An anti-let-7 sponge decoys and decays endogenous let-7 functions
Bibliographic record
Abstract
The let-7 family contains 12 members, which share identical seed regions, suggesting that they may target the same mRNAs. It is essential to develop a means that can regulate the functions of all members. Using a DNA synthesis technique, we have generated an anti-let-7 sponge aiming to modulate the function of all members. We found that products of the anti-let-7 construct could bind and inactivate all members of the let-7 family, producing decoy and decay effects. To test the role of the anti-let-7 sponge, we stably expressed the anti-let-7 construct in two types of cells, the breast carcinoma cells MT-1 and the oldest and most commonly used human cervical cancer cell line, HeLa cells. We found that expression of anti-let-7 increased cell survival, invasion and adhesion, which corroborate with known functions of let-7 family members. We further identified a novel target site across all species of the let-7 family in hyaluronan synthase 2 (HAS2). HAS2 overexpression produced similar effects as the anti-let-7 sponge. Silencing HAS2 expression by siRNAs produced opposite effects to anti-let-7 on cell survival and invasion. The ability of anti-let-7 to regulate multiple members of the let-7 family allows us to observe their multiple functions using a single reagent. This approach can be applied to other family members with conserved sequences.
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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) | 0.002 | 0.001 |
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".