Distribution of Curcumin and THC in Peripheral Blood Mononuclear Cells Isolated from Healthy Individuals and Patients with Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
Background/Aim: Curcumin is being widely investigated for its anticancer properties and studies in the literature suggest that curcumin distributes to a higher degree in tumor versus non-tumor cells. In the current study, we report on investigation of the distribution of curcumin and metabolism to THC in PBMC from healthy individuals and chronic lymphocytic leukemia (CLL) patients following exposure to Lipocurc™ (liposomal curcumin). Materials and Methods: The time and temperature-dependent distribution of liposomal curcumin and metabolism to tetrahydrocurcumin (THC) were measured in vitro in human peripheral blood mononuclear cells (PBMC) obtained from healthy individuals, PBMCHI(cryopreserved and freshly isolated PBMC) and CLL patients (cryopreserved PBMC) with lymphocyte counts ranging from 17-58×106 cells/ml (PBMCCLL,Grp 1) and >150×106 cells/ml (PBMCCLL,Grp 2). PBMC were incubated in plasma protein supplemented media with Lipocurc™ for 2-16 min at 37°C and 4°C and the cell and medium levels of curcumin determined by LC-MS/MS. Results: PBMC from CLL patients displayed a 2.2-2.6-fold higher distribution of curcumin compared to PBMCHI. Curcumin distribution into PBMCCLL, Grp 1/Grp 2 ranged from 384.75 - 574.50 ng/g w.w. of cell pellet and was greater compared to PBMCHIthat ranged from 122.27-220.59 ng/g w.w. of cell pellet following incubation for up to 15-16 min at 37°C. The distribution of curcumin into PBMCCLL,Grp 2 was time-dependent in comparison to PBMCHIwhich did not display a time-dependence and there was no temperature-dependence for curcumin distribution in either cell type. Curcumin was metabolized to THC in PBMC. The metabolism of curcumin to THC was not markedly different between PBMCHI(range=23.94-42.04 ng/g w.w. cell pellet) and PBMCCLL,Grp 1/Grp 2 (range=23.08-48.22 ng/g. w.w. cell pellet). However, a significantly greater time and temperature-dependence was noted for THC in PBMCCLL,Grp 2 compared to PBMCHI. Conclusion: Curcumin distribution into PBMC from CLL patients was higher compared to PBMC from healthy individuals, while metabolism to THC was similar. The potential for a greater distribution of curcumin into PBMC from CLL patients may be of therapeutic benefit.
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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) | 0.002 | 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".