Argininosuccinic aciduria: Recent pathophysiological insights and therapeutic prospects
Bibliographic record
Abstract
The first patients affected by argininosuccinic aciduria (ASA) were reported 60 years ago. The clinical presentation was initially described as similar to other urea cycle defects, but increasing evidence has shown overtime an atypical systemic phenotype with a paradoxical observation, that is, a higher rate of neurological complications contrasting with a lower rate of hyperammonaemic episodes. The disappointing long-term clinical outcomes of many of the patients have challenged the current standard of care and therapeutic strategy, which aims to normalize plasma ammonia and arginine levels. Interrogations have raised about the benefit of newborn screening or liver transplantation on the neurological phenotype. Over the last decade, novel discoveries enabled by the generation of new transgenic argininosuccinate lyase (ASL)-deficient mouse models have been achieved, such as, a better understanding of ASL and its close interaction with nitric oxide metabolism, ASL physiological role outside the liver, and the pathophysiological role of oxidative/nitrosative stress or excessive arginine treatment. Here, we present a collaborative review, which highlights these recent discoveries and novel emerging concepts about ASL role in human physiology, ASA clinical phenotype and geographic prevalence, limits of current standard of care and newborn screening, pathophysiology of the disease, and emerging novel therapies. We propose recommendations for monitoring of ASA patients. Ongoing research aims to better understand the underlying pathogenic mechanisms of the systemic disease to design novel therapies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".