MicroRNAs as Tools and Effectors for Patient Treatment in Gastrointestinal Carcinogenesis
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
In the last 20 years, microRNAs (miRNAs) have become the most promising class of diagnostic and prognostic biomarkers for human cancer. From a therapeutic perspective, advances in the understanding of the molecular role of miRNAs in the pathological processes have significantly influenced the selection of new therapeutic modalities. Moreover, the intrinsic characteristics that confer stability to miRNAs in vitro, allow a longer molecular/structural resistance and activity in vivo. Preclinical models have consistently underlined the feasibility and efficacy of miRNA-based therapies, either alone or in combination with current targeted therapies. The appealing strength of such therapeutic option dwells in miRNAs' ability to concurrently target multiple genes, frequently in the context of a specific network/pathway. This property allows miRNA-based therapy to be extremely efficient in regulating distinct biological processes relevant to normal and pathological cell homeostasis. The purpose of this review is to summarize the role of miRNAs in gastrointestinal carcinogenesis and their potential use as novel biomarkers and therapeutics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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