The new kids on the block: <scp>RNA</scp>‐binding proteins regulate autophagy in disease
Bibliographic record
Abstract
Mammalian autophagy is a highly regulated and conserved cellular homeostatic process. Its existence allows the degradation of self-components to mediate cell survival in different stress conditions. Autophagy is involved in the regulation of cellular metabolic needs, protecting the cell or tissue from starvation through the degradation and recycling of cytoplasmic materials and organelles to basic molecular building blocks. It also plays a critical role in eliminating damaged or harmful proteins, organelles, and intracellular pathogens. Thus, a deterioration of the process may result in pathological conditions, such as aging-associated disorders and cancer. Understanding the crucial role of autophagy in maintaining the normal physiological function of cells, tissue, or organs has led to copious and expansive research regarding the regulation of this process. So far, most of the research has revolved around transcriptional and post-translational regulation. Here, we discuss the regulation of autophagy-related (ATG) mRNA transcripts by RNA-binding proteins (RBPs). This analysis focuses on how RBPs modulate autophagy in disease. A deeper understanding of the involvement of RBPs in autophagy can facilitate further research and treatment of a variety of human diseases.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".