Hypoxia-induced <i>MIR155</i> is a potent autophagy inducer by targeting multiple players in the MTOR pathway
Bibliographic record
Abstract
Hypoxia activates autophagy, an evolutionarily conserved cellular catabolic process. Dysfunction in the autophagy pathway has been implicated in an increasing number of human diseases, including cancer. Hypoxia induces upregulation of a specific set of microRNAs (miRNAs) in a variety of cell types. Here, we describe hypoxia-induced MIR155 as a potent inducer of autophagy. Enforced expression of MIR155 increases autophagic activity in human nasopharyngeal cancer and cervical cancer cells. Knocking down endogenous MIR155 inhibits hypoxia-induced autophagy. We demonstrated that MIR155 targets multiple players in MTOR signaling, including RHEB, RICTOR, and RPS6KB2. MIR155 suppresses target-gene expression by directly interacting with their 3' untranslated regions (UTRs), mutations of the binding sites abolish their MIR155 responsiveness. Furthermore, by downregulating MTOR signaling, MIR155 also attenuates cell proliferation and induces G 1/S cell cycle arrest. Collectively, these data present a new role for MIR155 as a key regulator of autophagy via dysregulation of MTOR pathway.
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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".