Pharmacological inhibition of Peroxisome Proliferation-Activated Receptor Delta (PPARδ) imparts selective leukemia cell death
Bibliographic record
Abstract
BACKGROUND: Acute myeloid leukemia (AML) is a devastating hematological malignancy with limited therapeutic options and poor survival outcomes. Therefore, the development of novel and selective anti-AML therapies is needed. 6-methoxydihydroavicine (6ME), a benzophenanthridine alkaloid, imparted selective AML cell death in vitro and in vivo. Mechanistically, 6ME inhibited fatty acid oxidation (FAO) by binding to and decreasing the activity of PPARδ, a transcription factor involved in FAO. METHODS: AML cell lines and patient-derived cells were used to assess the activity of 6ME in vitro and in vivo. Computational methods, immunoblotting, and co-IP-HPLC analysis assessed the molecular target, and cellular consequence of 6ME activity. RESULTS: : 1.0 ± 0.13 μM) and patient-derived cells while sparing normal hematopoietic cells. Mouse engraftment studies showed that 6ME (5 mg/kg, three times/week for 4 weeks) selectively reduced patient-derived AML cell engraftment without affecting hematopoietic cell engraftment or imparting toxicity. Mechanistically, 6ME bound to and inhibited PPARδ leading to downregulated FAO gene expression (i.e., CD36 and CPT2) and reduced fatty acid cellular uptake resulting in FAO inhibition. CONCLUSION: Pharmacological inhibition of PPARδ with 6ME is a novel approach to inducing selective death in AML.
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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".