An integrative layer-resolved atlas of the adult human meninges
Bibliographic record
Abstract
Abstract The human meninges are a dynamic tri-layered brain border that plays a key role in brain development, CSF homeostasis, immune regulation, and higher-level brain function. The meninges have also been implicated in central nervous system (CNS) pathologies such as infection, autoimmunity, and brain trauma. To understand how the meningeal microenvironment is altered under pathological conditions it is necessary to have a complete understanding of its normotypic cellular architecture and function. To date, there is no complete atlas of the normotypic adult human meninges. By surgically extracting each human meningeal layer during surgery, we generated the first layer-resolved map of all meningeal cell types via an integration of whole cell single cell RNA sequencing, multiplexed error-robust fluorescence in situ hybridization (MERFISH), and protein immunolabelling. Since fibroblasts play key roles in meningeal homeostasis yet remain less well-characterised than other meningeal cell types, we deeply phenotyped these cells in all layers. We identified 10 fibroblast subpopulations with unique predicted functions that localise to distinct neuroanatomical niches. Fibroblast interaction analysis in the dura and subarachnoid space (SAS) uncovered novel interactions with vascular cell populations mediated by insulin growth factor signaling. Together, these data serve as a comprehensive resource for future investigations of meningeal function in the healthy and diseased brain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".