Toward three-dimensional in vitro models to study neurovascular unit functions in health and disease
Bibliographic record
Abstract
The high metabolic demands of the brain require an efficient vascular system to be coupled with neural activity to supply adequate nutrients and oxygen. This supply is coordinated by the action of neurons, glial and vascular cells, known collectively as the neurovascular unit, which temporally and spatially regulate local cerebral blood flow through a process known as neurovascular coupling. In many neurodegenerative diseases, changes in functions of the neurovascular unit not only impair neurovascular coupling but also permeability of the blood-brain barrier, cerebral blood flow and clearance of waste from the brain. In order to study disease mechanisms, we need improved physiologically-relevant human models of the neurovascular unit. Advances towards modeling the cellular complexity of the neurovascular unit in vitro have been made using stem-cell derived organoids and more recently, vascularized organoids, enabling intricate studies of non-cell autonomous processes. Engineering and design innovations in microfluidic devices and tissue engineering are progressing our ability to interrogate the cerebrovasculature. These advanced models are being used to gain a better understanding of neurodegenerative disease processes and potential therapeutics. Continued innovation is required to build more physiologically-relevant models of the neurovascular unit encompassing both the cellular complexity and designed features to interrogate neurovascular unit functionality.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".