Investigating the Role of Non-Coding RNA in Non-Alcoholic Fatty Liver Disease
Bibliographic record
Abstract
Non-coding RNAs (ncRNAs) are RNA molecules that do not code for protein but play key roles in regulating cellular processes. NcRNAs globally affect gene expression in diverse physiological and pathological contexts. Functionally important ncRNAs act in chromatin modifications, in mRNA stabilization and translation, and in regulation of various signaling pathways. Non-alcoholic fatty liver disease (NAFLD) is a set of conditions caused by the accumulation of triacylglycerol in the liver. Studies of ncRNA in NAFLD are limited but have demonstrated that ncRNAs play a critical role in the pathogenesis of NAFLD. In this review, we summarize NAFLD's pathogenesis and clinical features, discuss current treatment options, and review the involvement of ncRNAs as regulatory molecules in NAFLD and its progression to non-alcoholic steatohepatitis (NASH). In addition, we highlight signaling pathways dysregulated in NAFLD and review their crosstalk with ncRNAs. Having a thorough understanding of the disease process's molecular mechanisms will facilitate development of highly effective diagnostic and therapeutic treatments. Such insights can also inform preventive strategies to minimize the disease's future development.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".