The liver and muscle secreted HFE2-protein maintains central nervous system blood vessel integrity
Bibliographic record
Abstract
Liver failure causes breakdown of the Blood CNS Barrier (BCB) leading to damages of the Central-Nervous-System (CNS), however the mechanisms whereby the liver influences BCB-integrity remain elusive. One possibility is that the liver secretes an as-yet to be identified molecule(s) that circulate in the serum to directly promote BCB-integrity. To study BCB-integrity, we developed light-sheet imaging for three-dimensional analysis. We show that liver- or muscle-specific knockout of Hfe2/Rgmc induces BCB-breakdown, leading to accumulation of toxic-blood-derived fibrinogen in the brain, lower cortical neuron numbers, and behavioral deficits in mice. Soluble HFE2 competes with its homologue RGMa for binding to Neogenin, thereby blocking RGMa-induced downregulation of PDGF-B and Claudin-5 in endothelial cells, triggering BCB-disruption. HFE2 administration in female mice with experimental autoimmune encephalomyelitis, a model for multiple sclerosis, prevented paralysis and immune cell infiltration by inhibiting RGMa-mediated BCB alteration. This study has implications for the pathogenesis and potential treatment of diseases associated with BCB-dysfunction.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".