Arteriovenous malformations in hereditary haemorrhagic telangiectasia: looking beyond ALK1-NOTCH interactions
Bibliographic record
Abstract
Hereditary haemorrhagic telangiectasia (HHT) is characterized by the development of arteriovenous malformations--enlarged shunts allowing arterial flow to bypass capillaries and enter directly into veins. HHT is caused by mutations in ALK1 or Endoglin; however, the majority of arteriovenous malformations are idiopathic and arise spontaneously. Idiopathic arteriovenous malformations differ from those due to loss of ALK1 in terms of both location and disease progression. Furthermore, while arteriovenous malformations in HHT and Alk1 knockout models have decreased NOTCH signalling, some idiopathic arteriovenous malformations have increased NOTCH signalling. The pathogenesis of these lesions also differs, with loss of ALK1 causing expansion of the shunt through proliferation, and NOTCH gain of function inducing initial shunt enlargement by cellular hypertrophy. Hence, we propose that idiopathic arteriovenous malformations are distinct from those of HHT. In this review, we explore the role of ALK1-NOTCH interactions in the development of arteriovenous malformations and examine a possible role of two signalling pathways downstream of ALK1, TMEM100 and IDs, in the development of arteriovenous malformations in HHT. A nuanced understanding of the precise molecular mechanisms underlying idiopathic and HHT-associated arteriovenous malformations will allow for development of targeted treatments for these lesions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".