The Proteome of Mouse Cerebral Arteries
Bibliographic record
Abstract
The cerebral vasculature ensures proper cerebral function by transporting oxygen, nutrients, and other substances to the brain. Distribution of oxygenated blood throughout the neuroaxis takes place at the level of the circle of Willis (CW). While morphologic and functional alterations in CW arteries and its main branches have been reported in cerebrovascular and neurodegenerative diseases, accompanying changes in protein expression profiles remain largely uncharacterized. In this study, we performed proteomics to compile a novel list of proteins present in mouse CW arteries and its ramifications. Circle of Willis arteries were surgically removed from 6-month-old wild-type mice, proteins extracted and analyzed by two proteomics approaches, gel-free nanoLC-mass spectrometry (MS)/MS and gel-based GelLC-MS/MS, using nanoAcquity UPLC coupled with ESI-LTQ Orbitrap XL. The two approaches helped maximize arterial proteome coverage. Six biologic and two technical replicates were performed. In all, 2,188 proteins with at least 2 unique high-scoring peptides were identified (6,630 proteins total). Proteins were classified according to vasoactivity, blood-brain barrier specificity, tight junction and adhesion molecules, membrane transporters/channels, and extracellular matrix/basal lamina proteins. Furthermore, we compared the identified CW arterial proteome with the published brain microvascular proteome. Our database provides a vital resource for the study of CW cerebral arterial protein expression profiles in health and disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".