Metabolomic Analysis of Serum and Placenta in Preeclampsia
Bibliographic record
Abstract
Abstract Background: Preeclampsia (PE) is one of the main causes of maternal and fetal morbidity and mortality worldwide. This study was aimed to explore the potential metabolic alterations in women diagnosed with PE and reveal the underlying pathogenesis of disease. Methods; Healthy pregnant women and patients diagnosed with PE were recruited from August 2017 to February 2018. The metabolomic analysis of serum (n=90) and placenta (n=9) samples collected from the two groups were performed with the high performance liquid chromatography coupled with quadrupole-time-of light mass spectrometry (HPLC-QTOF-MS). Results: In serum, 16 metabolites that were present in different concentrations between the two groups were identified, of which pyroglutamic acid (pGlu), methionine, glutamine and taurocholic acid may be used as potential PE diagnosis biomarkers with the area under ROC curve of 0.901, 0.909, 0.892 and 0.873 respectively. Furthermore, the metabolic pathways analysis with differential metabolites in serum and placenta samples showed that linoleic acid and alpha- linolenic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, D-glutamine/D-glutamate metabolism, phenylalanine metabolism, glutathione metabolism and tryptophan metabolism were significantly altered and might be involved in PE pathogenesis. Conclusions: These results showed the altered metabolic pathways could contribute to the pathophysiologic mechanisms of PE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.009 |
| 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 teacher head, 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".