Phloridzin Docosahexaenoate (PZ-DHA) : A Novel Naturally Derived Drug Active in T-Cell Acute Lymphoblastic Leukemia (T-ALL)
Bibliographic record
Abstract
Abstract T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignant disease that accounts for about 15% of pediatric and 25% of adult ALL. Although risk stratification has provided more tailored therapy and improved the overall survival of T-ALL patients, clinical challenges such as suboptimal drug responses, morbidity from drug toxicities, and drug resistance still exist. Plant polyphenols have therapeutic efficacy as pharmacological adjuvants to help overcome these challenges. They can be acylated with fatty acids to overcome issues concerning bioavailability, such as poor intestinal absorption and low metabolic stability. Phloridzin (PZ), a flavonoid found in apple peels, was acylated with an omega-3 fatty acid, docosahexaenoic acid (DHA), to generate a novel ester called phloridzin docosahexaenoate (PZ-DHA). The cytotoxic effect of PZ-DHA was studied in the human Jurkat T-ALL cell line. PZ-DHA significantly reduced the viability and cellular ATP levels of treated cells. PZ-DHA was found to selectively induce apoptosis in Jurkat cells, while sparing normal murine T-cells. Apoptosis was further confirmed by demonstrating the ability of PZ-DHA to induce morphological alterations, DNA fragmentation, caspase activation, and the release of intracellular lactate dehydrogenase. PZ-DHA also significantly inhibited cell division in Jurkat cells. Furthermore, interferon-α-induced phosphorylation of the transcription factor, STAT3, was downregulated following PZ-DHA treatment. The in vitro efficacy of PZ-DHA was recapitulated in vivo in an established zebrafish xenograft model, where the proliferation of transplanted Jurkat cells was inhibited when PZ-DHA was added to the embryo water. Overall, these findings provide evidence for PZ-DHA as a novel therapeutic agent with activity in T-ALL. Studies examining the effect of PZ-DHA on patient-derived ALL cells engrafted in zebrafish are currently underway. Disclosures No relevant conflicts of interest to declare.
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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".