Stereoselective analysis of 2‐hydroxysebacic acid in urine of patients with Zellweger syndrome and of premature infants fed withmedium‐chain triglycerides
Bibliographic record
Abstract
The chiral metabolite 2-hydroxysebacic acid (2-HS) is considered to be an important diagnostic marker for peroxisomal disorders. The pathway of formation of 2-HS, excreted in increased amounts in patients with peroxisomal diseases, is not absolutely clear. Moreover, there is no information about the enantiomeric distribution of 2-HS in human urine. Here, we describe the stereodifferentiation of 2-HS in urine samples of nine patients with Zellweger syndrome (ZS), and for the first time in urine samples of premature infants fed a medium-chain triglyceride (MCT)-containing diet. Using enantioselective multidimensional gas chromatography-mass spectrometry, an increased excretion of 2R-HS was observed in all investigated ZS patients. 2-HS was also present in urine samples of premature infants fed MCT. Analogously to the ZS patients, a dominant 2R-HS excretion in the urine samples of the premature infants was identified. The formation of 2-HS is expected to result from the same or similar pathways as described for ZS patients. Additionally, we determined the absolute configuration of urinary 3-hydroxysebacic acid (3-HS) in the cases investigated. The enantioselective analysis provides further information for the diagnosis and treatment of patients with impaired peroxisomal fatty acid oxidation. Further insight into the metabolic origin and the biochemical pathway leading to these urinary metabolites is provided.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".