In vivo solid phase microextraction for therapeutic monitoring and pharmacometabolomic fingerprinting of lung during in vivo lung perfusion of FOLFOX
Bibliographic record
Abstract
In vivo lung perfusion (IVLP) is a novel isolated lung technique developed to enable the local, in situ administration of high-dose chemotherapy to treat metastatic lung cancer. Combination therapy using folinic acid (FOL), 5-fluorouracil (F), and oxaliplatin (OX) (FOLFOX) is routinely employed to treat several types of solid tumours in various tissues. However, F is characterized by large interpatient variability with respect to plasma concentration, which necessitates close monitoring during treatments using of this compound. Since plasma drug concentrations often do not reflect tissue drug concentrations, it is essential to utilize sample-preparation methods specifically suited to monitoring drug levels in target organs. In this work, in vivo solid-phase microextraction (in vivo SPME) is proposed as an effective tool for quantitative therapeutic drug monitoring of FOLFOX in porcine lungs during pre-clinical IVLP and intravenous (IV) trials. The concomitant extraction of other endogenous and exogenous small molecules from the lung and their detection via liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) enabled an assessment of FOLFOX's impact on the metabolomic profile of the lung and revealed the metabolic pathways associated with the route of administration (IVLP vs. IV) and the therapy itself. This study also shows that the immediate instrumental analysis of metabolomic samples is ideal, as long-term storage at -80 °C results in changes in the metabolite content in the sample extracts.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".