Analysis of Human Saliva Metabolome by Direct Immersion Solid-Phase Microextraction LC and Benchtop Orbitrap MS
Bibliographic record
Abstract
BACKGROUND: Saliva samples collected from one 58 year old male and one 35 year old female during 7 days of fasting were analyzed by direct immersion of both C18 and mixed-mode biocompatible solid-phase microextraction fibers, in combination with a LC-MS method using a benchtop orbitrap instrument in both positive and negative ionization modes, in order to evaluate the difference in terms of metabolite coverage. RESULTS: The mixed-mode coating provided better results, with the simultaneous extraction of a higher number of both hydrophilic and hydrophobic metabolites. The ability of detected features to distinguish differences between the individuals and changes in saliva metabolome induced by diet was also demonstrated. CONCLUSION: Saliva may be useful for medical diagnostics as it is non-invasive. The use of biocompatible solid-phase microextraction fibers can play an important role as an alternative sample preparation method for untargeted LC-MS metabolomics studies on human saliva because it provides simultaneous extraction of metabolites with a wide range of polarity, thus allowing the detection of changes in metabolic pathways with unsupervised statistical analyses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".