Peroxisome biogenesis disorders: Biological, clinical and pathophysiological perspectives
Bibliographic record
Abstract
The peroxisome biogenesis disorders (PBD) are a heterogeneous group of autosomal recessive disorders in which peroxisome assembly is impaired, leading to multiple peroxisome enzyme deficiencies, complex developmental sequelae and progressive disabilities. Mammalian peroxisome assembly involves the protein products of 16 PEX genes; defects in 14 of these have been shown to cause PBD. Three broad phenotypic groups are described on a spectrum of severity: Zellweger syndrome is the most severe, neonatal adrenoleukodystrophy is intermediate and infantile Refsum disease is less severe. Another group is Rhizomelic chondrodysplasia punctata spectrum. Recently, atypical phenotypes have been described, indicating that the full spectrum of these disorders remains to be identified. For most patients, there is a correlation between clinical severity and effect of the mutation on PEX protein function. Diagnosis relies on biochemical measurements of peroxisome functions and PEX gene sequencing. There are no targeted therapies, although management protocols have been suggested and research endeavors continue. In this review we will discuss peroxisome biology and PBD, and research contributions to pathophysiology and treatment.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 0.002 |
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".