Single-Cell Transcriptomics Identifies Brain Endothelium Inflammatory Networks in Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease characterized by infiltration of immune cells in multifocal areas of the CNS. The specific molecular processes allowing autoreactive immune cells to enter the CNS compartment through the blood-brain barrier remain elusive. METHODS: Using endothelial cell (EC) enrichment and single-cell RNA sequencing, we characterized the cells implicated in the neuroinflammatory processes in experimental autoimmune encephalomyelitis, an animal model of MS. Validations on human MS brain sections of the most differentially expressed genes in venous ECs were performed using immunohistochemistry and confocal microscopy. RESULTS: ) in MS lesions. DISCUSSION: In this study, we provide a landscape of the cellular heterogeneity associated with neuroinflammation. We also present important molecular insights for further exploration of specific cell processes that promote infiltration of immune cells inside the brain of experimental autoimmune encephalomyelitis mice.
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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 | 0.000 |
| 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".