental autoimmune encephalomyelitis (EAE) mouse model of MS were collected at different time points for immunohistochemical analysis of pericytes along the inflamed vasculature. These findings were validated using MS brain specimens, and further analysis of pericyte involvement in inflammation was carried out by culturing primary pericytes and macrophages. Multiplex ELISA, transmigration assay and real-time PCR were used to study the inflammatory potential of pericytes in cultures. RESULTS: We found that pericytes exhibit a heterogenous morphology, with notable elongation in the inflamed perivascular cuffs of EAE. This was manifested by a decrease in pericyte density but an increase in the coverage by pericytes along the vasculature. Chondroitin sulfate proteoglycans (CSPGs), a family of extracellular matrix proteins enriched within inflamed perivascular cuffs, elevated levels of pro-inflammatory chemokines/cytokines in pericytes in culture. Importantly, pericytes stimulated with CSPGs enhanced macrophage migration. We did not detect pericytes in the CNS parenchyma during EAE, and this was corroborated in MS brain samples. CONCLUSIONS: Our data suggest that pericytes seek to restore the BBB through increased coverage, but that their exposure to CSPGs prompt their facilitation of macrophages to enter the CNS to elevate neuroinflammation in EAE and MS.
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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 | 0.001 | 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 | 0.000 |
| 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".