Assessment of whole body cholesterol pool size in Smith‐Lemli‐ Opitz syndrome children using liquid chromatography tandem mass spectrometry
Bibliographic record
Abstract
Smith‐Lemli‐Opitz syndrome (SLOS) patients typically exhibit abnormally low cholesterol, high 7‐dehyrocholesterol (DHC) and 8‐DHC levels in tissues and plasma. Therapeutic intervention for SLOS is aimed at maximizing whole body cholesterol pool size (WBCP) while down‐regulating biosynthesis to decrease the buildup of potentially toxic precursors. The study aim was to develop a sensitive liquid chromatography‐tandem mass spectrometry (LC/MS/MS) method for detection of changes in blood isotope cholesterol enrichment over time, for assessment of WBCP in SLOS patients receiving supplemental dietary cholesterol. Subjects (n=13; mean age: 7±1 yr) were given iv [ 18 O]cholesterol (1.0–1.4 mg/kg bodyweight) or D 7 ‐cholesterol (0.9–1.4 mg/kg). Blood samples were collected at baseline and over a 10 wk period, cholesterol extracted from RBC, derivatized with piconyl ester and analyzed using LC/MS/MS. The [M+H] + >[M‐picolinic acid] + transition was chosen for monitoring, with 18 O‐cholesterol at m/z 494>369 and D 7 ‐cholesterol at 499>376. WBCP was 427.3 ±52.0 mg/kg bodyweight. Plasma cholesterol level was not related to WBCP (p>0.05), but inversely related to 7DHC and 8DHC (p<0.05). In summary, LC/MS/MS is a sensitive method for stable isotopic assessment of WBCP in humans. This study is the first assessment of WBCP in children and in SLOS patients. The data will be a useful reference for a longitudinal SLOS study. Grant Funding Source : NIH
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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 | 0.001 | 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".