Metabolism and pharmacokinetics of a novel polyphenol fatty acid ester phloridzin docosahexaenoate in Balb/c female mice
Bibliographic record
Abstract
Abstract Flavonoids are known to undergo phase II metabolism and produce metabolites with similar or stronger biological effects compared to the parent flavonoids. However, the limited cellular uptake and bioavailability restrict their clinical use. We synthesized phloridzin docosahexaenoate (PZ-DHA), a novel fatty acid ester of polyphenol, through an acylation reaction with the aim of increasing the cellular availability and stability of the parent biomolecules, phloridzin (PZ) and docosahexaenoic acid (DHA). Here, we report metabolites and pharmacokinetic parameters of PZ-DHA, determined using ultra-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry. PZ-DHA was taken-up by human (MDA-MB-231, MDA-MB-468, and MCF-7) and mouse (4T1) mammary carcinoma and human non-malignant mammary epithelial cells (MCF-10A) in cellular uptake assays. Our results suggested that the acylation improves the cellular uptake of PZ and stability of DHA within cells. In mouse hepatic microsomal assays, two major glucuronides of PZ-DHA, PZ-DHA-4-O-glucuronide and PZ-DHA-4′-O-glucuronide (MW = 923.02 g/mol), were detected. One tri-methylated- (4,4′,6′-O-trimethyl-PZ-DHA) (MW = 788.88 g/mol) and one di-sulphated- (PZ-DHA-4,4′-O-disulphide) PZ-DHA metabolite (MW = 906.20 g/mol) were also identified. Intraperitoneal injections of PZ-DHA (100 mg/kg) into Balb/c female mice was rapidly absorbed with a serum Cmax and Tmax of 23.7 µM and 60 min, respectively, and rapidly eliminated (t1/2 = 28.7 min). PZ-DHA and its metabolites are readily distributed throughout the body (Vd = 57 mL) into many organs. We identified in vitro and in vivo metabolites of PZ-DHA, which could be tested for potential use to treat diseases such as cancer in multiple organ systems.
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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 | 0.001 |
| 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".