MicroRNA-126 attenuates cell apoptosis by targeting TRAF7 in acute myeloid leukemia cells
Bibliographic record
Abstract
Acute myeloid leukemia (AML) has a 5-year survival rate of only about 30%-40% due to the self-renewal and differentiation ability of leukemia stem-like cells (LSCs). To address the potential for novel therapeutic targets in LSCs, we investigated the roles of miRNA-126 and tumor necrosis factor receptor-associated factor 7 (TRAF7) in AML. We used qRT-PCR and Western blot to investigate the expression levels of miRNA-126 and TRAF7 in AML cell lines. Then, we uncovered the effect of miRNA-126 on AML cell proliferation and apoptosis by MTT assay and flow cytometric analysis, respectively. Furthermore, dual-luciferase assay and Western blot were used to determine the target of miRNA-126 in AML and the potential mechanism by which cell apoptosis is suppressed by miRNA-126. We found that miRNA-126 was highly expressed in all of the AML cell lines, and that inhibition of miRNA-126 significantly induced cell death through apoptosis. The suppression of apoptosis in AML with high expression of miRNA-126 was caused by down-regulating TRAF7, which blocked the c-FLIP pathway. The role of miRNA-126 in AML makes it a potential therapeutic target to improve clinical outcomes for patients with 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 | 0.001 |
| 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".