Comprehensive Analysis of miRNA Regulation of MGAT3 Using the miRFluR Assay
Bibliographic record
Abstract
Studies related to miRNAs and their ability to tune protein expression have gained much attention in recent years. In the field of glycobiology, miRNAs are now given special consideration as they have been shown to be key regulators of many glycosylation pathways. The enzyme MGAT3 (β‐1,4‐mannosyl‐glycoprotein 4‐beta‐N‐acetylglucosaminyltransferase) is responsible for the addition of a bisecting GlcNAc to the core mannose residue of complex or hybrid N‐ glycans. This is a unique modification of complex N‐ glycans that has been reported to play important roles in signal transduction, growth factor signaling, tumor progression and metastasis. In this project, we generated a comprehensive map of the regulation of MGAT3 by miRNA using a newly developed high throughput assay: miRFluR. This assay uses ratiometric analysis of a genetically encoded dual‐color fluorescence reporter (cerulean/mCherry) to identify regulatory miRNA:mRNA interactions. A dataset for the interaction between the entire human miRome (~2700 miRs) and MGAT3 has been collected and analysis of the miR regulatory map is presented. Our data provides insight into the regulation of this important glycan and its functions in disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".