Method for isolation and molecular characterization of extracellular microvesicles released from brain endothelial cells
Bibliographic record
Abstract
BACKGROUND: In addition to possessing intracellular vesicles, eukaryotic cells also produce extracellular microvesicles, ranging from 50 to 1000 nm in diameter that are released or shed into the microenvironment under physiological and pathological conditions. These membranous extracellular organelles include both exosomes (originating from internal vesicles of endosomes) and ectosomes (originating from direct budding/shedding of plasma membranes). Extracellular microvesicles contain cell-specific collections of proteins, glycoproteins, lipids, nucleic acids and other molecules. These vesicles play important roles in intercellular communication by acting as carrier for essential cell-specific information to target cells. Endothelial cells in the brain form the blood-brain barrier, a specialized interface between the blood and the brain that tightly controls traffic of nutrients and macromolecules between two compartments and interacts closely with other cells forming the neurovascular unit. Therefore, brain endothelial cell extracellular microvesicles could potentially play important roles in 'externalizing' brain-specific biomarkers into the blood stream during pathological conditions, in transcytosis of blood-borne molecules into the brain, and in cell-cell communication within the neurovascular unit. METHODS: To study cell-specific molecular make-up and functions of brain endothelial cell exosomes, methods for isolation of extracellular microvesicles using mass spectrometry-compatible protocols and the characterization of their signature profiles using mass spectrometry -based proteomics were developed. RESULTS: A total of 1179 proteins were identified in the isolated extracellular microvesicles from brain endothelial cells. The microvesicles were validated by identification of almost 60 known markers, including Alix, TSG101 and the tetraspanin proteins CD81 and CD9. The surface proteins on isolated microvesicles could potentially interact with both primary astrocytes and cortical neurons, as cell-cell communication vesicles. Finally, brain endothelial cell extracellular microvesicles were shown to contain several receptors previously shown to carry macromolecules across the blood brain barrier, including transferrin receptor, insulin receptor, LRPs, LDL and TMEM30A. CONCLUSIONS: The methods described here permit identification of the molecular signatures for brain endothelial cell-specific extracellular microvesicles under various biological conditions. In addition to being a potential source of useful biomarkers, these vesicles contain potentially novel receptors known for delivering molecules across the blood-brain barrier.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".