A New Role for an Old Drug: Metformin Targets Micro<scp>RNA</scp>s in Treating Diabetes and Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
MicroRNAs (miRNAs) are a family of short, noncoding, 19-23 base pair RNA molecules. Due to their unique role in gene regulation in various tissues, miRNAs play important roles in regulating insulin secretion, metabolic disease, and cancer biology. Emerging evidence demonstrates that miRNAs could also be novel diagnostic markers for a variety of disease states. Additionally, miRNAs have been found to function either as oncogenes, or tumor suppressor genes in cerian cancers. An increasing number of studies have been conducted investigating new drugs targeting miRNAs as a potential anticancer therapy. Metformin is the most widely prescribed medication for treating Type 2 diabetes (T2D). Recent clinical data suggests that metformin impacts the miRNA profile in T2D subjects. Most excitingly, studies have found that metformin is protective against cancer. The anticancer activity of metformin is mediated through a direct regulation of miRNAs, which further modulates several downstream genes in metabolic or preoncogenic pathways. These miRNAs are, therefore, prospective therapeutic targets for treating diabetes and cancer which is the topic of this review. Further study on the regulation of miRNAs by metformin could result in novel therapeutic strategies for recurrent or drug-esistant cancer, and as part of combinatorial approaches with conventional anticancer therapies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it