VEGFR2 signaling drives meningeal vascular regeneration upon head injury
Bibliographic record
Abstract
Upon severe head injury (HI), blood vessels of the meninges and brain parenchyma are inevitably damaged. While limited vascular regeneration of the injured brain has been studied extensively, our understanding of meningeal vascular regeneration following head injury is quite limited. Here, we identify key pathways governing meningeal vascular regeneration following HI. Rapid and complete vascular regeneration in the meninges is predominantly driven by VEGFR2 signaling. Substantial increase of VEGFR2 is observed in both human patients and mouse models of HI, and endothelial cell-specific deletion of Vegfr2 in the latter inhibits meningeal vascular regeneration. We further identify the facilitating, stabilizing and arresting roles of Tie2, PDGFRβ and Dll4 signaling, respectively, in meningeal vascular regeneration. Prolonged inhibition of this angiogenic process following HI compromises immunological and stromal integrity of the injured meninges. These findings establish a molecular framework for meningeal vascular regeneration after HI, and may guide development of wound healing therapeutics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".